Methods for calculating confidence and credible intervals for the residual between-study variance in random effects meta-regression models

PubMed Central

2014-01-01

Background Meta-regression is becoming increasingly used to model study level covariate effects. However this type of statistical analysis presents many difficulties and challenges. Here two methods for calculating confidence intervals for the magnitude of the residual between-study variance in random effects meta-regression models are developed. A further suggestion for calculating credible intervals using informative prior distributions for the residual between-study variance is presented. Methods Two recently proposed and, under the assumptions of the random effects model, exact methods for constructing confidence intervals for the between-study variance in random effects meta-analyses are extended to the meta-regression setting. The use of Generalised Cochran heterogeneity statistics is extended to the meta-regression setting and a Newton-Raphson procedure is developed to implement the Q profile method for meta-analysis and meta-regression. WinBUGS is used to implement informative priors for the residual between-study variance in the context of Bayesian meta-regressions. Results Results are obtained for two contrasting examples, where the first example involves a binary covariate and the second involves a continuous covariate. Intervals for the residual between-study variance are wide for both examples. Conclusions Statistical methods, and R computer software, are available to compute exact confidence intervals for the residual between-study variance under the random effects model for meta-regression. These frequentist methods are almost as easily implemented as their established counterparts for meta-analysis. Bayesian meta-regressions are also easily performed by analysts who are comfortable using WinBUGS. Estimates of the residual between-study variance in random effects meta-regressions should be routinely reported and accompanied by some measure of their uncertainty. Confidence and/or credible intervals are well-suited to this purpose. PMID:25196829

Power in Bayesian Mediation Analysis for Small Sample Research

PubMed Central

Miočević, Milica; MacKinnon, David P.; Levy, Roy

2018-01-01

It was suggested that Bayesian methods have potential for increasing power in mediation analysis (Koopman, Howe, Hollenbeck, & Sin, 2015; Yuan & MacKinnon, 2009). This paper compares the power of Bayesian credibility intervals for the mediated effect to the power of normal theory, distribution of the product, percentile, and bias-corrected bootstrap confidence intervals at N≤ 200. Bayesian methods with diffuse priors have power comparable to the distribution of the product and bootstrap methods, and Bayesian methods with informative priors had the most power. Varying degrees of precision of prior distributions were also examined. Increased precision led to greater power only when N≥ 100 and the effects were small, N < 60 and the effects were large, and N < 200 and the effects were medium. An empirical example from psychology illustrated a Bayesian analysis of the single mediator model from prior selection to interpreting results. PMID:29662296

Power in Bayesian Mediation Analysis for Small Sample Research.

PubMed

Miočević, Milica; MacKinnon, David P; Levy, Roy

2017-01-01

It was suggested that Bayesian methods have potential for increasing power in mediation analysis (Koopman, Howe, Hollenbeck, & Sin, 2015; Yuan & MacKinnon, 2009). This paper compares the power of Bayesian credibility intervals for the mediated effect to the power of normal theory, distribution of the product, percentile, and bias-corrected bootstrap confidence intervals at N≤ 200. Bayesian methods with diffuse priors have power comparable to the distribution of the product and bootstrap methods, and Bayesian methods with informative priors had the most power. Varying degrees of precision of prior distributions were also examined. Increased precision led to greater power only when N≥ 100 and the effects were small, N < 60 and the effects were large, and N < 200 and the effects were medium. An empirical example from psychology illustrated a Bayesian analysis of the single mediator model from prior selection to interpreting results.

Teaching Note--Was the Champions League Draw Rigged?

ERIC Educational Resources Information Center

Tijms, Henk

2015-01-01

This teaching note gives a real-life example of Bayesian thinking. It discusses how credible accusations are that the outcome of the draw for the quarter-finals in the 2013 European Champions League Football was manipulated.

A hierarchical Bayesian GEV model for improving local and regional flood quantile estimates

NASA Astrophysics Data System (ADS)

Lima, Carlos H. R.; Lall, Upmanu; Troy, Tara; Devineni, Naresh

2016-10-01

We estimate local and regional Generalized Extreme Value (GEV) distribution parameters for flood frequency analysis in a multilevel, hierarchical Bayesian framework, to explicitly model and reduce uncertainties. As prior information for the model, we assume that the GEV location and scale parameters for each site come from independent log-normal distributions, whose mean parameter scales with the drainage area. From empirical and theoretical arguments, the shape parameter for each site is shrunk towards a common mean. Non-informative prior distributions are assumed for the hyperparameters and the MCMC method is used to sample from the joint posterior distribution. The model is tested using annual maximum series from 20 streamflow gauges located in an 83,000 km2 flood prone basin in Southeast Brazil. The results show a significant reduction of uncertainty estimates of flood quantile estimates over the traditional GEV model, particularly for sites with shorter records. For return periods within the range of the data (around 50 years), the Bayesian credible intervals for the flood quantiles tend to be narrower than the classical confidence limits based on the delta method. As the return period increases beyond the range of the data, the confidence limits from the delta method become unreliable and the Bayesian credible intervals provide a way to estimate satisfactory confidence bands for the flood quantiles considering parameter uncertainties and regional information. In order to evaluate the applicability of the proposed hierarchical Bayesian model for regional flood frequency analysis, we estimate flood quantiles for three randomly chosen out-of-sample sites and compare with classical estimates using the index flood method. The posterior distributions of the scaling law coefficients are used to define the predictive distributions of the GEV location and scale parameters for the out-of-sample sites given only their drainage areas and the posterior distribution of the average shape parameter is taken as the regional predictive distribution for this parameter. While the index flood method does not provide a straightforward way to consider the uncertainties in the index flood and in the regional parameters, the results obtained here show that the proposed Bayesian method is able to produce adequate credible intervals for flood quantiles that are in accordance with empirical estimates.

The Society of Thoracic Surgeons Composite Measure of Individual Surgeon Performance for Adult Cardiac Surgery: A Report of The Society of Thoracic Surgeons Quality Measurement Task Force.

PubMed

Shahian, David M; He, Xia; Jacobs, Jeffrey P; Kurlansky, Paul A; Badhwar, Vinay; Cleveland, Joseph C; Fazzalari, Frank L; Filardo, Giovanni; Normand, Sharon-Lise T; Furnary, Anthony P; Magee, Mitchell J; Rankin, J Scott; Welke, Karl F; Han, Jane; O'Brien, Sean M

2015-10-01

Previous composite performance measures of The Society of Thoracic Surgeons (STS) were estimated at the STS participant level, typically a hospital or group practice. The STS Quality Measurement Task Force has now developed a multiprocedural, multidimensional composite measure suitable for estimating the performance of individual surgeons. The development sample from the STS National Database included 621,489 isolated coronary artery bypass grafting procedures, isolated aortic valve replacement, aortic valve replacement plus coronary artery bypass grafting, mitral, or mitral plus coronary artery bypass grafting procedures performed by 2,286 surgeons between July 1, 2011, and June 30, 2014. Each surgeon's composite score combined their aggregate risk-adjusted mortality and major morbidity rates (each weighted inversely by their standard deviations) and reflected the proportion of case types they performed. Model parameters were estimated in a Bayesian framework. Composite star ratings were examined using 90%, 95%, or 98% Bayesian credible intervals. Measure reliability was estimated using various 3-year case thresholds. The final composite measure was defined as 0.81 × (1 minus risk-standardized mortality rate) + 0.19 × (1 minus risk-standardized complication rate). Risk-adjusted mortality (median, 2.3%; interquartile range, 1.7% to 3.0%), morbidity (median, 13.7%; interquartile range, 10.8% to 17.1%), and composite scores (median, 95.4%; interquartile range, 94.4% to 96.3%) varied substantially across surgeons. Using 98% Bayesian credible intervals, there were 207 1-star (lower performance) surgeons (9.1%), 1,701 2-star (as-expected performance) surgeons (74.4%), and 378 3-star (higher performance) surgeons (16.5%). With an eligibility threshold of 100 cases over 3 years, measure reliability was 0.81. The STS has developed a multiprocedural composite measure suitable for evaluating performance at the individual surgeon level. Copyright © 2015 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Bayesian inference for disease prevalence using negative binomial group testing

PubMed Central

Pritchard, Nicholas A.; Tebbs, Joshua M.

2011-01-01

Group testing, also known as pooled testing, and inverse sampling are both widely used methods of data collection when the goal is to estimate a small proportion. Taking a Bayesian approach, we consider the new problem of estimating disease prevalence from group testing when inverse (negative binomial) sampling is used. Using different distributions to incorporate prior knowledge of disease incidence and different loss functions, we derive closed form expressions for posterior distributions and resulting point and credible interval estimators. We then evaluate our new estimators, on Bayesian and classical grounds, and apply our methods to a West Nile Virus data set. PMID:21259308

Improving Bayesian credibility intervals for classifier error rates using maximum entropy empirical priors.

PubMed

Gustafsson, Mats G; Wallman, Mikael; Wickenberg Bolin, Ulrika; Göransson, Hanna; Fryknäs, M; Andersson, Claes R; Isaksson, Anders

2010-06-01

Successful use of classifiers that learn to make decisions from a set of patient examples require robust methods for performance estimation. Recently many promising approaches for determination of an upper bound for the error rate of a single classifier have been reported but the Bayesian credibility interval (CI) obtained from a conventional holdout test still delivers one of the tightest bounds. The conventional Bayesian CI becomes unacceptably large in real world applications where the test set sizes are less than a few hundred. The source of this problem is that fact that the CI is determined exclusively by the result on the test examples. In other words, there is no information at all provided by the uniform prior density distribution employed which reflects complete lack of prior knowledge about the unknown error rate. Therefore, the aim of the study reported here was to study a maximum entropy (ME) based approach to improved prior knowledge and Bayesian CIs, demonstrating its relevance for biomedical research and clinical practice. It is demonstrated how a refined non-uniform prior density distribution can be obtained by means of the ME principle using empirical results from a few designs and tests using non-overlapping sets of examples. Experimental results show that ME based priors improve the CIs when employed to four quite different simulated and two real world data sets. An empirically derived ME prior seems promising for improving the Bayesian CI for the unknown error rate of a designed classifier. Copyright 2010 Elsevier B.V. All rights reserved.

A Bayesian Analysis of a Randomized Clinical Trial Comparing Antimetabolite Therapies for Non-Infectious Uveitis.

PubMed

Browne, Erica N; Rathinam, Sivakumar R; Kanakath, Anuradha; Thundikandy, Radhika; Babu, Manohar; Lietman, Thomas M; Acharya, Nisha R

2017-02-01

To conduct a Bayesian analysis of a randomized clinical trial (RCT) for non-infectious uveitis using expert opinion as a subjective prior belief. A RCT was conducted to determine which antimetabolite, methotrexate or mycophenolate mofetil, is more effective as an initial corticosteroid-sparing agent for the treatment of intermediate, posterior, and pan-uveitis. Before the release of trial results, expert opinion on the relative effectiveness of these two medications was collected via online survey. Members of the American Uveitis Society executive committee were invited to provide an estimate for the relative decrease in efficacy with a 95% credible interval (CrI). A prior probability distribution was created from experts' estimates. A Bayesian analysis was performed using the constructed expert prior probability distribution and the trial's primary outcome. A total of 11 of the 12 invited uveitis specialists provided estimates. Eight of 11 experts (73%) believed mycophenolate mofetil is more effective. The group prior belief was that the odds of treatment success for patients taking mycophenolate mofetil were 1.4-fold the odds of those taking methotrexate (95% CrI 0.03-45.0). The odds of treatment success with mycophenolate mofetil compared to methotrexate was 0.4 from the RCT (95% confidence interval 0.1-1.2) and 0.7 (95% CrI 0.2-1.7) from the Bayesian analysis. A Bayesian analysis combining expert belief with the trial's result did not indicate preference for one drug. However, the wide credible interval leaves open the possibility of a substantial treatment effect. This suggests clinical equipoise necessary to allow a larger, more definitive RCT.

A Pragmatic Bayesian Perspective on Correlation Analysis. The exoplanetary gravity - stellar activity case

NASA Astrophysics Data System (ADS)

Figueira, P.; Faria, J. P.; Adibekyan, V. Zh.; Oshagh, M.; Santos, N. C.

2016-11-01

We apply the Bayesian framework to assess the presence of a correlation between two quantities. To do so, we estimate the probability distribution of the parameter of interest, ρ, characterizing the strength of the correlation. We provide an implementation of these ideas and concepts using python programming language and the pyMC module in a very short (˜ 130 lines of code, heavily commented) and user-friendly program. We used this tool to assess the presence and properties of the correlation between planetary surface gravity and stellar activity level as measured by the log(R^' }_{ {HK}}) indicator. The results of the Bayesian analysis are qualitatively similar to those obtained via p-value analysis, and support the presence of a correlation in the data. The results are more robust in their derivation and more informative, revealing interesting features such as asymmetric posterior distributions or markedly different credible intervals, and allowing for a deeper exploration. We encourage the reader interested in this kind of problem to apply our code to his/her own scientific problems. The full understanding of what the Bayesian framework is can only be gained through the insight that comes by handling priors, assessing the convergence of Monte Carlo runs, and a multitude of other practical problems. We hope to contribute so that Bayesian analysis becomes a tool in the toolkit of researchers, and they understand by experience its advantages and limitations.

Linking stroke mortality with air pollution, income, and greenness in northwest Florida: an ecological geographical study

PubMed Central

Hu, Zhiyong; Liebens, Johan; Rao, K Ranga

2008-01-01

Background Relatively few studies have examined the association between air pollution and stroke mortality. Inconsistent and inclusive results from existing studies on air pollution and stroke justify the need to continue to investigate the linkage between stroke and air pollution. No studies have been done to investigate the association between stroke and greenness. The objective of this study was to examine if there is association of stroke with air pollution, income and greenness in northwest Florida. Results Our study used an ecological geographical approach and dasymetric mapping technique. We adopted a Bayesian hierarchical model with a convolution prior considering five census tract specific covariates. A 95% credible set which defines an interval having a 0.95 posterior probability of containing the parameter for each covariate was calculated from Markov Chain Monte Carlo simulations. The 95% credible sets are (-0.286, -0.097) for household income, (0.034, 0.144) for traffic air pollution effect, (0.419, 1.495) for emission density of monitored point source polluters, (0.413, 1.522) for simple point density of point source polluters without emission data, and (-0.289,-0.031) for greenness. Household income and greenness show negative effects (the posterior densities primarily cover negative values). Air pollution covariates have positive effects (the 95% credible sets cover positive values). Conclusion High risk of stroke mortality was found in areas with low income level, high air pollution level, and low level of exposure to green space. PMID:18452609

Bayesian estimation of seasonal course of canopy leaf area index from hyperspectral satellite data

NASA Astrophysics Data System (ADS)

Varvia, Petri; Rautiainen, Miina; Seppänen, Aku

2018-03-01

In this paper, Bayesian inversion of a physically-based forest reflectance model is investigated to estimate of boreal forest canopy leaf area index (LAI) from EO-1 Hyperion hyperspectral data. The data consist of multiple forest stands with different species compositions and structures, imaged in three phases of the growing season. The Bayesian estimates of canopy LAI are compared to reference estimates based on a spectral vegetation index. The forest reflectance model contains also other unknown variables in addition to LAI, for example leaf single scattering albedo and understory reflectance. In the Bayesian approach, these variables are estimated simultaneously with LAI. The feasibility and seasonal variation of these estimates is also examined. Credible intervals for the estimates are also calculated and evaluated. The results show that the Bayesian inversion approach is significantly better than using a comparable spectral vegetation index regression.

A Bayesian Analysis of a Randomized Clinical Trial Comparing Antimetabolite Therapies for Non-Infectious Uveitis

PubMed Central

Browne, Erica N; Rathinam, Sivakumar R; Kanakath, Anuradha; Thundikandy, Radhika; Babu, Manohar; Lietman, Thomas M; Acharya, Nisha R

2017-01-01

Purpose To conduct a Bayesian analysis of a randomized clinical trial (RCT) for non-infectious uveitis using expert opinion as a subjective prior belief. Methods A RCT was conducted to determine which antimetabolite, methotrexate or mycophenolate mofetil, is more effective as an initial corticosteroid-sparing agent for the treatment of intermediate, posterior, and pan- uveitis. Before the release of trial results, expert opinion on the relative effectiveness of these two medications was collected via online survey. Members of the American Uveitis Society executive committee were invited to provide an estimate for the relative decrease in efficacy with a 95% credible interval (CrI). A prior probability distribution was created from experts’ estimates. A Bayesian analysis was performed using the constructed expert prior probability distribution and the trial’s primary outcome. Results 11 of 12 invited uveitis specialists provided estimates. Eight of 11 experts (73%) believed mycophenolate mofetil is more effective. The group prior belief was that the odds of treatment success for patients taking mycophenolate mofetil were 1.4-fold the odds of those taking methotrexate (95% CrI 0.03 – 45.0). The odds of treatment success with mycophenolate mofetil compared to methotrexate was 0.4 from the RCT (95% confidence interval 0.1–1.2) and 0.7 (95% CrI 0.2–1.7) from the Bayesian analysis. Conclusions A Bayesian analysis combining expert belief with the trial’s result did not indicate preference for one drug. However, the wide credible interval leaves open the possibility of a substantial treatment effect. This suggests clinical equipoise necessary to allow a larger, more definitive RCT. PMID:27982726

Bayesian Statistical Analysis of Historical and Late Holocene Rates of Sea-Level Change

NASA Astrophysics Data System (ADS)

Cahill, Niamh; Parnell, Andrew; Kemp, Andrew; Horton, Benjamin

2014-05-01

A fundamental concern associated with climate change is the rate at which sea levels are rising. Studies of past sea level (particularly beyond the instrumental data range) allow modern sea-level rise to be placed in a more complete context. Considering this, we perform a Bayesian statistical analysis on historical and late Holocene rates of sea-level change. The data that form the input to the statistical model are tide-gauge measurements and proxy reconstructions from cores of coastal sediment. The aims are to estimate rates of sea-level rise, to determine when modern rates of sea-level rise began and to observe how these rates have been changing over time. Many of the current methods for doing this use simple linear regression to estimate rates. This is often inappropriate as it is too rigid and it can ignore uncertainties that arise as part of the data collection exercise. This can lead to over confidence in the sea-level trends being characterized. The proposed Bayesian model places a Gaussian process prior on the rate process (i.e. the process that determines how rates of sea-level are changing over time). The likelihood of the observed data is the integral of this process. When dealing with proxy reconstructions, this is set in an errors-in-variables framework so as to take account of age uncertainty. It is also necessary, in this case, for the model to account for glacio-isostatic adjustment, which introduces a covariance between individual age and sea-level observations. This method provides a flexible fit and it allows for the direct estimation of the rate process with full consideration of all sources of uncertainty. Analysis of tide-gauge datasets and proxy reconstructions in this way means that changing rates of sea level can be estimated more comprehensively and accurately than previously possible. The model captures the continuous and dynamic evolution of sea-level change and results show that not only are modern sea levels rising but that the rates of rise are continuously increasing. Analysis of the a global tide-gauge record (Church and White, 2011) indicated that the rate of sea-level rise increased continuously since 1880AD and is currently 2.57mm/yr (95% credible interval of 1.71 to 4.35mm/yr). Application of the model a proxy reconstruction from North Carolina (Kemp et al., 2011) indicated that the mean rate of rise in this locality since the middle of the 19th century (current rate of 2.66 mm/yr with a 95% credible interval of 1.29 to 4.59mm/yr) is in agreement with results from the tide gauge analysis and is unprecedented in at least the last 2000 years.

A Bayesian Interpretation of Data Trimming to Remove Excess Claims. Excess Claims and Data Trimming in the Context of Credibility Rating Procedures.

DTIC Science & Technology

1981-12-01

Gisler, William S. Jewell* 1. Motivation In Ratemaking and in Experience Rating one is often confronted with the dileina of whether or not to fully...are greatly indebted to R. Schnieper who did all the numerical work on the ETE computer. 4 -, -2- 2. The Basic Model Throughout the paper we work...l )~1) f - (1-i0)po (xl) + ipe(X) 3. The Basic Problem As always in the credibility context our aim is to estimate ua(s) based on the observations of

On a full Bayesian inference for force reconstruction problems

NASA Astrophysics Data System (ADS)

Aucejo, M.; De Smet, O.

2018-05-01

In a previous paper, the authors introduced a flexible methodology for reconstructing mechanical sources in the frequency domain from prior local information on both their nature and location over a linear and time invariant structure. The proposed approach was derived from Bayesian statistics, because of its ability in mathematically accounting for experimenter's prior knowledge. However, since only the Maximum a Posteriori estimate was computed, the posterior uncertainty about the regularized solution given the measured vibration field, the mechanical model and the regularization parameter was not assessed. To answer this legitimate question, this paper fully exploits the Bayesian framework to provide, from a Markov Chain Monte Carlo algorithm, credible intervals and other statistical measures (mean, median, mode) for all the parameters of the force reconstruction problem.

Resolved Stellar Streams around NGC 4631 from a Subaru/Hyper Suprime-Cam Survey

NASA Astrophysics Data System (ADS)

Tanaka, Mikito; Chiba, Masashi; Komiyama, Yutaka

2017-06-01

We present the first results of the Subaru/Hyper Suprime-Cam survey of the interacting galaxy system, NGC 4631 and NGC 4656. From the maps of resolved stellar populations, we identify 11 dwarf galaxies (including already-known dwarfs) in the outer region of NGC 4631 and the two tidal stellar streams around NGC 4631, named Stream SE and Stream NW, respectively. This paper describes the fundamental properties of these tidal streams. Based on the tip of the red giant branch method and the Bayesian statistics, we find that Stream SE (7.10 Mpc in expected a posteriori, EAP, with 90% credible intervals of [6.22, 7.29] Mpc) and Stream NW (7.91 Mpc in EAP with 90% credible intervals of [6.44, 7.97] Mpc) are located in front of and behind NGC 4631, respectively. We also calculate the metallicity distribution of stellar streams by comparing the member stars with theoretical isochrones on the color-magnitude diagram. We find that both streams have the same stellar population based on the Bayesian model selection method, suggesting that they originated from a tidal interaction between NGC 4631 and a single dwarf satellite. The expected progenitor has a positively skewed metallicity distribution function with {[M/H]}{EAP}=-0.92, with 90% credible intervals of [-1.46, -0.51]. The stellar mass of the progenitor is estimated as 3.7× {10}8 {M}⊙ , with 90% credible intervals of [5.8× {10}6,8.6× {10}9] {M}⊙ based on the mass-metallicity relation for Local group dwarf galaxies. This is in good agreement with the initial stellar mass of the progenitor that was presumed in the previous N-body simulation.

A Two-Step Bayesian Approach for Propensity Score Analysis: Simulations and Case Study.

PubMed

Kaplan, David; Chen, Jianshen

2012-07-01

A two-step Bayesian propensity score approach is introduced that incorporates prior information in the propensity score equation and outcome equation without the problems associated with simultaneous Bayesian propensity score approaches. The corresponding variance estimators are also provided. The two-step Bayesian propensity score is provided for three methods of implementation: propensity score stratification, weighting, and optimal full matching. Three simulation studies and one case study are presented to elaborate the proposed two-step Bayesian propensity score approach. Results of the simulation studies reveal that greater precision in the propensity score equation yields better recovery of the frequentist-based treatment effect. A slight advantage is shown for the Bayesian approach in small samples. Results also reveal that greater precision around the wrong treatment effect can lead to seriously distorted results. However, greater precision around the correct treatment effect parameter yields quite good results, with slight improvement seen with greater precision in the propensity score equation. A comparison of coverage rates for the conventional frequentist approach and proposed Bayesian approach is also provided. The case study reveals that credible intervals are wider than frequentist confidence intervals when priors are non-informative.

Search for a fermiophobic Higgs boson decaying into diphotons in pp[over] collisions at sqrt[s] = 1.96 TeV.

PubMed

Aaltonen, T; Adelman, J; Akimoto, T; Alvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Apresyan, A; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Azzurri, P; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Bartsch, V; Bauer, G; Beauchemin, P-H; Bedeschi, F; Beecher, D; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Beringer, J; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bolla, G; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Bridgeman, A; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Burke, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Byrum, K L; Cabrera, S; Calancha, C; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carls, B; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chou, J P; Choudalakis, G; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Chwalek, T; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Compostella, G; Convery, M E; Conway, J; Cordelli, M; Cortiana, G; Cox, C A; Cox, D J; Crescioli, F; Cuenca Almenar, C; Cuevas, J; Culbertson, R; Cully, J C; Dagenhart, D; Datta, M; Davies, T; de Barbaro, P; De Cecco, S; Deisher, A; De Lorenzo, G; Dell'orso, M; Deluca, C; Demay, C; Demortier, L; Deng, J; Deninno, M; Derwent, P F; di Giovanni, G P; Dionisi, C; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Donini, J; Dorigo, T; Dube, S; Efron, J; Elagin, A; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fang, H C; Farrington, S; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Frank, M J; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garberson, F; Garcia, J E; Garfinkel, A F; Genser, K; Gerberich, H; Gerdes, D; Gessler, A; Giagu, S; Giakoumopoulou, V; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C M; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Grinstein, S; Grosso-Pilcher, C; Grundler, U; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, K; Hahn, S R; Halkiadakis, E; Han, B-Y; Han, J Y; Happacher, F; Hara, K; Hare, D; Hare, M; Harper, S; Harr, R F; Harris, R M; Hartz, M; Hatakeyama, K; Hays, C; Heck, M; Heijboer, A; Heinrich, J; Henderson, C; Herndon, M; Heuser, J; Hewamanage, S; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Hou, S; Houlden, M; Hsu, S-C; Huffman, B T; Hughes, R E; Husemann, U; Hussein, M; Husemann, U; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jayatilaka, B; Jeon, E J; Jha, M K; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Kar, D; Karchin, P E; Kato, Y; Kephart, R; Keung, J; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, H W; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirsch, L; Klimenko, S; Knuteson, B; Ko, B R; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kreps, M; Kroll, J; Krop, D; Krumnack, N; Kruse, M; Krutelyov, V; Kubo, T; Kuhr, T; Kulkarni, N P; Kurata, M; Kwang, S; Laasanen, A T; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; Lecompte, T; Lee, E; Lee, H S; Lee, S W; Leone, S; Lewis, J D; Lin, C-S; Linacre, J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, C; Liu, T; Lockyer, N S; Loginov, A; Loreti, M; Lovas, L; Lucchesi, D; Luci, C; Lueck, J; Lujan, P; Lukens, P; Lungu, G; Lyons, L; Lys, J; Lysak, R; Macqueen, D; Madrak, R; Maeshima, K; Makhoul, K; Maki, T; Maksimovic, P; Malde, S; Malik, S; Manca, G; Manousakis-Katsikakis, A; Margaroli, F; Marino, C; Marino, C P; Martin, A; Martin, V; Martínez, M; Martínez-Ballarín, R; Maruyama, T; Mastrandrea, P; Masubuchi, T; Mathis, M; Mattson, M E; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Menzione, A; Merkel, P; Mesropian, C; Miao, T; Miladinovic, N; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyake, H; Moggi, N; Moon, C S; Moore, R; Morello, M J; Morlock, J; Movilla Fernandez, P; Mülmenstädt, J; Mukherjee, A; Muller, Th; Mumford, R; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Nagano, A; Naganoma, J; Nakamura, K; Nakano, I; Napier, A; Necula, V; Nett, J; Neu, C; Neubauer, M S; Neubauer, S; Nielsen, J; Nodulman, L; Norman, M; Norniella, O; Nurse, E; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Osterberg, K; Pagan Griso, S; Palencia, E; Papadimitriou, V; Papaikonomou, A; Paramonov, A A; Parks, B; Pashapour, S; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Peiffer, T; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Pianori, E; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Poukhov, O; Pounder, N; Prakoshyn, F; Pronko, A; Proudfoot, J; Ptohos, F; Pueschel, E; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Ray, J; Redondo, I; Renton, P; Renz, M; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rodriguez, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rossin, R; Roy, P; Ruiz, A; Russ, J; Rusu, V; Saarikko, H; Safonov, A; Sakumoto, W K; Saltó, O; Santi, L; Sarkar, S; Sartori, L; Sato, K; Savoy-Navarro, A; Schlabach, P; Schmidt, A; Schmidt, E E; Schmidt, M A; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sexton-Kennedy, L; Sforza, F; Sfyrla, A; Shalhout, S Z; Shears, T; Shepard, P F; Shimojima, M; Shiraishi, S; Shochet, M; Shon, Y; Shreyber, I; Sidoti, A; Sinervo, P; Sisakyan, A; Slaughter, A J; Slaunwhite, J; Sliwa, K; Smith, J R; Snider, F D; Snihur, R; Soha, A; Somalwar, S; Sorin, V; Spalding, J; Spreitzer, T; Squillacioti, P; Stanitzki, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Strycker, G L; Stuart, D; Suh, J S; Sukhanov, A; Suslov, I; Suzuki, T; Taffard, A; Takashima, R; Takeuchi, Y; Tanaka, R; Tecchio, M; Teng, P K; Terashi, K; Thom, J; Thompson, A S; Thompson, G A; Thomson, E; Tipton, P; Ttito-Guzmán, P; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Tourneur, S; Trovato, M; Tsai, S-Y; Tu, Y; Turini, N; Ukegawa, F; Vallecorsa, S; van Remortel, N; Varganov, A; Vataga, E; Vázquez, F; Velev, G; Vellidis, C; Vidal, M; Vidal, R; Vila, I; Vilar, R; Vine, T; Vogel, M; Volobouev, I; Volpi, G; Wagner, P; Wagner, R G; Wagner, R L; Wagner, W; Wagner-Kuhr, J; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Weinberger, M; Weinelt, J; Wester, W C; Whitehouse, B; Whiteson, D; Wicklund, A B; Wicklund, E; Wilbur, S; Williams, G; Williams, H H; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, C; Wright, T; Wu, X; Würthwein, F; Xie, S; Yagil, A; Yamamoto, K; Yamaoka, J; Yang, U K; Yang, Y C; Yao, W M; Yeh, G P; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanello, L; Zanetti, A; Zhang, X; Zheng, Y; Zucchelli, S

2009-08-07

A search for a narrow diphoton mass resonance is presented based on data from 3.0 fb;{-1} of integrated luminosity from pp[over ] collisions at sqrt[s] = 1.96 TeV collected by the CDF experiment. No evidence of a resonance in the diphoton mass spectrum is observed, and upper limits are set on the cross section times branching fraction of the resonant state as a function of Higgs boson mass. The resulting limits exclude Higgs bosons with masses below 106 GeV/c;{2} at a 95% Bayesian credibility level for one fermiophobic benchmark model.

Airborne culturable fungi in naturally ventilated primary school environments in a subtropical climate

NASA Astrophysics Data System (ADS)

Salonen, Heidi; Duchaine, Caroline; Mazaheri, Mandana; Clifford, Sam; Morawska, Lidia

2015-04-01

There is currently a lack of reference values for indoor air fungal concentrations to allow for the interpretation of measurement results in subtropical school settings. Analysis of the results of this work established that, in the majority of properly maintained subtropical school buildings, without any major affecting events such as floods or visible mould or moisture contamination, indoor culturable fungi levels were driven by outdoor concentration. The results also allowed us to benchmark the "baseline range" concentrations for total culturable fungi, Penicillium spp., Cladosporium spp. and Aspergillus spp. in such school settings. The measured concentration of total culturable fungi and three individual fungal genera were estimated using Bayesian hierarchical modelling. Pooling of these estimates provided a predictive distribution for concentrations at an unobserved school. The results indicated that "baseline" indoor concentration levels for indoor total fungi, Penicillium spp., Cladosporium spp. and Aspergillus spp. in such school settings were generally ≤1450, ≤680, ≤480 and ≤90 cfu/m3, respectively, and elevated levels would indicate mould damage in building structures. The indoor/outdoor ratio for most classrooms had 95% credible intervals containing 1, indicating that fungi concentrations are generally the same indoors and outdoors at each school. Bayesian fixed effects regression modelling showed that increasing both temperature and humidity resulted in higher levels of fungi concentration.

A transdiagnostic study of education, employment, and training outcomes in young people with mental illness.

PubMed

Lee, R S C; Hermens, D F; Scott, J; O'Dea, B; Glozier, N; Scott, E M; Hickie, I B

2017-09-01

Optimizing functional recovery in young individuals with severe mental illness constitutes a major healthcare priority. The current study sought to quantify the cognitive and clinical factors underpinning academic and vocational engagement in a transdiagnostic and prospective youth mental health cohort. The primary outcome measure was 'not in education, employment or training' ('NEET') status. A clinical sample of psychiatric out-patients aged 15-25 years (n = 163) was assessed at two time points, on average, 24 months apart. Functional status, and clinical and neuropsychological data were collected. Bayesian structural equation modelling was used to confirm the factor structure of predictors and cross-lagged effects at follow-up. Individually, NEET status, cognitive dysfunction and negative symptoms at baseline were predictive of NEET status at follow-up (p < 0.05). Baseline cognitive functioning was the only predictor of follow-up NEET status in the multivariate Bayesian model, while controlling for baseline NEET status. For every 1 s.d. deficit in cognition, the probability of being disengaged at follow-up increased by 40% (95% credible interval 19-58%). Baseline NEET status predicted poorer negative symptoms at follow-up (β = 0.24, 95% credible interval 0.04-0.43). Disengagement with education, employment or training (i.e. being NEET) was reported in about one in four members of this cohort. The initial level of cognitive functioning was the strongest determinant of future NEET status, whereas being academically or vocationally engaged had an impact on future negative symptomatology. If replicated, these findings support the need to develop early interventions that target cognitive phenotypes transdiagnostically.

A Bayesian procedure for evaluating the frequency of calibration factor updates in highway safety manual (HSM) applications.

PubMed

Saha, Dibakar; Alluri, Priyanka; Gan, Albert

2017-01-01

The Highway Safety Manual (HSM) presents statistical models to quantitatively estimate an agency's safety performance. The models were developed using data from only a few U.S. states. To account for the effects of the local attributes and temporal factors on crash occurrence, agencies are required to calibrate the HSM-default models for crash predictions. The manual suggests updating calibration factors every two to three years, or preferably on an annual basis. Given that the calibration process involves substantial time, effort, and resources, a comprehensive analysis of the required calibration factor update frequency is valuable to the agencies. Accordingly, the objective of this study is to evaluate the HSM's recommendation and determine the required frequency of calibration factor updates. A robust Bayesian estimation procedure is used to assess the variation between calibration factors computed annually, biennially, and triennially using data collected from over 2400 miles of segments and over 700 intersections on urban and suburban facilities in Florida. Bayesian model yields a posterior distribution of the model parameters that give credible information to infer whether the difference between calibration factors computed at specified intervals is credibly different from the null value which represents unaltered calibration factors between the comparison years or in other words, zero difference. The concept of the null value is extended to include the range of values that are practically equivalent to zero. Bayesian inference shows that calibration factors based on total crash frequency are required to be updated every two years in cases where the variations between calibration factors are not greater than 0.01. When the variations are between 0.01 and 0.05, calibration factors based on total crash frequency could be updated every three years. Copyright © 2016 Elsevier Ltd. All rights reserved.

Psychosocial stress factors, including the relationship with the coach, and their influence on acute and overuse injury risk in elite female football players.

PubMed

Pensgaard, Anne Marte; Ivarsson, Andreas; Nilstad, Agnethe; Solstad, Bård Erlend; Steffen, Kathrin

2018-01-01

The relationship between specific types of stressors (eg, teammates, coach) and acute versus overuse injuries is not well understood. To examine the roles of different types of stressors as well as the effect of motivational climate on the occurrence of acute and overuse injuries. Players in the Norwegian elite female football league (n=193 players from 12 teams) participated in baseline screening tests prior to the 2009 competitive football season. As part of the screening, we included the Life Event Survey for Collegiate Athletes and the Perceived Motivational Climate in Sport Questionnaire (Norwegian short version). Acute and overuse time-loss injuries and exposure to training and matches were recorded prospectively in the football season using weekly text messaging. Data were analysed with Bayesian logistic regression analyses. Using Bayesian logistic regression analyses, we showed that perceived negative life event stress from teammates was associated with an increased risk of acute injuries (OR=1.23, 95% credibility interval (1.01 to 1.48)). There was a credible positive association between perceived negative life event stress from the coach and the risk of overuse injuries (OR=1.21, 95% credibility interval (1.01 to 1.45)). Players who report teammates as a source of stress have a greater risk of sustaining an acute injury, while players reporting the coach as a source of stress are at greater risk of sustaining an overuse injury. Motivational climate did not relate to increased injury occurrence.

Estimating Tree Height-Diameter Models with the Bayesian Method

PubMed Central

Duan, Aiguo; Zhang, Jianguo; Xiang, Congwei

2014-01-01

Six candidate height-diameter models were used to analyze the height-diameter relationships. The common methods for estimating the height-diameter models have taken the classical (frequentist) approach based on the frequency interpretation of probability, for example, the nonlinear least squares method (NLS) and the maximum likelihood method (ML). The Bayesian method has an exclusive advantage compared with classical method that the parameters to be estimated are regarded as random variables. In this study, the classical and Bayesian methods were used to estimate six height-diameter models, respectively. Both the classical method and Bayesian method showed that the Weibull model was the “best” model using data1. In addition, based on the Weibull model, data2 was used for comparing Bayesian method with informative priors with uninformative priors and classical method. The results showed that the improvement in prediction accuracy with Bayesian method led to narrower confidence bands of predicted value in comparison to that for the classical method, and the credible bands of parameters with informative priors were also narrower than uninformative priors and classical method. The estimated posterior distributions for parameters can be set as new priors in estimating the parameters using data2. PMID:24711733

Estimating tree height-diameter models with the Bayesian method.

PubMed

Zhang, Xiongqing; Duan, Aiguo; Zhang, Jianguo; Xiang, Congwei

2014-01-01

Six candidate height-diameter models were used to analyze the height-diameter relationships. The common methods for estimating the height-diameter models have taken the classical (frequentist) approach based on the frequency interpretation of probability, for example, the nonlinear least squares method (NLS) and the maximum likelihood method (ML). The Bayesian method has an exclusive advantage compared with classical method that the parameters to be estimated are regarded as random variables. In this study, the classical and Bayesian methods were used to estimate six height-diameter models, respectively. Both the classical method and Bayesian method showed that the Weibull model was the "best" model using data1. In addition, based on the Weibull model, data2 was used for comparing Bayesian method with informative priors with uninformative priors and classical method. The results showed that the improvement in prediction accuracy with Bayesian method led to narrower confidence bands of predicted value in comparison to that for the classical method, and the credible bands of parameters with informative priors were also narrower than uninformative priors and classical method. The estimated posterior distributions for parameters can be set as new priors in estimating the parameters using data2.

Author Correction: Phase-resolved X-ray polarimetry of the Crab pulsar with the AstroSat CZT Imager

NASA Astrophysics Data System (ADS)

Vadawale, S. V.; Chattopadhyay, T.; Mithun, N. P. S.; Rao, A. R.; Bhattacharya, D.; Vibhute, A.; Bhalerao, V. B.; Dewangan, G. C.; Misra, R.; Paul, B.; Basu, A.; Joshi, B. C.; Sreekumar, S.; Samuel, E.; Priya, P.; Vinod, P.; Seetha, S.

2018-05-01

In the Supplementary Information file originally published for this Letter, in Supplementary Fig. 7 the error bars for the polarization fraction were provided as confidence intervals but instead should have been Bayesian credibility intervals. This has been corrected and does not alter the conclusions of the Letter in any way.

Time-varying nonstationary multivariate risk analysis using a dynamic Bayesian copula

NASA Astrophysics Data System (ADS)

Sarhadi, Ali; Burn, Donald H.; Concepción Ausín, María.; Wiper, Michael P.

2016-03-01

A time-varying risk analysis is proposed for an adaptive design framework in nonstationary conditions arising from climate change. A Bayesian, dynamic conditional copula is developed for modeling the time-varying dependence structure between mixed continuous and discrete multiattributes of multidimensional hydrometeorological phenomena. Joint Bayesian inference is carried out to fit the marginals and copula in an illustrative example using an adaptive, Gibbs Markov Chain Monte Carlo (MCMC) sampler. Posterior mean estimates and credible intervals are provided for the model parameters and the Deviance Information Criterion (DIC) is used to select the model that best captures different forms of nonstationarity over time. This study also introduces a fully Bayesian, time-varying joint return period for multivariate time-dependent risk analysis in nonstationary environments. The results demonstrate that the nature and the risk of extreme-climate multidimensional processes are changed over time under the impact of climate change, and accordingly the long-term decision making strategies should be updated based on the anomalies of the nonstationary environment.

Search for the decays B_{(s)};{0} --> e;{+} micro;{-} and B_{(s)};{0} --> e;{+} e;{-} in CDF run II.

PubMed

Aaltonen, T; Adelman, J; Akimoto, T; Alvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Apresyan, A; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Azzurri, P; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Bartsch, V; Bauer, G; Beauchemin, P-H; Bedeschi, F; Beecher, D; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Beringer, J; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bolla, G; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Bridgeman, A; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Burke, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Byrum, K L; Cabrera, S; Calancha, C; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carls, B; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chou, J P; Choudalakis, G; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Chwalek, T; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Compostella, G; Convery, M E; Conway, J; Cordelli, M; Cortiana, G; Cox, C A; Cox, D J; Crescioli, F; Cuenca Almenar, C; Cuevas, J; Culbertson, R; Cully, J C; Dagenhart, D; Datta, M; Davies, T; de Barbaro, P; De Cecco, S; Deisher, A; De Lorenzo, G; Dell'orso, M; Deluca, C; Demortier, L; Deng, J; Deninno, M; Derwent, P F; di Giovanni, G P; Dionisi, C; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Donini, J; Dorigo, T; Dube, S; Efron, J; Elagin, A; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fang, H C; Farrington, S; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Frank, M J; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garberson, F; Garcia, J E; Garfinkel, A F; Genser, K; Gerberich, H; Gerdes, D; Gessler, A; Giagu, S; Giakoumopoulou, V; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C M; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Grinstein, S; Grosso-Pilcher, C; Grundler, U; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, K; Hahn, S R; Halkiadakis, E; Han, B-Y; Han, J Y; Happacher, F; Hara, K; Hare, D; Hare, M; Harper, S; Harr, R F; Harris, R M; Hartz, M; Hatakeyama, K; Hays, C; Heck, M; Heijboer, A; Heinrich, J; Henderson, C; Herndon, M; Heuser, J; Hewamanage, S; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Hou, S; Houlden, M; Hsu, S-C; Huffman, B T; Hughes, R E; Husemann, U; Hussein, M; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jang, D; Jayatilaka, B; Jeon, E J; Jha, M K; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Kar, D; Karchin, P E; Kato, Y; Kephart, R; Keung, J; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, H W; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirsch, L; Klimenko, S; Knuteson, B; Ko, B R; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kreps, M; Kroll, J; Krop, D; Krumnack, N; Kruse, M; Krutelyov, V; Kubo, T; Kuhr, T; Kulkarni, N P; Kurata, M; Kwang, S; Laasanen, A T; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; Lecompte, T; Lee, E; Lee, H S; Lee, S W; Leone, S; Lewis, J D; Lin, C-S; Linacre, J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, C; Liu, T; Lockyer, N S; Loginov, A; Loreti, M; Lovas, L; Lucchesi, D; Luci, C; Lueck, J; Lujan, P; Lukens, P; Lungu, G; Lyons, L; Lys, J; Lysak, R; Macqueen, D; Madrak, R; Maeshima, K; Makhoul, K; Maki, T; Maksimovic, P; Malde, S; Malik, S; Manca, G; Manousakis-Katsikakis, A; Margaroli, F; Marino, C; Marino, C P; Martin, A; Martin, V; Martínez, M; Martínez-Ballarín, R; Maruyama, T; Mastrandrea, P; Masubuchi, T; Mathis, M; Mattson, M E; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Menzione, A; Merkel, P; Mesropian, C; Miao, T; Miladinovic, N; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyake, H; Moggi, N; Moon, C S; Moore, R; Morello, M J; Morlock, J; Movilla Fernandez, P; Mülmenstädt, J; Mukherjee, A; Muller, Th; Mumford, R; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Nagano, A; Naganoma, J; Nakamura, K; Nakano, I; Napier, A; Necula, V; Nett, J; Neu, C; Neubauer, M S; Neubauer, S; Nielsen, J; Nodulman, L; Norman, M; Norniella, O; Nurse, E; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Osterberg, K; Griso, S Pagan; Palencia, E; Papadimitriou, V; Papaikonomou, A; Paramonov, A A; Parks, B; Pashapour, S; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Peiffer, T; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Pianori, E; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Poukhov, O; Pounder, N; Prakoshyn, F; Pronko, A; Proudfoot, J; Ptohos, F; Pueschel, E; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Renton, P; Renz, M; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rodriguez, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rossin, R; Roy, P; Ruiz, A; Russ, J; Rusu, V; Rutherford, B; Saarikko, H; Safonov, A; Sakumoto, W K; Saltó, O; Santi, L; Sarkar, S; Sartori, L; Sato, K; Savoy-Navarro, A; Schlabach, P; Schmidt, A; Schmidt, E E; Schmidt, M A; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sexton-Kennedy, L; Sforza, F; Sfyrla, A; Shalhout, S Z; Shears, T; Shepard, P F; Shimojima, M; Shiraishi, S; Shochet, M; Shon, Y; Shreyber, I; Sidoti, A; Sinervo, P; Sisakyan, A; Slaughter, A J; Slaunwhite, J; Sliwa, K; Smith, J R; Snider, F D; Snihur, R; Soha, A; Somalwar, S; Sorin, V; Spalding, J; Spreitzer, T; Squillacioti, P; Stanitzki, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Strycker, G L; Stuart, D; Suh, J S; Sukhanov, A; Suslov, I; Suzuki, T; Taffard, A; Takashima, R; Takeuchi, Y; Tanaka, R; Tecchio, M; Teng, P K; Terashi, K; Thom, J; Thompson, A S; Thompson, G A; Thomson, E; Tipton, P; Ttito-Guzmán, P; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Tourneur, S; Trovato, M; Tsai, S-Y; Tu, Y; Turini, N; Ukegawa, F; Vallecorsa, S; van Remortel, N; Varganov, A; Vataga, E; Vázquez, F; Velev, G; Vellidis, C; Vidal, M; Vidal, R; Vila, I; Vilar, R; Vine, T; Vogel, M; Volobouev, I; Volpi, G; Wagner, P; Wagner, R G; Wagner, R L; Wagner, W; Wagner-Kuhr, J; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Weinberger, M; Weinelt, J; Wenzel, H; Wester, W C; Whitehouse, B; Whiteson, D; Wicklund, A B; Wicklund, E; Wilbur, S; Williams, G; Williams, H H; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, C; Wright, T; Wu, X; Würthwein, F; Xie, S; Yagil, A; Yamamoto, K; Yamaoka, J; Yang, U K; Yang, Y C; Yao, W M; Yeh, G P; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanello, L; Zanetti, A; Zhang, X; Zheng, Y; Zucchelli, S

2009-05-22

We report results from a search for the lepton flavor violating decays B_{s};{0} --> e;{+} micro;{-} and B;{0} --> e;{+} micro;{-}, and the flavor-changing neutral-current decays B_{s};{0} --> e;{+} e;{-} and B;{0} --> e;{+} e;{-}. The analysis uses data corresponding to 2 fb;{-1} of integrated luminosity of pp[over ] collisions at sqrt[s] = 1.96 TeV collected with the upgraded Collider Detector (CDF II) at the Fermilab Tevatron. The observed number of B0 and B_{s};{0} candidates is consistent with background expectations. The resulting Bayesian upper limits on the branching ratios at 90% credibility level are B(B_{s};{0} --> e;{+} micro;{-}) < 2.0 x 10;{-7}, B(B;{0} --> e;{+} micro;{-}) < 6.4 x 10;{-8}, B(B_{s};{0} --> e;{+} e;{-}) < 2.8 x 10;{-7}, and B(B;{0} --> e;{+} e;{-}) < 8.3 x 10;{-8}. From the limits on B(B_{(s)};{0} --> e;{+} micro;{-}), the following lower bounds on the Pati-Salam leptoquark masses are also derived: M_{LQ}(B_{s};{0} --> e;{+} micro;{-}) > 47.8 TeV/c;{2}, and M_{LQ}(B;{0} --> e;{+} micro;{-}) > 59.3 TeV / c;{2}, at 90% credibility level.

Bayesian Spatial Design of Optimal Deep Tubewell Locations in Matlab, Bangladesh.

PubMed

Warren, Joshua L; Perez-Heydrich, Carolina; Yunus, Mohammad

2013-09-01

We introduce a method for statistically identifying the optimal locations of deep tubewells (dtws) to be installed in Matlab, Bangladesh. Dtw installations serve to mitigate exposure to naturally occurring arsenic found at groundwater depths less than 200 meters, a serious environmental health threat for the population of Bangladesh. We introduce an objective function, which incorporates both arsenic level and nearest town population size, to identify optimal locations for dtw placement. Assuming complete knowledge of the arsenic surface, we then demonstrate how minimizing the objective function over a domain favors dtws placed in areas with high arsenic values and close to largely populated regions. Given only a partial realization of the arsenic surface over a domain, we use a Bayesian spatial statistical model to predict the full arsenic surface and estimate the optimal dtw locations. The uncertainty associated with these estimated locations is correctly characterized as well. The new method is applied to a dataset from a village in Matlab and the estimated optimal locations are analyzed along with their respective 95% credible regions.

Psychosocial stress factors, including the relationship with the coach, and their influence on acute and overuse injury risk in elite female football players

PubMed Central

Pensgaard, Anne Marte; Ivarsson, Andreas; Nilstad, Agnethe; Solstad, Bård Erlend; Steffen, Kathrin

2018-01-01

Background The relationship between specific types of stressors (eg, teammates, coach) and acute versus overuse injuries is not well understood. Objective To examine the roles of different types of stressors as well as the effect of motivational climate on the occurrence of acute and overuse injuries. Methods Players in the Norwegian elite female football league (n=193 players from 12 teams) participated in baseline screening tests prior to the 2009 competitive football season. As part of the screening, we included the Life Event Survey for Collegiate Athletes and the Perceived Motivational Climate in Sport Questionnaire (Norwegian short version). Acute and overuse time-loss injuries and exposure to training and matches were recorded prospectively in the football season using weekly text messaging. Data were analysed with Bayesian logistic regression analyses. Results Using Bayesian logistic regression analyses, we showed that perceived negative life event stress from teammates was associated with an increased risk of acute injuries (OR=1.23, 95% credibility interval (1.01 to 1.48)). There was a credible positive association between perceived negative life event stress from the coach and the risk of overuse injuries (OR=1.21, 95% credibility interval (1.01 to 1.45)). Conclusions Players who report teammates as a source of stress have a greater risk of sustaining an acute injury, while players reporting the coach as a source of stress are at greater risk of sustaining an overuse injury. Motivational climate did not relate to increased injury occurrence. PMID:29629182

Vertical land motion controls regional sea level rise patterns on the United States east coast since 1900

NASA Astrophysics Data System (ADS)

Piecuch, C. G.; Huybers, P. J.; Hay, C.; Mitrovica, J. X.; Little, C. M.; Ponte, R. M.; Tingley, M.

2017-12-01

Understanding observed spatial variations in centennial relative sea level trends on the United States east coast has important scientific and societal applications. Past studies based on models and proxies variously suggest roles for crustal displacement, ocean dynamics, and melting of the Greenland ice sheet. Here we perform joint Bayesian inference on regional relative sea level, vertical land motion, and absolute sea level fields based on tide gauge records and GPS data. Posterior solutions show that regional vertical land motion explains most (80% median estimate) of the spatial variance in the large-scale relative sea level trend field on the east coast over 1900-2016. The posterior estimate for coastal absolute sea level rise is remarkably spatially uniform compared to previous studies, with a spatial average of 1.4-2.3 mm/yr (95% credible interval). Results corroborate glacial isostatic adjustment models and reveal that meaningful long-period, large-scale vertical velocity signals can be extracted from short GPS records.

Sequential Designs Based on Bayesian Uncertainty Quantification in Sparse Representation Surrogate Modeling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Ray -Bing; Wang, Weichung; Jeff Wu, C. F.

A numerical method, called OBSM, was recently proposed which employs overcomplete basis functions to achieve sparse representations. While the method can handle non-stationary response without the need of inverting large covariance matrices, it lacks the capability to quantify uncertainty in predictions. We address this issue by proposing a Bayesian approach which first imposes a normal prior on the large space of linear coefficients, then applies the MCMC algorithm to generate posterior samples for predictions. From these samples, Bayesian credible intervals can then be obtained to assess prediction uncertainty. A key application for the proposed method is the efficient construction ofmore » sequential designs. Several sequential design procedures with different infill criteria are proposed based on the generated posterior samples. As a result, numerical studies show that the proposed schemes are capable of solving problems of positive point identification, optimization, and surrogate fitting.« less

Sequential Designs Based on Bayesian Uncertainty Quantification in Sparse Representation Surrogate Modeling

DOE PAGES

Chen, Ray -Bing; Wang, Weichung; Jeff Wu, C. F.

2017-04-12

A numerical method, called OBSM, was recently proposed which employs overcomplete basis functions to achieve sparse representations. While the method can handle non-stationary response without the need of inverting large covariance matrices, it lacks the capability to quantify uncertainty in predictions. We address this issue by proposing a Bayesian approach which first imposes a normal prior on the large space of linear coefficients, then applies the MCMC algorithm to generate posterior samples for predictions. From these samples, Bayesian credible intervals can then be obtained to assess prediction uncertainty. A key application for the proposed method is the efficient construction ofmore » sequential designs. Several sequential design procedures with different infill criteria are proposed based on the generated posterior samples. As a result, numerical studies show that the proposed schemes are capable of solving problems of positive point identification, optimization, and surrogate fitting.« less

A Fast Surrogate-facilitated Data-driven Bayesian Approach to Uncertainty Quantification of a Regional Groundwater Flow Model with Structural Error

NASA Astrophysics Data System (ADS)

Xu, T.; Valocchi, A. J.; Ye, M.; Liang, F.

2016-12-01

Due to simplification and/or misrepresentation of the real aquifer system, numerical groundwater flow and solute transport models are usually subject to model structural error. During model calibration, the hydrogeological parameters may be overly adjusted to compensate for unknown structural error. This may result in biased predictions when models are used to forecast aquifer response to new forcing. In this study, we extend a fully Bayesian method [Xu and Valocchi, 2015] to calibrate a real-world, regional groundwater flow model. The method uses a data-driven error model to describe model structural error and jointly infers model parameters and structural error. In this study, Bayesian inference is facilitated using high performance computing and fast surrogate models. The surrogate models are constructed using machine learning techniques to emulate the response simulated by the computationally expensive groundwater model. We demonstrate in the real-world case study that explicitly accounting for model structural error yields parameter posterior distributions that are substantially different from those derived by the classical Bayesian calibration that does not account for model structural error. In addition, the Bayesian with error model method gives significantly more accurate prediction along with reasonable credible intervals.

Rediscovery of Good-Turing estimators via Bayesian nonparametrics.

PubMed

Favaro, Stefano; Nipoti, Bernardo; Teh, Yee Whye

2016-03-01

The problem of estimating discovery probabilities originated in the context of statistical ecology, and in recent years it has become popular due to its frequent appearance in challenging applications arising in genetics, bioinformatics, linguistics, designs of experiments, machine learning, etc. A full range of statistical approaches, parametric and nonparametric as well as frequentist and Bayesian, has been proposed for estimating discovery probabilities. In this article, we investigate the relationships between the celebrated Good-Turing approach, which is a frequentist nonparametric approach developed in the 1940s, and a Bayesian nonparametric approach recently introduced in the literature. Specifically, under the assumption of a two parameter Poisson-Dirichlet prior, we show that Bayesian nonparametric estimators of discovery probabilities are asymptotically equivalent, for a large sample size, to suitably smoothed Good-Turing estimators. As a by-product of this result, we introduce and investigate a methodology for deriving exact and asymptotic credible intervals to be associated with the Bayesian nonparametric estimators of discovery probabilities. The proposed methodology is illustrated through a comprehensive simulation study and the analysis of Expressed Sequence Tags data generated by sequencing a benchmark complementary DNA library. © 2015, The International Biometric Society.

New insights into faster computation of uncertainties

NASA Astrophysics Data System (ADS)

Bhattacharya, Atreyee

2012-11-01

Heavy computation power, lengthy simulations, and an exhaustive number of model runs—often these seem like the only statistical tools that scientists have at their disposal when computing uncertainties associated with predictions, particularly in cases of environmental processes such as groundwater movement. However, calculation of uncertainties need not be as lengthy, a new study shows. Comparing two approaches—the classical Bayesian “credible interval” and a less commonly used regression-based “confidence interval” method—Lu et al. show that for many practical purposes both methods provide similar estimates of uncertainties. The advantage of the regression method is that it demands 10-1000 model runs, whereas the classical Bayesian approach requires 10,000 to millions of model runs.

Search for a Higgs boson decaying to two W bosons at CDF.

PubMed

Aaltonen, T; Adelman, J; Akimoto, T; Albrow, M G; Alvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Apresyan, A; Arisawa, T; Artikov, A; Ashmanskas, W; Attal, A; Aurisano, A; Azfar, F; Azzurri, P; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Bartsch, V; Bauer, G; Beauchemin, P-H; Bedeschi, F; Beecher, D; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Beringer, J; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Blair, R E; Blocker, C; Blumenfeld, B; Bocci, A; Bodek, A; Boisvert, V; Bolla, G; Bortoletto, D; Boudreau, J; Boveia, A; Brau, B; Bridgeman, A; Brigliadori, L; Bromberg, C; Brubaker, E; Budagov, J; Budd, H S; Budd, S; Burke, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Byrum, K L; Cabrera, S; Calancha, C; Campanelli, M; Campbell, M; Canelli, F; Canepa, A; Carls, B; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chang, S H; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chou, J P; Choudalakis, G; Chuang, S H; Chung, K; Chung, W H; Chung, Y S; Chwalek, T; Ciobanu, C I; Ciocci, M A; Clark, A; Clark, D; Compostella, G; Convery, M E; Conway, J; Cordelli, M; Cortiana, G; Cox, C A; Cox, D J; Crescioli, F; Cuenca Almenar, C; Cuevas, J; Culbertson, R; Cully, J C; Dagenhart, D; Datta, M; Davies, T; de Barbaro, P; De Cecco, S; Deisher, A; De Lorenzo, G; Dell'orso, M; Deluca, C; Demortier, L; Deng, J; Deninno, M; Derwent, P F; di Giovanni, G P; Dionisi, C; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Donini, J; Dorigo, T; Dube, S; Efron, J; Elagin, A; Erbacher, R; Errede, D; Errede, S; Eusebi, R; Fang, H C; Farrington, S; Fedorko, W T; Feild, R G; Feindt, M; Fernandez, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Frank, M J; Franklin, M; Freeman, J C; Furic, I; Gallinaro, M; Galyardt, J; Garberson, F; Garcia, J E; Garfinkel, A F; Genser, K; Gerberich, H; Gerdes, D; Gessler, A; Giagu, S; Giakoumopoulou, V; Giannetti, P; Gibson, K; Gimmell, J L; Ginsburg, C M; Giokaris, N; Giordani, M; Giromini, P; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gresele, A; Grinstein, S; Grosso-Pilcher, C; Grundler, U; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, K; Hahn, S R; Halkiadakis, E; Han, B-Y; Han, J Y; Happacher, F; Hara, K; Hare, D; Hare, M; Harper, S; Harr, R F; Harris, R M; Hartz, M; Hatakeyama, K; Hays, C; Heck, M; Heijboer, A; Heinrich, J; Henderson, C; Herndon, M; Heuser, J; Hewamanage, S; Hidas, D; Hill, C S; Hirschbuehl, D; Hocker, A; Hou, S; Houlden, M; Hsu, S-C; Huffman, B T; Hughes, R E; Husemann, U; Huston, J; Incandela, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jayatilaka, B; Jeon, E J; Jha, M K; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Jung, J E; Junk, T R; Kamon, T; Kar, D; Karchin, P E; Kato, Y; Kephart, R; Keung, J; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, H W; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirsch, L; Klimenko, S; Knuteson, B; Ko, B R; Kondo, K; Kong, D J; Konigsberg, J; Korytov, A; Kotwal, A V; Kreps, M; Kroll, J; Krop, D; Krumnack, N; Kruse, M; Krutelyov, V; Kubo, T; Kuhr, T; Kulkarni, N P; Kurata, M; Kusakabe, Y; Kwang, S; Laasanen, A T; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lazzizzera, I; Lecompte, T; Lee, E; Lee, H S; Lee, S W; Leone, S; Lewis, J D; Lin, C-S; Linacre, J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, C; Liu, T; Lockyer, N S; Loginov, A; Loreti, M; Lovas, L; Lucchesi, D; Luci, C; Lueck, J; Lujan, P; Lukens, P; Lungu, G; Lyons, L; Lys, J; Lysak, R; Macqueen, D; Madrak, R; Maeshima, K; Makhoul, K; Maki, T; Maksimovic, P; Malde, S; Malik, S; Manca, G; Manousakis-Katsikakis, A; Margaroli, F; Marino, C; Marino, C P; Martin, A; Martin, V; Martínez, M; Martínez-Ballarín, R; Maruyama, T; Mastrandrea, P; Masubuchi, T; Mathis, M; Mattson, M E; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Menzione, A; Merkel, P; Mesropian, C; Miao, T; Miladinovic, N; Miller, R; Mills, C; Milnik, M; Mitra, A; Mitselmakher, G; Miyake, H; Moggi, N; Moon, C S; Moore, R; Morello, M J; Morlok, J; Movilla Fernandez, P; Mülmenstädt, J; Mukherjee, A; Muller, Th; Mumford, R; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Nagano, A; Naganoma, J; Nakamura, K; Nakano, I; Napier, A; Necula, V; Nett, J; Neu, C; Neubauer, M S; Neubauer, S; Nielsen, J; Nodulman, L; Norman, M; Norniella, O; Nurse, E; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Griso, S Pagan; Palencia, E; Papadimitriou, V; Papaikonomou, A; Paramonov, A A; Parks, B; Pashapour, S; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Peiffer, T; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Pianori, E; Pinera, L; Pitts, K; Plager, C; Pondrom, L; Poukhov, O; Pounder, N; Prakoshyn, F; Pronko, A; Proudfoot, J; Ptohos, F; Pueschel, E; Punzi, G; Pursley, J; Rademacker, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Redondo, I; Rekovic, V; Renton, P; Renz, M; Rescigno, M; Richter, S; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rodriguez, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rossin, R; Roy, P; Ruiz, A; Russ, J; Rusu, V; Safonov, A; Sakumoto, W K; Saltó, O; Santi, L; Sarkar, S; Sartori, L; Sato, K; Savoy-Navarro, A; Schlabach, P; Schmidt, A; Schmidt, E E; Schmidt, M A; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sexton-Kennedy, L; Sforza, F; Sfyrla, A; Shalhout, S Z; Shears, T; Shepard, P F; Shimojima, M; Shiraishi, S; Shochet, M; Shon, Y; Shreyber, I; Sidoti, A; Sinervo, P; Sisakyan, A; Slaughter, A J; Slaunwhite, J; Sliwa, K; Smith, J R; Snider, F D; Snihur, R; Soha, A; Somalwar, S; Sorin, V; Spalding, J; Spreitzer, T; Squillacioti, P; Stanitzki, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Strycker, G L; Stuart, D; Suh, J S; Sukhanov, A; Suslov, I; Suzuki, T; Taffard, A; Takashima, R; Takeuchi, Y; Tanaka, R; Tecchio, M; Teng, P K; Terashi, K; Thom, J; Thompson, A S; Thompson, G A; Thomson, E; Tipton, P; Ttito-Guzmán, P; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Tourneur, S; Trovato, M; Tsai, S-Y; Tu, Y; Turini, N; Ukegawa, F; Vallecorsa, S; van Remortel, N; Varganov, A; Vataga, E; Vázquez, F; Velev, G; Vellidis, C; Veszpremi, V; Vidal, M; Vidal, R; Vila, I; Vilar, R; Vine, T; Vogel, M; Volobouev, I; Volpi, G; Wagner, P; Wagner, R G; Wagner, R L; Wagner, W; Wagner-Kuhr, J; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Weinberger, M; Weinelt, J; Wester Iii, W C; Whitehouse, B; Whiteson, D; Wicklund, A B; Wicklund, E; Wilbur, S; Williams, G; Williams, H H; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, C; Wright, T; Wu, X; Würthwein, F; Wynne, S M; Xie, S; Yagil, A; Yamamoto, K; Yamaoka, J; Yang, U K; Yang, Y C; Yao, W M; Yeh, G P; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanello, L; Zanetti, A; Zhang, X; Zheng, Y; Zucchelli, S

2009-01-16

We present a search for a Higgs boson decaying to two W bosons in pp[over ] collisions at sqrt[s]=1.96 TeV center-of-mass energy. The data sample corresponds to an integrated luminosity of 3.0 fb;(-1) collected with the CDF II detector. We find no evidence for production of a Higgs boson with mass between 110 and 200 GeV/c;(2), and determine upper limits on the production cross section. For the mass of 160 GeV/c;(2), where the analysis is most sensitive, the observed (expected) limit is 0.7 pb (0.9 pb) at 95% Bayesian credibility level which is 1.7 (2.2) times the standard model cross section.

Bayesian model selection validates a biokinetic model for zirconium processing in humans

PubMed Central

2012-01-01

Background In radiation protection, biokinetic models for zirconium processing are of crucial importance in dose estimation and further risk analysis for humans exposed to this radioactive substance. They provide limiting values of detrimental effects and build the basis for applications in internal dosimetry, the prediction for radioactive zirconium retention in various organs as well as retrospective dosimetry. Multi-compartmental models are the tool of choice for simulating the processing of zirconium. Although easily interpretable, determining the exact compartment structure and interaction mechanisms is generally daunting. In the context of observing the dynamics of multiple compartments, Bayesian methods provide efficient tools for model inference and selection. Results We are the first to apply a Markov chain Monte Carlo approach to compute Bayes factors for the evaluation of two competing models for zirconium processing in the human body after ingestion. Based on in vivo measurements of human plasma and urine levels we were able to show that a recently published model is superior to the standard model of the International Commission on Radiological Protection. The Bayes factors were estimated by means of the numerically stable thermodynamic integration in combination with a recently developed copula-based Metropolis-Hastings sampler. Conclusions In contrast to the standard model the novel model predicts lower accretion of zirconium in bones. This results in lower levels of noxious doses for exposed individuals. Moreover, the Bayesian approach allows for retrospective dose assessment, including credible intervals for the initially ingested zirconium, in a significantly more reliable fashion than previously possible. All methods presented here are readily applicable to many modeling tasks in systems biology. PMID:22863152

A computer program for uncertainty analysis integrating regression and Bayesian methods

USGS Publications Warehouse

Lu, Dan; Ye, Ming; Hill, Mary C.; Poeter, Eileen P.; Curtis, Gary

2014-01-01

This work develops a new functionality in UCODE_2014 to evaluate Bayesian credible intervals using the Markov Chain Monte Carlo (MCMC) method. The MCMC capability in UCODE_2014 is based on the FORTRAN version of the differential evolution adaptive Metropolis (DREAM) algorithm of Vrugt et al. (2009), which estimates the posterior probability density function of model parameters in high-dimensional and multimodal sampling problems. The UCODE MCMC capability provides eleven prior probability distributions and three ways to initialize the sampling process. It evaluates parametric and predictive uncertainties and it has parallel computing capability based on multiple chains to accelerate the sampling process. This paper tests and demonstrates the MCMC capability using a 10-dimensional multimodal mathematical function, a 100-dimensional Gaussian function, and a groundwater reactive transport model. The use of the MCMC capability is made straightforward and flexible by adopting the JUPITER API protocol. With the new MCMC capability, UCODE_2014 can be used to calculate three types of uncertainty intervals, which all can account for prior information: (1) linear confidence intervals which require linearity and Gaussian error assumptions and typically 10s–100s of highly parallelizable model runs after optimization, (2) nonlinear confidence intervals which require a smooth objective function surface and Gaussian observation error assumptions and typically 100s–1,000s of partially parallelizable model runs after optimization, and (3) MCMC Bayesian credible intervals which require few assumptions and commonly 10,000s–100,000s or more partially parallelizable model runs. Ready access allows users to select methods best suited to their work, and to compare methods in many circumstances.

Modeling epilepsy disparities among ethnic groups in Philadelphia, PA

PubMed Central

Wheeler, David C.; Waller, Lance A.; Elliott, John O.

2014-01-01

SUMMARY The Centers for Disease Control and Prevention defined epilepsy as an emerging public health issue in a recent report and emphasized the importance of epilepsy studies in minorities and people of low socioeconomic status. Previous research has suggested that the incidence rate for epilepsy is positively associated with various measures of social and economic disadvantage. In response, we utilize hierarchical Bayesian models to analyze health disparities in epilepsy and seizure risks among multiple ethnicities in the city of Philadelphia, Pennsylvania. The goals of the analysis are to highlight any overall significant disparities in epilepsy risks between the populations of Caucasians, African Americans, and Hispanics in the study area during the years 2002–2004 and to visualize the spatial pattern of epilepsy risks by ethnicity to indicate where certain ethnic populations were most adversely affected by epilepsy within the study area. Results of the Bayesian model indicate that Hispanics have the highest epilepsy risk overall, followed by African Americans, and then Caucasians. There are significant increases in relative risk for both African Americans and Hispanics when compared with Caucasians, as indicated by the posterior mean estimates of 2.09 with a 95 per cent credible interval of (1.67, 2.62) for African Americans and 2.97 with a 95 per cent credible interval of (2.37, 3.71) for Hispanics. Results also demonstrate that using a Bayesian analysis in combination with geographic information system (GIS) technology can reveal spatial patterns in patient data and highlight areas of disparity in epilepsy risk among subgroups of the population. PMID:18381676

Bayesian stock assessment of Pacific herring in Prince William Sound, Alaska.

PubMed

Muradian, Melissa L; Branch, Trevor A; Moffitt, Steven D; Hulson, Peter-John F

2017-01-01

The Pacific herring (Clupea pallasii) population in Prince William Sound, Alaska crashed in 1993 and has yet to recover, affecting food web dynamics in the Sound and impacting Alaskan communities. To help researchers design and implement the most effective monitoring, management, and recovery programs, a Bayesian assessment of Prince William Sound herring was developed by reformulating the current model used by the Alaska Department of Fish and Game. The Bayesian model estimated pre-fishery spawning biomass of herring age-3 and older in 2013 to be a median of 19,410 mt (95% credibility interval 12,150-31,740 mt), with a 54% probability that biomass in 2013 was below the management limit used to regulate fisheries in Prince William Sound. The main advantages of the Bayesian model are that it can more objectively weight different datasets and provide estimates of uncertainty for model parameters and outputs, unlike the weighted sum-of-squares used in the original model. In addition, the revised model could be used to manage herring stocks with a decision rule that considers both stock status and the uncertainty in stock status.

Bayesian stock assessment of Pacific herring in Prince William Sound, Alaska

PubMed Central

Moffitt, Steven D.; Hulson, Peter-John F.

2017-01-01

The Pacific herring (Clupea pallasii) population in Prince William Sound, Alaska crashed in 1993 and has yet to recover, affecting food web dynamics in the Sound and impacting Alaskan communities. To help researchers design and implement the most effective monitoring, management, and recovery programs, a Bayesian assessment of Prince William Sound herring was developed by reformulating the current model used by the Alaska Department of Fish and Game. The Bayesian model estimated pre-fishery spawning biomass of herring age-3 and older in 2013 to be a median of 19,410 mt (95% credibility interval 12,150–31,740 mt), with a 54% probability that biomass in 2013 was below the management limit used to regulate fisheries in Prince William Sound. The main advantages of the Bayesian model are that it can more objectively weight different datasets and provide estimates of uncertainty for model parameters and outputs, unlike the weighted sum-of-squares used in the original model. In addition, the revised model could be used to manage herring stocks with a decision rule that considers both stock status and the uncertainty in stock status. PMID:28222151

Joint-level energetics differentiate isoinertial from speed-power resistance training-a Bayesian analysis.

PubMed

Liew, Bernard X W; Drovandi, Christopher C; Clifford, Samuel; Keogh, Justin W L; Morris, Susan; Netto, Kevin

2018-01-01

There is convincing evidence for the benefits of resistance training on vertical jump improvements, but little evidence to guide optimal training prescription. The inability to detect small between modality effects may partially reflect the use of ANOVA statistics. This study represents the results of a sub-study from a larger project investigating the effects of two resistance training methods on load carriage running energetics. Bayesian statistics were used to compare the effectiveness of isoinertial resistance against speed-power training to change countermovement jump (CMJ) and squat jump (SJ) height, and joint energetics. Active adults were randomly allocated to either a six-week isoinertial ( n  = 16; calf raises, leg press, and lunge), or a speed-power training program ( n  = 14; countermovement jumps, hopping, with hip flexor training to target pre-swing running energetics). Primary outcome variables included jump height and joint power. Bayesian mixed modelling and Functional Data Analysis were used, where significance was determined by a non-zero crossing of the 95% Bayesian Credible Interval (CrI). The gain in CMJ height after isoinertial training was 1.95 cm (95% CrI [0.85-3.04] cm) greater than the gain after speed-power training, but the gain in SJ height was similar between groups. In the CMJ, isoinertial training produced a larger increase in power absorption at the hip by a mean 0.018% (equivalent to 35 W) (95% CrI [0.007-0.03]), knee by 0.014% (equivalent to 27 W) (95% CrI [0.006-0.02]) and foot by 0.011% (equivalent to 21 W) (95% CrI [0.005-0.02]) compared to speed-power training. Short-term isoinertial training improved CMJ height more than speed-power training. The principle adaptive difference between training modalities was at the level of hip, knee and foot power absorption.

Bayesian Parameter Inference and Model Selection by Population Annealing in Systems Biology

PubMed Central

Murakami, Yohei

2014-01-01

Parameter inference and model selection are very important for mathematical modeling in systems biology. Bayesian statistics can be used to conduct both parameter inference and model selection. Especially, the framework named approximate Bayesian computation is often used for parameter inference and model selection in systems biology. However, Monte Carlo methods needs to be used to compute Bayesian posterior distributions. In addition, the posterior distributions of parameters are sometimes almost uniform or very similar to their prior distributions. In such cases, it is difficult to choose one specific value of parameter with high credibility as the representative value of the distribution. To overcome the problems, we introduced one of the population Monte Carlo algorithms, population annealing. Although population annealing is usually used in statistical mechanics, we showed that population annealing can be used to compute Bayesian posterior distributions in the approximate Bayesian computation framework. To deal with un-identifiability of the representative values of parameters, we proposed to run the simulations with the parameter ensemble sampled from the posterior distribution, named “posterior parameter ensemble”. We showed that population annealing is an efficient and convenient algorithm to generate posterior parameter ensemble. We also showed that the simulations with the posterior parameter ensemble can, not only reproduce the data used for parameter inference, but also capture and predict the data which was not used for parameter inference. Lastly, we introduced the marginal likelihood in the approximate Bayesian computation framework for Bayesian model selection. We showed that population annealing enables us to compute the marginal likelihood in the approximate Bayesian computation framework and conduct model selection depending on the Bayes factor. PMID:25089832

A Bayesian Approach for Summarizing and Modeling Time-Series Exposure Data with Left Censoring.

PubMed

Houseman, E Andres; Virji, M Abbas

2017-08-01

Direct reading instruments are valuable tools for measuring exposure as they provide real-time measurements for rapid decision making. However, their use is limited to general survey applications in part due to issues related to their performance. Moreover, statistical analysis of real-time data is complicated by autocorrelation among successive measurements, non-stationary time series, and the presence of left-censoring due to limit-of-detection (LOD). A Bayesian framework is proposed that accounts for non-stationary autocorrelation and LOD issues in exposure time-series data in order to model workplace factors that affect exposure and estimate summary statistics for tasks or other covariates of interest. A spline-based approach is used to model non-stationary autocorrelation with relatively few assumptions about autocorrelation structure. Left-censoring is addressed by integrating over the left tail of the distribution. The model is fit using Markov-Chain Monte Carlo within a Bayesian paradigm. The method can flexibly account for hierarchical relationships, random effects and fixed effects of covariates. The method is implemented using the rjags package in R, and is illustrated by applying it to real-time exposure data. Estimates for task means and covariates from the Bayesian model are compared to those from conventional frequentist models including linear regression, mixed-effects, and time-series models with different autocorrelation structures. Simulations studies are also conducted to evaluate method performance. Simulation studies with percent of measurements below the LOD ranging from 0 to 50% showed lowest root mean squared errors for task means and the least biased standard deviations from the Bayesian model compared to the frequentist models across all levels of LOD. In the application, task means from the Bayesian model were similar to means from the frequentist models, while the standard deviations were different. Parameter estimates for covariates were significant in some frequentist models, but in the Bayesian model their credible intervals contained zero; such discrepancies were observed in multiple datasets. Variance components from the Bayesian model reflected substantial autocorrelation, consistent with the frequentist models, except for the auto-regressive moving average model. Plots of means from the Bayesian model showed good fit to the observed data. The proposed Bayesian model provides an approach for modeling non-stationary autocorrelation in a hierarchical modeling framework to estimate task means, standard deviations, quantiles, and parameter estimates for covariates that are less biased and have better performance characteristics than some of the contemporary methods. Published by Oxford University Press on behalf of the British Occupational Hygiene Society 2017.

Search for a Higgs Boson in the Diphoton Final State in p-pbar Collisions at \\(\\sqrt{s}=1.96\\) TeV

DOE PAGES

Aaltonen, T.

2012-01-04

A search for a narrow Higgs boson resonance in the diphoton mass spectrum is presented based on data corresponding to 7.0 fb -1 of integrated luminosity from pp⁻ collisions at \\(\\sqrt{s}=1.96\\) TeV collected by the CDF experiment. No evidence of such a resonance is observed, and upper limits are set on the cross section times branching ratio of the resonant state as a function of Higgs boson mass. The limits are interpreted in the context of the standard model and one fermiophobic benchmark model where the data exclude fermiophobic Higgs bosons with masses below 114 GeV/c 2 at a 95%more » Bayesian credibility level.« less

Search for a Higgs boson in the diphoton final state in pp collisions at sqrt[s]=1.96  TeV.

PubMed

Aaltonen, T; Alvarez González, B; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Appel, J A; Apresyan, A; Arisawa, T; Artikov, A; Asaadi, J; Ashmanskas, W; Auerbach, B; Aurisano, A; Azfar, F; Badgett, W; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Barria, P; Bartos, P; Bauce, M; Bauer, G; Bedeschi, F; Beecher, D; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Bhatti, A; Binkley, M; Bisello, D; Bizjak, I; Bland, K R; Blumenfeld, B; Bocci, A; Bodek, A; Bortoletto, D; Boudreau, J; Boveia, A; Brigliadori, L; Brisuda, A; Bromberg, C; Brucken, E; Bucciantonio, M; Budagov, J; Budd, H S; Budd, S; Burkett, K; Busetto, G; Bussey, P; Buzatu, A; Calancha, C; Camarda, S; Campanelli, M; Campbell, M; Canelli, F; Carls, B; Carlsmith, D; Carosi, R; Carrillo, S; Carron, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Chlebana, F; Cho, K; Chokheli, D; Chou, J P; Chung, W H; Chung, Y S; Ciobanu, C I; Ciocci, M A; Clark, A; Clarke, C; Compostella, G; Convery, M E; Conway, J; Corbo, M; Cordelli, M; Cox, C A; Cox, D J; Crescioli, F; Cuenca Almenar, C; Cuevas, J; Culbertson, R; Dagenhart, D; d'Ascenzo, N; Datta, M; de Barbaro, P; De Cecco, S; De Lorenzo, G; Dell'orso, M; Deluca, C; Demortier, L; Deng, J; Deninno, M; Devoto, F; d'Errico, M; Di Canto, A; Di Ruzza, B; Dittmann, J R; D'Onofrio, M; Donati, S; Dong, P; Dorigo, M; Dorigo, T; Ebina, K; Elagin, A; Eppig, A; Erbacher, R; Errede, D; Errede, S; Ershaidat, N; Eusebi, R; Fang, H C; Farrington, S; Feindt, M; Fernandez, J P; Ferrazza, C; Field, R; Flanagan, G; Forrest, R; Frank, M J; Franklin, M; Freeman, J C; Funakoshi, Y; Furic, I; Gallinaro, M; Galyardt, J; Garcia, J E; Garfinkel, A F; Garosi, P; Gerberich, H; Gerchtein, E; Giagu, S; Giakoumopoulou, V; Giannetti, P; Gibson, K; Ginsburg, C M; Giokaris, N; Giromini, P; Giunta, M; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldin, D; Goldschmidt, N; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González, O; Gorelov, I; Goshaw, A T; Goulianos, K; Grinstein, S; Grosso-Pilcher, C; Group, R C; Guimaraes da Costa, J; Gunay-Unalan, Z; Haber, C; Hahn, S R; Halkiadakis, E; Hamaguchi, A; Han, J Y; Happacher, F; Hara, K; Hare, D; Hare, M; Harr, R F; Hatakeyama, K; Hays, C; Heck, M; Heinrich, J; Herndon, M; Hewamanage, S; Hidas, D; Hocker, A; Hopkins, W; Horn, D; Hou, S; Hughes, R E; Hurwitz, M; Husemann, U; Hussain, N; Hussein, M; Huston, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jang, D; Jayatilaka, B; Jeon, E J; Jha, M K; Jindariani, S; Johnson, W; Jones, M; Joo, K K; Jun, S Y; Junk, T R; Kamon, T; Karchin, P E; Kasmi, A; Kato, Y; Ketchum, W; Keung, J; Khotilovich, V; Kilminster, B; Kim, D H; Kim, H S; Kim, H W; Kim, J E; Kim, M J; Kim, S B; Kim, S H; Kim, Y K; Kimura, N; Kirby, M; Klimenko, S; Kondo, K; Kong, D J; Konigsberg, J; Kotwal, A V; Kreps, M; Kroll, J; Krop, D; Krumnack, N; Kruse, M; Krutelyov, V; Kuhr, T; Kurata, M; Kwang, S; Laasanen, A T; Lami, S; Lammel, S; Lancaster, M; Lander, R L; Lannon, K; Lath, A; Latino, G; Lecompte, T; Lee, E; Lee, H S; Lee, J S; Lee, S W; Leo, S; Leone, S; Lewis, J D; Limosani, A; Lin, C-J; Linacre, J; Lindgren, M; Lipeles, E; Lister, A; Litvintsev, D O; Liu, C; Liu, Q; Liu, T; Lockwitz, S; Loginov, A; Lucchesi, D; Lueck, J; Lujan, P; Lukens, P; Lungu, G; Lys, J; Lysak, R; Madrak, R; Maeshima, K; Makhoul, K; Malik, S; Manca, G; Manousakis-Katsikakis, A; Margaroli, F; Marino, C; Martínez, M; Martínez-Ballarín, R; Mastrandrea, P; Mattson, M E; Mazzanti, P; McFarland, K S; McIntyre, P; McNulty, R; Mehta, A; Mehtala, P; Menzione, A; Mesropian, C; Miao, T; Mietlicki, D; Mitra, A; Miyake, H; Moed, S; Moggi, N; Mondragon, M N; Moon, C S; Moore, R; Morello, M J; Morlock, J; Movilla Fernandez, P; Mukherjee, A; Muller, Th; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Naganoma, J; Nakano, I; Napier, A; Nett, J; Neu, C; Neubauer, M S; Nielsen, J; Nodulman, L; Norniella, O; Nurse, E; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Ortolan, L; Pagan Griso, S; Pagliarone, C; Palencia, E; Papadimitriou, V; Paramonov, A A; Patrick, J; Pauletta, G; Paulini, M; Paus, C; Pellett, D E; Penzo, A; Phillips, T J; Piacentino, G; Pianori, E; Pilot, J; Pitts, K; Plager, C; Pondrom, L; Poprocki, S; Potamianos, K; Poukhov, O; Prokoshin, F; Pronko, A; Ptohos, F; Pueschel, E; Punzi, G; Pursley, J; Rahaman, A; Ramakrishnan, V; Ranjan, N; Ray, J; Redondo, I; Renton, P; Rescigno, M; Riddick, T; Rimondi, F; Ristori, L; Robson, A; Rodrigo, T; Rodriguez, T; Rogers, E; Rolli, S; Roser, R; Rossi, M; Rubbo, F; Ruffini, F; Ruiz, A; Russ, J; Rusu, V; Safonov, A; Sakumoto, W K; Sakurai, Y; Santi, L; Sartori, L; Sato, K; Saveliev, V; Savoy-Navarro, A; Schlabach, P; Schmidt, A; Schmidt, E E; Schmidt, M P; Schmitt, M; Schwarz, T; Scodellaro, L; Scribano, A; Scuri, F; Sedov, A; Seidel, S; Seiya, Y; Semenov, A; Sforza, F; Sfyrla, A; Shalhout, S Z; Shears, T; Shepard, P F; Shimojima, M; Shiraishi, S; Shochet, M; Shreyber, I; Simonenko, A; Sinervo, P; Sissakian, A; Sliwa, K; Smith, J R; Snider, F D; Soha, A; Somalwar, S; Sorin, V; Squillacioti, P; Stancari, M; Stanitzki, M; St Denis, R; Stelzer, B; Stelzer-Chilton, O; Stentz, D; Strologas, J; Strycker, G L; Sudo, Y; Sukhanov, A; Suslov, I; Takemasa, K; Takeuchi, Y; Tang, J; Tecchio, M; Teng, P K; Thom, J; Thome, J; Thompson, G A; Thomson, E; Ttito-Guzmán, P; Tkaczyk, S; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Trovato, M; Tu, Y; Ukegawa, F; Uozumi, S; Varganov, A; Vázquez, F; Velev, G; Vellidis, C; Vidal, M; Vila, I; Vilar, R; Vizán, J; Vogel, M; Volpi, G; Wagner, P; Wagner, R L; Wakisaka, T; Wallny, R; Wang, S M; Warburton, A; Waters, D; Weinberger, M; Wester, W C; Whitehouse, B; Whiteson, D; Wicklund, A B; Wicklund, E; Wilbur, S; Wick, F; Williams, H H; Wilson, J S; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, H; Wright, T; Wu, X; Wu, Z; Yamamoto, K; Yamaoka, J; Yang, T; Yang, U K; Yang, Y C; Yao, W-M; Yeh, G P; Yi, K; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Yu, S S; Yun, J C; Zanetti, A; Zeng, Y; Zucchelli, S

2012-01-06

A search for a narrow Higgs boson resonance in the diphoton mass spectrum is presented based on data corresponding to 7.0  fb{-1} of integrated luminosity from pp collisions at sqrt[s]=1.96  TeV collected by the CDF experiment. No evidence of such a resonance is observed, and upper limits are set on the cross section times branching ratio of the resonant state as a function of Higgs boson mass. The limits are interpreted in the context of the standard model and one fermiophobic benchmark model where the data exclude fermiophobic Higgs bosons with masses below 114  GeV/c{2} at a 95% Bayesian credibility level.

Bayesian estimation of the sensitivity and specificity of individual fecal culture and Paralisa to detect Mycobacterium avium subspecies paratuberculosis infection in young farmed deer.

PubMed

Stringer, Lesley A; Jones, Geoff; Jewell, Chris P; Noble, Alasdair D; Heuer, Cord; Wilson, Peter R; Johnson, Wesley O

2013-11-01

A Bayesian latent class model was used to estimate the sensitivity and specificity of an immunoglobulin G1 serum enzyme-linked immunosorbent assay (Paralisa) and individual fecal culture to detect young deer infected with Mycobacterium avium subsp. paratuberculosis. Paired fecal and serum samples were collected, between July 2009 and April 2010, from 20 individual yearling (12-24-month-old) deer in each of 20 South Island and 18 North Island herds in New Zealand and subjected to culture and Paralisa, respectively. Two fecal samples and 16 serum samples from 356 North Island deer, and 55 fecal and 37 serum samples from 401 South Island deer, were positive. The estimate of individual fecal culture sensitivity was 77% (95% credible interval [CI] = 61-92%) with specificity of 99% (95% CI = 98-99.7%). The Paralisa sensitivity estimate was 19% (95% CI = 10-30%), with specificity of 94% (95% CI = 93-96%). All estimates were robust to variation of priors and assumptions tested in a sensitivity analysis. The data informs the use of the tests in determining infection status at the individual and herd level.

Applications of Bayesian Procrustes shape analysis to ensemble radar reflectivity nowcast verification

NASA Astrophysics Data System (ADS)

Fox, Neil I.; Micheas, Athanasios C.; Peng, Yuqiang

2016-07-01

This paper introduces the use of Bayesian full Procrustes shape analysis in object-oriented meteorological applications. In particular, the Procrustes methodology is used to generate mean forecast precipitation fields from a set of ensemble forecasts. This approach has advantages over other ensemble averaging techniques in that it can produce a forecast that retains the morphological features of the precipitation structures and present the range of forecast outcomes represented by the ensemble. The production of the ensemble mean avoids the problems of smoothing that result from simple pixel or cell averaging, while producing credible sets that retain information on ensemble spread. Also in this paper, the full Bayesian Procrustes scheme is used as an object verification tool for precipitation forecasts. This is an extension of a previously presented Procrustes shape analysis based verification approach into a full Bayesian format designed to handle the verification of precipitation forecasts that match objects from an ensemble of forecast fields to a single truth image. The methodology is tested on radar reflectivity nowcasts produced in the Warning Decision Support System - Integrated Information (WDSS-II) by varying parameters in the K-means cluster tracking scheme.

Bayesian approach to the assessment of the population-specific risk of inhibitors in hemophilia A patients: a case study

PubMed Central

Cheng, Ji; Iorio, Alfonso; Marcucci, Maura; Romanov, Vadim; Pullenayegum, Eleanor M; Marshall, John K; Thabane, Lehana

2016-01-01

Background Developing inhibitors is a rare event during the treatment of hemophilia A. The multifacets and uncertainty surrounding the development of inhibitors further complicate the process of estimating inhibitor rate from the limited data. Bayesian statistical modeling provides a useful tool in generating, enhancing, and exploring the evidence through incorporating all the available information. Methods We built our Bayesian analysis using three study cases to estimate the inhibitor rates of patients with hemophilia A in three different scenarios: Case 1, a single cohort of previously treated patients (PTPs) or previously untreated patients; Case 2, a meta-analysis of PTP cohorts; and Case 3, a previously unexplored patient population – patients with baseline low-titer inhibitor or history of inhibitor development. The data used in this study were extracted from three published ADVATE (antihemophilic factor [recombinant] is a product of Baxter for treating hemophilia A) post-authorization surveillance studies. Noninformative and informative priors were applied to Bayesian standard (Case 1) or random-effects (Case 2 and Case 3) logistic models. Bayesian probabilities of satisfying three meaningful thresholds of the risk of developing a clinical significant inhibitor (10/100, 5/100 [high rates], and 1/86 [the Food and Drug Administration mandated cutoff rate in PTPs]) were calculated. The effect of discounting prior information or scaling up the study data was evaluated. Results Results based on noninformative priors were similar to the classical approach. Using priors from PTPs lowered the point estimate and narrowed the 95% credible intervals (Case 1: from 1.3 [0.5, 2.7] to 0.8 [0.5, 1.1]; Case 2: from 1.9 [0.6, 6.0] to 0.8 [0.5, 1.1]; Case 3: 2.3 [0.5, 6.8] to 0.7 [0.5, 1.1]). All probabilities of satisfying a threshold of 1/86 were above 0.65. Increasing the number of patients by two and ten times substantially narrowed the credible intervals for the single cohort study (1.4 [0.7, 2.3] and 1.4 [1.1, 1.8], respectively). Increasing the number of studies by two and ten times for the multiple study scenarios (Case 2: 1.9 [0.6, 4.0] and 1.9 [1.5, 2.6]; Case 3: 2.4 [0.9, 5.0] and 2.6 [1.9, 3.5], respectively) had a similar effect. Conclusion Bayesian approach as a robust, transparent, and reproducible analytic method can be efficiently used to estimate the inhibitor rate of hemophilia A in complex clinical settings. PMID:27822129

Bayesian approach to the assessment of the population-specific risk of inhibitors in hemophilia A patients: a case study.

PubMed

Cheng, Ji; Iorio, Alfonso; Marcucci, Maura; Romanov, Vadim; Pullenayegum, Eleanor M; Marshall, John K; Thabane, Lehana

2016-01-01

Developing inhibitors is a rare event during the treatment of hemophilia A. The multifacets and uncertainty surrounding the development of inhibitors further complicate the process of estimating inhibitor rate from the limited data. Bayesian statistical modeling provides a useful tool in generating, enhancing, and exploring the evidence through incorporating all the available information. We built our Bayesian analysis using three study cases to estimate the inhibitor rates of patients with hemophilia A in three different scenarios: Case 1, a single cohort of previously treated patients (PTPs) or previously untreated patients; Case 2, a meta-analysis of PTP cohorts; and Case 3, a previously unexplored patient population - patients with baseline low-titer inhibitor or history of inhibitor development. The data used in this study were extracted from three published ADVATE (antihemophilic factor [recombinant] is a product of Baxter for treating hemophilia A) post-authorization surveillance studies. Noninformative and informative priors were applied to Bayesian standard (Case 1) or random-effects (Case 2 and Case 3) logistic models. Bayesian probabilities of satisfying three meaningful thresholds of the risk of developing a clinical significant inhibitor (10/100, 5/100 [high rates], and 1/86 [the Food and Drug Administration mandated cutoff rate in PTPs]) were calculated. The effect of discounting prior information or scaling up the study data was evaluated. Results based on noninformative priors were similar to the classical approach. Using priors from PTPs lowered the point estimate and narrowed the 95% credible intervals (Case 1: from 1.3 [0.5, 2.7] to 0.8 [0.5, 1.1]; Case 2: from 1.9 [0.6, 6.0] to 0.8 [0.5, 1.1]; Case 3: 2.3 [0.5, 6.8] to 0.7 [0.5, 1.1]). All probabilities of satisfying a threshold of 1/86 were above 0.65. Increasing the number of patients by two and ten times substantially narrowed the credible intervals for the single cohort study (1.4 [0.7, 2.3] and 1.4 [1.1, 1.8], respectively). Increasing the number of studies by two and ten times for the multiple study scenarios (Case 2: 1.9 [0.6, 4.0] and 1.9 [1.5, 2.6]; Case 3: 2.4 [0.9, 5.0] and 2.6 [1.9, 3.5], respectively) had a similar effect. Bayesian approach as a robust, transparent, and reproducible analytic method can be efficiently used to estimate the inhibitor rate of hemophilia A in complex clinical settings.

A Bayesian framework for infrasound location

NASA Astrophysics Data System (ADS)

Modrak, Ryan T.; Arrowsmith, Stephen J.; Anderson, Dale N.

2010-04-01

We develop a framework for location of infrasound events using backazimuth and infrasonic arrival times from multiple arrays. Bayesian infrasonic source location (BISL) developed here estimates event location and associated credibility regions. BISL accounts for unknown source-to-array path or phase by formulating infrasonic group velocity as random. Differences between observed and predicted source-to-array traveltimes are partitioned into two additive Gaussian sources, measurement error and model error, the second of which accounts for the unknown influence of wind and temperature on path. By applying the technique to both synthetic tests and ground-truth events, we highlight the complementary nature of back azimuths and arrival times for estimating well-constrained event locations. BISL is an extension to methods developed earlier by Arrowsmith et al. that provided simple bounds on location using a grid-search technique.

Dose-Finding Study of Omeprazole on Gastric pH in Neonates with Gastro-Esophageal Acid Reflux Using a Bayesian Sequential Approach.

PubMed

Kaguelidou, Florentia; Alberti, Corinne; Biran, Valerie; Bourdon, Olivier; Farnoux, Caroline; Zohar, Sarah; Jacqz-Aigrain, Evelyne

2016-01-01

Proton pump inhibitors are frequently administered on clinical symptoms in neonates but benefit remains controversial. Clinical trials validating omeprazole dosage in neonates are limited. The objective of this trial was to determine the minimum effective dose (MED) of omeprazole to treat pathological acid reflux in neonates using reflux index as surrogate marker. Double blind dose-finding trial with continual reassessment method of individual dose administration using a Bayesian approach, aiming to select drug dose as close as possible to the predefined target level of efficacy (with a credibility interval of 95%). Neonatal Intensive Care unit of the Robert Debré University Hospital in Paris, France. Neonates with a postmenstrual age ≥ 35 weeks and a pathologic 24-hour intra-esophageal pH monitoring defined by a reflux index ≥ 5% over 24 hours were considered for participation. Recruitment was stratified to 3 groups according to gestational age at birth. Five preselected doses of oral omeprazole from 1 to 3 mg/kg/day. Primary outcome, measured at 35 weeks postmenstrual age or more, was a reflux index <5% during the 24-h pH monitoring registered 72±24 hours after omeprazole initiation. Fifty-four neonates with a reflux index ranging from 5.06 to 27.7% were included. Median age was 37.5 days and median postmenstrual age was 36 weeks. In neonates born at less than 32 weeks of GA (n = 30), the MED was 2.5mg/kg/day with an estimated mean posterior probability of success of 97.7% (95% credibility interval: 90.3-99.7%). The MED was 1mg/kg/day for neonates born at more than 32 GA (n = 24). Omeprazole is extensively prescribed on clinical symptoms but efficacy is not demonstrated while safety concerns do exist. When treatment is required, the daily dose needs to be validated in preterm and term neonates. Optimal doses of omeprazole to increase gastric pH and decrease reflux index below 5% over 24 hours, determined using an adaptive Bayesian design differ among neonates. Both gestational and postnatal ages account for these differences but their differential impact on omeprazole doses remains to be determined.

Inverse analysis and regularisation in conditional source-term estimation modelling

NASA Astrophysics Data System (ADS)

Labahn, Jeffrey W.; Devaud, Cecile B.; Sipkens, Timothy A.; Daun, Kyle J.

2014-05-01

Conditional Source-term Estimation (CSE) obtains the conditional species mass fractions by inverting a Fredholm integral equation of the first kind. In the present work, a Bayesian framework is used to compare two different regularisation methods: zeroth-order temporal Tikhonov regulatisation and first-order spatial Tikhonov regularisation. The objectives of the current study are: (i) to elucidate the ill-posedness of the inverse problem; (ii) to understand the origin of the perturbations in the data and quantify their magnitude; (iii) to quantify the uncertainty in the solution using different priors; and (iv) to determine the regularisation method best suited to this problem. A singular value decomposition shows that the current inverse problem is ill-posed. Perturbations to the data may be caused by the use of a discrete mixture fraction grid for calculating the mixture fraction PDF. The magnitude of the perturbations is estimated using a box filter and the uncertainty in the solution is determined based on the width of the credible intervals. The width of the credible intervals is significantly reduced with the inclusion of a smoothing prior and the recovered solution is in better agreement with the exact solution. The credible intervals for temporal and spatial smoothing are shown to be similar. Credible intervals for temporal smoothing depend on the solution from the previous time step and a smooth solution is not guaranteed. For spatial smoothing, the credible intervals are not dependent upon a previous solution and better predict characteristics for higher mixture fraction values. These characteristics make spatial smoothing a promising alternative method for recovering a solution from the CSE inversion process.

Demography and population status of polar bears in western Hudson Bay

USGS Publications Warehouse

Lunn, Nicholas J.; Regher, Eric V; Servanty, Sabrina; Converse, Sarah J.; Richardson, Evan S.; Stirling, Ian

2013-01-01

The 2011 abundance estimate from this analysis was 806 bears with a 95% Bayesian credible interval of 653-984. This is lower than, but broadly consistent with, the abundance estimate of 1,030 (95% confidence interval = 745-1406) from a 2011 aerial survey (Stapleton et al. 2014). The capture-recapture and aerial survey approaches have different spatial and temporal coverage of the WH subpopulation and, consequently, the effective study population considered by each approach is different.

Bayesian approach to estimate AUC, partition coefficient and drug targeting index for studies with serial sacrifice design.

PubMed

Wang, Tianli; Baron, Kyle; Zhong, Wei; Brundage, Richard; Elmquist, William

2014-03-01

The current study presents a Bayesian approach to non-compartmental analysis (NCA), which provides the accurate and precise estimate of AUC 0 (∞) and any AUC 0 (∞) -based NCA parameter or derivation. In order to assess the performance of the proposed method, 1,000 simulated datasets were generated in different scenarios. A Bayesian method was used to estimate the tissue and plasma AUC 0 (∞) s and the tissue-to-plasma AUC 0 (∞) ratio. The posterior medians and the coverage of 95% credible intervals for the true parameter values were examined. The method was applied to laboratory data from a mice brain distribution study with serial sacrifice design for illustration. Bayesian NCA approach is accurate and precise in point estimation of the AUC 0 (∞) and the partition coefficient under a serial sacrifice design. It also provides a consistently good variance estimate, even considering the variability of the data and the physiological structure of the pharmacokinetic model. The application in the case study obtained a physiologically reasonable posterior distribution of AUC, with a posterior median close to the value estimated by classic Bailer-type methods. This Bayesian NCA approach for sparse data analysis provides statistical inference on the variability of AUC 0 (∞) -based parameters such as partition coefficient and drug targeting index, so that the comparison of these parameters following destructive sampling becomes statistically feasible.

Association between Pesticide Profiles Used on Agricultural Fields near Maternal Residences during Pregnancy and IQ at Age 7 Years.

PubMed

Coker, Eric; Gunier, Robert; Bradman, Asa; Harley, Kim; Kogut, Katherine; Molitor, John; Eskenazi, Brenda

2017-05-09

We previously showed that potential prenatal exposure to agricultural pesticides was associated with adverse neurodevelopmental outcomes in children, yet the effects of joint exposure to multiple pesticides is poorly understood. In this paper, we investigate associations between the joint distribution of agricultural use patterns of multiple pesticides (denoted as "pesticide profiles") applied near maternal residences during pregnancy and Full-Scale Intelligence Quotient (FSIQ) at 7 years of age. Among a cohort of children residing in California's Salinas Valley, we used Pesticide Use Report (PUR) data to characterize potential exposure from use within 1 km of maternal residences during pregnancy for 15 potentially neurotoxic pesticides from five different chemical classes. We used Bayesian profile regression (BPR) to examine associations between clustered pesticide profiles and deficits in childhood FSIQ. BPR identified eight distinct clusters of prenatal pesticide profiles. Two of the pesticide profile clusters exhibited some of the highest cumulative pesticide use levels and were associated with deficits in adjusted FSIQ of -6.9 (95% credible interval: -11.3, -2.2) and -6.4 (95% credible interval: -13.1, 0.49), respectively, when compared with the pesticide profile cluster that showed the lowest level of pesticides use. Although maternal residence during pregnancy near high agricultural use of multiple neurotoxic pesticides was associated with FSIQ deficit, the magnitude of the associations showed potential for sub-additive effects. Epidemiologic analysis of pesticides and their potential health effects can benefit from a multi-pollutant approach to analysis.

A history of chagas disease transmission, control, and re-emergence in peri-rural La Joya, Peru.

PubMed

Delgado, Stephen; Castillo Neyra, Ricardo; Quispe Machaca, Víctor R; Ancca Juárez, Jenny; Chou Chu, Lily; Verastegui, Manuela Renee; Moscoso Apaza, Giovanna M; Bocángel, César D; Tustin, Aaron W; Sterling, Charles R; Comrie, Andrew C; Náquira, César; Cornejo del Carpio, Juan G; Gilman, Robert H; Bern, Caryn; Levy, Michael Z

2011-02-22

The history of Chagas disease control in Peru and many other nations is marked by scattered and poorly documented vector control campaigns. The complexities of human migration and sporadic control campaigns complicate evaluation of the burden of Chagas disease and dynamics of Trypanosoma cruzi transmission. We conducted a cross-sectional serological and entomological study to evaluate temporal and spatial patterns of T. cruzi transmission in a peri-rural region of La Joya, Peru. We use a multivariate catalytic model and Bayesian methods to estimate incidence of infection over time and thereby elucidate the complex history of transmission in the area. Of 1,333 study participants, 101 (7.6%; 95% CI: 6.2-9.0%) were confirmed T. cruzi seropositive. Spatial clustering of parasitic infection was found in vector insects, but not in human cases. Expanded catalytic models suggest that transmission was interrupted in the study area in 1996 (95% credible interval: 1991-2000), with a resultant decline in the average annual incidence of infection from 0.9% (95% credible interval: 0.6-1.3%) to 0.1% (95% credible interval: 0.005-0.3%). Through a search of archival newspaper reports, we uncovered documentation of a 1995 vector control campaign, and thereby independently validated the model estimates. High levels of T. cruzi transmission had been ongoing in peri-rural La Joya prior to interruption of parasite transmission through a little-documented vector control campaign in 1995. Despite the efficacy of the 1995 control campaign, T. cruzi was rapidly reemerging in vector populations in La Joya, emphasizing the need for continuing surveillance and control at the rural-urban interface.

A History of Chagas Disease Transmission, Control, and Re-Emergence in Peri-Rural La Joya, Peru

PubMed Central

Delgado, Stephen; Castillo Neyra, Ricardo; Quispe Machaca, Víctor R.; Ancca Juárez, Jenny; Chou Chu, Lily; Verastegui, Manuela Renee; Moscoso Apaza, Giovanna M.; Bocángel, César D.; Tustin, Aaron W.; Sterling, Charles R.; Comrie, Andrew C.; Náquira, César; Cornejo del Carpio, Juan G.; Gilman, Robert H.; Bern, Caryn; Levy, Michael Z.

2011-01-01

Background The history of Chagas disease control in Peru and many other nations is marked by scattered and poorly documented vector control campaigns. The complexities of human migration and sporadic control campaigns complicate evaluation of the burden of Chagas disease and dynamics of Trypanosoma cruzi transmission. Methodology/Principal Findings We conducted a cross-sectional serological and entomological study to evaluate temporal and spatial patterns of T. cruzi transmission in a peri-rural region of La Joya, Peru. We use a multivariate catalytic model and Bayesian methods to estimate incidence of infection over time and thereby elucidate the complex history of transmission in the area. Of 1,333 study participants, 101 (7.6%; 95% CI: 6.2–9.0%) were confirmed T. cruzi seropositive. Spatial clustering of parasitic infection was found in vector insects, but not in human cases. Expanded catalytic models suggest that transmission was interrupted in the study area in 1996 (95% credible interval: 1991–2000), with a resultant decline in the average annual incidence of infection from 0.9% (95% credible interval: 0.6–1.3%) to 0.1% (95% credible interval: 0.005–0.3%). Through a search of archival newspaper reports, we uncovered documentation of a 1995 vector control campaign, and thereby independently validated the model estimates. Conclusions/Significance High levels of T. cruzi transmission had been ongoing in peri-rural La Joya prior to interruption of parasite transmission through a little-documented vector control campaign in 1995. Despite the efficacy of the 1995 control campaign, T. cruzi was rapidly reemerging in vector populations in La Joya, emphasizing the need for continuing surveillance and control at the rural-urban interface. PMID:21364970

Estimation of divergence from Hardy-Weinberg form.

PubMed

Stark, Alan E

2015-08-01

The Hardy–Weinberg (HW) principle explains how random mating (RM) can produce and maintain a population in equilibrium, that is, with constant genotypic proportions. When proportions diverge from HW form, it is of interest to estimate the fixation index F, which reflects the degree of divergence. Starting from a sample of genotypic counts, a mixed procedure gives first the orthodox estimate of gene frequency q and then a Bayesian estimate of F, based on a credible prior distribution of F, which is described here.

Bayesian dose-response analysis for epidemiological studies with complex uncertainty in dose estimation.

PubMed

Kwon, Deukwoo; Hoffman, F Owen; Moroz, Brian E; Simon, Steven L

2016-02-10

Most conventional risk analysis methods rely on a single best estimate of exposure per person, which does not allow for adjustment for exposure-related uncertainty. Here, we propose a Bayesian model averaging method to properly quantify the relationship between radiation dose and disease outcomes by accounting for shared and unshared uncertainty in estimated dose. Our Bayesian risk analysis method utilizes multiple realizations of sets (vectors) of doses generated by a two-dimensional Monte Carlo simulation method that properly separates shared and unshared errors in dose estimation. The exposure model used in this work is taken from a study of the risk of thyroid nodules among a cohort of 2376 subjects who were exposed to fallout from nuclear testing in Kazakhstan. We assessed the performance of our method through an extensive series of simulations and comparisons against conventional regression risk analysis methods. When the estimated doses contain relatively small amounts of uncertainty, the Bayesian method using multiple a priori plausible draws of dose vectors gave similar results to the conventional regression-based methods of dose-response analysis. However, when large and complex mixtures of shared and unshared uncertainties are present, the Bayesian method using multiple dose vectors had significantly lower relative bias than conventional regression-based risk analysis methods and better coverage, that is, a markedly increased capability to include the true risk coefficient within the 95% credible interval of the Bayesian-based risk estimate. An evaluation of the dose-response using our method is presented for an epidemiological study of thyroid disease following radiation exposure. Copyright © 2015 John Wiley & Sons, Ltd.

A Bayesian approach to meta-analysis of plant pathology studies.

PubMed

Mila, A L; Ngugi, H K

2011-01-01

Bayesian statistical methods are used for meta-analysis in many disciplines, including medicine, molecular biology, and engineering, but have not yet been applied for quantitative synthesis of plant pathology studies. In this paper, we illustrate the key concepts of Bayesian statistics and outline the differences between Bayesian and classical (frequentist) methods in the way parameters describing population attributes are considered. We then describe a Bayesian approach to meta-analysis and present a plant pathological example based on studies evaluating the efficacy of plant protection products that induce systemic acquired resistance for the management of fire blight of apple. In a simple random-effects model assuming a normal distribution of effect sizes and no prior information (i.e., a noninformative prior), the results of the Bayesian meta-analysis are similar to those obtained with classical methods. Implementing the same model with a Student's t distribution and a noninformative prior for the effect sizes, instead of a normal distribution, yields similar results for all but acibenzolar-S-methyl (Actigard) which was evaluated only in seven studies in this example. Whereas both the classical (P = 0.28) and the Bayesian analysis with a noninformative prior (95% credibility interval [CRI] for the log response ratio: -0.63 to 0.08) indicate a nonsignificant effect for Actigard, specifying a t distribution resulted in a significant, albeit variable, effect for this product (CRI: -0.73 to -0.10). These results confirm the sensitivity of the analytical outcome (i.e., the posterior distribution) to the choice of prior in Bayesian meta-analyses involving a limited number of studies. We review some pertinent literature on more advanced topics, including modeling of among-study heterogeneity, publication bias, analyses involving a limited number of studies, and methods for dealing with missing data, and show how these issues can be approached in a Bayesian framework. Bayesian meta-analysis can readily include information not easily incorporated in classical methods, and allow for a full evaluation of competing models. Given the power and flexibility of Bayesian methods, we expect them to become widely adopted for meta-analysis of plant pathology studies.

Bayesian adjustment for measurement error in continuous exposures in an individually matched case-control study.

PubMed

Espino-Hernandez, Gabriela; Gustafson, Paul; Burstyn, Igor

2011-05-14

In epidemiological studies explanatory variables are frequently subject to measurement error. The aim of this paper is to develop a Bayesian method to correct for measurement error in multiple continuous exposures in individually matched case-control studies. This is a topic that has not been widely investigated. The new method is illustrated using data from an individually matched case-control study of the association between thyroid hormone levels during pregnancy and exposure to perfluorinated acids. The objective of the motivating study was to examine the risk of maternal hypothyroxinemia due to exposure to three perfluorinated acids measured on a continuous scale. Results from the proposed method are compared with those obtained from a naive analysis. Using a Bayesian approach, the developed method considers a classical measurement error model for the exposures, as well as the conditional logistic regression likelihood as the disease model, together with a random-effect exposure model. Proper and diffuse prior distributions are assigned, and results from a quality control experiment are used to estimate the perfluorinated acids' measurement error variability. As a result, posterior distributions and 95% credible intervals of the odds ratios are computed. A sensitivity analysis of method's performance in this particular application with different measurement error variability was performed. The proposed Bayesian method to correct for measurement error is feasible and can be implemented using statistical software. For the study on perfluorinated acids, a comparison of the inferences which are corrected for measurement error to those which ignore it indicates that little adjustment is manifested for the level of measurement error actually exhibited in the exposures. Nevertheless, a sensitivity analysis shows that more substantial adjustments arise if larger measurement errors are assumed. In individually matched case-control studies, the use of conditional logistic regression likelihood as a disease model in the presence of measurement error in multiple continuous exposures can be justified by having a random-effect exposure model. The proposed method can be successfully implemented in WinBUGS to correct individually matched case-control studies for several mismeasured continuous exposures under a classical measurement error model.

New-generation stents compared with coronary bypass surgery for unprotected left main disease: A word of caution.

PubMed

Benedetto, Umberto; Taggart, David P; Sousa-Uva, Miguel; Biondi-Zoccai, Giuseppe; Di Franco, Antonino; Ohmes, Lucas B; Rahouma, Mohamed; Kamel, Mohamed; Caputo, Massimo; Girardi, Leonard N; Angelini, Gianni D; Gaudino, Mario

2018-05-01

With the advent of bare metal stents and drug-eluting stents, percutaneous coronary intervention has emerged as an alternative to coronary artery bypass grafting surgery for unprotected left main disease. However, whether the evolution of stents technology has translated into better results after percutaneous coronary intervention remains unclear. We aimed to compare coronary artery bypass grafting with stents of different generations for left main disease by performing a Bayesian network meta-analysis of available randomized controlled trials. All randomized controlled trials with at least 1 arm randomized to percutaneous coronary intervention with stents or coronary artery bypass grafting for left main disease were included. Bare metal stents and drug-eluting stents of first- and second-generation were compared with coronary artery bypass grafting. Poisson methods and Bayesian framework were used to compute the head-to-head incidence rate ratio and 95% credible intervals. Primary end points were the composite of death/myocardial infarction/stroke and repeat revascularization. Nine randomized controlled trials were included in the final analysis. Six trials compared percutaneous coronary intervention with coronary artery bypass grafting (n = 4654), and 3 trials compared different types of stents (n = 1360). Follow-up ranged from 6 months to 5 years. Second-generation drug-eluting stents (incidence rate ratio, 1.3; 95% credible interval, 1.1-1.6), but not bare metal stents (incidence rate ratio, 0.63; 95% credible interval, 0.27-1.4), and first-generation drug-eluting stents (incidence rate ratio, 0.85; 95% credible interval, 0.65-1.1) were associated with a significantly increased risk of death/myocardial infarction/stroke when compared with coronary artery bypass grafting. When compared with coronary artery bypass grafting, the highest risk of repeat revascularization was observed for bare metal stents (hazard ratio, 5.1; 95% confidence interval, 2.1-14), whereas first-generation drug-eluting stents (incidence rate ratio, 1.8; 95% confidence interval, 1.4-2.4) and second-generation drug-eluting stents (incidence rate ratio, 1.8; 95% confidence interval, 1.4-2.4) were comparable. The introduction of new-generation drug-eluting stents did not translate into better outcomes for percutaneous coronary intervention when compared with coronary artery bypass grafting. Copyright © 2017 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Associations between feedlot management practices and bovine respiratory disease in Australian feedlot cattle.

PubMed

Hay, K E; Morton, J M; Clements, A C A; Mahony, T J; Barnes, T S

2016-06-01

Bovine respiratory disease (BRD) is the major cause of clinical disease and death in feedlot cattle. A prospective longitudinal study was conducted in a population of Australian feedlot cattle to assess associations between factors related to feedlot management and risk of BRD. In total, 35,131 animals in 170 pens (cohorts) inducted into 14 feedlots were included in statistical analyses. Causal diagrams were used to inform model building to allow separate estimation of total and direct effects. Multilevel mixed effects logistic regression models were fitted within the Bayesian framework. The placement of pen water troughs such that they could be accessed by animals in adjoining pens was associated with markedly increased risk of BRD (OR 4.3, 95% credible interval: 1.4-10.3). Adding animals to pens over multiple days was associated with increased risk of BRD across all animals in those pens compared to placing all animals in the pen on a single day (total effect: OR 1.9, 95% credible interval: 1.2-2.8). The much attenuated direct effect indicated that this was primarily mediated via factors on indirect pathways so it may be possible to ameliorate the adverse effects of adding animals to pens over multiple days by altering exposure to these intervening factors (e.g. mixing history). In pens in which animals were added to the pen over multiple days, animals added ≥7 days (OR: 0.7, credible interval: 0.5-0.9) or 1-6 days (OR: 0.8, credible interval: 0.7-1.0) before the last animal was added were at modestly reduced risk of BRD compared to the animals that were added to the pen on the latest day. Further research is required to disentangle effects of cohort formation patterns at animal-level and higher levels on animal-level risk of BRD. Vaccination against Bovine herpesvirus 1 at feedlot entry was investigated but results were inconclusive and further research is required to evaluate vaccine efficacy. We conclude that there are practical interventions available to feedlot managers to reduce the risk of cattle developing BRD at the feedlot. We recommend placement of water troughs in feedlot pens so that they cannot be accessed by animals in adjoining pens. Further research is required to identify practical and cost-effective management strategies that allow longer adaption times for cattle identified prior to induction as being at higher risk of developing BRD. Copyright © 2016 Elsevier B.V. All rights reserved.

A Bayesian analysis of trends in ozone sounding data series from 9 Nordic stations

NASA Astrophysics Data System (ADS)

Christiansen, Bo; Jepsen, Nis; Larsen, Niels; Korsholm, Ulrik S.

2016-04-01

Ozone soundings from 9 Nordic stations have been homogenized and interpolated to standard pressure levels. The different stations have very different data coverage; the longest period with data is from the end of the 1980ies to 2013. We apply a model which includes both low-frequency variability in form of a polynomial, an annual cycle with harmonics, the possibility for low-frequency variability in the annual amplitude and phasing, and either white noise or AR1 noise. The fitting of the parameters is performed with a Bayesian approach not only giving the posterior mean values but also credible intervals. We find that all stations agree on an well-defined annual cycle in the free troposphere with a relatively confined maximum in the early summer. Regarding the low-frequency variability we find that Scoresbysund, Ny Aalesund, and Sodankyla show similar structures with a maximum near 2005 followed by a decrease. However, these results are only weakly significant. A significant change in the amplitude of the annual cycle was only found for Ny Aalesund. Here the peak-to-peak amplitude changes from 0.9 to 0.8 mhPa between 1995-2000 and 2007-2012. The results are shown to be robust to the different settings of the model parameters (order of the polynomial, number of harmonics in the annual cycle, type of noise, etc). The results are also shown to be characteristic for all pressure levels in the free troposphere.

Geographic Variation of Overweight and Obesity among Women in Nigeria: A Case for Nutritional Transition in Sub-Saharan Africa

PubMed Central

Kandala, Ngianga-Bakwin; Stranges, Saverio

2014-01-01

Background Nutritional research in sub-Saharan Africa has primarily focused on under-nutrition. However, there is evidence of an ongoing nutritional transition in these settings. This study aimed to examine the geographic variation of overweight and obesity prevalence at the state-level among women in Nigeria, while accounting for individual-level risk factors. Methods The analysis was based on the 2008 Nigerian Demographic and Health Survey (NDHS), including 27,967 women aged 15–49 years. Individual data were collected on socio-demographics, but were aggregated to the country's states. We used a Bayesian geo-additive mixed model to map the geographic distribution of overweight and obesity at the state-level, accounting for individual-level risk factors. Results The overall prevalence of combined overweight and obesity (body mass index ≥25) was 20.9%. In multivariate Bayesian geo-additive models, higher education [odds ratio (OR) & 95% Credible Region (CR): 1.68 (1.38, 2.00)], higher wealth index [3.45 (2.98, 4.05)], living in urban settings [1.24 (1.14, 1.36)] and increasing age were all significantly associated with a higher prevalence of overweight/obesity. There was also a striking variation in overweight/obesity prevalence across ethnic groups and state of residence, the highest being in Cross River State, in south-eastern Nigeria [2.32 (1.62, 3.40)], the lowest in Osun State in south-western Nigeria [0.48 (0.36, 0.61)]. Conclusions This study suggests distinct geographic patterns in the combined prevalence of overweight and obesity among Nigerian women, as well as the role of demographic, socio-economic and environmental factors in the ongoing nutritional transition in these settings. PMID:24979753

Building a Database for a Quantitative Model

NASA Technical Reports Server (NTRS)

Kahn, C. Joseph; Kleinhammer, Roger

2014-01-01

A database can greatly benefit a quantitative analysis. The defining characteristic of a quantitative risk, or reliability, model is the use of failure estimate data. Models can easily contain a thousand Basic Events, relying on hundreds of individual data sources. Obviously, entering so much data by hand will eventually lead to errors. Not so obviously entering data this way does not aid linking the Basic Events to the data sources. The best way to organize large amounts of data on a computer is with a database. But a model does not require a large, enterprise-level database with dedicated developers and administrators. A database built in Excel can be quite sufficient. A simple spreadsheet database can link every Basic Event to the individual data source selected for them. This database can also contain the manipulations appropriate for how the data is used in the model. These manipulations include stressing factors based on use and maintenance cycles, dormancy, unique failure modes, the modeling of multiple items as a single "Super component" Basic Event, and Bayesian Updating based on flight and testing experience. A simple, unique metadata field in both the model and database provides a link from any Basic Event in the model to its data source and all relevant calculations. The credibility for the entire model often rests on the credibility and traceability of the data.

Bayesian Spatiotemporal Pattern and Eco-climatological Drivers of Striped Skunk Rabies in the North Central Plains

PubMed Central

Raghavan, Ram K.; Hanlon, Cathleen A.; Goodin, Douglas G.; Anderson, Gary A.

2016-01-01

Striped skunks are one of the most important terrestrial reservoirs of rabies virus in North America, and yet the prevalence of rabies among this host is only passively monitored and the disease among this host remains largely unmanaged. Oral vaccination campaigns have not efficiently targeted striped skunks, while periodic spillovers of striped skunk variant viruses to other animals, including some domestic animals, are routinely recorded. In this study we evaluated the spatial and spatio-temporal patterns of infection status among striped skunk cases submitted for rabies testing in the North Central Plains of US in a Bayesian hierarchical framework, and also evaluated potential eco-climatological drivers of such patterns. Two Bayesian hierarchical models were fitted to point-referenced striped skunk rabies cases [n = 656 (negative), and n = 310 (positive)] received at a leading rabies diagnostic facility between the years 2007–2013. The first model included only spatial and temporal terms and a second covariate model included additional covariates representing eco-climatic conditions within a 4km2 home-range area for striped skunks. The better performing covariate model indicated the presence of significant spatial and temporal trends in the dataset and identified higher amounts of land covered by low-intensity developed areas [Odds ratio (OR) = 3.41; 95% Bayesian Credible Intervals (CrI) = 2.08, 3.85], higher level of patch fragmentation (OR = 1.70; 95% CrI = 1.25, 2.89), and diurnal temperature range (OR = 0.54; 95% CrI = 0.27, 0.91) to be important drivers of striped skunk rabies incidence in the study area. Model validation statistics indicated satisfactory performance for both models; however, the covariate model fared better. The findings of this study are important in the context of rabies management among striped skunks in North America, and the relevance of physical and climatological factors as risk factors for skunk to human rabies transmission and the space-time patterns of striped skunk rabies are discussed. PMID:27127994

Association between Pesticide Profiles Used on Agricultural Fields near Maternal Residences during Pregnancy and IQ at Age 7 Years

PubMed Central

Coker, Eric; Gunier, Robert; Bradman, Asa; Harley, Kim; Kogut, Katherine; Molitor, John; Eskenazi, Brenda

2017-01-01

We previously showed that potential prenatal exposure to agricultural pesticides was associated with adverse neurodevelopmental outcomes in children, yet the effects of joint exposure to multiple pesticides is poorly understood. In this paper, we investigate associations between the joint distribution of agricultural use patterns of multiple pesticides (denoted as “pesticide profiles”) applied near maternal residences during pregnancy and Full-Scale Intelligence Quotient (FSIQ) at 7 years of age. Among a cohort of children residing in California’s Salinas Valley, we used Pesticide Use Report (PUR) data to characterize potential exposure from use within 1 km of maternal residences during pregnancy for 15 potentially neurotoxic pesticides from five different chemical classes. We used Bayesian profile regression (BPR) to examine associations between clustered pesticide profiles and deficits in childhood FSIQ. BPR identified eight distinct clusters of prenatal pesticide profiles. Two of the pesticide profile clusters exhibited some of the highest cumulative pesticide use levels and were associated with deficits in adjusted FSIQ of −6.9 (95% credible interval: −11.3, −2.2) and −6.4 (95% credible interval: −13.1, 0.49), respectively, when compared with the pesticide profile cluster that showed the lowest level of pesticides use. Although maternal residence during pregnancy near high agricultural use of multiple neurotoxic pesticides was associated with FSIQ deficit, the magnitude of the associations showed potential for sub-additive effects. Epidemiologic analysis of pesticides and their potential health effects can benefit from a multi-pollutant approach to analysis. PMID:28486423

A Bayesian Meta-Analysis on Prevalence of Hepatitis B Virus Infection among Chinese Volunteer Blood Donors

PubMed Central

Liu, Guang-ying; Zheng, Yang; Deng, Yan; Gao, Yan-yan; Wang, Lie

2013-01-01

Background Although transfusion-transmitted infection of hepatitis B virus (HBV) threatens the blood safety of China, the nationwide circumstance of HBV infection among blood donors is still unclear. Objectives To comprehensively estimate the prevalence of HBsAg positive and HBV occult infection (OBI) among Chinese volunteer blood donors through bayesian meta-analysis. Methods We performed an electronic search in Pub-Med, Web of Knowledge, Medline, Wanfang Data and CNKI, complemented by a hand search of relevant reference lists. Two authors independently extracted data from the eligible studies. Then two bayesian random-effect meta-analyses were performed, followed by bayesian meta-regressions. Results 5957412 and 571227 donors were identified in HBsAg group and OBI group, respectively. The pooled prevalence of HBsAg group and OBI group among donors is 1.085% (95% credible interval [CI] 0.859%∼1.398%) and 0.094% (95% CI 0.0578%∼0.1655%). For HBsAg group, subgroup analysis shows the more developed area has a lower prevalence than the less developed area; meta-regression indicates there is a significant decreasing trend in HBsAg positive prevalence with sampling year (beta = −0.1202, 95% −0.2081∼−0.0312). Conclusion Blood safety against HBV infection in China is suffering serious threats and the government should take effective measures to improve this situation. PMID:24236110

A Bayesian Meta-Analysis of the Effect of Alcohol Use on HCV-Treatment Outcomes with a Comparison of Resampling Methods to Assess Uncertainty in Parameter Estimates.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cauthen, Katherine Regina; Lambert, Gregory Joseph; Finley, Patrick D.

There is mounting evidence that alcohol use is significantly linked to lower HCV treatment response rates in interferon-based therapies, though some of the evidence is conflicting. Furthermore, although health care providers recommend reducing or abstaining from alcohol use prior to treatment, many patients do not succeed in doing so. The goal of this meta-analysis was to systematically review and summarize the Englishlanguage literature up through January 30, 2015 regarding the relationship between alcohol use and HCV treatment outcomes, among patients who were not required to abstain from alcohol use in order to receive treatment. Seven pertinent articles studying 1,751 HCV-infectedmore » patients were identified. Log-ORs of HCV treatment response for heavy alcohol use and light alcohol use were calculated and compared. We employed a hierarchical Bayesian meta-analytic model to accommodate the small sample size. The summary estimate for the log-OR of HCV treatment response was -0.775 with a 95% credible interval of (-1.397, -0.236). The results of the Bayesian meta-analysis are slightly more conservative compared to those obtained from a boot-strapped, random effects model. We found evidence of heterogeneity (Q = 14.489, p = 0.025), accounting for 60.28% of the variation among log-ORs. Meta-regression to capture the sources of this heterogeneity did not identify any of the covariates investigated as significant. This meta-analysis confirms that heavy alcohol use is associated with decreased HCV treatment response compared to lighter levels of alcohol use. Further research is required to characterize the mechanism by which alcohol use affects HCV treatment response.« less

Uncertainty analysis of depth predictions from seismic reflection data using Bayesian statistics

NASA Astrophysics Data System (ADS)

Michelioudakis, Dimitrios G.; Hobbs, Richard W.; Caiado, Camila C. S.

2018-03-01

Estimating the depths of target horizons from seismic reflection data is an important task in exploration geophysics. To constrain these depths we need a reliable and accurate velocity model. Here, we build an optimum 2D seismic reflection data processing flow focused on pre - stack deghosting filters and velocity model building and apply Bayesian methods, including Gaussian process emulation and Bayesian History Matching (BHM), to estimate the uncertainties of the depths of key horizons near the borehole DSDP-258 located in the Mentelle Basin, south west of Australia, and compare the results with the drilled core from that well. Following this strategy, the tie between the modelled and observed depths from DSDP-258 core was in accordance with the ± 2σ posterior credibility intervals and predictions for depths to key horizons were made for the two new drill sites, adjacent the existing borehole of the area. The probabilistic analysis allowed us to generate multiple realizations of pre-stack depth migrated images, these can be directly used to better constrain interpretation and identify potential risk at drill sites. The method will be applied to constrain the drilling targets for the upcoming International Ocean Discovery Program (IODP), leg 369.

Uncertainty analysis of depth predictions from seismic reflection data using Bayesian statistics

NASA Astrophysics Data System (ADS)

Michelioudakis, Dimitrios G.; Hobbs, Richard W.; Caiado, Camila C. S.

2018-06-01

Estimating the depths of target horizons from seismic reflection data is an important task in exploration geophysics. To constrain these depths we need a reliable and accurate velocity model. Here, we build an optimum 2-D seismic reflection data processing flow focused on pre-stack deghosting filters and velocity model building and apply Bayesian methods, including Gaussian process emulation and Bayesian History Matching, to estimate the uncertainties of the depths of key horizons near the Deep Sea Drilling Project (DSDP) borehole 258 (DSDP-258) located in the Mentelle Basin, southwest of Australia, and compare the results with the drilled core from that well. Following this strategy, the tie between the modelled and observed depths from DSDP-258 core was in accordance with the ±2σ posterior credibility intervals and predictions for depths to key horizons were made for the two new drill sites, adjacent to the existing borehole of the area. The probabilistic analysis allowed us to generate multiple realizations of pre-stack depth migrated images, these can be directly used to better constrain interpretation and identify potential risk at drill sites. The method will be applied to constrain the drilling targets for the upcoming International Ocean Discovery Program, leg 369.

A Bayesian framework to estimate diversification rates and their variation through time and space

PubMed Central

2011-01-01

Background Patterns of species diversity are the result of speciation and extinction processes, and molecular phylogenetic data can provide valuable information to derive their variability through time and across clades. Bayesian Markov chain Monte Carlo methods offer a promising framework to incorporate phylogenetic uncertainty when estimating rates of diversification. Results We introduce a new approach to estimate diversification rates in a Bayesian framework over a distribution of trees under various constant and variable rate birth-death and pure-birth models, and test it on simulated phylogenies. Furthermore, speciation and extinction rates and their posterior credibility intervals can be estimated while accounting for non-random taxon sampling. The framework is particularly suitable for hypothesis testing using Bayes factors, as we demonstrate analyzing dated phylogenies of Chondrostoma (Cyprinidae) and Lupinus (Fabaceae). In addition, we develop a model that extends the rate estimation to a meta-analysis framework in which different data sets are combined in a single analysis to detect general temporal and spatial trends in diversification. Conclusions Our approach provides a flexible framework for the estimation of diversification parameters and hypothesis testing while simultaneously accounting for uncertainties in the divergence times and incomplete taxon sampling. PMID:22013891

A generalized fuzzy credibility-constrained linear fractional programming approach for optimal irrigation water allocation under uncertainty

NASA Astrophysics Data System (ADS)

Zhang, Chenglong; Guo, Ping

2017-10-01

The vague and fuzzy parametric information is a challenging issue in irrigation water management problems. In response to this problem, a generalized fuzzy credibility-constrained linear fractional programming (GFCCFP) model is developed for optimal irrigation water allocation under uncertainty. The model can be derived from integrating generalized fuzzy credibility-constrained programming (GFCCP) into a linear fractional programming (LFP) optimization framework. Therefore, it can solve ratio optimization problems associated with fuzzy parameters, and examine the variation of results under different credibility levels and weight coefficients of possibility and necessary. It has advantages in: (1) balancing the economic and resources objectives directly; (2) analyzing system efficiency; (3) generating more flexible decision solutions by giving different credibility levels and weight coefficients of possibility and (4) supporting in-depth analysis of the interrelationships among system efficiency, credibility level and weight coefficient. The model is applied to a case study of irrigation water allocation in the middle reaches of Heihe River Basin, northwest China. Therefore, optimal irrigation water allocation solutions from the GFCCFP model can be obtained. Moreover, factorial analysis on the two parameters (i.e. λ and γ) indicates that the weight coefficient is a main factor compared with credibility level for system efficiency. These results can be effective for support reasonable irrigation water resources management and agricultural production.

Estimating micro area behavioural risk factor prevalence from large population-based surveys: a full Bayesian approach.

PubMed

Seliske, L; Norwood, T A; McLaughlin, J R; Wang, S; Palleschi, C; Holowaty, E

2016-06-07

An important public health goal is to decrease the prevalence of key behavioural risk factors, such as tobacco use and obesity. Survey information is often available at the regional level, but heterogeneity within large geographic regions cannot be assessed. Advanced spatial analysis techniques are demonstrated to produce sensible micro area estimates of behavioural risk factors that enable identification of areas with high prevalence. A spatial Bayesian hierarchical model was used to estimate the micro area prevalence of current smoking and excess bodyweight for the Erie-St. Clair region in southwestern Ontario. Estimates were mapped for male and female respondents of five cycles of the Canadian Community Health Survey (CCHS). The micro areas were 2006 Census Dissemination Areas, with an average population of 400-700 people. Two individual-level models were specified: one controlled for survey cycle and age group (model 1), and one controlled for survey cycle, age group and micro area median household income (model 2). Post-stratification was used to derive micro area behavioural risk factor estimates weighted to the population structure. SaTScan analyses were conducted on the granular, postal-code level CCHS data to corroborate findings of elevated prevalence. Current smoking was elevated in two urban areas for both sexes (Sarnia and Windsor), and an additional small community (Chatham) for males only. Areas of excess bodyweight were prevalent in an urban core (Windsor) among males, but not females. Precision of the posterior post-stratified current smoking estimates was improved in model 2, as indicated by narrower credible intervals and a lower coefficient of variation. For excess bodyweight, both models had similar precision. Aggregation of the micro area estimates to CCHS design-based estimates validated the findings. This is among the first studies to apply a full Bayesian model to complex sample survey data to identify micro areas with variation in risk factor prevalence, accounting for spatial correlation and other covariates. Application of micro area analysis techniques helps define areas for public health planning, and may be informative to surveillance and research modeling of relevant chronic disease outcomes.

Iowa radon leukaemia study: a hierarchical population risk model for spatially correlated exposure measured with error.

PubMed

Smith, Brian J; Zhang, Lixun; Field, R William

2007-11-10

This paper presents a Bayesian model that allows for the joint prediction of county-average radon levels and estimation of the associated leukaemia risk. The methods are motivated by radon data from an epidemiologic study of residential radon in Iowa that include 2726 outdoor and indoor measurements. Prediction of county-average radon is based on a geostatistical model for the radon data which assumes an underlying continuous spatial process. In the radon model, we account for uncertainties due to incomplete spatial coverage, spatial variability, characteristic differences between homes, and detector measurement error. The predicted radon averages are, in turn, included as a covariate in Poisson models for incident cases of acute lymphocytic (ALL), acute myelogenous (AML), chronic lymphocytic (CLL), and chronic myelogenous (CML) leukaemias reported to the Iowa cancer registry from 1973 to 2002. Since radon and leukaemia risk are modelled simultaneously in our approach, the resulting risk estimates accurately reflect uncertainties in the predicted radon exposure covariate. Posterior mean (95 per cent Bayesian credible interval) estimates of the relative risk associated with a 1 pCi/L increase in radon for ALL, AML, CLL, and CML are 0.91 (0.78-1.03), 1.01 (0.92-1.12), 1.06 (0.96-1.16), and 1.12 (0.98-1.27), respectively. Copyright 2007 John Wiley & Sons, Ltd.

Bayesian Correction of Misclassification of Pertussis in Vaccine Effectiveness Studies: How Much Does Underreporting Matter?

PubMed

Goldstein, Neal D; Burstyn, Igor; Newbern, E Claire; Tabb, Loni P; Gutowski, Jennifer; Welles, Seth L

2016-06-01

Diagnosis of pertussis remains a challenge, and consequently research on the risk of disease might be biased because of misclassification. We quantified this misclassification and corrected for it in a case-control study of children in Philadelphia, Pennsylvania, who were 3 months to 6 years of age and diagnosed with pertussis between 2011 and 2013. Vaccine effectiveness (VE; calculated as (1 - odds ratio) × 100) was used to describe the average reduction in reported pertussis incidence resulting from persons being up to date on pertussis-antigen containing vaccines. Bayesian techniques were used to correct for purported nondifferential misclassification by reclassifying the cases per the 2014 Council of State and Territorial Epidemiologists pertussis case definition. Naïve VE was 50% (95% confidence interval: 16%, 69%). After correcting for misclassification, VE ranged from 57% (95% credible interval: 30, 73) to 82% (95% credible interval: 43, 95), depending on the amount of underreporting of pertussis that was assumed to have occurred in the study period. Meaningful misclassification was observed in terms of false negatives detected after the incorporation of infant apnea to the 2014 case definition. Although specificity was nearly perfect, sensitivity of the case definition varied from 90% to 20%, depending on the assumption about missed cases. Knowing the degree of the underreporting is essential to the accurate evaluation of VE. © The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Evaluating propagation method performance over time with Bayesian updating: An application to incubator testing

USGS Publications Warehouse

Converse, Sarah J.; Chandler, J. N.; Olsen, Glenn H.; Shafer, C. C.; Hartup, Barry K.; Urbanek, Richard P.

2010-01-01

In captive-rearing programs, small sample sizes can limit the quality of information on performance of propagation methods. Bayesian updating can be used to increase information on method performance over time. We demonstrate an application to incubator testing at USGS Patuxent Wildlife Research Center. A new type of incubator was purchased for use in the whooping crane (Grus americana) propagation program, which produces birds for release. We tested the new incubator for reliability, using sandhill crane (Grus canadensis) eggs as surrogates. We determined that the new incubator should result in hatching rates no more than 5% lower than the available incubators, with 95% confidence, before it would be used to incubate whooping crane eggs. In 2007, 5 healthy chicks hatched from 12 eggs in the new incubator, and 2 hatched from 5 in an available incubator, for a median posterior difference of <1%, but with a large 95% credible interval (-41%, 43%). In 2008, we implemented a double-blind evaluation method, where a veterinarian determined whether eggs produced chicks that, at hatching, had no apparent health problems that would impede future release. We used the 2007 estimates as priors in the 2008 analysis. In 2008, 7 normal chicks hatched from 15 eggs in the new incubator, and 11 hatched from 15 in an available incubator, for a median posterior difference of 19%, with 95% credible interval (-8%, 44%). The increased sample size has increased our understanding of incubator performance. While additional data will be collected, at this time the new incubator does not appear adequate for use with whooping crane eggs.

Hypertensive disorders during pregnancy and risk of type 2 diabetes in later life: a systematic review and meta-analysis.

PubMed

Wang, Zengfang; Wang, Zengyan; Wang, Luang; Qiu, Mingyue; Wang, Yangang; Hou, Xu; Guo, Zhong; Wang, Bin

2017-03-01

Many studies assessed the association between hypertensive disorders during pregnancy and risk of type 2 diabetes mellitus in later life, but contradictory findings were reported. A systemic review and meta-analysis was carried out to elucidate type 2 diabetes mellitus risk in women with hypertensive disorders during pregnancy. Pubmed, Embase, and Web of Science were searched for cohort or case-control studies on the association between hypertensive disorders during pregnancy and subsequent type 2 diabetes mellitus. Random-effect model was used to pool risk estimates. Bayesian meta-analysis was carried out to further estimate the type 2 diabetes mellitus risk associated with hypertensive disorders during pregnancy. Seventeen cohort or prospective matched case-control studies were finally included. Those 17 studies involved 2,984,634 women and 46,732 type 2 diabetes mellitus cases. Overall, hypertensive disorders during pregnancy were significantly correlated with type 2 diabetes mellitus risk (relative risk = 1.56, 95 % confidence interval 1.21-2.01, P = 0.001). Preeclampsia was significantly and independently correlated with type 2 diabetes mellitus risk (relative risk = 2.25, 95 % confidence interval 1.73-2.90, P < 0.001). In addition, gestational hypertension was also significantly and independently correlated with subsequent type 2 diabetes mellitus risk (relative risk = 2.06, 95 % confidence interval 1.57-2.69, P < 0.001). The pooled estimates were not significantly altered in the subgroup analyses of studies on preeclampsia or gestational hypertension. Bayesian meta-analysis showed the relative risks of type 2 diabetes mellitus risk for individuals with hypertensive disorders during pregnancy, preeclampsia, and gestational hypertension were 1.59 (95 % credibility interval: 1.11-2.32), 2.27 (95 % credibility interval: 1.67-2.97), and 2.06 (95 % credibility interval: 1.41-2.84), respectively. Publication bias was not evident in the meta-analysis. Preeclampsia and gestational hypertension are independently associated with substantially elevated risk of type 2 diabetes mellitus in later life.

Air toxics and birth defects: a Bayesian hierarchical approach to evaluate multiple pollutants and spina bifida.

PubMed

Swartz, Michael D; Cai, Yi; Chan, Wenyaw; Symanski, Elaine; Mitchell, Laura E; Danysh, Heather E; Langlois, Peter H; Lupo, Philip J

2015-02-09

While there is evidence that maternal exposure to benzene is associated with spina bifida in offspring, to our knowledge there have been no assessments to evaluate the role of multiple hazardous air pollutants (HAPs) simultaneously on the risk of this relatively common birth defect. In the current study, we evaluated the association between maternal exposure to HAPs identified by the United States Environmental Protection Agency (U.S. EPA) and spina bifida in offspring using hierarchical Bayesian modeling that includes Stochastic Search Variable Selection (SSVS). The Texas Birth Defects Registry provided data on spina bifida cases delivered between 1999 and 2004. The control group was a random sample of unaffected live births, frequency matched to cases on year of birth. Census tract-level estimates of annual HAP levels were obtained from the U.S. EPA's 1999 Assessment System for Population Exposure Nationwide. Using the distribution among controls, exposure was categorized as high exposure (>95(th) percentile), medium exposure (5(th)-95(th) percentile), and low exposure (<5(th) percentile, reference). We used hierarchical Bayesian logistic regression models with SSVS to evaluate the association between HAPs and spina bifida by computing an odds ratio (OR) for each HAP using the posterior mean, and a 95% credible interval (CI) using the 2.5(th) and 97.5(th) quantiles of the posterior samples. Based on previous assessments, any pollutant with a Bayes factor greater than 1 was selected for inclusion in a final model. Twenty-five HAPs were selected in the final analysis to represent "bins" of highly correlated HAPs (ρ > 0.80). We identified two out of 25 HAPs with a Bayes factor greater than 1: quinoline (ORhigh = 2.06, 95% CI: 1.11-3.87, Bayes factor = 1.01) and trichloroethylene (ORmedium = 2.00, 95% CI: 1.14-3.61, Bayes factor = 3.79). Overall there is evidence that quinoline and trichloroethylene may be significant contributors to the risk of spina bifida. Additionally, the use of Bayesian hierarchical models with SSVS is an alternative approach in the evaluation of multiple environmental pollutants on disease risk. This approach can be easily extended to environmental exposures, where novel approaches are needed in the context of multi-pollutant modeling.

A Growing Consensus for Change in Interpretation of Clinical Research Evidence.

PubMed

Wilkerson, Gary B; Denegar, Craig R

2018-03-01

  The paradigm of evidence-based practice (EBP) is well established among the health care professions, but perspectives on the best methods for acquiring, analyzing, appraising, and using research evidence are evolving.   The EBP paradigm has shifted away from a hierarchy of research-evidence quality to recognize that multiple research methods can yield evidence to guide clinicians and patients through a decision-making process. Whereas the "frequentist" approach to data interpretation through hypothesis testing has been the dominant analytical method used by and taught to athletic training students and scholars, this approach is not optimal for integrating evidence into routine clinical practice. Moreover, the dichotomy of rejecting, or failing to reject, a null hypothesis is inconsistent with the Bayesian-like clinical decision-making process that skilled health care providers intuitively use. We propose that data derived from multiple research methods can be best interpreted by reporting a credible lower limit that represents the smallest treatment effect at a specified level of certainty, which should be judged in relation to the smallest effect considered to be clinically meaningful. Such an approach can provide a quantifiable estimate of certainty that an individual patient needs follow-up attention to prevent an adverse outcome or that a meaningful level of therapeutic benefit will be derived from a given intervention.   The practice of athletic training will be influenced by the evolution of the EBP paradigm. Contemporary practice will require clinicians to expand their critical-appraisal skills to effectively integrate the results derived from clinical research into the care of individual patients. Proper interpretation of a credible lower limit value for a magnitude ratio has the potential to increase the likelihood of favorable patient outcomes, thereby advancing the practice of evidence-based athletic training.

Systematic meta-analyses and field synopsis of genetic association studies in colorectal adenomas

PubMed Central

Montazeri, Zahra; Theodoratou, Evropi; Nyiraneza, Christine; Timofeeva, Maria; Chen, Wanjing; Svinti, Victoria; Sivakumaran, Shanya; Gresham, Gillian; Cubitt, Laura; Carvajal-Carmona, Luis; Bertagnolli, Monica M; Zauber, Ann G; Tomlinson, Ian; Farrington, Susan M; Dunlop, Malcolm G; Campbell, Harry; Little, Julian

2018-01-01

Background Low penetrance genetic variants, primarily single nucleotide polymorphisms, have substantial influence on colorectal cancer (CRC) susceptibility. Most CRCs develop from colorectal adenomas (CRA). Here, we report the first comprehensive field synopsis that catalogues all genetic association studies on CRA, with a parallel online database (http://www.chs.med.ed.ac.uk/CRAgene/). Methods We performed a systematic review, reviewing 9750 titles and then extracted data from 130 publications reporting on 181 polymorphisms in 74 genes. We conducted meta-analyses to derive summary effect estimates for 37 polymorphisms in 26 genes. We applied the Venice criteria and Bayesian False Discovery Probability (BFDP) to assess the levels of the credibility of associations. Results We considered the association with the rs6983267 variant at 8q24 as “highly credible”, reaching genome wide statistical significance in at least one meta-analysis model. We identified “less credible” associations (higher heterogeneity, lower statistical power, BFDP>0.02) with a further four variants of four independent genes: MTHFR c.677C>T p.A222V (rs1801133), TP53 c.215C>G p.R72P (rs1042522), NQO1 c.559C>T p.P187S (rs1800566), and NAT1 alleles imputed as fast acetylator genotypes. For the remaining 32 variants of 22 genes for which positive associations with CRA risk have been previously reported, the meta-analyses revealed no credible evidence to support these as true associations. Conclusions The limited number of credible associations between low penetrance genetic variants and CRA reflects the lower volume of evidence and associated lack of statistical power to detect associations of the magnitude typically observed for genetic variants and chronic diseases. The CRAgene database provides context for CRA genetic association data and will help inform future research directions. PMID:26451011

Fuzzy robust credibility-constrained programming for environmental management and planning.

PubMed

Zhang, Yimei; Hang, Guohe

2010-06-01

In this study, a fuzzy robust credibility-constrained programming (FRCCP) is developed and applied to the planning for waste management systems. It incorporates the concepts of credibility-based chance-constrained programming and robust programming within an optimization framework. The developed method can reflect uncertainties presented as possibility-density by fuzzy-membership functions. Fuzzy credibility constraints are transformed to the crisp equivalents with different credibility levels, and ordinary fuzzy inclusion constraints are determined by their robust deterministic constraints by setting a-cut levels. The FRCCP method can provide different system costs under different credibility levels (lambda). From the results of sensitivity analyses, the operation cost of the landfill is a critical parameter. For the management, any factors that would induce cost fluctuation during landfilling operation would deserve serious observation and analysis. By FRCCP, useful solutions can be obtained to provide decision-making support for long-term planning of solid waste management systems. It could be further enhanced through incorporating methods of inexact analysis into its framework. It can also be applied to other environmental management problems.

Improving Photometric Redshifts for Hyper Suprime-Cam

NASA Astrophysics Data System (ADS)

Speagle, Josh S.; Leauthaud, Alexie; Eisenstein, Daniel; Bundy, Kevin; Capak, Peter L.; Leistedt, Boris; Masters, Daniel C.; Mortlock, Daniel; Peiris, Hiranya; HSC Photo-z Team; HSC Weak Lensing Team

2017-01-01

Deriving accurate photometric redshift (photo-z) probability distribution functions (PDFs) are crucial science components for current and upcoming large-scale surveys. We outline how rigorous Bayesian inference and machine learning can be combined to quickly derive joint photo-z PDFs to individual galaxies and their parent populations. Using the first 170 deg^2 of data from the ongoing Hyper Suprime-Cam survey, we demonstrate our method is able to generate accurate predictions and reliable credible intervals over ~370k high-quality redshifts. We then use galaxy-galaxy lensing to empirically validate our predicted photo-z's over ~14M objects, finding a robust signal.

A fuzzy Bayesian approach to flood frequency estimation with imprecise historical information

PubMed Central

Kiss, Andrea; Viglione, Alberto; Viertl, Reinhard; Blöschl, Günter

2016-01-01

Abstract This paper presents a novel framework that links imprecision (through a fuzzy approach) and stochastic uncertainty (through a Bayesian approach) in estimating flood probabilities from historical flood information and systematic flood discharge data. The method exploits the linguistic characteristics of historical source material to construct membership functions, which may be wider or narrower, depending on the vagueness of the statements. The membership functions are either included in the prior distribution or the likelihood function to obtain a fuzzy version of the flood frequency curve. The viability of the approach is demonstrated by three case studies that differ in terms of their hydromorphological conditions (from an Alpine river with bedrock profile to a flat lowland river with extensive flood plains) and historical source material (including narratives, town and county meeting protocols, flood marks and damage accounts). The case studies are presented in order of increasing fuzziness (the Rhine at Basel, Switzerland; the Werra at Meiningen, Germany; and the Tisza at Szeged, Hungary). Incorporating imprecise historical information is found to reduce the range between the 5% and 95% Bayesian credibility bounds of the 100 year floods by 45% and 61% for the Rhine and Werra case studies, respectively. The strengths and limitations of the framework are discussed relative to alternative (non‐fuzzy) methods. The fuzzy Bayesian inference framework provides a flexible methodology that fits the imprecise nature of linguistic information on historical floods as available in historical written documentation. PMID:27840456

A fuzzy Bayesian approach to flood frequency estimation with imprecise historical information

NASA Astrophysics Data System (ADS)

Salinas, José Luis; Kiss, Andrea; Viglione, Alberto; Viertl, Reinhard; Blöschl, Günter

2016-09-01

This paper presents a novel framework that links imprecision (through a fuzzy approach) and stochastic uncertainty (through a Bayesian approach) in estimating flood probabilities from historical flood information and systematic flood discharge data. The method exploits the linguistic characteristics of historical source material to construct membership functions, which may be wider or narrower, depending on the vagueness of the statements. The membership functions are either included in the prior distribution or the likelihood function to obtain a fuzzy version of the flood frequency curve. The viability of the approach is demonstrated by three case studies that differ in terms of their hydromorphological conditions (from an Alpine river with bedrock profile to a flat lowland river with extensive flood plains) and historical source material (including narratives, town and county meeting protocols, flood marks and damage accounts). The case studies are presented in order of increasing fuzziness (the Rhine at Basel, Switzerland; the Werra at Meiningen, Germany; and the Tisza at Szeged, Hungary). Incorporating imprecise historical information is found to reduce the range between the 5% and 95% Bayesian credibility bounds of the 100 year floods by 45% and 61% for the Rhine and Werra case studies, respectively. The strengths and limitations of the framework are discussed relative to alternative (non-fuzzy) methods. The fuzzy Bayesian inference framework provides a flexible methodology that fits the imprecise nature of linguistic information on historical floods as available in historical written documentation.

A fuzzy Bayesian approach to flood frequency estimation with imprecise historical information.

PubMed

Salinas, José Luis; Kiss, Andrea; Viglione, Alberto; Viertl, Reinhard; Blöschl, Günter

2016-09-01

This paper presents a novel framework that links imprecision (through a fuzzy approach) and stochastic uncertainty (through a Bayesian approach) in estimating flood probabilities from historical flood information and systematic flood discharge data. The method exploits the linguistic characteristics of historical source material to construct membership functions, which may be wider or narrower, depending on the vagueness of the statements. The membership functions are either included in the prior distribution or the likelihood function to obtain a fuzzy version of the flood frequency curve. The viability of the approach is demonstrated by three case studies that differ in terms of their hydromorphological conditions (from an Alpine river with bedrock profile to a flat lowland river with extensive flood plains) and historical source material (including narratives, town and county meeting protocols, flood marks and damage accounts). The case studies are presented in order of increasing fuzziness (the Rhine at Basel, Switzerland; the Werra at Meiningen, Germany; and the Tisza at Szeged, Hungary). Incorporating imprecise historical information is found to reduce the range between the 5% and 95% Bayesian credibility bounds of the 100 year floods by 45% and 61% for the Rhine and Werra case studies, respectively. The strengths and limitations of the framework are discussed relative to alternative (non-fuzzy) methods. The fuzzy Bayesian inference framework provides a flexible methodology that fits the imprecise nature of linguistic information on historical floods as available in historical written documentation.

Diversity Dynamics in Nymphalidae Butterflies: Effect of Phylogenetic Uncertainty on Diversification Rate Shift Estimates

PubMed Central

Peña, Carlos; Espeland, Marianne

2015-01-01

The species rich butterfly family Nymphalidae has been used to study evolutionary interactions between plants and insects. Theories of insect-hostplant dynamics predict accelerated diversification due to key innovations. In evolutionary biology, analysis of maximum credibility trees in the software MEDUSA (modelling evolutionary diversity using stepwise AIC) is a popular method for estimation of shifts in diversification rates. We investigated whether phylogenetic uncertainty can produce different results by extending the method across a random sample of trees from the posterior distribution of a Bayesian run. Using the MultiMEDUSA approach, we found that phylogenetic uncertainty greatly affects diversification rate estimates. Different trees produced diversification rates ranging from high values to almost zero for the same clade, and both significant rate increase and decrease in some clades. Only four out of 18 significant shifts found on the maximum clade credibility tree were consistent across most of the sampled trees. Among these, we found accelerated diversification for Ithomiini butterflies. We used the binary speciation and extinction model (BiSSE) and found that a hostplant shift to Solanaceae is correlated with increased net diversification rates in Ithomiini, congruent with the diffuse cospeciation hypothesis. Our results show that taking phylogenetic uncertainty into account when estimating net diversification rate shifts is of great importance, as very different results can be obtained when using the maximum clade credibility tree and other trees from the posterior distribution. PMID:25830910

Diversity dynamics in Nymphalidae butterflies: effect of phylogenetic uncertainty on diversification rate shift estimates.

PubMed

Peña, Carlos; Espeland, Marianne

2015-01-01

The species rich butterfly family Nymphalidae has been used to study evolutionary interactions between plants and insects. Theories of insect-hostplant dynamics predict accelerated diversification due to key innovations. In evolutionary biology, analysis of maximum credibility trees in the software MEDUSA (modelling evolutionary diversity using stepwise AIC) is a popular method for estimation of shifts in diversification rates. We investigated whether phylogenetic uncertainty can produce different results by extending the method across a random sample of trees from the posterior distribution of a Bayesian run. Using the MultiMEDUSA approach, we found that phylogenetic uncertainty greatly affects diversification rate estimates. Different trees produced diversification rates ranging from high values to almost zero for the same clade, and both significant rate increase and decrease in some clades. Only four out of 18 significant shifts found on the maximum clade credibility tree were consistent across most of the sampled trees. Among these, we found accelerated diversification for Ithomiini butterflies. We used the binary speciation and extinction model (BiSSE) and found that a hostplant shift to Solanaceae is correlated with increased net diversification rates in Ithomiini, congruent with the diffuse cospeciation hypothesis. Our results show that taking phylogenetic uncertainty into account when estimating net diversification rate shifts is of great importance, as very different results can be obtained when using the maximum clade credibility tree and other trees from the posterior distribution.

Mindfulness Mechanisms in Sports: Mediating Effects of Rumination and Emotion Regulation on Sport-Specific Coping.

PubMed

Josefsson, Torbjörn; Ivarsson, Andreas; Lindwall, Magnus; Gustafsson, Henrik; Stenling, Andreas; Böröy, Jan; Mattsson, Emil; Carnebratt, Jakob; Sevholt, Simon; Falkevik, Emil

2017-01-01

The main objective of the project was to examine a proposed theoretical model of mindfulness mechanisms in sports. We conducted two studies (the first study using a cross-sectional design and the second a longitudinal design) to investigate if rumination and emotion regulation mediate the relation between dispositional mindfulness and sport-specific coping. Two hundred and forty-two young elite athletes, drawn from various sports, were recruited for the cross-sectional study. For the longitudinal study, 65 elite athletes were recruited. All analyses were performed using Bayesian statistics. The path analyses showed credible indirect effects of dispositional mindfulness on coping via rumination and emotion regulation in both the cross-sectional study and the longitudinal study. Additionally, the results in both studies showed credible direct effects of dispositional mindfulness on rumination and emotion regulation. Further, credible direct effects of emotion regulation as well as rumination on coping were also found in both studies. Our findings support the theoretical model, indicating that rumination and emotion regulation function as essential mechanisms in the relation between dispositional mindfulness and sport-specific coping skills. Increased dispositional mindfulness in competitive athletes (i.e. by practicing mindfulness) may lead to reductions in rumination, as well as an improved capacity to regulate negative emotions. By doing so, athletes may improve their sport-related coping skills, and thereby enhance athletic performance.

Maternal Concentrations of Perfluoroalkyl Substances and Fetal Markers of Metabolic Function and Birth Weight

PubMed Central

Ashley-Martin, Jillian; Dodds, Linda; Arbuckle, Tye E.; Bouchard, Maryse F.; Fisher, Mandy; Morriset, Anne-Sophie; Monnier, Patricia; Shapiro, Gabriel D.; Ettinger, Adrienne S.; Dallaire, Renee; Taback, Shayne; Fraser, William; Platt, Robert W.

2017-01-01

Abstract Perfluoroalkyl substances (PFAS) are ubiquitous, persistent chemicals that have been widely used in the production of common household and consumer goods for their nonflammable, lipophobic, and hydrophobic properties. Inverse associations between maternal or umbilical cord blood concentrations of perfluorooctanoic acid and perfluorooctanesulfonate and birth weight have been identified. This literature has primarily examined each PFAS individually without consideration of the potential influence of correlated exposures. Further, the association between PFAS exposures and indicators of metabolic function (i.e., leptin and adiponectin) has received limited attention. We examined associations between first-trimester maternal plasma PFAS concentrations and birth weight and cord blood concentrations of leptin and adiponectin using data on 1,705 mother-infant pairs from the Maternal Infant Research on Environmental Chemicals (MIREC) Study, a trans-Canada birth cohort study that recruited women between 2008 and 2011. Bayesian hierarchical models were used to quantify associations and calculate credible intervals. Maternal perfluorooctanoic acid concentrations were inversely associated with birth weight z score, though the null value was included in all credible intervals (log10 β = −0.10, 95% credible interval: −0.34, 0.13). All associations between maternal PFAS concentrations and cord blood adipocytokine concentrations were of small magnitude and centered around the null value. Follow-up in a cohort of children is required to determine how the observed associations manifest in childhood. PMID:28172036

Problems in the fingerprints based polycyclic aromatic hydrocarbons source apportionment analysis and a practical solution.

PubMed

Zou, Yonghong; Wang, Lixia; Christensen, Erik R

2015-10-01

This work intended to explain the challenges of the fingerprints based source apportionment method for polycyclic aromatic hydrocarbons (PAH) in the aquatic environment, and to illustrate a practical and robust solution. The PAH data detected in the sediment cores from the Illinois River provide the basis of this study. Principal component analysis (PCA) separates PAH compounds into two groups reflecting their possible airborne transport patterns; but it is not able to suggest specific sources. Not all positive matrix factorization (PMF) determined sources are distinguishable due to the variability of source fingerprints. However, they constitute useful suggestions for inputs for a Bayesian chemical mass balance (CMB) analysis. The Bayesian CMB analysis takes into account the measurement errors as well as the variations of source fingerprints, and provides a credible source apportionment. Major PAH sources for Illinois River sediments are traffic (35%), coke oven (24%), coal combustion (18%), and wood combustion (14%). Copyright © 2015. Published by Elsevier Ltd.

Bayesian Spatiotemporal Analysis of Socio-Ecologic Drivers of Ross River Virus Transmission in Queensland, Australia

PubMed Central

Hu, Wenbiao; Clements, Archie; Williams, Gail; Tong, Shilu; Mengersen, Kerrie

2010-01-01

This study aims to examine the impact of socio-ecologic factors on the transmission of Ross River virus (RRV) infection and to identify areas prone to social and ecologic-driven epidemics in Queensland, Australia. We used a Bayesian spatiotemporal conditional autoregressive model to quantify the relationship between monthly variation of RRV incidence and socio-ecologic factors and to determine spatiotemporal patterns. Our results show that the average increase in monthly RRV incidence was 2.4% (95% credible interval (CrI): 0.1–4.5%) and 2.0% (95% CrI: 1.6–2.3%) for a 1°C increase in monthly average maximum temperature and a 10 mm increase in monthly average rainfall, respectively. A significant spatiotemporal variation and interactive effect between temperature and rainfall on RRV incidence were found. No association between Socio-economic Index for Areas (SEIFA) and RRV was observed. The transmission of RRV in Queensland, Australia appeared to be primarily driven by ecologic variables rather than social factors. PMID:20810846

Diagnostic accuracy of clinical illness for bovine respiratory disease (BRD) diagnosis in beef cattle placed in feedlots: A systematic literature review and hierarchical Bayesian latent-class meta-analysis.

PubMed

Timsit, E; Dendukuri, N; Schiller, I; Buczinski, S

2016-12-01

Diagnosis of bovine respiratory disease (BRD) in beef cattle placed in feedlots is typically based on clinical illness (CI) detected by pen-checkers. Unfortunately, the accuracy of this diagnostic approach (namely, sensitivity [Se] and specificity [Sp]) remains poorly understood, in part due to the absence of a reference test for ante-mortem diagnosis of BRD. Our objective was to pool available estimates of CI's diagnostic accuracy for BRD diagnosis in feedlot beef cattle while adjusting for the inaccuracy in the reference test. The presence of lung lesions (LU) at slaughter was used as the reference test. A systematic review of the literature was conducted to identify research articles comparing CI detected by pen-checkers during the feeding period to LU at slaughter. A hierarchical Bayesian latent-class meta-analysis was used to model test accuracy. This approach accounted for imperfections of both tests as well as the within and between study variability in the accuracy of CI. Furthermore, it also predicted the Se CI and Sp CI for future studies. Conditional independence between CI and LU was assumed, as these two tests are not based on similar biological principles. Seven studies were included in the meta-analysis. Estimated pooled Se CI and Sp CI were 0.27 (95% Bayesian credible interval: 0.12-0.65) and 0.92 (0.72-0.98), respectively, whereas estimated pooled Se LU and Sp LU were 0.91 (0.82-0.99) and 0.67 (0.64-0.79). Predicted Se CI and Sp CI for future studies were 0.27 (0.01-0.96) and 0.92 (0.14-1.00), respectively. The wide credible intervals around predicted Se CI and Sp CI estimates indicated considerable heterogeneity among studies, which suggests that pooled Se CI and Sp CI are not generalizable to individual studies. In conclusion, CI appeared to have poor Se but high Sp for BRD diagnosis in feedlots. Furthermore, considerable heterogeneity among studies highlighted an urgent need to standardize BRD diagnosis in feedlots. Copyright © 2016 Elsevier B.V. All rights reserved.

Associations between prior management of cattle and risk of bovine respiratory disease in feedlot cattle.

PubMed

Hay, K E; Morton, J M; Schibrowski, M L; Clements, A C A; Mahony, T J; Barnes, T S

2016-05-01

Bovine respiratory disease (BRD) is the major cause of clinical disease and death in feedlot populations worldwide. A longitudinal study was conducted to assess associations between risk factors related to on-farm management prior to transport to the feedlot and risk of BRD in a population of feedlot beef cattle sourced from throughout the cattle producing regions of Australia. Exposure variables were derived from questionnaire data provided by farmers supplying cattle (N=10,721) that were a subset of the population included in a nationwide prospective study investigating numerous putative risk factors for BRD. Causal diagrams were used to inform model building to allow estimation of effects of interest. Multilevel mixed effects logistic regression models were fitted within the Bayesian framework. Animals that were yard weaned were at reduced risk (OR: 0.7, 95% credible interval: 0.5-1.0) of BRD at the feedlot compared to animals immediately returned to pasture after weaning. Animals that had previously been fed grain (OR: 0.6, 95% credible interval: 0.3-1.1) were probably at reduced risk of BRD at the feedlot compared to animals not previously fed grain. Animals that received prior vaccinations against Bovine viral diarrhoea virus 1 (OR: 0.8, 95% credible interval: 0.5-1.1) or Mannheimia haemolytica (OR: 0.8, 95% credible interval: 0.6-1.0) were also probably at reduced risk compared to non-vaccinated animals. The results of this study confirm that on-farm management before feedlot entry can alter risk of BRD after beef cattle enter feedlots. Copyright © 2016 Elsevier B.V. All rights reserved.

Planning of water resources management and pollution control for Heshui River watershed, China: A full credibility-constrained programming approach.

PubMed

Zhang, Y M; Huang, G; Lu, H W; He, Li

2015-08-15

A key issue facing integrated water resources management and water pollution control is to address the vague parametric information. A full credibility-based chance-constrained programming (FCCP) method is thus developed by introducing the new concept of credibility into the modeling framework. FCCP can deal with fuzzy parameters appearing concurrently in the objective and both sides of the constraints of the model, but also provide a credibility level indicating how much confidence one can believe the optimal modeling solutions. The method is applied to Heshui River watershed in the south-central China for demonstration. Results from the case study showed that groundwater would make up for the water shortage in terms of the shrinking surface water and rising water demand, and the optimized total pumpage of groundwater from both alluvial and karst aquifers would exceed 90% of its maximum allowable levels when credibility level is higher than or equal to 0.9. It is also indicated that an increase in credibility level would induce a reduction in cost for surface water acquisition, a rise in cost from groundwater withdrawal, and negligible variation in cost for water pollution control. Copyright © 2015 Elsevier B.V. All rights reserved.

Prion Amplification and Hierarchical Bayesian Modeling Refine Detection of Prion Infection

NASA Astrophysics Data System (ADS)

Wyckoff, A. Christy; Galloway, Nathan; Meyerett-Reid, Crystal; Powers, Jenny; Spraker, Terry; Monello, Ryan J.; Pulford, Bruce; Wild, Margaret; Antolin, Michael; Vercauteren, Kurt; Zabel, Mark

2015-02-01

Prions are unique infectious agents that replicate without a genome and cause neurodegenerative diseases that include chronic wasting disease (CWD) of cervids. Immunohistochemistry (IHC) is currently considered the gold standard for diagnosis of a prion infection but may be insensitive to early or sub-clinical CWD that are important to understanding CWD transmission and ecology. We assessed the potential of serial protein misfolding cyclic amplification (sPMCA) to improve detection of CWD prior to the onset of clinical signs. We analyzed tissue samples from free-ranging Rocky Mountain elk (Cervus elaphus nelsoni) and used hierarchical Bayesian analysis to estimate the specificity and sensitivity of IHC and sPMCA conditional on simultaneously estimated disease states. Sensitivity estimates were higher for sPMCA (99.51%, credible interval (CI) 97.15-100%) than IHC of obex (brain stem, 76.56%, CI 57.00-91.46%) or retropharyngeal lymph node (90.06%, CI 74.13-98.70%) tissues, or both (98.99%, CI 90.01-100%). Our hierarchical Bayesian model predicts the prevalence of prion infection in this elk population to be 18.90% (CI 15.50-32.72%), compared to previous estimates of 12.90%. Our data reveal a previously unidentified sub-clinical prion-positive portion of the elk population that could represent silent carriers capable of significantly impacting CWD ecology.

Prion amplification and hierarchical Bayesian modeling refine detection of prion infection.

PubMed

Wyckoff, A Christy; Galloway, Nathan; Meyerett-Reid, Crystal; Powers, Jenny; Spraker, Terry; Monello, Ryan J; Pulford, Bruce; Wild, Margaret; Antolin, Michael; VerCauteren, Kurt; Zabel, Mark

2015-02-10

Prions are unique infectious agents that replicate without a genome and cause neurodegenerative diseases that include chronic wasting disease (CWD) of cervids. Immunohistochemistry (IHC) is currently considered the gold standard for diagnosis of a prion infection but may be insensitive to early or sub-clinical CWD that are important to understanding CWD transmission and ecology. We assessed the potential of serial protein misfolding cyclic amplification (sPMCA) to improve detection of CWD prior to the onset of clinical signs. We analyzed tissue samples from free-ranging Rocky Mountain elk (Cervus elaphus nelsoni) and used hierarchical Bayesian analysis to estimate the specificity and sensitivity of IHC and sPMCA conditional on simultaneously estimated disease states. Sensitivity estimates were higher for sPMCA (99.51%, credible interval (CI) 97.15-100%) than IHC of obex (brain stem, 76.56%, CI 57.00-91.46%) or retropharyngeal lymph node (90.06%, CI 74.13-98.70%) tissues, or both (98.99%, CI 90.01-100%). Our hierarchical Bayesian model predicts the prevalence of prion infection in this elk population to be 18.90% (CI 15.50-32.72%), compared to previous estimates of 12.90%. Our data reveal a previously unidentified sub-clinical prion-positive portion of the elk population that could represent silent carriers capable of significantly impacting CWD ecology.

Bayesian GGE biplot models applied to maize multi-environments trials.

PubMed

de Oliveira, L A; da Silva, C P; Nuvunga, J J; da Silva, A Q; Balestre, M

2016-06-17

The additive main effects and multiplicative interaction (AMMI) and the genotype main effects and genotype x environment interaction (GGE) models stand out among the linear-bilinear models used in genotype x environment interaction studies. Despite the advantages of their use to describe genotype x environment (AMMI) or genotype and genotype x environment (GGE) interactions, these methods have known limitations that are inherent to fixed effects models, including difficulty in treating variance heterogeneity and missing data. Traditional biplots include no measure of uncertainty regarding the principal components. The present study aimed to apply the Bayesian approach to GGE biplot models and assess the implications for selecting stable and adapted genotypes. Our results demonstrated that the Bayesian approach applied to GGE models with non-informative priors was consistent with the traditional GGE biplot analysis, although the credible region incorporated into the biplot enabled distinguishing, based on probability, the performance of genotypes, and their relationships with the environments in the biplot. Those regions also enabled the identification of groups of genotypes and environments with similar effects in terms of adaptability and stability. The relative position of genotypes and environments in biplots is highly affected by the experimental accuracy. Thus, incorporation of uncertainty in biplots is a key tool for breeders to make decisions regarding stability selection and adaptability and the definition of mega-environments.

Bayesian Approach for Reliability Assessment of Sunshield Deployment on JWST

NASA Technical Reports Server (NTRS)

Kaminskiy, Mark P.; Evans, John W.; Gallo, Luis D.

2013-01-01

Deployable subsystems are essential to mission success of most spacecraft. These subsystems enable critical functions including power, communications and thermal control. The loss of any of these functions will generally result in loss of the mission. These subsystems and their components often consist of unique designs and applications, for which various standardized data sources are not applicable for estimating reliability and for assessing risks. In this study, a Bayesian approach for reliability estimation of spacecraft deployment was developed for this purpose. This approach was then applied to the James Webb Space Telescope (JWST) Sunshield subsystem, a unique design intended for thermal control of the observatory's telescope and science instruments. In order to collect the prior information on deployable systems, detailed studies of "heritage information", were conducted extending over 45 years of spacecraft launches. The NASA Goddard Space Flight Center (GSFC) Spacecraft Operational Anomaly and Reporting System (SOARS) data were then used to estimate the parameters of the conjugative beta prior distribution for anomaly and failure occurrence, as the most consistent set of available data and that could be matched to launch histories. This allows for an emperical Bayesian prediction for the risk of an anomaly occurrence of the complex Sunshield deployment, with credibility limits, using prior deployment data and test information.

A Bayesian Framework for Reliability Analysis of Spacecraft Deployments

NASA Technical Reports Server (NTRS)

Evans, John W.; Gallo, Luis; Kaminsky, Mark

2012-01-01

Deployable subsystems are essential to mission success of most spacecraft. These subsystems enable critical functions including power, communications and thermal control. The loss of any of these functions will generally result in loss of the mission. These subsystems and their components often consist of unique designs and applications for which various standardized data sources are not applicable for estimating reliability and for assessing risks. In this study, a two stage sequential Bayesian framework for reliability estimation of spacecraft deployment was developed for this purpose. This process was then applied to the James Webb Space Telescope (JWST) Sunshield subsystem, a unique design intended for thermal control of the Optical Telescope Element. Initially, detailed studies of NASA deployment history, "heritage information", were conducted, extending over 45 years of spacecraft launches. This information was then coupled to a non-informative prior and a binomial likelihood function to create a posterior distribution for deployments of various subsystems uSing Monte Carlo Markov Chain sampling. Select distributions were then coupled to a subsequent analysis, using test data and anomaly occurrences on successive ground test deployments of scale model test articles of JWST hardware, to update the NASA heritage data. This allowed for a realistic prediction for the reliability of the complex Sunshield deployment, with credibility limits, within this two stage Bayesian framework.

On the applicability of surrogate-based Markov chain Monte Carlo-Bayesian inversion to the Community Land Model: Case studies at flux tower sites

NASA Astrophysics Data System (ADS)

Huang, Maoyi; Ray, Jaideep; Hou, Zhangshuan; Ren, Huiying; Liu, Ying; Swiler, Laura

2016-07-01

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesian model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. Analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.

Resolving the Antarctic contribution to sea-level rise: a hierarchical modelling framework.

PubMed

Zammit-Mangion, Andrew; Rougier, Jonathan; Bamber, Jonathan; Schön, Nana

2014-06-01

Determining the Antarctic contribution to sea-level rise from observational data is a complex problem. The number of physical processes involved (such as ice dynamics and surface climate) exceeds the number of observables, some of which have very poor spatial definition. This has led, in general, to solutions that utilise strong prior assumptions or physically based deterministic models to simplify the problem. Here, we present a new approach for estimating the Antarctic contribution, which only incorporates descriptive aspects of the physically based models in the analysis and in a statistical manner. By combining physical insights with modern spatial statistical modelling techniques, we are able to provide probability distributions on all processes deemed to play a role in both the observed data and the contribution to sea-level rise. Specifically, we use stochastic partial differential equations and their relation to geostatistical fields to capture our physical understanding and employ a Gaussian Markov random field approach for efficient computation. The method, an instantiation of Bayesian hierarchical modelling, naturally incorporates uncertainty in order to reveal credible intervals on all estimated quantities. The estimated sea-level rise contribution using this approach corroborates those found using a statistically independent method. © 2013 The Authors. Environmetrics Published by John Wiley & Sons, Ltd.

Resolving the Antarctic contribution to sea-level rise: a hierarchical modelling framework†

PubMed Central

Zammit-Mangion, Andrew; Rougier, Jonathan; Bamber, Jonathan; Schön, Nana

2014-01-01

Determining the Antarctic contribution to sea-level rise from observational data is a complex problem. The number of physical processes involved (such as ice dynamics and surface climate) exceeds the number of observables, some of which have very poor spatial definition. This has led, in general, to solutions that utilise strong prior assumptions or physically based deterministic models to simplify the problem. Here, we present a new approach for estimating the Antarctic contribution, which only incorporates descriptive aspects of the physically based models in the analysis and in a statistical manner. By combining physical insights with modern spatial statistical modelling techniques, we are able to provide probability distributions on all processes deemed to play a role in both the observed data and the contribution to sea-level rise. Specifically, we use stochastic partial differential equations and their relation to geostatistical fields to capture our physical understanding and employ a Gaussian Markov random field approach for efficient computation. The method, an instantiation of Bayesian hierarchical modelling, naturally incorporates uncertainty in order to reveal credible intervals on all estimated quantities. The estimated sea-level rise contribution using this approach corroborates those found using a statistically independent method. © 2013 The Authors. Environmetrics Published by John Wiley & Sons, Ltd. PMID:25505370

Inter-Ethnic/Racial Facial Variations: A Systematic Review and Bayesian Meta-Analysis of Photogrammetric Studies

PubMed Central

Wen, Yi Feng; Wong, Hai Ming; Lin, Ruitao; Yin, Guosheng; McGrath, Colman

2015-01-01

Background Numerous facial photogrammetric studies have been published around the world. We aimed to critically review these studies so as to establish population norms for various angular and linear facial measurements; and to determine inter-ethnic/racial facial variations. Methods and Findings A comprehensive and systematic search of PubMed, ISI Web of Science, Embase, and Scopus was conducted to identify facial photogrammetric studies published before December, 2014. Subjects of eligible studies were either Africans, Asians or Caucasians. A Bayesian hierarchical random effects model was developed to estimate posterior means and 95% credible intervals (CrI) for each measurement by ethnicity/race. Linear contrasts were constructed to explore inter-ethnic/racial facial variations. We identified 38 eligible studies reporting 11 angular and 18 linear facial measurements. Risk of bias of the studies ranged from 0.06 to 0.66. At the significance level of 0.05, African males were found to have smaller nasofrontal angle (posterior mean difference: 8.1°, 95% CrI: 2.2°–13.5°) compared to Caucasian males and larger nasofacial angle (7.4°, 0.1°–13.2°) compared to Asian males. Nasolabial angle was more obtuse in Caucasian females than in African (17.4°, 0.2°–35.3°) and Asian (9.1°, 0.4°–17.3°) females. Additional inter-ethnic/racial variations were revealed when the level of statistical significance was set at 0.10. Conclusions A comprehensive database for angular and linear facial measurements was established from existing studies using the statistical model and inter-ethnic/racial variations of facial features were observed. The results have implications for clinical practice and highlight the need and value for high quality photogrammetric studies. PMID:26247212

Effect of Weather Variability on Seasonal Influenza Among Different Age Groups in Queensland, Australia: A Bayesian Spatiotemporal Analysis.

PubMed

Huang, Xiaodong; Mengersen, Kerrie; Milinovich, Gabriel; Hu, Wenbiao

2017-06-01

The effects of weather variability on seasonal influenza among different age groups remain unclear. The comparative study aims to explore the differences in the associations between weather variability and seasonal influenza, and growth rates of seasonal influenza epidemics among different age groups in Queensland, Australia. Three Bayesian spatiotemporal conditional autoregressive models were fitted at the postal area level to quantify the relationships between seasonal influenza and monthly minimum temperature (MIT), monthly vapor pressure, school calendar pattern, and Index of Relative Socio-Economic Advantage and Disadvantage for 3 age groups (<15, 15-64, and ≥65 years). The results showed that the expected decrease in monthly influenza cases was 19.3% (95% credible interval [CI], 14.7%-23.4%), 16.3% (95% CI, 13.6%-19.0%), and 8.5% (95% CI, 1.5%-15.0%) for a 1°C increase in monthly MIT at <15, 15-64, and ≥65 years of age, respectively, while the average increase in the monthly influenza cases was 14.6% (95% CI, 9.0%-21.0%), 12.1% (95% CI, 8.8%-16.1%), and 9.2% (95% CI, 1.4%-16.9%) for a 1-hPa increase in vapor pressure. Weather variability appears to be more influential on seasonal influenza transmission in younger (0-14) age groups. The growth rates of influenza at postal area level were relatively small for older (≥65) age groups in Queensland, Australia. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

Inter-Ethnic/Racial Facial Variations: A Systematic Review and Bayesian Meta-Analysis of Photogrammetric Studies.

PubMed

Wen, Yi Feng; Wong, Hai Ming; Lin, Ruitao; Yin, Guosheng; McGrath, Colman

2015-01-01

Numerous facial photogrammetric studies have been published around the world. We aimed to critically review these studies so as to establish population norms for various angular and linear facial measurements; and to determine inter-ethnic/racial facial variations. A comprehensive and systematic search of PubMed, ISI Web of Science, Embase, and Scopus was conducted to identify facial photogrammetric studies published before December, 2014. Subjects of eligible studies were either Africans, Asians or Caucasians. A Bayesian hierarchical random effects model was developed to estimate posterior means and 95% credible intervals (CrI) for each measurement by ethnicity/race. Linear contrasts were constructed to explore inter-ethnic/racial facial variations. We identified 38 eligible studies reporting 11 angular and 18 linear facial measurements. Risk of bias of the studies ranged from 0.06 to 0.66. At the significance level of 0.05, African males were found to have smaller nasofrontal angle (posterior mean difference: 8.1°, 95% CrI: 2.2°-13.5°) compared to Caucasian males and larger nasofacial angle (7.4°, 0.1°-13.2°) compared to Asian males. Nasolabial angle was more obtuse in Caucasian females than in African (17.4°, 0.2°-35.3°) and Asian (9.1°, 0.4°-17.3°) females. Additional inter-ethnic/racial variations were revealed when the level of statistical significance was set at 0.10. A comprehensive database for angular and linear facial measurements was established from existing studies using the statistical model and inter-ethnic/racial variations of facial features were observed. The results have implications for clinical practice and highlight the need and value for high quality photogrammetric studies.

Web Site Credibility: Why Do People Believe What They Believe?

ERIC Educational Resources Information Center

Iding, Marie K.; Crosby, Martha E.; Auernheimer, Brent; Klemm, E. Barbara

2009-01-01

This research investigates university students' determinations of credibility of information on Web sites, confidence in their determinations, and perceptions of Web site authors' vested interests. In Study 1, university-level computer science and education students selected Web sites determined to be credible and Web sites that exemplified…

Joint analysis of input and parametric uncertainties in watershed water quality modeling: A formal Bayesian approach

NASA Astrophysics Data System (ADS)

Han, Feng; Zheng, Yi

2018-06-01

Significant Input uncertainty is a major source of error in watershed water quality (WWQ) modeling. It remains challenging to address the input uncertainty in a rigorous Bayesian framework. This study develops the Bayesian Analysis of Input and Parametric Uncertainties (BAIPU), an approach for the joint analysis of input and parametric uncertainties through a tight coupling of Markov Chain Monte Carlo (MCMC) analysis and Bayesian Model Averaging (BMA). The formal likelihood function for this approach is derived considering a lag-1 autocorrelated, heteroscedastic, and Skew Exponential Power (SEP) distributed error model. A series of numerical experiments were performed based on a synthetic nitrate pollution case and on a real study case in the Newport Bay Watershed, California. The Soil and Water Assessment Tool (SWAT) and Differential Evolution Adaptive Metropolis (DREAM(ZS)) were used as the representative WWQ model and MCMC algorithm, respectively. The major findings include the following: (1) the BAIPU can be implemented and used to appropriately identify the uncertain parameters and characterize the predictive uncertainty; (2) the compensation effect between the input and parametric uncertainties can seriously mislead the modeling based management decisions, if the input uncertainty is not explicitly accounted for; (3) the BAIPU accounts for the interaction between the input and parametric uncertainties and therefore provides more accurate calibration and uncertainty results than a sequential analysis of the uncertainties; and (4) the BAIPU quantifies the credibility of different input assumptions on a statistical basis and can be implemented as an effective inverse modeling approach to the joint inference of parameters and inputs.

Bayesian phylogenetic estimation of fossil ages.

PubMed

Drummond, Alexei J; Stadler, Tanja

2016-07-19

Recent advances have allowed for both morphological fossil evidence and molecular sequences to be integrated into a single combined inference of divergence dates under the rule of Bayesian probability. In particular, the fossilized birth-death tree prior and the Lewis-Mk model of discrete morphological evolution allow for the estimation of both divergence times and phylogenetic relationships between fossil and extant taxa. We exploit this statistical framework to investigate the internal consistency of these models by producing phylogenetic estimates of the age of each fossil in turn, within two rich and well-characterized datasets of fossil and extant species (penguins and canids). We find that the estimation accuracy of fossil ages is generally high with credible intervals seldom excluding the true age and median relative error in the two datasets of 5.7% and 13.2%, respectively. The median relative standard error (RSD) was 9.2% and 7.2%, respectively, suggesting good precision, although with some outliers. In fact, in the two datasets we analyse, the phylogenetic estimate of fossil age is on average less than 2 Myr from the mid-point age of the geological strata from which it was excavated. The high level of internal consistency found in our analyses suggests that the Bayesian statistical model employed is an adequate fit for both the geological and morphological data, and provides evidence from real data that the framework used can accurately model the evolution of discrete morphological traits coded from fossil and extant taxa. We anticipate that this approach will have diverse applications beyond divergence time dating, including dating fossils that are temporally unconstrained, testing of the 'morphological clock', and for uncovering potential model misspecification and/or data errors when controversial phylogenetic hypotheses are obtained based on combined divergence dating analyses.This article is part of the themed issue 'Dating species divergences using rocks and clocks'. © 2016 The Authors.

Bayesian phylogenetic estimation of fossil ages

PubMed Central

Drummond, Alexei J.; Stadler, Tanja

2016-01-01

Recent advances have allowed for both morphological fossil evidence and molecular sequences to be integrated into a single combined inference of divergence dates under the rule of Bayesian probability. In particular, the fossilized birth–death tree prior and the Lewis-Mk model of discrete morphological evolution allow for the estimation of both divergence times and phylogenetic relationships between fossil and extant taxa. We exploit this statistical framework to investigate the internal consistency of these models by producing phylogenetic estimates of the age of each fossil in turn, within two rich and well-characterized datasets of fossil and extant species (penguins and canids). We find that the estimation accuracy of fossil ages is generally high with credible intervals seldom excluding the true age and median relative error in the two datasets of 5.7% and 13.2%, respectively. The median relative standard error (RSD) was 9.2% and 7.2%, respectively, suggesting good precision, although with some outliers. In fact, in the two datasets we analyse, the phylogenetic estimate of fossil age is on average less than 2 Myr from the mid-point age of the geological strata from which it was excavated. The high level of internal consistency found in our analyses suggests that the Bayesian statistical model employed is an adequate fit for both the geological and morphological data, and provides evidence from real data that the framework used can accurately model the evolution of discrete morphological traits coded from fossil and extant taxa. We anticipate that this approach will have diverse applications beyond divergence time dating, including dating fossils that are temporally unconstrained, testing of the ‘morphological clock', and for uncovering potential model misspecification and/or data errors when controversial phylogenetic hypotheses are obtained based on combined divergence dating analyses. This article is part of the themed issue ‘Dating species divergences using rocks and clocks’. PMID:27325827

Towards a Credibility Assessment of Models and Simulations

NASA Technical Reports Server (NTRS)

Blattnig, Steve R.; Green, Lawrence L.; Luckring, James M.; Morrison, Joseph H.; Tripathi, Ram K.; Zang, Thomas A.

2008-01-01

A scale is presented to evaluate the rigor of modeling and simulation (M&S) practices for the purpose of supporting a credibility assessment of the M&S results. The scale distinguishes required and achieved levels of rigor for a set of M&S elements that contribute to credibility including both technical and process measures. The work has its origins in an interest within NASA to include a Credibility Assessment Scale in development of a NASA standard for models and simulations.

Bayesian inference for the distribution of grams of marijuana in a joint.

PubMed

Ridgeway, Greg; Kilmer, Beau

2016-08-01

The average amount of marijuana in a joint is unknown, yet this figure is a critical quantity for creating credible measures of marijuana consumption. It is essential for projecting tax revenues post-legalization, estimating the size of illicit marijuana markets, and learning about how much marijuana users are consuming in order to understand health and behavioral consequences. Arrestee Drug Abuse Monitoring data collected between 2000 and 2010 contain relevant information on 10,628 marijuana transactions, joints and loose marijuana purchases, including the city in which the purchase occurred and the price paid for the marijuana. Using the Brown-Silverman drug pricing model to link marijuana price and weight, we are able to infer the distribution of grams of marijuana in a joint and provide a Bayesian posterior distribution for the mean weight of marijuana in a joint. We estimate that the mean weight of marijuana in a joint is 0.32g (95% Bayesian posterior interval: 0.30-0.35). Our estimate of the mean weight of marijuana in a joint is lower than figures commonly used to make estimates of marijuana consumption. These estimates can be incorporated into drug policy discussions to produce better understanding about illicit marijuana markets, the size of potential legalized marijuana markets, and health and behavior outcomes. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Bayesian Nonparametric Ordination for the Analysis of Microbial Communities.

PubMed

Ren, Boyu; Bacallado, Sergio; Favaro, Stefano; Holmes, Susan; Trippa, Lorenzo

2017-01-01

Human microbiome studies use sequencing technologies to measure the abundance of bacterial species or Operational Taxonomic Units (OTUs) in samples of biological material. Typically the data are organized in contingency tables with OTU counts across heterogeneous biological samples. In the microbial ecology community, ordination methods are frequently used to investigate latent factors or clusters that capture and describe variations of OTU counts across biological samples. It remains important to evaluate how uncertainty in estimates of each biological sample's microbial distribution propagates to ordination analyses, including visualization of clusters and projections of biological samples on low dimensional spaces. We propose a Bayesian analysis for dependent distributions to endow frequently used ordinations with estimates of uncertainty. A Bayesian nonparametric prior for dependent normalized random measures is constructed, which is marginally equivalent to the normalized generalized Gamma process, a well-known prior for nonparametric analyses. In our prior, the dependence and similarity between microbial distributions is represented by latent factors that concentrate in a low dimensional space. We use a shrinkage prior to tune the dimensionality of the latent factors. The resulting posterior samples of model parameters can be used to evaluate uncertainty in analyses routinely applied in microbiome studies. Specifically, by combining them with multivariate data analysis techniques we can visualize credible regions in ecological ordination plots. The characteristics of the proposed model are illustrated through a simulation study and applications in two microbiome datasets.

Bivariate Left-Censored Bayesian Model for Predicting Exposure: Preliminary Analysis of Worker Exposure during the Deepwater Horizon Oil Spill.

PubMed

Groth, Caroline; Banerjee, Sudipto; Ramachandran, Gurumurthy; Stenzel, Mark R; Sandler, Dale P; Blair, Aaron; Engel, Lawrence S; Kwok, Richard K; Stewart, Patricia A

2017-01-01

In April 2010, the Deepwater Horizon oil rig caught fire and exploded, releasing almost 5 million barrels of oil into the Gulf of Mexico over the ensuing 3 months. Thousands of oil spill workers participated in the spill response and clean-up efforts. The GuLF STUDY being conducted by the National Institute of Environmental Health Sciences is an epidemiological study to investigate potential adverse health effects among these oil spill clean-up workers. Many volatile chemicals were released from the oil into the air, including total hydrocarbons (THC), which is a composite of the volatile components of oil including benzene, toluene, ethylbenzene, xylene, and hexane (BTEXH). Our goal is to estimate exposure levels to these toxic chemicals for groups of oil spill workers in the study (hereafter called exposure groups, EGs) with likely comparable exposure distributions. A large number of air measurements were collected, but many EGs are characterized by datasets with a large percentage of censored measurements (below the analytic methods' limits of detection) and/or a limited number of measurements. We use THC for which there was less censoring to develop predictive linear models for specific BTEXH air exposures with higher degrees of censoring. We present a novel Bayesian hierarchical linear model that allows us to predict, for different EGs simultaneously, exposure levels of a second chemical while accounting for censoring in both THC and the chemical of interest. We illustrate the methodology by estimating exposure levels for several EGs on the Development Driller III, a rig vessel charged with drilling one of the relief wells. The model provided credible estimates in this example for geometric means, arithmetic means, variances, correlations, and regression coefficients for each group. This approach should be considered when estimating exposures in situations when multiple chemicals are correlated and have varying degrees of censoring. © The Author 2017. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.

Hierarchical Bayesian Approach To Reduce Uncertainty in the Aquatic Effect Assessment of Realistic Chemical Mixtures.

PubMed

Oldenkamp, Rik; Hendriks, Harrie W M; van de Meent, Dik; Ragas, Ad M J

2015-09-01

Species in the aquatic environment differ in their toxicological sensitivity to the various chemicals they encounter. In aquatic risk assessment, this interspecies variation is often quantified via species sensitivity distributions. Because the information available for the characterization of these distributions is typically limited, optimal use of information is essential to reduce uncertainty involved in the assessment. In the present study, we show that the credibility intervals on the estimated potentially affected fraction of species after exposure to a mixture of chemicals at environmentally relevant surface water concentrations can be extremely wide if a classical approach is followed, in which each chemical in the mixture is considered in isolation. As an alternative, we propose a hierarchical Bayesian approach, in which knowledge on the toxicity of chemicals other than those assessed is incorporated. A case study with a mixture of 13 pharmaceuticals demonstrates that this hierarchical approach results in more realistic estimations of the potentially affected fraction, as a result of reduced uncertainty in species sensitivity distributions for data-poor chemicals.

A Bayesian inferential approach to quantify the transmission intensity of disease outbreak.

PubMed

Kadi, Adiveppa S; Avaradi, Shivakumari R

2015-01-01

Emergence of infectious diseases like influenza pandemic (H1N1) 2009 has become great concern, which posed new challenges to the health authorities worldwide. To control these diseases various studies have been developed in the field of mathematical modelling, which is useful tool for understanding the epidemiological dynamics and their dependence on social mixing patterns. We have used Bayesian approach to quantify the disease outbreak through key epidemiological parameter basic reproduction number (R0), using effective contacts, defined as sum of the product of incidence cases and probability of generation time distribution. We have estimated R0 from daily case incidence data for pandemic influenza A/H1N1 2009 in India, for the initial phase. The estimated R0 with 95% credible interval is consistent with several other studies on the same strain. Through sensitivity analysis our study indicates that infectiousness affects the estimate of R0. Basic reproduction number R0 provides the useful information to the public health system to do some effort in controlling the disease by using mitigation strategies like vaccination, quarantine, and so forth.

Taking error into account when fitting models using Approximate Bayesian Computation.

PubMed

van der Vaart, Elske; Prangle, Dennis; Sibly, Richard M

2018-03-01

Stochastic computer simulations are often the only practical way of answering questions relating to ecological management. However, due to their complexity, such models are difficult to calibrate and evaluate. Approximate Bayesian Computation (ABC) offers an increasingly popular approach to this problem, widely applied across a variety of fields. However, ensuring the accuracy of ABC's estimates has been difficult. Here, we obtain more accurate estimates by incorporating estimation of error into the ABC protocol. We show how this can be done where the data consist of repeated measures of the same quantity and errors may be assumed to be normally distributed and independent. We then derive the correct acceptance probabilities for a probabilistic ABC algorithm, and update the coverage test with which accuracy is assessed. We apply this method, which we call error-calibrated ABC, to a toy example and a realistic 14-parameter simulation model of earthworms that is used in environmental risk assessment. A comparison with exact methods and the diagnostic coverage test show that our approach improves estimation of parameter values and their credible intervals for both models. © 2017 by the Ecological Society of America.

A Bayesian approach for estimating under-reported dengue incidence with a focus on non-linear associations between climate and dengue in Dhaka, Bangladesh.

PubMed

Sharmin, Sifat; Glass, Kathryn; Viennet, Elvina; Harley, David

2018-04-01

Determining the relation between climate and dengue incidence is challenging due to under-reporting of disease and consequent biased incidence estimates. Non-linear associations between climate and incidence compound this. Here, we introduce a modelling framework to estimate dengue incidence from passive surveillance data while incorporating non-linear climate effects. We estimated the true number of cases per month using a Bayesian generalised linear model, developed in stages to adjust for under-reporting. A semi-parametric thin-plate spline approach was used to quantify non-linear climate effects. The approach was applied to data collected from the national dengue surveillance system of Bangladesh. The model estimated that only 2.8% (95% credible interval 2.7-2.8) of all cases in the capital Dhaka were reported through passive case reporting. The optimal mean monthly temperature for dengue transmission is 29℃ and average monthly rainfall above 15 mm decreases transmission. Our approach provides an estimate of true incidence and an understanding of the effects of temperature and rainfall on dengue transmission in Dhaka, Bangladesh.

Impact of Bayesian Priors on the Characterization of Binary Black Hole Coalescences

NASA Astrophysics Data System (ADS)

Vitale, Salvatore; Gerosa, Davide; Haster, Carl-Johan; Chatziioannou, Katerina; Zimmerman, Aaron

2017-12-01

In a regime where data are only mildly informative, prior choices can play a significant role in Bayesian statistical inference, potentially affecting the inferred physics. We show this is indeed the case for some of the parameters inferred from current gravitational-wave measurements of binary black hole coalescences. We reanalyze the first detections performed by the twin LIGO interferometers using alternative (and astrophysically motivated) prior assumptions. We find different prior distributions can introduce deviations in the resulting posteriors that impact the physical interpretation of these systems. For instance, (i) limits on the 90% credible interval on the effective black hole spin χeff are subject to variations of ˜10 % if a prior with black hole spins mostly aligned to the binary's angular momentum is considered instead of the standard choice of isotropic spin directions, and (ii) under priors motivated by the initial stellar mass function, we infer tighter constraints on the black hole masses, and in particular, we find no support for any of the inferred masses within the putative mass gap M ≲5 M⊙.

Impact of Bayesian Priors on the Characterization of Binary Black Hole Coalescences.

PubMed

Vitale, Salvatore; Gerosa, Davide; Haster, Carl-Johan; Chatziioannou, Katerina; Zimmerman, Aaron

2017-12-22

In a regime where data are only mildly informative, prior choices can play a significant role in Bayesian statistical inference, potentially affecting the inferred physics. We show this is indeed the case for some of the parameters inferred from current gravitational-wave measurements of binary black hole coalescences. We reanalyze the first detections performed by the twin LIGO interferometers using alternative (and astrophysically motivated) prior assumptions. We find different prior distributions can introduce deviations in the resulting posteriors that impact the physical interpretation of these systems. For instance, (i) limits on the 90% credible interval on the effective black hole spin χ_{eff} are subject to variations of ∼10% if a prior with black hole spins mostly aligned to the binary's angular momentum is considered instead of the standard choice of isotropic spin directions, and (ii) under priors motivated by the initial stellar mass function, we infer tighter constraints on the black hole masses, and in particular, we find no support for any of the inferred masses within the putative mass gap M≲5  M_{⊙}.

Estimating the extent and distribution of new-onset adult asthma in British Columbia using frequentist and Bayesian approaches.

PubMed

Beach, Jeremy; Burstyn, Igor; Cherry, Nicola

2012-07-01

We previously described a method to identify the incidence of new-onset adult asthma (NOAA) in Alberta by industry and occupation, utilizing Workers' Compensation Board (WCB) and physician billing data. The aim of this study was to extend this method to data from British Columbia (BC) so as to compare the two provinces and to incorporate Bayesian methodology into estimates of risk. WCB claims for any reason 1995-2004 were linked to physician billing data. NOAA was defined as a billing for asthma (ICD-9 493) in the 12 months before a WCB claim without asthma in the previous 3 years. Incidence was calculated by occupation and industry. In a matched case-referent analysis, associations with exposures were examined using an asthma-specific job exposure matrix (JEM). Posterior distributions from the Alberta analysis and estimated misclassification parameters were used as priors in the Bayesian analysis of the BC data. Among 1 118 239 eligible WCB claims the incidence of NOAA was 1.4%. Sixteen occupations and 44 industries had a significantly increased risk; six industries had a decreased risk. The JEM identified wood dust [odds ratio (OR) 1.55, 95% confidence interval (CI) 1.08-2.24] and animal antigens (OR 1.66, 95% CI 1.17-2.36) as related to an increased risk of NOAA. Exposure to isocyanates was associated with decreased risk (OR 0.57, 95% CI 0.39-0.85). Bayesian analyses taking account of exposure misclassification and informative priors resulted in posterior distributions of ORs with lower boundary of 95% credible intervals >1.00 for almost all exposures. The distribution of NOAA in BC appeared somewhat similar to that in Alberta, except for isocyanates. Bayesian analyses allowed incorporation of prior evidence into risk estimates, permitting reconsideration of the apparently protective effect of isocyanate exposure.

Genomic prediction using an iterative conditional expectation algorithm for a fast BayesC-like model.

PubMed

Dong, Linsong; Wang, Zhiyong

2018-06-11

Genomic prediction is feasible for estimating genomic breeding values because of dense genome-wide markers and credible statistical methods, such as Genomic Best Linear Unbiased Prediction (GBLUP) and various Bayesian methods. Compared with GBLUP, Bayesian methods propose more flexible assumptions for the distributions of SNP effects. However, most Bayesian methods are performed based on Markov chain Monte Carlo (MCMC) algorithms, leading to computational efficiency challenges. Hence, some fast Bayesian approaches, such as fast BayesB (fBayesB), were proposed to speed up the calculation. This study proposed another fast Bayesian method termed fast BayesC (fBayesC). The prior distribution of fBayesC assumes that a SNP with probability γ has a non-zero effect which comes from a normal density with a common variance. The simulated data from QTLMAS XII workshop and actual data on large yellow croaker were used to compare the predictive results of fBayesB, fBayesC and (MCMC-based) BayesC. The results showed that when γ was set as a small value, such as 0.01 in the simulated data or 0.001 in the actual data, fBayesB and fBayesC yielded lower prediction accuracies (abilities) than BayesC. In the actual data, fBayesC could yield very similar predictive abilities as BayesC when γ ≥ 0.01. When γ = 0.01, fBayesB could also yield similar results as fBayesC and BayesC. However, fBayesB could not yield an explicit result when γ ≥ 0.1, but a similar situation was not observed for fBayesC. Moreover, the computational speed of fBayesC was significantly faster than that of BayesC, making fBayesC a promising method for genomic prediction.

Bayesian hierarchical piecewise regression models: a tool to detect trajectory divergence between groups in long-term observational studies.

PubMed

Buscot, Marie-Jeanne; Wotherspoon, Simon S; Magnussen, Costan G; Juonala, Markus; Sabin, Matthew A; Burgner, David P; Lehtimäki, Terho; Viikari, Jorma S A; Hutri-Kähönen, Nina; Raitakari, Olli T; Thomson, Russell J

2017-06-06

Bayesian hierarchical piecewise regression (BHPR) modeling has not been previously formulated to detect and characterise the mechanism of trajectory divergence between groups of participants that have longitudinal responses with distinct developmental phases. These models are useful when participants in a prospective cohort study are grouped according to a distal dichotomous health outcome. Indeed, a refined understanding of how deleterious risk factor profiles develop across the life-course may help inform early-life interventions. Previous techniques to determine between-group differences in risk factors at each age may result in biased estimate of the age at divergence. We demonstrate the use of Bayesian hierarchical piecewise regression (BHPR) to generate a point estimate and credible interval for the age at which trajectories diverge between groups for continuous outcome measures that exhibit non-linear within-person response profiles over time. We illustrate our approach by modeling the divergence in childhood-to-adulthood body mass index (BMI) trajectories between two groups of adults with/without type 2 diabetes mellitus (T2DM) in the Cardiovascular Risk in Young Finns Study (YFS). Using the proposed BHPR approach, we estimated the BMI profiles of participants with T2DM diverged from healthy participants at age 16 years for males (95% credible interval (CI):13.5-18 years) and 21 years for females (95% CI: 19.5-23 years). These data suggest that a critical window for weight management intervention in preventing T2DM might exist before the age when BMI growth rate is naturally expected to decrease. Simulation showed that when using pairwise comparison of least-square means from categorical mixed models, smaller sample sizes tended to conclude a later age of divergence. In contrast, the point estimate of the divergence time is not biased by sample size when using the proposed BHPR method. BHPR is a powerful analytic tool to model long-term non-linear longitudinal outcomes, enabling the identification of the age at which risk factor trajectories diverge between groups of participants. The method is suitable for the analysis of unbalanced longitudinal data, with only a limited number of repeated measures per participants and where the time-related outcome is typically marked by transitional changes or by distinct phases of change over time.

How Environmental Uncertainty Moderates the Effect of Relative Advantage and Perceived Credibility on the Adoption of Mobile Health Services by Chinese Organizations in the Big Data Era.

PubMed

Chen, Xing; Zhang, Xing

2016-01-01

Despite the importance of adoption of mobile health services by an organization on the diffusion of mobile technology in the big data era, it has received minimal attention in literature. This study investigates how relative advantage and perceived credibility affect an organization's adoption of mobile health services, as well as how environmental uncertainty changes the relationship of relative advantage and perceived credibility with adoption. A research model that integrates relative advantage, perceived credibility, environmental uncertainty, and an organization's intention to use mobile health service is developed. Quantitative data are collected from senior managers and information systems managers in 320 Chinese healthcare organizations. The empirical findings show that while relative advantage and perceived credibility both have positive effects on an organization's intention to use mobile health services, relative advantage plays a more important role than perceived credibility. Moreover, environmental uncertainty positively moderates the effect of relative advantage on an organization's adoption of mobile health services. Thus, mobile health services in environments characterized with high levels of uncertainty are more likely to be adopted because of relative advantage than in environments with low levels of uncertainty.

How Environmental Uncertainty Moderates the Effect of Relative Advantage and Perceived Credibility on the Adoption of Mobile Health Services by Chinese Organizations in the Big Data Era

PubMed Central

2016-01-01

Despite the importance of adoption of mobile health services by an organization on the diffusion of mobile technology in the big data era, it has received minimal attention in literature. This study investigates how relative advantage and perceived credibility affect an organization's adoption of mobile health services, as well as how environmental uncertainty changes the relationship of relative advantage and perceived credibility with adoption. A research model that integrates relative advantage, perceived credibility, environmental uncertainty, and an organization's intention to use mobile health service is developed. Quantitative data are collected from senior managers and information systems managers in 320 Chinese healthcare organizations. The empirical findings show that while relative advantage and perceived credibility both have positive effects on an organization's intention to use mobile health services, relative advantage plays a more important role than perceived credibility. Moreover, environmental uncertainty positively moderates the effect of relative advantage on an organization's adoption of mobile health services. Thus, mobile health services in environments characterized with high levels of uncertainty are more likely to be adopted because of relative advantage than in environments with low levels of uncertainty. PMID:28115932

Colony-level assessment of Brucella and Leptospira in the Guadalupe fur seal, Isla Guadalupe, Mexico.

PubMed

Ziehl-Quirós, E Carolina; García-Aguilar, María C; Mellink, Eric

2017-01-24

The relatively small population size and restricted distribution of the Guadalupe fur seal Arctocephalus townsendi could make it highly vulnerable to infectious diseases. We performed a colony-level assessment in this species of the prevalence and presence of Brucella spp. and Leptospira spp., pathogenic bacteria that have been reported in several pinniped species worldwide. Forty-six serum samples were collected in 2014 from pups at Isla Guadalupe, the only place where the species effectively reproduces. Samples were tested for Brucella using 3 consecutive serological tests, and for Leptospira using the microscopic agglutination test. For each bacterium, a Bayesian approach was used to estimate prevalence to exposure, and an epidemiological model was used to test the null hypothesis that the bacterium was present in the colony. No serum sample tested positive for Brucella, and the statistical analyses concluded that the colony was bacterium-free with a 96.3% confidence level. However, a Brucella surveillance program would be highly recommendable. Twelve samples were positive (titers 1:50) to 1 or more serovars of Leptospira. The prevalence was calculated at 27.1% (95% credible interval: 15.6-40.3%), and the posterior analyses indicated that the colony was not Leptospira-free with a 100% confidence level. Serovars Icterohaemorrhagiae, Canicola, and Bratislava were detected, but only further research can unveil whether they affect the fur seal population.

Bayesian methods to determine performance differences and to quantify variability among centers in multi-center trials: the IHAST trial.

PubMed

Bayman, Emine O; Chaloner, Kathryn M; Hindman, Bradley J; Todd, Michael M

2013-01-16

To quantify the variability among centers and to identify centers whose performance are potentially outside of normal variability in the primary outcome and to propose a guideline that they are outliers. Novel statistical methodology using a Bayesian hierarchical model is used. Bayesian methods for estimation and outlier detection are applied assuming an additive random center effect on the log odds of response: centers are similar but different (exchangeable). The Intraoperative Hypothermia for Aneurysm Surgery Trial (IHAST) is used as an example. Analyses were adjusted for treatment, age, gender, aneurysm location, World Federation of Neurological Surgeons scale, Fisher score and baseline NIH stroke scale scores. Adjustments for differences in center characteristics were also examined. Graphical and numerical summaries of the between-center standard deviation (sd) and variability, as well as the identification of potential outliers are implemented. In the IHAST, the center-to-center variation in the log odds of favorable outcome at each center is consistent with a normal distribution with posterior sd of 0.538 (95% credible interval: 0.397 to 0.726) after adjusting for the effects of important covariates. Outcome differences among centers show no outlying centers. Four potential outlying centers were identified but did not meet the proposed guideline for declaring them as outlying. Center characteristics (number of subjects enrolled from the center, geographical location, learning over time, nitrous oxide, and temporary clipping use) did not predict outcome, but subject and disease characteristics did. Bayesian hierarchical methods allow for determination of whether outcomes from a specific center differ from others and whether specific clinical practices predict outcome, even when some centers/subgroups have relatively small sample sizes. In the IHAST no outlying centers were found. The estimated variability between centers was moderately large.

Identifiability of sorption parameters in stirred flow-through reactor experiments and their identification with a Bayesian approach.

PubMed

Nicoulaud-Gouin, V; Garcia-Sanchez, L; Giacalone, M; Attard, J C; Martin-Garin, A; Bois, F Y

2016-10-01

This paper addresses the methodological conditions -particularly experimental design and statistical inference- ensuring the identifiability of sorption parameters from breakthrough curves measured during stirred flow-through reactor experiments also known as continuous flow stirred-tank reactor (CSTR) experiments. The equilibrium-kinetic (EK) sorption model was selected as nonequilibrium parameterization embedding the K d approach. Parameter identifiability was studied formally on the equations governing outlet concentrations. It was also studied numerically on 6 simulated CSTR experiments on a soil with known equilibrium-kinetic sorption parameters. EK sorption parameters can not be identified from a single breakthrough curve of a CSTR experiment, because K d,1 and k - were diagnosed collinear. For pairs of CSTR experiments, Bayesian inference allowed to select the correct models of sorption and error among sorption alternatives. Bayesian inference was conducted with SAMCAT software (Sensitivity Analysis and Markov Chain simulations Applied to Transfer models) which launched the simulations through the embedded simulation engine GNU-MCSim, and automated their configuration and post-processing. Experimental designs consisting in varying flow rates between experiments reaching equilibrium at contamination stage were found optimal, because they simultaneously gave accurate sorption parameters and predictions. Bayesian results were comparable to maximum likehood method but they avoided convergence problems, the marginal likelihood allowed to compare all models, and credible interval gave directly the uncertainty of sorption parameters θ. Although these findings are limited to the specific conditions studied here, in particular the considered sorption model, the chosen parameter values and error structure, they help in the conception and analysis of future CSTR experiments with radionuclides whose kinetic behaviour is suspected. Copyright © 2016 Elsevier Ltd. All rights reserved.

The effect of top-level domains and advertisements on health web-site credibility.

PubMed

Walther, Joseph B; Wang, Zuoming; Loh, Tracy

2004-09-03

Concerns over health information on the Internet have generated efforts to enhance credibility markers; yet how users actually assess the credibility of online health information is largely unknown. This study set out to (1) establish a parsimonious and valid questionnaire instrument to measure credibility of Internet health information by drawing on various previous measures of source, news, and other credibility scales; and (2) to identify the effects of Web-site domains and advertising on credibility perceptions. Respondents (N = 156) examined one of 12 Web-site mock-ups and completed credibility scales in a 3 x 2 x 2 between-subjects experimental design. Factor analysis and validity checks were used for item reduction, and analysis of variance was employed for hypothesis testing of Web-site features' effects. In an attempt to construct a credibility instrument, three dimensions of credibility (safety, trustworthiness, and dynamism) were retained, reflecting traditional credibility sub-themes, but composed of items from disparate sources. When testing the effect of the presence or absence of advertising on a Web site on credibility, we found that this depends on the site's domain, with a trend for advertisements having deleterious effects on the credibility of sites with .org domain, but positive effects on sites with .com or .edu domains. Health-information Web-site providers should select domains purposefully when they can, especially if they must accept on-site advertising. Credibility perceptions may not be invariant or stable, but rather are sensitive to topic and context. Future research may employ these findings in order to compare other forms of health-information delivery to optimal Web-site features.

[Risk profiling in cancer surveillance in contaminated sites: an example from the ISS-AIRTUM collaborative study].

PubMed

Catelan, Dolores; Buzzoni, Carlotta; Coviello, Enzo; Crocetti, Emanuele; Pasetto, Roberto; Pirastu, Roberta; Biggeri, Annibale

2014-01-01

Epidemiological surveillance on high risk environmental areas or areas covered by cancer registration yields long inventories of relative risks. Summaries of the results' tables must be produced to identify priorities and tailor public health actions. The aim is, therefore, to draw conclusions from each area's disease profile, or from the area signature of each disease.With this inmind, we used data on cancer incidence from 17 Cancer Registries that participated in the ISS-AIRTUM (National Institute of Health-Italian Network of Cancer Registries) study, and we produced conditional and marginal rankings of areas/diseases using a multivariate hierarchical Bayesian model. In this context, it is important to obtain an uncertainty evaluation by calculating the credibility intervals of ranks. The areas marginal ranking shows a large overlapping of credibility intervals, such that it is not possible to speak of a limited number of ISS-AIRTUM areas as being particularly affected. Every ISS-AIRTUMarea, therefore,must be considered individually and ordering themby ranking of cancer incidence wouldn't be appropriate. Instead,marginal ranking of diseases highlights the impact of asbestos exposure in all the analyzed areas.

The role of probability arguments in the history of science.

PubMed

Weinert, Friedel

2010-03-01

The paper examines Wesley Salmon's claim that the primary role of plausibility arguments in the history of science is to impose constraints on the prior probability of hypotheses (in the language of Bayesian confirmation theory). A detailed look at Copernicanism and Darwinism and, more briefly, Rutherford's discovery of the atomic nucleus reveals a further and arguably more important role of plausibility arguments. It resides in the consideration of likelihoods, which state how likely a given hypothesis makes a given piece of evidence. In each case the likelihoods raise the probability of one of the competing hypotheses and diminish the credibility of its rival, and this may happen either on the basis of 'old' or 'new' evidence.

Understanding independence

NASA Astrophysics Data System (ADS)

Annan, James; Hargreaves, Julia

2016-04-01

In order to perform any Bayesian processing of a model ensemble, we need a prior over the ensemble members. In the case of multimodel ensembles such as CMIP, the historical approach of ``model democracy'' (i.e. equal weight for all models in the sample) is no longer credible (if it ever was) due to model duplication and inbreeding. The question of ``model independence'' is central to the question of prior weights. However, although this question has been repeatedly raised, it has not yet been satisfactorily addressed. Here I will discuss the issue of independence and present a theoretical foundation for understanding and analysing the ensemble in this context. I will also present some simple examples showing how these ideas may be applied and developed.

Associations of teacher credibility and teacher affinity with learning outcomes in health classrooms

PubMed Central

Anderman, Eric M.; O’Connell, Ann A.

2011-01-01

In the present study (N = 633), we examine the role of teacher credibility and teacher affinity in classrooms. We explore the relations among these two characteristics and student gains in knowledge and valuing of learning about HIV and pregnancy prevention across high school classrooms. Results marshaled support for the notion that teacher characteristics are associated with classroom-level gains in learning outcomes. Above and beyond student-level predictors, teacher credibility (aggregated to the classroom level) was positively related to increases in knowledge across classrooms, whereas aggregated teacher affinity was positively related to an increased valuing of learning about HIV and pregnancy prevention across classrooms. Future directions and implications for practice are discussed. PMID:24876800

A search for [Formula: see text] resonances with the ATLAS detector in 2.05 fb-1 of proton-proton collisions at [Formula: see text].

PubMed

Aad, G; Abbott, B; Abdallah, J; Abdel Khalek, S; Abdelalim, A A; Abdinov, O; Abi, B; Abolins, M; AbouZeid, O S; Abramowicz, H; Abreu, H; Acerbi, E; Acharya, B S; Adamczyk, L; Adams, D L; Addy, T N; Adelman, J; Adomeit, S; Adragna, P; Adye, T; Aefsky, S; Aguilar-Saavedra, J A; Agustoni, M; Aharrouche, M; Ahlen, S P; Ahles, F; Ahmad, A; Ahsan, M; Aielli, G; Akdogan, T; Åkesson, T P A; Akimoto, G; Akimov, A V; Alam, M S; Alam, M A; Albert, J; Albrand, S; Aleksa, M; Aleksandrov, I N; Alessandria, F; Alexa, C; Alexander, G; Alexandre, G; Alexopoulos, T; Alhroob, M; Aliev, M; Alimonti, G; Alison, J; Allbrooke, B M M; Allport, P P; Allwood-Spiers, S E; Almond, J; Aloisio, A; Alon, R; Alonso, A; Alvarez Gonzalez, B; Alviggi, M G; Amako, K; Amelung, C; Ammosov, V V; Amorim, A; Amram, N; Anastopoulos, C; Ancu, L S; Andari, N; Andeen, T; Anders, C F; Anders, G; Anderson, K J; Andreazza, A; Andrei, V; Anduaga, X S; Anger, P; Angerami, A; Anghinolfi, F; Anisenkov, A; Anjos, N; Annovi, A; Antonaki, A; Antonelli, M; Antonov, A; Antos, J; Anulli, F; Aoun, S; Aperio Bella, L; Apolle, R; Arabidze, G; Aracena, I; Arai, Y; Arce, A T H; Arfaoui, S; Arguin, J-F; Arik, E; Arik, M; Armbruster, A J; Arnaez, O; Arnal, V; Arnault, C; Artamonov, A; Artoni, G; Arutinov, D; Asai, S; Asfandiyarov, R; Ask, S; Åsman, B; Asquith, L; Assamagan, K; Astbury, A; Aubert, B; Auge, E; Augsten, K; Aurousseau, M; Avolio, G; Avramidou, R; Axen, D; Azuelos, G; Azuma, Y; Baak, M A; Baccaglioni, G; Bacci, C; Bach, A M; Bachacou, H; Bachas, K; Backes, M; Backhaus, M; Badescu, E; Bagnaia, P; Bahinipati, S; Bai, Y; Bailey, D C; Bain, T; Baines, J T; Baker, O K; Baker, M D; Baker, S; Banas, E; Banerjee, P; Banerjee, Sw; Banfi, D; Bangert, A; Bansal, V; Bansil, H S; Barak, L; Baranov, S P; Barbaro Galtieri, A; Barber, T; Barberio, E L; Barberis, D; Barbero, M; Bardin, D Y; Barillari, T; Barisonzi, M; Barklow, T; Barlow, N; Barnett, B M; Barnett, R M; Baroncelli, A; Barone, G; Barr, A J; Barreiro, F; Barreiro Guimarães da Costa, J; Barrillon, P; Bartoldus, R; Barton, A E; Bartsch, V; Bates, R L; Batkova, L; Batley, J R; Battaglia, A; Battistin, M; Bauer, F; Bawa, H S; Beale, S; Beau, T; Beauchemin, P H; Beccherle, R; Bechtle, P; Beck, H P; Becker, A K; Becker, S; Beckingham, M; Becks, K H; Beddall, A J; Beddall, A; Bedikian, S; Bednyakov, V A; Bee, C P; Begel, M; Behar Harpaz, S; Beimforde, M; Belanger-Champagne, C; Bell, P J; Bell, W H; Bella, G; Bellagamba, L; Bellina, F; Bellomo, M; Belloni, A; Beloborodova, O; Belotskiy, K; Beltramello, O; Benary, O; Benchekroun, D; Bendtz, K; Benekos, N; Benhammou, Y; Benhar Noccioli, E; Benitez Garcia, J A; Benjamin, D P; Benoit, M; Bensinger, J R; Benslama, K; Bentvelsen, S; Berge, D; Bergeaas Kuutmann, E; Berger, N; Berghaus, F; Berglund, E; Beringer, J; Bernat, P; Bernhard, R; Bernius, C; Berry, T; Bertella, C; Bertin, A; Bertolucci, F; Besana, M I; Besjes, G J; Besson, N; Bethke, S; Bhimji, W; Bianchi, R M; Bianco, M; Biebel, O; Bieniek, S P; Bierwagen, K; Biesiada, J; Biglietti, M; Bilokon, H; Bindi, M; Binet, S; Bingul, A; Bini, C; Biscarat, C; Bitenc, U; Black, K M; Blair, R E; Blanchard, J-B; Blanchot, G; Blazek, T; Blocker, C; Blocki, J; Blondel, A; Blum, W; Blumenschein, U; Bobbink, G J; Bobrovnikov, V B; Bocchetta, S S; Bocci, A; Boddy, C R; Boehler, M; Boek, J; Boelaert, N; Bogaerts, J A; Bogdanchikov, A; Bogouch, A; Bohm, C; Bohm, J; Boisvert, V; Bold, T; Boldea, V; Bolnet, N M; Bomben, M; Bona, M; Boonekamp, M; Booth, C N; Bordoni, S; Borer, C; Borisov, A; Borissov, G; Borjanovic, I; Borri, M; Borroni, S; Bortolotto, V; Bos, K; Boscherini, D; Bosman, M; Boterenbrood, H; Botterill, D; Bouchami, J; Boudreau, J; Bouhova-Thacker, E V; Boumediene, D; Bourdarios, C; Bousson, N; Boveia, A; Boyd, J; Boyko, I R; Bozovic-Jelisavcic, I; Bracinik, J; Branchini, P; Brandt, A; Brandt, G; Brandt, O; Bratzler, U; Brau, B; Brau, J E; Braun, H M; Brazzale, S F; Brelier, B; Bremer, J; Brendlinger, K; Brenner, R; Bressler, S; Britton, D; Brochu, F M; Brock, I; Brock, R; Brodet, E; Broggi, F; Bromberg, C; Bronner, J; Brooijmans, G; Brooks, T; Brooks, W K; Brown, G; Brown, H; Bruckman de Renstrom, P A; Bruncko, D; Bruneliere, R; Brunet, S; Bruni, A; Bruni, G; Bruschi, M; Buanes, T; Buat, Q; Bucci, F; Buchanan, J; Buchholz, P; Buckingham, R M; Buckley, A G; Buda, S I; Budagov, I A; Budick, B; Büscher, V; Bugge, L; Bulekov, O; Bundock, A C; Bunse, M; Buran, T; Burckhart, H; Burdin, S; Burgess, T; Burke, S; Busato, E; Bussey, P; Buszello, C P; Butler, B; Butler, J M; Buttar, C M; Butterworth, J M; Buttinger, W; Cabrera Urbán, S; Caforio, D; Cakir, O; Calafiura, P; Calderini, G; Calfayan, P; Calkins, R; Caloba, L P; Caloi, R; Calvet, D; Calvet, S; Camacho Toro, R; Camarri, P; Cameron, D; Caminada, L M; Campana, S; Campanelli, M; Canale, V; Canelli, F; Canepa, A; Cantero, J; Cantrill, R; Capasso, L; Capeans Garrido, M D M; Caprini, I; Caprini, M; Capriotti, D; Capua, M; Caputo, R; Cardarelli, R; Carli, T; Carlino, G; Carminati, L; Caron, B; Caron, S; Carquin, E; Carrillo Montoya, G D; Carter, A A; Carter, J R; Carvalho, J; Casadei, D; Casado, M P; Cascella, M; Caso, C; Castaneda Hernandez, A M; Castaneda-Miranda, E; Castillo Gimenez, V; Castro, N F; Cataldi, G; Catastini, P; Catinaccio, A; Catmore, J R; Cattai, A; Cattani, G; Caughron, S; Cavalleri, P; Cavalli, D; Cavalli-Sforza, M; Cavasinni, V; Ceradini, F; Cerqueira, A S; Cerri, A; Cerrito, L; Cerutti, F; Cetin, S A; Chafaq, A; Chakraborty, D; Chalupkova, I; Chan, K; Chapleau, B; Chapman, J D; Chapman, J W; Chareyre, E; Charlton, D G; Chavda, V; Chavez Barajas, C A; Cheatham, S; Chekanov, S; Chekulaev, S V; Chelkov, G A; Chelstowska, M A; Chen, C; Chen, H; Chen, S; Chen, X; Chen, Y; Cheplakov, A; Cherkaoui El Moursli, R; Chernyatin, V; Cheu, E; Cheung, S L; Chevalier, L; Chiefari, G; Chikovani, L; Childers, J T; Chilingarov, A; Chiodini, G; Chisholm, A S; Chislett, R T; Chitan, A; Chizhov, M V; Choudalakis, G; Chouridou, S; Christidi, I A; Christov, A; Chromek-Burckhart, D; Chu, M L; Chudoba, J; Ciapetti, G; Ciftci, A K; Ciftci, R; Cinca, D; Cindro, V; Ciocca, C; Ciocio, A; Cirilli, M; Cirkovic, P; Citterio, M; Ciubancan, M; Clark, A; Clark, P J; Clarke, R N; Cleland, W; Clemens, J C; Clement, B; Clement, C; Coadou, Y; Cobal, M; Coccaro, A; Cochran, J; Cogan, J G; Coggeshall, J; Cogneras, E; Colas, J; Colijn, A P; Collins, N J; Collins-Tooth, C; Collot, J; Colombo, T; Colon, G; Conde Muiño, P; Coniavitis, E; Conidi, M C; Consonni, S M; Consorti, V; Constantinescu, S; Conta, C; Conti, G; Conventi, F; Cooke, M; Cooper, B D; Cooper-Sarkar, A M; Copic, K; Cornelissen, T; Corradi, M; Corriveau, F; Cortes-Gonzalez, A; Cortiana, G; Costa, G; Costa, M J; Costanzo, D; Costin, T; Côté, D; Courneyea, L; Cowan, G; Cowden, C; Cox, B E; Cranmer, K; Crescioli, F; Cristinziani, M; Crosetti, G; Crupi, R; Crépé-Renaudin, S; Cuciuc, C-M; Cuenca Almenar, C; Cuhadar Donszelmann, T; Curatolo, M; Curtis, C J; Cuthbert, C; Cwetanski, P; Czirr, H; Czodrowski, P; Czyczula, Z; D'Auria, S; D'Onofrio, M; D'Orazio, A; Da Cunha Sargedas De Sousa, M J; Da Via, C; Dabrowski, W; Dafinca, A; Dai, T; Dallapiccola, C; Dam, M; Dameri, M; Damiani, D S; Danielsson, H O; Dao, V; Darbo, G; Darlea, G L; Davey, W; Davidek, T; Davidson, N; Davidson, R; Davies, E; Davies, M; Davison, A R; Davygora, Y; Dawe, E; Dawson, I; Daya-Ishmukhametova, R K; De, K; de Asmundis, R; De Castro, S; De Cecco, S; de Graat, J; De Groot, N; de Jong, P; De La Taille, C; De la Torre, H; De Lorenzi, F; de Mora, L; De Nooij, L; De Pedis, D; De Salvo, A; De Sanctis, U; De Santo, A; De Vivie De Regie, J B; De Zorzi, G; Dearnaley, W J; Debbe, R; Debenedetti, C; Dechenaux, B; Dedovich, D V; Degenhardt, J; Del Papa, C; Del Peso, J; Del Prete, T; Delemontex, T; Deliyergiyev, M; Dell'Acqua, A; Dell'Asta, L; Della Pietra, M; Della Volpe, D; Delmastro, M; Delsart, P A; Deluca, C; Demers, S; Demichev, M; Demirkoz, B; Deng, J; Denisov, S P; Derendarz, D; Derkaoui, J E; Derue, F; Dervan, P; Desch, K; Devetak, E; Deviveiros, P O; Dewhurst, A; DeWilde, B; Dhaliwal, S; Dhullipudi, R; Di Ciaccio, A; Di Ciaccio, L; Di Girolamo, A; Di Girolamo, B; Di Luise, S; Di Mattia, A; Di Micco, B; Di Nardo, R; Di Simone, A; Di Sipio, R; Diaz, M A; Diehl, E B; Dietrich, J; Dietzsch, T A; Diglio, S; Dindar Yagci, K; Dingfelder, J; Dinut, F; Dionisi, C; Dita, P; Dita, S; Dittus, F; Djama, F; Djobava, T; do Vale, M A B; Do Valle Wemans, A; Doan, T K O; Dobbs, M; Dobinson, R; Dobos, D; Dobson, E; Dodd, J; Doglioni, C; Doherty, T; Doi, Y; Dolejsi, J; Dolenc, I; Dolezal, Z; Dolgoshein, B A; Dohmae, T; Donadelli, M; Donini, J; Dopke, J; Doria, A; Dos Anjos, A; Dotti, A; Dova, M T; Doxiadis, A D; Doyle, A T; Dris, M; Dubbert, J; Dube, S; Duchovni, E; Duckeck, G; Dudarev, A; Dudziak, F; Dührssen, M; Duerdoth, I P; Duflot, L; Dufour, M-A; Dunford, M; Duran Yildiz, H; Duxfield, R; Dwuznik, M; Dydak, F; Düren, M; Ebke, J; Eckweiler, S; Edmonds, K; Edwards, C A; Edwards, N C; Ehrenfeld, W; Eifert, T; Eigen, G; Einsweiler, K; Eisenhandler, E; Ekelof, T; El Kacimi, M; Ellert, M; Elles, S; Ellinghaus, F; Ellis, K; Ellis, N; Elmsheuser, J; Elsing, M; Emeliyanov, D; Engelmann, R; Engl, A; Epp, B; Eppig, A; Erdmann, J; Ereditato, A; Eriksson, D; Ernst, J; Ernst, M; Ernwein, J; Errede, D; Errede, S; Ertel, E; Escalier, M; Esch, H; Escobar, C; Espinal Curull, X; Esposito, B; Etienne, F; Etienvre, A I; Etzion, E; Evangelakou, D; Evans, H; Fabbri, L; Fabre, C; Fakhrutdinov, R M; Falciano, S; Fang, Y; Fanti, M; Farbin, A; Farilla, A; Farley, J; Farooque, T; Farrell, S; Farrington, S M; Farthouat, P; Fassnacht, P; Fassouliotis, D; Fatholahzadeh, B; Favareto, A; Fayard, L; Fazio, S; Febbraro, R; Federic, P; Fedin, O L; Fedorko, W; Fehling-Kaschek, M; Feligioni, L; Fellmann, D; Feng, C; Feng, E J; Fenyuk, A B; Ferencei, J; Fernando, W; Ferrag, S; Ferrando, J; Ferrara, V; Ferrari, A; Ferrari, P; Ferrari, R; Ferreira de Lima, D E; Ferrer, A; Ferrere, D; Ferretti, C; Ferretto Parodi, A; Fiascaris, M; Fiedler, F; Filipčič, A; Filthaut, F; Fincke-Keeler, M; Fiolhais, M C N; Fiorini, L; Firan, A; Fischer, G; Fisher, M J; Flechl, M; Fleck, I; Fleckner, J; Fleischmann, P; Fleischmann, S; Flick, T; Floderus, A; Flores Castillo, L R; Flowerdew, M J; Fonseca Martin, T; Formica, A; Forti, A; Fortin, D; Fournier, D; Fox, H; Francavilla, P; Franchino, S; Francis, D; Frank, T; Franz, S; Fraternali, M; Fratina, S; French, S T; Friedrich, C; Friedrich, F; Froeschl, R; Froidevaux, D; Frost, J A; Fukunaga, C; Fullana Torregrosa, E; Fulsom, B G; Fuster, J; Gabaldon, C; Gabizon, O; Gadfort, T; Gadomski, S; Gagliardi, G; Gagnon, P; Galea, C; Gallas, E J; Gallo, V; Gallop, B J; Gallus, P; Gan, K K; Gao, Y S; Gaponenko, A; Garberson, F; Garcia-Sciveres, M; García, C; García Navarro, J E; Gardner, R W; Garelli, N; Garitaonandia, H; Garonne, V; Garvey, J; Gatti, C; Gaudio, G; Gaur, B; Gauthier, L; Gauzzi, P; Gavrilenko, I L; Gay, C; Gaycken, G; Gazis, E N; Ge, P; Gecse, Z; Gee, C N P; Geerts, D A A; Geich-Gimbel, Ch; Gellerstedt, K; Gemme, C; Gemmell, A; Genest, M H; Gentile, S; George, M; George, S; Gerlach, P; Gershon, A; Geweniger, C; Ghazlane, H; Ghodbane, N; Giacobbe, B; Giagu, S; Giakoumopoulou, V; Giangiobbe, V; Gianotti, F; Gibbard, B; Gibson, A; Gibson, S M; Gillberg, D; Gillman, A R; Gingrich, D M; Ginzburg, J; Giokaris, N; Giordani, M P; Giordano, R; Giorgi, F M; Giovannini, P; Giraud, P F; Giugni, D; Giunta, M; Giusti, P; Gjelsten, B K; Gladilin, L K; Glasman, C; Glatzer, J; Glazov, A; Glitza, K W; Glonti, G L; Goddard, J R; Godfrey, J; Godlewski, J; Goebel, M; Göpfert, T; Goeringer, C; Gössling, C; Goldfarb, S; Golling, T; Gomes, A; Gomez Fajardo, L S; Gonçalo, R; Goncalves Pinto Firmino Da Costa, J; Gonella, L; Gonzalez, S; González de la Hoz, S; Gonzalez Parra, G; Gonzalez Silva, M L; Gonzalez-Sevilla, S; Goodson, J J; Goossens, L; Gorbounov, P A; Gordon, H A; Gorelov, I; Gorfine, G; Gorini, B; Gorini, E; Gorišek, A; Gornicki, E; Gosdzik, B; Goshaw, A T; Gosselink, M; Gostkin, M I; Gough Eschrich, I; Gouighri, M; Goujdami, D; Goulette, M P; Goussiou, A G; Goy, C; Gozpinar, S; Grabowska-Bold, I; Grafström, P; Grahn, K-J; Grancagnolo, F; Grancagnolo, S; Grassi, V; Gratchev, V; Grau, N; Gray, H M; Gray, J A; Graziani, E; Grebenyuk, O G; Greenshaw, T; Greenwood, Z D; Gregersen, K; Gregor, I M; Grenier, P; Griffiths, J; Grigalashvili, N; Grillo, A A; Grinstein, S; Grishkevich, Y V; Grivaz, J-F; Gross, E; Grosse-Knetter, J; Groth-Jensen, J; Grybel, K; Guest, D; Guicheney, C; Guida, A; Guindon, S; Gul, U; Guler, H; Gunther, J; Guo, B; Guo, J; Gutierrez, P; Guttman, N; Gutzwiller, O; Guyot, C; Gwenlan, C; Gwilliam, C B; Haas, A; Haas, S; Haber, C; Hadavand, H K; Hadley, D R; Haefner, P; Hahn, F; Haider, S; Hajduk, Z; Hakobyan, H; Hall, D; Haller, J; Hamacher, K; Hamal, P; Hamer, M; Hamilton, A; Hamilton, S; Han, L; Hanagaki, K; Hanawa, K; Hance, M; Handel, C; Hanke, P; Hansen, J R; Hansen, J B; Hansen, J D; Hansen, P H; Hansson, P; Hara, K; Hare, G A; Harenberg, T; Harkusha, S; Harper, D; Harrington, R D; Harris, O M; Hartert, J; Hartjes, F; Haruyama, T; Harvey, A; Hasegawa, S; Hasegawa, Y; Hassani, S; Haug, S; Hauschild, M; Hauser, R; Havranek, M; Hawkes, C M; Hawkings, R J; Hawkins, A D; Hawkins, D; Hayakawa, T; Hayashi, T; Hayden, D; Hays, C P; Hayward, H S; Haywood, S J; He, M; Head, S J; Hedberg, V; Heelan, L; Heim, S; Heinemann, B; Heisterkamp, S; Helary, L; Heller, C; Heller, M; Hellman, S; Hellmich, D; Helsens, C; Henderson, R C W; Henke, M; Henrichs, A; Henriques Correia, A M; Henrot-Versille, S; Hensel, C; Henß, T; Hernandez, C M; Hernández Jiménez, Y; Herrberg, R; Herten, G; Hertenberger, R; Hervas, L; Hesketh, G G; Hessey, N P; Higón-Rodriguez, E; Hill, J C; Hiller, K H; Hillert, S; Hillier, S J; Hinchliffe, I; Hines, E; Hirose, M; Hirsch, F; Hirschbuehl, D; Hobbs, J; Hod, N; Hodgkinson, M C; Hodgson, P; Hoecker, A; Hoeferkamp, M R; Hoffman, J; Hoffmann, D; Hohlfeld, M; Holder, M; Holmgren, S O; Holy, T; Holzbauer, J L; Hong, T M; Hooft van Huysduynen, L; Horn, C; Horner, S; Hostachy, J-Y; Hou, S; Hoummada, A; Howard, J; Howarth, J; Hristova, I; Hrivnac, J; Hryn'ova, T; Hsu, P J; Hsu, S-C; Hubacek, Z; Hubaut, F; Huegging, F; Huettmann, A; Huffman, T B; Hughes, E W; Hughes, G; Huhtinen, M; Hurwitz, M; Husemann, U; Huseynov, N; Huston, J; Huth, J; Iacobucci, G; Iakovidis, G; Ibbotson, M; Ibragimov, I; Iconomidou-Fayard, L; Idarraga, J; Iengo, P; Igonkina, O; Ikegami, Y; Ikeno, M; Iliadis, D; Ilic, N; Ince, T; Inigo-Golfin, J; Ioannou, P; Iodice, M; Iordanidou, K; Ippolito, V; Irles Quiles, A; Isaksson, C; Ishino, M; Ishitsuka, M; Ishmukhametov, R; Issever, C; Istin, S; Ivashin, A V; Iwanski, W; Iwasaki, H; Izen, J M; Izzo, V; Jackson, B; Jackson, J N; Jackson, P; Jaekel, M R; Jain, V; Jakobs, K; Jakobsen, S; Jakoubek, T; Jakubek, J; Jana, D K; Jansen, E; Jansen, H; Jantsch, A; Janus, M; Jarlskog, G; Jeanty, L; Jen-La Plante, I; Jenni, P; Jeremie, A; Jež, P; Jézéquel, S; Jha, M K; Ji, H; Ji, W; Jia, J; Jiang, Y; Jimenez Belenguer, M; Jin, S; Jinnouchi, O; Joergensen, M D; Joffe, D; Johansen, M; Johansson, K E; Johansson, P; Johnert, S; Johns, K A; Jon-And, K; Jones, G; Jones, R W L; Jones, T J; Joram, C; Jorge, P M; Joshi, K D; Jovicevic, J; Jovin, T; Ju, X; Jung, C A; Jungst, R M; Juranek, V; Jussel, P; Juste Rozas, A; Kabana, S; Kaci, M; Kaczmarska, A; Kadlecik, P; Kado, M; Kagan, H; Kagan, M; Kajomovitz, E; Kalinin, S; Kalinovskaya, L V; Kama, S; Kanaya, N; Kaneda, M; Kaneti, S; Kanno, T; Kantserov, V A; Kanzaki, J; Kaplan, B; Kapliy, A; Kaplon, J; Kar, D; Karagounis, M; Karakostas, K; Karnevskiy, M; Kartvelishvili, V; Karyukhin, A N; Kashif, L; Kasieczka, G; Kass, R D; Kastanas, A; Kataoka, M; Kataoka, Y; Katsoufis, E; Katzy, J; Kaushik, V; Kawagoe, K; Kawamoto, T; Kawamura, G; Kayl, M S; Kazanin, V A; Kazarinov, M Y; Keeler, R; Kehoe, R; Keil, M; Kekelidze, G D; Keller, J S; Kenyon, M; Kepka, O; Kerschen, N; Kerševan, B P; Kersten, S; Kessoku, K; Keung, J; Khalil-Zada, F; Khandanyan, H; Khanov, A; Kharchenko, D; Khodinov, A; Khomich, A; Khoo, T J; Khoriauli, G; Khoroshilov, A; Khovanskiy, V; Khramov, E; Khubua, J; Kim, H; Kim, S H; Kimura, N; Kind, O; King, B T; King, M; King, R S B; Kirk, J; Kiryunin, A E; Kishimoto, T; Kisielewska, D; Kittelmann, T; Kladiva, E; Klein, M; Klein, U; Kleinknecht, K; Klemetti, M; Klier, A; Klimek, P; Klimentov, A; Klingenberg, R; Klinger, J A; Klinkby, E B; Klioutchnikova, T; Klok, P F; Klous, S; Kluge, E-E; Kluge, T; Kluit, P; Kluth, S; Knecht, N S; Kneringer, E; Knoops, E B F G; Knue, A; Ko, B R; Kobayashi, T; Kobel, M; Kocian, M; Kodys, P; Köneke, K; König, A C; Koenig, S; Köpke, L; Koetsveld, F; Koevesarki, P; Koffas, T; Koffeman, E; Kogan, L A; Kohlmann, S; Kohn, F; Kohout, Z; Kohriki, T; Koi, T; Kolachev, G M; Kolanoski, H; Kolesnikov, V; Koletsou, I; Koll, J; Kollefrath, M; Komar, A A; Komori, Y; Kondo, T; Kono, T; Kononov, A I; Konoplich, R; Konstantinidis, N; Koperny, S; Korcyl, K; Kordas, K; Korn, A; Korol, A; Korolkov, I; Korolkova, E V; Korotkov, V A; Kortner, O; Kortner, S; Kostyukhin, V V; Kotov, S; Kotov, V M; Kotwal, A; Kourkoumelis, C; Kouskoura, V; Koutsman, A; Kowalewski, R; Kowalski, T Z; Kozanecki, W; Kozhin, A S; Kral, V; Kramarenko, V A; Kramberger, G; Krasny, M W; Krasznahorkay, A; Kraus, J; Kraus, J K; Kreiss, S; Krejci, F; Kretzschmar, J; Krieger, N; Krieger, P; Kroeninger, K; Kroha, H; Kroll, J; Kroseberg, J; Krstic, J; Kruchonak, U; Krüger, H; Kruker, T; Krumnack, N; Krumshteyn, Z V; Kruth, A; Kubota, T; Kuday, S; Kuehn, S; Kugel, A; Kuhl, T; Kuhn, D; Kukhtin, V; Kulchitsky, Y; Kuleshov, S; Kummer, C; Kuna, M; Kunkle, J; Kupco, A; Kurashige, H; Kurata, M; Kurochkin, Y A; Kus, V; Kuwertz, E S; Kuze, M; Kvita, J; Kwee, R; La Rosa, A; La Rotonda, L; Labarga, L; Labbe, J; Lablak, S; Lacasta, C; Lacava, F; Lacker, H; Lacour, D; Lacuesta, V R; Ladygin, E; Lafaye, R; Laforge, B; Lagouri, T; Lai, S; Laisne, E; Lamanna, M; Lambourne, L; Lampen, C L; Lampl, W; Lancon, E; Landgraf, U; Landon, M P J; Lane, J L; Lang, V S; Lange, C; Lankford, A J; Lanni, F; Lantzsch, K; Laplace, S; Lapoire, C; Laporte, J F; Lari, T; Larner, A; Lassnig, M; Laurelli, P; Lavorini, V; Lavrijsen, W; Laycock, P; Le Dortz, O; Le Guirriec, E; Le Maner, C; Le Menedeu, E; LeCompte, T; Ledroit-Guillon, F; Lee, H; Lee, J S H; Lee, S C; Lee, L; Lefebvre, M; Legendre, M; Legger, F; Leggett, C; Lehmacher, M; Lehmann Miotto, G; Lei, X; Leite, M A L; Leitner, R; Lellouch, D; Lemmer, B; Lendermann, V; Leney, K J C; Lenz, T; Lenzen, G; Lenzi, B; Leonhardt, K; Leontsinis, S; Lepold, F; Leroy, C; Lessard, J-R; Lester, C G; Lester, C M; Levêque, J; Levin, D; Levinson, L J; Lewis, A; Lewis, G H; Leyko, A M; Leyton, M; Li, B; Li, H; Li, S; Li, X; Liang, Z; Liao, H; Liberti, B; Lichard, P; Lichtnecker, M; Lie, K; Liebig, W; Limbach, C; Limosani, A; Limper, M; Lin, S C; Linde, F; Linnemann, J T; Lipeles, E; Lipniacka, A; Liss, T M; Lissauer, D; Lister, A; Litke, A M; Liu, C; Liu, D; Liu, H; Liu, J B; Liu, L; Liu, M; Liu, Y; Livan, M; Livermore, S S A; Lleres, A; Llorente Merino, J; Lloyd, S L; Lobodzinska, E; Loch, P; Lockman, W S; Loddenkoetter, T; Loebinger, F K; Loginov, A; Loh, C W; Lohse, T; Lohwasser, K; Lokajicek, M; Lombardo, V P; Long, R E; Lopes, L; Lopez Mateos, D; Lorenz, J; Lorenzo Martinez, N; Losada, M; Loscutoff, P; Lo Sterzo, F; Losty, M J; Lou, X; Lounis, A; Loureiro, K F; Love, J; Love, P A; Lowe, A J; Lu, F; Lubatti, H J; Luci, C; Lucotte, A; Ludwig, A; Ludwig, D; Ludwig, I; Ludwig, J; Luehring, F; Luijckx, G; Lukas, W; Lumb, D; Luminari, L; Lund, E; Lund-Jensen, B; Lundberg, B; Lundberg, J; Lundberg, O; Lundquist, J; Lungwitz, M; Lynn, D; Lytken, E; Ma, H; Ma, L L; Maccarrone, G; Macchiolo, A; Maček, B; Machado Miguens, J; Mackeprang, R; Madaras, R J; Mader, W F; Maenner, R; Maeno, T; Mättig, P; Mättig, S; Magnoni, L; Magradze, E; Mahboubi, K; Mahmoud, S; Mahout, G; Maiani, C; Maidantchik, C; Maio, A; Majewski, S; Makida, Y; Makovec, N; Mal, P; Malaescu, B; Malecki, Pa; Malecki, P; Maleev, V P; Malek, F; Mallik, U; Malon, D; Malone, C; Maltezos, S; Malyshev, V; Malyukov, S; Mameghani, R; Mamuzic, J; Manabe, A; Mandelli, L; Mandić, I; Mandrysch, R; Maneira, J; Mangeard, P S; Manhaes de Andrade Filho, L; Mann, A; Manning, P M; Manousakis-Katsikakis, A; Mansoulie, B; Mapelli, A; Mapelli, L; March, L; Marchand, J F; Marchese, F; Marchiori, G; Marcisovsky, M; Marino, C P; Marroquim, F; Marshall, Z; Martens, F K; Marti, L F; Marti-Garcia, S; Martin, B; Martin, B; Martin, J P; Martin, T A; Martin, V J; Martin Dit Latour, B; Martin-Haugh, S; Martinez, M; Martinez Outschoorn, V; Martyniuk, A C; Marx, M; Marzano, F; Marzin, A; Masetti, L; Mashimo, T; Mashinistov, R; Masik, J; Maslennikov, A L; Massa, I; Massaro, G; Massol, N; Mastroberardino, A; Masubuchi, T; Matricon, P; Matsunaga, H; Matsushita, T; Mattravers, C; Maurer, J; Maxfield, S J; Mayne, A; Mazini, R; Mazur, M; Mazzaferro, L; Mazzanti, M; Mc Kee, S P; McCarn, A; McCarthy, R L; McCarthy, T G; McCubbin, N A; McFarlane, K W; Mcfayden, J A; McGlone, H; Mchedlidze, G; Mclaughlan, T; McMahon, S J; McPherson, R A; Meade, A; Mechnich, J; Mechtel, M; Medinnis, M; Meera-Lebbai, R; Meguro, T; Mehdiyev, R; Mehlhase, S; Mehta, A; Meier, K; Meirose, B; Melachrinos, C; Mellado Garcia, B R; Meloni, F; Mendoza Navas, L; Meng, Z; Mengarelli, A; Menke, S; Meoni, E; Mercurio, K M; Mermod, P; Merola, L; Meroni, C; Merritt, F S; Merritt, H; Messina, A; Metcalfe, J; Mete, A S; Meyer, C; Meyer, C; Meyer, J-P; Meyer, J; Meyer, J; Meyer, T C; Meyer, W T; Miao, J; Michal, S; Micu, L; Middleton, R P; Migas, S; Mijović, L; Mikenberg, G; Mikestikova, M; Mikuž, M; Miller, D W; Miller, R J; Mills, W J; Mills, C; Milov, A; Milstead, D A; Milstein, D; Minaenko, A A; Miñano Moya, M; Minashvili, I A; Mincer, A I; Mindur, B; Mineev, M; Ming, Y; Mir, L M; Mirabelli, G; Mitrevski, J; Mitsou, V A; Mitsui, S; Miyagawa, P S; Mjörnmark, J U; Moa, T; Moeller, V; Mönig, K; Möser, N; Mohapatra, S; Mohr, W; Moles-Valls, R; Monk, J; Monnier, E; Montejo Berlingen, J; Montesano, S; Monticelli, F; Monzani, S; Moore, R W; Moorhead, G F; Mora Herrera, C; Moraes, A; Morange, N; Morel, J; Morello, G; Moreno, D; Moreno Llácer, M; Morettini, P; Morgenstern, M; Morii, M; Morley, A K; Mornacchi, G; Morris, J D; Morvaj, L; Moser, H G; Mosidze, M; Moss, J; Mount, R; Mountricha, E; Mouraviev, S V; Moyse, E J W; Mueller, F; Mueller, J; Mueller, K; Müller, T A; Mueller, T; Muenstermann, D; Munwes, Y; Murray, W J; Mussche, I; Musto, E; Myagkov, A G; Myska, M; Nadal, J; Nagai, K; Nagano, K; Nagarkar, A; Nagasaka, Y; Nagel, M; Nairz, A M; Nakahama, Y; Nakamura, K; Nakamura, T; Nakano, I; Nanava, G; Napier, A; Narayan, R; Nash, M; Nattermann, T; Naumann, T; Navarro, G; Neal, H A; Nechaeva, P Yu; Neep, T J; Negri, A; Negri, G; Nektarijevic, S; Nelson, A; Nelson, T K; Nemecek, S; Nemethy, P; Nepomuceno, A A; Nessi, M; Neubauer, M S; Neusiedl, A; Neves, R M; Nevski, P; Newman, P R; Nguyen Thi Hong, V; Nickerson, R B; Nicolaidou, R; Nicquevert, B; Niedercorn, F; Nielsen, J; Nikiforou, N; Nikiforov, A; Nikolaenko, V; Nikolic-Audit, I; Nikolics, K; Nikolopoulos, K; Nilsen, H; Nilsson, P; Ninomiya, Y; Nisati, A; Nisius, R; Nobe, T; Nodulman, L; Nomachi, M; Nomidis, I; Nordberg, M; Norton, P R; Novakova, J; Nozaki, M; Nozka, L; Nugent, I M; Nuncio-Quiroz, A-E; Nunes Hanninger, G; Nunnemann, T; Nurse, E; O'Brien, B J; O'Neale, S W; O'Neil, D C; O'Shea, V; Oakes, L B; Oakham, F G; Oberlack, H; Ocariz, J; Ochi, A; Oda, S; Odaka, S; Odier, J; Ogren, H; Oh, A; Oh, S H; Ohm, C C; Ohshima, T; Okawa, H; Okumura, Y; Okuyama, T; Olariu, A; Olchevski, A G; Olivares Pino, S A; Oliveira, M; Oliveira Damazio, D; Oliver Garcia, E; Olivito, D; Olszewski, A; Olszowska, J; Onofre, A; Onyisi, P U E; Oram, C J; Oreglia, M J; Oren, Y; Orestano, D; Orlando, N; Orlov, I; Oropeza Barrera, C; Orr, R S; Osculati, B; Ospanov, R; Osuna, C; Otero Y Garzon, G; Ottersbach, J P; Ouchrif, M; Ouellette, E A; Ould-Saada, F; Ouraou, A; Ouyang, Q; Ovcharova, A; Owen, M; Owen, S; Ozcan, V E; Ozturk, N; Pacheco Pages, A; Padilla Aranda, C; Pagan Griso, S; Paganis, E; Paige, F; Pais, P; Pajchel, K; Palacino, G; Paleari, C P; Palestini, S; Pallin, D; Palma, A; Palmer, J D; Pan, Y B; Panagiotopoulou, E; Pani, P; Panikashvili, N; Panitkin, S; Pantea, D; Papadelis, A; Papadopoulou, Th D; Paramonov, A; Paredes Hernandez, D; Park, W; Parker, M A; Parodi, F; Parsons, J A; Parzefall, U; Pashapour, S; Pasqualucci, E; Passaggio, S; Passeri, A; Pastore, F; Pastore, Fr; Pásztor, G; Pataraia, S; Patel, N; Pater, J R; Patricelli, S; Pauly, T; Pecsy, M; Pedraza Morales, M I; Peleganchuk, S V; Pelikan, D; Peng, H; Penning, B; Penson, A; Penwell, J; Perantoni, M; Perez, K; Perez Cavalcanti, T; Perez Codina, E; Pérez García-Estañ, M T; Perez Reale, V; Perini, L; Pernegger, H; Perrino, R; Perrodo, P; Peshekhonov, V D; Peters, K; Petersen, B A; Petersen, J; Petersen, T C; Petit, E; Petridis, A; Petridou, C; Petrolo, E; Petrucci, F; Petschull, D; Petteni, M; Pezoa, R; Phan, A; Phillips, P W; Piacquadio, G; Picazio, A; Piccaro, E; Piccinini, M; Piec, S M; Piegaia, R; Pignotti, D T; Pilcher, J E; Pilkington, A D; Pina, J; Pinamonti, M; Pinder, A; Pinfold, J L; Pinto, B; Pizio, C; Plamondon, M; Pleier, M-A; Plotnikova, E; Poblaguev, A; Poddar, S; Podlyski, F; Poggioli, L; Poghosyan, T; Pohl, M; Polesello, G; Policicchio, A; Polini, A; Poll, J; Pollard, C S; Polychronakos, V; Pomeroy, D; Pommès, K; Pontecorvo, L; Pope, B G; Popeneciu, G A; Popovic, D S; Poppleton, A; Portell Bueso, X; Pospelov, G E; Pospisil, S; Potrap, I N; Potter, C J; Potter, C T; Poulard, G; Poveda, J; Pozdnyakov, V; Prabhu, R; Pralavorio, P; Pranko, A; Prasad, S; Pravahan, R; Prell, S; Pretzl, K; Price, D; Price, J; Price, L E; Prieur, D; Primavera, M; Prokofiev, K; Prokoshin, F; Protopopescu, S; Proudfoot, J; Prudent, X; Przybycien, M; Przysiezniak, H; Psoroulas, S; Ptacek, E; Pueschel, E; Purdham, J; Purohit, M; Puzo, P; Pylypchenko, Y; Qian, J; Quadt, A; Quarrie, D R; Quayle, W B; Quinonez, F; Raas, M; Radescu, V; Radloff, P; Rador, T; Ragusa, F; Rahal, G; Rahimi, A M; Rahm, D; Rajagopalan, S; Rammensee, M; Rammes, M; Randle-Conde, A S; Randrianarivony, K; Rauscher, F; Rave, T C; Raymond, M; Read, A L; Rebuzzi, D M; Redelbach, A; Redlinger, G; Reece, R; Reeves, K; Reinherz-Aronis, E; Reinsch, A; Reisinger, I; Rembser, C; Ren, Z L; Renaud, A; Rescigno, M; Resconi, S; Resende, B; Reznicek, P; Rezvani, R; Richter, R; Richter-Was, E; Ridel, M; Rijpstra, M; Rijssenbeek, M; Rimoldi, A; Rinaldi, L; Rios, R R; Riu, I; Rivoltella, G; Rizatdinova, F; Rizvi, E; Robertson, S H; Robichaud-Veronneau, A; Robinson, D; Robinson, J E M; Robson, A; Rocha de Lima, J G; Roda, C; Roda Dos Santos, D; Roe, A; Roe, S; Røhne, O; Rolli, S; Romaniouk, A; Romano, M; Romeo, G; Romero Adam, E; Roos, L; Ros, E; Rosati, S; Rosbach, K; Rose, A; Rose, M; Rosenbaum, G A; Rosenberg, E I; Rosendahl, P L; Rosenthal, O; Rosselet, L; Rossetti, V; Rossi, E; Rossi, L P; Rotaru, M; Roth, I; Rothberg, J; Rousseau, D; Royon, C R; Rozanov, A; Rozen, Y; Ruan, X; Rubbo, F; Rubinskiy, I; Ruckert, B; Ruckstuhl, N; Rud, V I; Rudolph, C; Rudolph, G; Rühr, F; Ruiz-Martinez, A; Rumyantsev, L; Rurikova, Z; Rusakovich, N A; Rutherfoord, J P; Ruwiedel, C; Ruzicka, P; Ryabov, Y F; Ryan, P; Rybar, M; Rybkin, G; Ryder, N C; Saavedra, A F; Sadeh, I; Sadrozinski, H F-W; Sadykov, R; Safai Tehrani, F; Sakamoto, H; Salamanna, G; Salamon, A; Saleem, M; Salek, D; Salihagic, D; Salnikov, A; Salt, J; Salvachua Ferrando, B M; Salvatore, D; Salvatore, F; Salvucci, A; Salzburger, A; Sampsonidis, D; Samset, B H; Sanchez, A; Sanchez Martinez, V; Sandaker, H; Sander, H G; Sanders, M P; Sandhoff, M; Sandoval, T; Sandoval, C; Sandstroem, R; Sankey, D P C; Sansoni, A; Santamarina Rios, C; Santoni, C; Santonico, R; Santos, H; Saraiva, J G; Sarangi, T; Sarkisyan-Grinbaum, E; Sarri, F; Sartisohn, G; Sasaki, O; Sasao, N; Satsounkevitch, I; Sauvage, G; Sauvan, E; Sauvan, J B; Savard, P; Savinov, V; Savu, D O; Sawyer, L; Saxon, D H; Saxon, J; Sbarra, C; Sbrizzi, A; Scallon, O; Scannicchio, D A; Scarcella, M; Schaarschmidt, J; Schacht, P; Schaefer, D; Schäfer, U; Schaepe, S; Schaetzel, S; Schaffer, A C; Schaile, D; Schamberger, R D; Schamov, A G; Scharf, V; Schegelsky, V A; Scheirich, D; Schernau, M; Scherzer, M I; Schiavi, C; Schieck, J; Schioppa, M; Schlenker, S; Schmidt, E; Schmieden, K; Schmitt, C; Schmitt, S; Schmitz, M; Schneider, B; Schnoor, U; Schöning, A; Schorlemmer, A L S; Schott, M; Schouten, D; Schovancova, J; Schram, M; Schroeder, C; Schroer, N; Schultens, M J; Schultes, J; Schultz-Coulon, H-C; Schulz, H; Schumacher, M; Schumm, B A; Schune, Ph; Schwanenberger, C; Schwartzman, A; Schwemling, Ph; Schwienhorst, R; Schwierz, R; Schwindling, J; Schwindt, T; Schwoerer, M; Sciolla, G; Scott, W G; Searcy, J; Sedov, G; Sedykh, E; Seidel, S C; Seiden, A; Seifert, F; Seixas, J M; Sekhniaidze, G; Sekula, S J; Selbach, K E; Seliverstov, D M; Sellden, B; Sellers, G; Seman, M; Semprini-Cesari, N; Serfon, C; Serin, L; Serkin, L; Seuster, R; Severini, H; Sfyrla, A; Shabalina, E; Shamim, M; Shan, L Y; Shank, J T; Shao, Q T; Shapiro, M; Shatalov, P B; Shaw, K; Sherman, D; Sherwood, P; Shibata, A; Shimizu, S; Shimojima, M; Shin, T; Shiyakova, M; Shmeleva, A; Shochet, M J; Short, D; Shrestha, S; Shulga, E; Shupe, M A; Sicho, P; Sidoti, A; Siegert, F; Sijacki, Dj; Silbert, O; Silva, J; Silver, Y; Silverstein, D; Silverstein, S B; Simak, V; Simard, O; Simic, Lj; Simion, S; Simioni, E; Simmons, B; Simoniello, R; Simonyan, M; Sinervo, P; Sinev, N B; Sipica, V; Siragusa, G; Sircar, A; Sisakyan, A N; Sivoklokov, S Yu; Sjölin, J; Sjursen, T B; Skinnari, L A; Skottowe, H P; Skovpen, K; Skubic, P; Slater, M; Slavicek, T; Sliwa, K; Smakhtin, V; Smart, B H; Smirnov, S Yu; Smirnov, Y; Smirnova, L N; Smirnova, O; Smith, B C; Smith, D; Smith, K M; Smizanska, M; Smolek, K; Snesarev, A A; Snow, S W; Snow, J; Snyder, S; Sobie, R; Sodomka, J; Soffer, A; Solans, C A; Solar, M; Solc, J; Soldatov, E Yu; Soldevila, U; Solfaroli Camillocci, E; Solodkov, A A; Solovyanov, O V; Soni, N; Sopko, V; Sopko, B; Sosebee, M; Soualah, R; Soukharev, A; Spagnolo, S; Spanò, F; Spighi, R; Spigo, G; Spila, F; Spiwoks, R; Spousta, M; Spreitzer, T; Spurlock, B; St Denis, R D; Stahlman, J; Stamen, R; Stanecka, E; Stanek, R W; Stanescu, C; Stanescu-Bellu, M; Stapnes, S; Starchenko, E A; Stark, J; Staroba, P; Starovoitov, P; Staszewski, R; Staude, A; Stavina, P; Steele, G; Steinbach, P; Steinberg, P; Stekl, I; Stelzer, B; Stelzer, H J; Stelzer-Chilton, O; Stenzel, H; Stern, S; Stewart, G A; Stillings, J A; Stockton, M C; Stoerig, K; Stoicea, G; Stonjek, S; Strachota, P; Stradling, A R; Straessner, A; Strandberg, J; Strandberg, S; Strandlie, A; Strang, M; Strauss, E; Strauss, M; Strizenec, P; Ströhmer, R; Strom, D M; Strong, J A; Stroynowski, R; Strube, J; Stugu, B; Stumer, I; Stupak, J; Sturm, P; Styles, N A; Soh, D A; Su, D; Subramania, Hs; Succurro, A; Sugaya, Y; Suhr, C; Suk, M; Sulin, V V; Sultansoy, S; Sumida, T; Sun, X; Sundermann, J E; Suruliz, K; Susinno, G; Sutton, M R; Suzuki, Y; Suzuki, Y; Svatos, M; Swedish, S; Sykora, I; Sykora, T; Sánchez, J; Ta, D; Tackmann, K; Taffard, A; Tafirout, R; Taiblum, N; Takahashi, Y; Takai, H; Takashima, R; Takeda, H; Takeshita, T; Takubo, Y; Talby, M; Talyshev, A; Tamsett, M C; Tanaka, J; Tanaka, R; Tanaka, S; Tanaka, S; Tanasijczuk, A J; Tani, K; Tannoury, N; Tapprogge, S; Tardif, D; Tarem, S; Tarrade, F; Tartarelli, G F; Tas, P; Tasevsky, M; Tassi, E; Tatarkhanov, M; Tayalati, Y; Taylor, C; Taylor, F E; Taylor, G N; Taylor, W; Teinturier, M; Teixeira Dias Castanheira, M; Teixeira-Dias, P; Temming, K K; Ten Kate, H; Teng, P K; Terada, S; Terashi, K; Terron, J; Testa, M; Teuscher, R J; Therhaag, J; Theveneaux-Pelzer, T; Thoma, S; Thomas, J P; Thompson, E N; Thompson, P D; Thompson, P D; Thompson, A S; Thomsen, L A; Thomson, E; Thomson, M; Thun, R P; Tian, F; Tibbetts, M J; Tic, T; Tikhomirov, V O; Tikhonov, Y A; Timoshenko, S; Tipton, P; Tique Aires Viegas, F J; Tisserant, S; Todorov, T; Todorova-Nova, S; Toggerson, B; Tojo, J; Tokár, S; Tokushuku, K; Tollefson, K; Tomoto, M; Tompkins, L; Toms, K; Tonoyan, A; Topfel, C; Topilin, N D; Torchiani, I; Torrence, E; Torres, H; Torró Pastor, E; Toth, J; Touchard, F; Tovey, D R; Trefzger, T; Tremblet, L; Tricoli, A; Trigger, I M; Trincaz-Duvoid, S; Tripiana, M F; Trischuk, W; Trocmé, B; Troncon, C; Trottier-McDonald, M; Trzebinski, M; Trzupek, A; Tsarouchas, C; Tseng, J C-L; Tsiakiris, M; Tsiareshka, P V; Tsionou, D; Tsipolitis, G; Tsiskaridze, V; Tskhadadze, E G; Tsukerman, I I; Tsulaia, V; Tsung, J-W; Tsuno, S; Tsybychev, D; Tua, A; Tudorache, A; Tudorache, V; Tuggle, J M; Turala, M; Turecek, D; Turk Cakir, I; Turlay, E; Turra, R; Tuts, P M; Tykhonov, A; Tylmad, M; Tyndel, M; Tzanakos, G; Uchida, K; Ueda, I; Ueno, R; Ugland, M; Uhlenbrock, M; Uhrmacher, M; Ukegawa, F; Unal, G; Undrus, A; Unel, G; Unno, Y; Urbaniec, D; Usai, G; Uslenghi, M; Vacavant, L; Vacek, V; Vachon, B; Vahsen, S; Valenta, J; Valente, P; Valentinetti, S; Valero, A; Valkar, S; Valladolid Gallego, E; Vallecorsa, S; Valls Ferrer, J A; van der Graaf, H; van der Kraaij, E; Van Der Leeuw, R; van der Poel, E; van der Ster, D; van Eldik, N; van Gemmeren, P; van Vulpen, I; Vanadia, M; Vandelli, W; Vaniachine, A; Vankov, P; Vannucci, F; Vari, R; Varol, T; Varouchas, D; Vartapetian, A; Varvell, K E; Vassilakopoulos, V I; Vazeille, F; Vazquez Schroeder, T; Vegni, G; Veillet, J J; Veloso, F; Veness, R; Veneziano, S; Ventura, A; Ventura, D; Venturi, M; Venturi, N; Vercesi, V; Verducci, M; Verkerke, W; Vermeulen, J C; Vest, A; Vetterli, M C; Vichou, I; Vickey, T; Vickey Boeriu, O E; Viehhauser, G H A; Viel, S; Villa, M; Villaplana Perez, M; Vilucchi, E; Vincter, M G; Vinek, E; Vinogradov, V B; Virchaux, M; Virzi, J; Vitells, O; Viti, M; Vivarelli, I; Vives Vaque, F; Vlachos, S; Vladoiu, D; Vlasak, M; Vogel, A; Vokac, P; Volpi, G; Volpi, M; Volpini, G; von der Schmitt, H; von Loeben, J; von Radziewski, H; von Toerne, E; Vorobel, V; Vorwerk, V; Vos, M; Voss, R; Voss, T T; Vossebeld, J H; Vranjes, N; Vranjes Milosavljevic, M; Vrba, V; Vreeswijk, M; Vu Anh, T; Vuillermet, R; Vukotic, I; Wagner, W; Wagner, P; Wahlen, H; Wahrmund, S; Wakabayashi, J; Walch, S; Walder, J; Walker, R; Walkowiak, W; Wall, R; Waller, P; Wang, C; Wang, H; Wang, H; Wang, J; Wang, J; Wang, R; Wang, S M; Wang, T; Warburton, A; Ward, C P; Warsinsky, M; Washbrook, A; Wasicki, C; Watkins, P M; Watson, A T; Watson, I J; Watson, M F; Watts, G; Watts, S; Waugh, A T; Waugh, B M; Weber, M; Weber, M S; Weber, P; Weidberg, A R; Weigell, P; Weingarten, J; Weiser, C; Wellenstein, H; Wells, P S; Wenaus, T; Wendland, D; Weng, Z; Wengler, T; Wenig, S; Wermes, N; Werner, M; Werner, P; Werth, M; Wessels, M; Wetter, J; Weydert, C; Whalen, K; Wheeler-Ellis, S J; White, A; White, M J; White, S; Whitehead, S R; Whiteson, D; Whittington, D; Wicek, F; Wicke, D; Wickens, F J; Wiedenmann, W; Wielers, M; Wienemann, P; Wiglesworth, C; Wiik-Fuchs, L A M; Wijeratne, P A; Wildauer, A; Wildt, M A; Wilhelm, I; Wilkens, H G; Will, J Z; Williams, E; Williams, H H; Willis, W; Willocq, S; Wilson, J A; Wilson, M G; Wilson, A; Wingerter-Seez, I; Winkelmann, S; Winklmeier, F; Wittgen, M; Wollstadt, S J; Wolter, M W; Wolters, H; Wong, W C; Wooden, G; Wosiek, B K; Wotschack, J; Woudstra, M J; Wozniak, K W; Wraight, K; Wright, C; Wright, M; Wrona, B; Wu, S L; Wu, X; Wu, Y; Wulf, E; Wynne, B M; Xella, S; Xiao, M; Xie, S; Xu, C; Xu, D; Yabsley, B; Yacoob, S; Yamada, M; Yamaguchi, H; Yamamoto, A; Yamamoto, K; Yamamoto, S; Yamamura, T; Yamanaka, T; Yamaoka, J; Yamazaki, T; Yamazaki, Y; Yan, Z; Yang, H; Yang, U K; Yang, Y; Yang, Z; Yanush, S; Yao, L; Yao, Y; Yasu, Y; Ybeles Smit, G V; Ye, J; Ye, S; Yilmaz, M; Yoosoofmiya, R; Yorita, K; Yoshida, R; Young, C; Young, C J; Youssef, S; Yu, D; Yu, J; Yu, J; Yuan, L; Yurkewicz, A; Zabinski, B; Zaidan, R; Zaitsev, A M; Zajacova, Z; Zanello, L; Zaytsev, A; Zeitnitz, C; Zeman, M; Zemla, A; Zendler, C; Zenin, O; Ženiš, T; Zinonos, Z; Zenz, S; Zerwas, D; Zevi Della Porta, G; Zhan, Z; Zhang, D; Zhang, H; Zhang, J; Zhang, X; Zhang, Z; Zhao, L; Zhao, T; Zhao, Z; Zhemchugov, A; Zhong, J; Zhou, B; Zhou, N; Zhou, Y; Zhu, C G; Zhu, H; Zhu, J; Zhu, Y; Zhuang, X; Zhuravlov, V; Zieminska, D; Zimin, N I; Zimmermann, R; Zimmermann, S; Zimmermann, S; Ziolkowski, M; Zitoun, R; Živković, L; Zmouchko, V V; Zobernig, G; Zoccoli, A; Zur Nedden, M; Zutshi, V; Zwalinski, L

A search for top quark pair resonances in final states containing at least one electron or muon has been performed with the ATLAS experiment at the CERN Large Hadron Collider. The search uses a data sample corresponding to an integrated luminosity of 2.05 fb -1 , which was recorded in 2011 at a proton-proton centre-of-mass energy of 7 TeV. No evidence for a resonance is found and limits are set on the production cross-section times branching ratio to [Formula: see text] for narrow and wide resonances. For narrow Z ' bosons, the observed 95 % Bayesian credibility level limits range from 9.3 pb to 0.95 pb for masses in the range of m Z ' =500 GeV to m Z ' =1300 GeV. The corresponding excluded mass region for a leptophobic topcolour Z ' boson (Kaluza-Klein gluon excitation in the Randall-Sundrum model) is m Z ' <880 GeV ([Formula: see text]).

Admixture analysis in relation to pedigree studies of introgression in a minority British cattle breed: the Lincoln Red.

PubMed

Bray, T C; Hall, S J G; Bruford, M W

2014-02-01

Investigation of historic population processes using molecular data has been facilitated by the use of approximate Bayesian computation (ABC), which enables the consideration of multiple alternative demographic scenarios. The Lincoln Red cattle breed provides a relatively simple example of two well-documented admixture events. Using molecular data for this breed, we found that structure did not resolve very low (<5% levels) of introgression, possibly due to sampling limitations. We evaluated the performance of two ABC approaches (2BAD and DIYABC) against those of two earlier methodologies, ADMIX and LEADMIX, by comparing their interpretations with the conclusions drawn from herdbook analysis. The ABC methods gave credible values for the proportions of the Lincoln Red genotype that are attributable to Aberdeen Angus and Limousin, although estimates of effective population size and event timing were not realistic. We suggest ABC methods are a valuable supplement to pedigree-based studies but that the accuracy of admixture determination is likely to diminish with increasing complexity of the admixture scenario. © 2013 Blackwell Verlag GmbH.

A search for $$t\\bar{t}$$ resonances with the ATLAS detector in 2.05 fb -1 of proton-proton collisions at $$\\sqrt{s} = 7~\\mathrm{TeV}$$

DOE PAGES

Aad, G.; Abbott, B.; Abdallah, J.; ...

2012-07-26

A search for top quark pair resonances in final states containing at least one electron or muon has been performed with the ATLAS experiment at the CERN Large Hadron Collider. The search uses a data sample corresponding to an integrated luminosity of 2.05 fb -1, which was recorded in 2011 at a proton-proton centre-of-mass energy of 7 TeV. No evidence for a resonance is found and limits are set on the production cross-section times branching ratio tomore » $$t\\overline{t}$$ for narrow and wide resonances. For narrow Z' bosons, the observed 95 % Bayesian credibility level limits range from 9.3 pb to 0.95 pb for masses in the range of m Z'=500 GeV to mZ'=1300 GeV. The corresponding excluded mass region for a leptophobic topcolour Z' boson (Kaluza-Klein gluon excitation in the Randall-Sundrum model) is m Z'<880 GeV (m gKK<1130 GeV).« less

Using SPM 12’s Second-Level Bayesian Inference Procedure for fMRI Analysis: Practical Guidelines for End Users

PubMed Central

Han, Hyemin; Park, Joonsuk

2018-01-01

Recent debates about the conventional traditional threshold used in the fields of neuroscience and psychology, namely P < 0.05, have spurred researchers to consider alternative ways to analyze fMRI data. A group of methodologists and statisticians have considered Bayesian inference as a candidate methodology. However, few previous studies have attempted to provide end users of fMRI analysis tools, such as SPM 12, with practical guidelines about how to conduct Bayesian inference. In the present study, we aim to demonstrate how to utilize Bayesian inference, Bayesian second-level inference in particular, implemented in SPM 12 by analyzing fMRI data available to public via NeuroVault. In addition, to help end users understand how Bayesian inference actually works in SPM 12, we examine outcomes from Bayesian second-level inference implemented in SPM 12 by comparing them with those from classical second-level inference. Finally, we provide practical guidelines about how to set the parameters for Bayesian inference and how to interpret the results, such as Bayes factors, from the inference. We also discuss the practical and philosophical benefits of Bayesian inference and directions for future research. PMID:29456498

Illicit and pharmaceutical drug consumption estimated via wastewater analysis. Part B: placing back-calculations in a formal statistical framework.

PubMed

Jones, Hayley E; Hickman, Matthew; Kasprzyk-Hordern, Barbara; Welton, Nicky J; Baker, David R; Ades, A E

2014-07-15

Concentrations of metabolites of illicit drugs in sewage water can be measured with great accuracy and precision, thanks to the development of sensitive and robust analytical methods. Based on assumptions about factors including the excretion profile of the parent drug, routes of administration and the number of individuals using the wastewater system, the level of consumption of a drug can be estimated from such measured concentrations. When presenting results from these 'back-calculations', the multiple sources of uncertainty are often discussed, but are not usually explicitly taken into account in the estimation process. In this paper we demonstrate how these calculations can be placed in a more formal statistical framework by assuming a distribution for each parameter involved, based on a review of the evidence underpinning it. Using a Monte Carlo simulations approach, it is then straightforward to propagate uncertainty in each parameter through the back-calculations, producing a distribution for instead of a single estimate of daily or average consumption. This can be summarised for example by a median and credible interval. To demonstrate this approach, we estimate cocaine consumption in a large urban UK population, using measured concentrations of two of its metabolites, benzoylecgonine and norbenzoylecgonine. We also demonstrate a more sophisticated analysis, implemented within a Bayesian statistical framework using Markov chain Monte Carlo simulation. Our model allows the two metabolites to simultaneously inform estimates of daily cocaine consumption and explicitly allows for variability between days. After accounting for this variability, the resulting credible interval for average daily consumption is appropriately wider, representing additional uncertainty. We discuss possibilities for extensions to the model, and whether analysis of wastewater samples has potential to contribute to a prevalence model for illicit drug use. Copyright © 2014. Published by Elsevier B.V.

Illicit and pharmaceutical drug consumption estimated via wastewater analysis. Part B: Placing back-calculations in a formal statistical framework

PubMed Central

Jones, Hayley E.; Hickman, Matthew; Kasprzyk-Hordern, Barbara; Welton, Nicky J.; Baker, David R.; Ades, A.E.

2014-01-01

Concentrations of metabolites of illicit drugs in sewage water can be measured with great accuracy and precision, thanks to the development of sensitive and robust analytical methods. Based on assumptions about factors including the excretion profile of the parent drug, routes of administration and the number of individuals using the wastewater system, the level of consumption of a drug can be estimated from such measured concentrations. When presenting results from these ‘back-calculations’, the multiple sources of uncertainty are often discussed, but are not usually explicitly taken into account in the estimation process. In this paper we demonstrate how these calculations can be placed in a more formal statistical framework by assuming a distribution for each parameter involved, based on a review of the evidence underpinning it. Using a Monte Carlo simulations approach, it is then straightforward to propagate uncertainty in each parameter through the back-calculations, producing a distribution for instead of a single estimate of daily or average consumption. This can be summarised for example by a median and credible interval. To demonstrate this approach, we estimate cocaine consumption in a large urban UK population, using measured concentrations of two of its metabolites, benzoylecgonine and norbenzoylecgonine. We also demonstrate a more sophisticated analysis, implemented within a Bayesian statistical framework using Markov chain Monte Carlo simulation. Our model allows the two metabolites to simultaneously inform estimates of daily cocaine consumption and explicitly allows for variability between days. After accounting for this variability, the resulting credible interval for average daily consumption is appropriately wider, representing additional uncertainty. We discuss possibilities for extensions to the model, and whether analysis of wastewater samples has potential to contribute to a prevalence model for illicit drug use. PMID:24636801

Spatial analysis of community-onset Staphylococcus aureus bacteremia in Queensland, Australia.

PubMed

Marquess, John; Hu, Wenbiao; Nimmo, Graeme R; Clements, Archie C A

2013-03-01

To investigate and describe the relationship between indigenous Australian populations, residential aged care services, and community-onset Staphylococcus aureus bacteremia (SAB) among patients admitted to public hospitals in Queensland, Australia. Ecological study. We used administrative healthcare data linked to microbiology results from patients with SAB admitted to Queensland public hospitals from 2005 through 2010 to identify community-onset infections. Data about indigenous Australian population and residential aged care services at the local government area level were obtained from the Queensland Office of Economic and Statistical Research. Associations between community-onset SAB and indigenous Australian population and residential aged care services were calculated using Poisson regression models in a Bayesian framework. Choropleth maps were used to describe the spatial patterns of SAB risk. We observed a 21% increase in relative risk (RR) of bacteremia with methicillin-susceptible S. aureus (MSSA; RR, 1.21 [95% credible interval, 1.15-1.26]) and a 24% increase in RR with nonmultiresistant methicillin-resistant S. aureus (nmMRSA; RR, 1.24 [95% credible interval, 1.13-1.34]) with a 10% increase in the indigenous Australian population proportion. There was no significant association between RR of SAB and the number of residential aged care services. Areas with the highest RR for nmMRSA and MSSA bacteremia were identified in the northern and western regions of Queensland. The RR of community-onset SAB varied spatially across Queensland. There was increased RR of community-onset SAB with nmMRSA and MSSA in areas of Queensland with increased indigenous population proportions. Additional research should be undertaken to understand other factors that increase the risk of infection due to this organism.

The Effect of Top-Level Domains and Advertisements on Health Web Site Credibility

PubMed Central

Wang, Zuoming; Loh, Tracy

2004-01-01

Background Concerns over health information on the Internet have generated efforts to enhance credibility markers; yet how users actually assess the credibility of online health information is largely unknown. Objective This study set out to (1) establish a parsimonious and valid questionnaire instrument to measure credibility of Internet health information by drawing on various previous measures of source, news, and other credibility scales; and (2) to identify the effects of Web-site domains and advertising on credibility perceptions. Methods Respondents (N = 156) examined one of 12 Web-site mock-ups and completed credibility scales in a 3 x 2 x 2 between-subjects experimental design. Factor analysis and validity checks were used for item reduction, and analysis of variance was employed for hypothesis testing of Web-site features' effects. Results In an attempt to construct a credibility instrument, three dimensions of credibility (safety, trustworthiness, and dynamism) were retained, reflecting traditional credibility sub-themes, but composed of items from disparate sources. When testing the effect of the presence or absence of advertising on a Web site on credibility, we found that this depends on the site's domain, with a trend for advertisements having deleterious effects on the credibility of sites with .org domain, but positive effects on sites with .com or .edu domains. Conclusions Health-information Web-site providers should select domains purposefully when they can, especially if they must accept on-site advertising. Credibility perceptions may not be invariant or stable, but rather are sensitive to topic and context. Future research may employ these findings in order to compare other forms of health-information delivery to optimal Web-site features. PMID:15471750

Perceived credibility and eyewitness testimony of children with intellectual disabilities.

PubMed

Henry, L; Ridley, A; Perry, J; Crane, L

2011-04-01

Although children with intellectual disabilities (ID) often provide accurate witness testimony, jurors tend to perceive their witness statements to be inherently unreliable. The current study explored the free recall transcripts of child witnesses with ID who had watched a video clip, relative to those of typically developing (TD) age-matched children, and assessed how mock jurors perceived these transcripts in the absence of knowledge of group (ID or TD) membership. A further aim of this research was to determine whether perceptions of credibility were associated with levels of free recall and witness characteristics (anxiety and mental age). Mock jurors rated the testimony of children with ID as less credible than that of a TD age-matched comparison group. This was largely because of the transcripts of the children with ID containing fewer details than those of the TD children. Anxiety and mental age were found to have no effect on perceived levels of credibility. It appears that even in the absence of knowledge of whether a child does or does not have ID, this factor still affects perceptions of credibility among mock jurors. Our findings suggest that fundamental differences in the quality of the witness transcripts lead to lower perceptions of credibility for children with ID. © 2011 The Authors. Journal of Intellectual Disability Research © 2011 Blackwell Publishing Ltd.

Prenatal Treatment for Serious Neurological Sequelae of Congenital Toxoplasmosis: An Observational Prospective Cohort Study

PubMed Central

Cortina-Borja, Mario; Tan, Hooi Kuan; Wallon, Martine; Paul, Malgorzata; Prusa, Andrea; Buffolano, Wilma; Malm, Gunilla; Salt, Alison; Freeman, Katherine; Petersen, Eskild; Gilbert, Ruth E.

2010-01-01

Background The effectiveness of prenatal treatment to prevent serious neurological sequelae (SNSD) of congenital toxoplasmosis is not known. Methods and Findings Congenital toxoplasmosis was prospectively identified by universal prenatal or neonatal screening in 14 European centres and children were followed for a median of 4 years. We evaluated determinants of postnatal death or SNSD defined by one or more of functional neurological abnormalities, severe bilateral visual impairment, or pregnancy termination for confirmed congenital toxoplasmosis. Two-thirds of the cohort received prenatal treatment (189/293; 65%). 23/293 (8%) fetuses developed SNSD of which nine were pregnancy terminations. Prenatal treatment reduced the risk of SNSD. The odds ratio for prenatal treatment, adjusted for gestational age at maternal seroconversion, was 0.24 (95% Bayesian credible intervals 0.07–0.71). This effect was robust to most sensitivity analyses. The number of infected fetuses needed to be treated to prevent one case of SNSD was three (95% Bayesian credible intervals 2–15) after maternal seroconversion at 10 weeks, and 18 (9–75) at 30 weeks of gestation. Pyrimethamine-sulphonamide treatment did not reduce SNSD compared with spiramycin alone (adjusted odds ratio 0.78, 0.21–2.95). The proportion of live-born infants with intracranial lesions detected postnatally who developed SNSD was 31.0% (17.0%–38.1%). Conclusion The finding that prenatal treatment reduced the risk of SNSD in infected fetuses should be interpreted with caution because of the low number of SNSD cases and uncertainty about the timing of maternal seroconversion. As these are observational data, policy decisions about screening require further evidence from a randomized trial of prenatal screening and from cost-effectiveness analyses that take into account the incidence and prevalence of maternal infection. Please see later in the article for the Editors' Summary PMID:20967235

A brain-machine interface for control of medically-induced coma.

PubMed

Shanechi, Maryam M; Chemali, Jessica J; Liberman, Max; Solt, Ken; Brown, Emery N

2013-10-01

Medically-induced coma is a drug-induced state of profound brain inactivation and unconsciousness used to treat refractory intracranial hypertension and to manage treatment-resistant epilepsy. The state of coma is achieved by continually monitoring the patient's brain activity with an electroencephalogram (EEG) and manually titrating the anesthetic infusion rate to maintain a specified level of burst suppression, an EEG marker of profound brain inactivation in which bursts of electrical activity alternate with periods of quiescence or suppression. The medical coma is often required for several days. A more rational approach would be to implement a brain-machine interface (BMI) that monitors the EEG and adjusts the anesthetic infusion rate in real time to maintain the specified target level of burst suppression. We used a stochastic control framework to develop a BMI to control medically-induced coma in a rodent model. The BMI controlled an EEG-guided closed-loop infusion of the anesthetic propofol to maintain precisely specified dynamic target levels of burst suppression. We used as the control signal the burst suppression probability (BSP), the brain's instantaneous probability of being in the suppressed state. We characterized the EEG response to propofol using a two-dimensional linear compartment model and estimated the model parameters specific to each animal prior to initiating control. We derived a recursive Bayesian binary filter algorithm to compute the BSP from the EEG and controllers using a linear-quadratic-regulator and a model-predictive control strategy. Both controllers used the estimated BSP as feedback. The BMI accurately controlled burst suppression in individual rodents across dynamic target trajectories, and enabled prompt transitions between target levels while avoiding both undershoot and overshoot. The median performance error for the BMI was 3.6%, the median bias was -1.4% and the overall posterior probability of reliable control was 1 (95% Bayesian credibility interval of [0.87, 1.0]). A BMI can maintain reliable and accurate real-time control of medically-induced coma in a rodent model suggesting this strategy could be applied in patient care.

Rainfall runoff modelling of the Upper Ganga and Brahmaputra basins using PERSiST.

PubMed

Futter, M N; Whitehead, P G; Sarkar, S; Rodda, H; Crossman, J

2015-06-01

There are ongoing discussions about the appropriate level of complexity and sources of uncertainty in rainfall runoff models. Simulations for operational hydrology, flood forecasting or nutrient transport all warrant different levels of complexity in the modelling approach. More complex model structures are appropriate for simulations of land-cover dependent nutrient transport while more parsimonious model structures may be adequate for runoff simulation. The appropriate level of complexity is also dependent on data availability. Here, we use PERSiST; a simple, semi-distributed dynamic rainfall-runoff modelling toolkit to simulate flows in the Upper Ganges and Brahmaputra rivers. We present two sets of simulations driven by single time series of daily precipitation and temperature using simple (A) and complex (B) model structures based on uniform and hydrochemically relevant land covers respectively. Models were compared based on ensembles of Bayesian Information Criterion (BIC) statistics. Equifinality was observed for parameters but not for model structures. Model performance was better for the more complex (B) structural representations than for parsimonious model structures. The results show that structural uncertainty is more important than parameter uncertainty. The ensembles of BIC statistics suggested that neither structural representation was preferable in a statistical sense. Simulations presented here confirm that relatively simple models with limited data requirements can be used to credibly simulate flows and water balance components needed for nutrient flux modelling in large, data-poor basins.

Bayesian assessment of uncertainty in aerosol size distributions and index of refraction retrieved from multiwavelength lidar measurements.

PubMed

Herman, Benjamin R; Gross, Barry; Moshary, Fred; Ahmed, Samir

2008-04-01

We investigate the assessment of uncertainty in the inference of aerosol size distributions from backscatter and extinction measurements that can be obtained from a modern elastic/Raman lidar system with a Nd:YAG laser transmitter. To calculate the uncertainty, an analytic formula for the correlated probability density function (PDF) describing the error for an optical coefficient ratio is derived based on a normally distributed fractional error in the optical coefficients. Assuming a monomodal lognormal particle size distribution of spherical, homogeneous particles with a known index of refraction, we compare the assessment of uncertainty using a more conventional forward Monte Carlo method with that obtained from a Bayesian posterior PDF assuming a uniform prior PDF and show that substantial differences between the two methods exist. In addition, we use the posterior PDF formalism, which was extended to include an unknown refractive index, to find credible sets for a variety of optical measurement scenarios. We find the uncertainty is greatly reduced with the addition of suitable extinction measurements in contrast to the inclusion of extra backscatter coefficients, which we show to have a minimal effect and strengthens similar observations based on numerical regularization methods.

Including independent estimates and uncertainty to quantify total abundance of fish migrating in a large river system: walleye (Sander vitreus) in the Maumee River, Ohio

USGS Publications Warehouse

Pritt, Jeremy J.; DuFour, Mark R.; Mayer, Christine M.; Kocovsky, Patrick M.; Tyson, Jeffrey T.; Weimer, Eric J.; Vandergoot, Christopher S.

2013-01-01

Walleye (Sander vitreus) in Lake Erie is a valuable and migratory species that spawns in tributaries. We used hydroacoustic sampling, gill net sampling, and Bayesian state-space modeling to estimate the spawning stock abundance, characterize size and sex structure, and explore environmental factors cuing migration of walleye in the Maumee River for 2011 and 2012. We estimated the spawning stock abundance to be between 431,000 and 1,446,000 individuals in 2011 and between 386,400 and 857,200 individuals in 2012 (95% Bayesian credible intervals). A back-calculation from a concurrent larval fish study produced an estimate of 78,000 to 237,000 spawners for 2011. The sex ratio was skewed towards males early in the spawning season but approached 1:1 later, and larger individuals entered the river earlier in the season than smaller individuals. Walleye migration was greater during low river discharge and intermediate temperatures. Our approach to estimating absolute abundance and uncertainty as well as characterization of the spawning stock could improve assessment and management of this species, and our methodology is applicable to other diadromous populations.

Performing Contrast Analysis in Factorial Designs: From NHST to Confidence Intervals and Beyond

PubMed Central

Wiens, Stefan; Nilsson, Mats E.

2016-01-01

Because of the continuing debates about statistics, many researchers may feel confused about how to analyze and interpret data. Current guidelines in psychology advocate the use of effect sizes and confidence intervals (CIs). However, researchers may be unsure about how to extract effect sizes from factorial designs. Contrast analysis is helpful because it can be used to test specific questions of central interest in studies with factorial designs. It weighs several means and combines them into one or two sets that can be tested with t tests. The effect size produced by a contrast analysis is simply the difference between means. The CI of the effect size informs directly about direction, hypothesis exclusion, and the relevance of the effects of interest. However, any interpretation in terms of precision or likelihood requires the use of likelihood intervals or credible intervals (Bayesian). These various intervals and even a Bayesian t test can be obtained easily with free software. This tutorial reviews these methods to guide researchers in answering the following questions: When I analyze mean differences in factorial designs, where can I find the effects of central interest, and what can I learn about their effect sizes? PMID:29805179

Bayesian latent class estimation of the incidence of chest radiograph-confirmed pneumonia in rural Thailand.

PubMed

Lu, Y; Baggett, H C; Rhodes, J; Thamthitiwat, S; Joseph, L; Gregory, C J

2016-10-01

Pneumonia is a leading cause of mortality and morbidity worldwide with radiographically confirmed pneumonia a key disease burden indicator. This is usually determined by a radiology panel which is assumed to be the best available standard; however, this assumption may introduce bias into pneumonia incidence estimates. To improve estimates of radiographic pneumonia incidence, we applied Bayesian latent class modelling (BLCM) to a large database of hospitalized patients with acute lower respiratory tract illness in Sa Kaeo and Nakhon Phanom provinces, Thailand from 2005 to 2010 with chest radiographs read by both a radiology panel and a clinician. We compared these estimates to those from conventional analysis. For children aged <5 years, estimated radiographically confirmed pneumonia incidence by BLCM was 2394/100 000 person-years (95% credible interval 2185-2574) vs. 1736/100 000 person-years (95% confidence interval 1706-1766) from conventional analysis. For persons aged ⩾5 years, estimated radiographically confirmed pneumonia incidence was similar between BLCM and conventional analysis (235 vs. 215/100 000 person-years). BLCM suggests the incidence of radiographically confirmed pneumonia in young children is substantially larger than estimated from the conventional approach using radiology panels as the reference standard.

Strong Bayesian evidence for the normal neutrino hierarchy

NASA Astrophysics Data System (ADS)

Simpson, Fergus; Jimenez, Raul; Pena-Garay, Carlos; Verde, Licia

2017-06-01

The configuration of the three neutrino masses can take two forms, known as the normal and inverted hierarchies. We compute the Bayesian evidence associated with these two hierarchies. Previous studies found a mild preference for the normal hierarchy, and this was driven by the asymmetric manner in which cosmological data has confined the available parameter space. Here we identify the presence of a second asymmetry, which is imposed by data from neutrino oscillations. By combining constraints on the squared-mass splittings [1] with the limit on the sum of neutrino masses of Σmν < 0.13 eV [2], and using a minimally informative prior on the masses, we infer odds of 42:1 in favour of the normal hierarchy, which is classified as "strong" in the Jeffreys' scale. We explore how these odds may evolve in light of higher precision cosmological data, and discuss the implications of this finding with regards to the nature of neutrinos. Finally the individual masses are inferred to be m1=3.80+26.2-3.73meV; m2=8.8+18-1.2meV; m3=50.4+5.8-1.2meV (95% credible intervals).

A Bayesian Inferential Approach to Quantify the Transmission Intensity of Disease Outbreak

PubMed Central

Kadi, Adiveppa S.; Avaradi, Shivakumari R.

2015-01-01

Background. Emergence of infectious diseases like influenza pandemic (H1N1) 2009 has become great concern, which posed new challenges to the health authorities worldwide. To control these diseases various studies have been developed in the field of mathematical modelling, which is useful tool for understanding the epidemiological dynamics and their dependence on social mixing patterns. Method. We have used Bayesian approach to quantify the disease outbreak through key epidemiological parameter basic reproduction number (R 0), using effective contacts, defined as sum of the product of incidence cases and probability of generation time distribution. We have estimated R 0 from daily case incidence data for pandemic influenza A/H1N1 2009 in India, for the initial phase. Result. The estimated R 0 with 95% credible interval is consistent with several other studies on the same strain. Through sensitivity analysis our study indicates that infectiousness affects the estimate of R 0. Conclusion. Basic reproduction number R 0 provides the useful information to the public health system to do some effort in controlling the disease by using mitigation strategies like vaccination, quarantine, and so forth. PMID:25784956

Small area clustering of under-five children's mortality and associated factors using geo-additive Bayesian discrete-time survival model in Kersa HDSS, Ethiopia.

PubMed

Dedefo, Melkamu; Oljira, Lemessa; Assefa, Nega

2016-02-01

Child mortality reflects a country's level of socio-economic development and quality of life. In Ethiopia, limited studies were conducted on under-five mortality and almost none of them tried to identify the spatial effect on mortality. Thus, this study explored the small area clustering of under-five mortality and associated factors in Kersa HDSS, Eastern Ethiopia. The study population included all children under the age of five years during the time September, 2008-august 31, 2012 which are registered in Kersa Health and Demographic Surveillance System (Kersa HDSS). A flexible Bayesian geo-additive discrete-time survival mixed model was used. Some of the factors that are significantly associated with under-five mortality, with posterior odds ratio and 95% credible intervals, are maternal educational status 1.31(1.13,-1.49), place of delivery 1.016(1.013-1.12), no of live birth at a delivery 0.35(0.23,1.83), low household wealth index 1.26(1.10 1.43) middle level household wealth index 0.95 (0.84 1.07) pre-term duration of pregnancy 1.95(1.27,2.91), post-term duration of pregnancy 0.74(0.60,0.93) and antenatal visit 1.19(1.06, 1.35). Variation was noted in the risk of under-five mortality by the selected small administrative regions (kebeles). This study reveals geographic patterns in rates of under-five mortality in those selected small administrative regions and shows some important determinants of under-five mortality. More importantly, we observed clustering of under-five mortality, which indicates the importance of spatial effects and presentation of this clustering through maps that facilitates visuality and highlights differentials across geographical areas that would, otherwise, be overlooked in traditional data-analytic methods. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Chandra Source Catalog: X-ray Aperture Photometry

NASA Astrophysics Data System (ADS)

Kashyap, Vinay; Primini, F. A.; Glotfelty, K. J.; Anderson, C. S.; Bonaventura, N. R.; Chen, J. C.; Davis, J. E.; Doe, S. M.; Evans, I. N.; Evans, J. D.; Fabbiano, G.; Galle, E. C.; Gibbs, D. G., II; Grier, J. D.; Hain, R.; Hall, D. M.; Harbo, P. N.; He, X.; Houck, J. C.; Karovska, M.; Lauer, J.; McCollough, M. L.; McDowell, J. C.; Miller, J. B.; Mitschang, A. W.; Morgan, D. L.; Nichols, J. S.; Nowak, M. A.; Plummer, D. A.; Refsdal, B. L.; Rots, A. H.; Siemiginowska, A. L.; Sundheim, B. A.; Tibbetts, M. S.; van Stone, D. W.; Winkelman, S. L.; Zografou, P.

2009-09-01

The Chandra Source Catalog (CSC) represents a reanalysis of the entire ACIS and HRC imaging observations over the 9-year Chandra mission. We describe here the method by which fluxes are measured for detected sources. Source detection is carried out on a uniform basis, using the CIAO tool wavdetect. Source fluxes are estimated post-facto using a Bayesian method that accounts for background, spatial resolution effects, and contamination from nearby sources. We use gamma-function prior distributions, which could be either non-informative, or in case there exist previous observations of the same source, strongly informative. The current implementation is however limited to non-informative priors. The resulting posterior probability density functions allow us to report the flux and a robust credible range on it.

Statistical inferences with jointly type-II censored samples from two Pareto distributions

NASA Astrophysics Data System (ADS)

Abu-Zinadah, Hanaa H.

2017-08-01

In the several fields of industries the product comes from more than one production line, which is required to work the comparative life tests. This problem requires sampling of the different production lines, then the joint censoring scheme is appeared. In this article we consider the life time Pareto distribution with jointly type-II censoring scheme. The maximum likelihood estimators (MLE) and the corresponding approximate confidence intervals as well as the bootstrap confidence intervals of the model parameters are obtained. Also Bayesian point and credible intervals of the model parameters are presented. The life time data set is analyzed for illustrative purposes. Monte Carlo results from simulation studies are presented to assess the performance of our proposed method.

The effects of stakeholder involvement on perceptions of an evaluation's credibility.

PubMed

Jacobson, Miriam R; Azzam, Tarek

2018-06-01

This article presents a study of the effects of stakeholder involvement on perceptions of an evaluation's credibility. Crowdsourced members of the public and a group of educational administrators read a description of a hypothetical program and two evaluations of the program: one conducted by a researcher and one conducted by program staff (i.e. program stakeholders). Study participants were randomly assigned versions of the scenario with different levels of stakeholder credibility and types of findings. Results showed that both samples perceived the researcher's evaluation findings to be more credible than the program staff's, but that this difference was significantly reduced when the program staff were described to be highly credible. The article concludes with implications for theory and research on evaluation dissemination and stakeholder involvement. Copyright © 2018 Elsevier Ltd. All rights reserved.

Examining driver injury severity outcomes in rural non-interstate roadway crashes using a hierarchical ordered logit model.

PubMed

Chen, Cong; Zhang, Guohui; Huang, Helai; Wang, Jiangfeng; Tarefder, Rafiqul A

2016-11-01

Rural non-interstate crashes induce a significant amount of severe injuries and fatalities. Examination of such injury patterns and the associated contributing factors is of practical importance. Taking into account the ordinal nature of injury severity levels and the hierarchical feature of crash data, this study employs a hierarchical ordered logit model to examine the significant factors in predicting driver injury severities in rural non-interstate crashes based on two-year New Mexico crash records. Bayesian inference is utilized in model estimation procedure and 95% Bayesian Credible Interval (BCI) is applied to testing variable significance. An ordinary ordered logit model omitting the between-crash variance effect is evaluated as well for model performance comparison. Results indicate that the model employed in this study outperforms ordinary ordered logit model in model fit and parameter estimation. Variables regarding crash features, environment conditions, and driver and vehicle characteristics are found to have significant influence on the predictions of driver injury severities in rural non-interstate crashes. Factors such as road segments far from intersection, wet road surface condition, collision with animals, heavy vehicle drivers, male drivers and driver seatbelt used tend to induce less severe driver injury outcomes than the factors such as multiple-vehicle crashes, severe vehicle damage in a crash, motorcyclists, females, senior drivers, driver with alcohol or drug impairment, and other major collision types. Research limitations regarding crash data and model assumptions are also discussed. Overall, this research provides reasonable results and insight in developing effective road safety measures for crash injury severity reduction and prevention. Copyright © 2016 Elsevier Ltd. All rights reserved.

Inferring the 1985-2014 impact of mobile phone use on selected brain cancer subtypes using Bayesian structural time series and synthetic controls.

PubMed

de Vocht, Frank

2016-12-01

Mobile phone use has been increasing rapidly in the past decades and, in parallel, so has the annual incidence of certain types of brain cancers. However, it remains unclear whether this correlation is coincidental or whether use of mobile phones may cause the development, promotion or progression of specific cancers. The 1985-2014 incidence of selected brain cancer subtypes in England were analyzed and compared to counterfactual 'synthetic control' timeseries. Annual 1985-2014 incidence of malignant glioma, glioblastoma multiforme, and malignant neoplasms of the temporal and parietal lobes in England were modelled based on population-level covariates using Bayesian structural time series models assuming 5,10 and 15year minimal latency periods. Post-latency counterfactual 'synthetic England' timeseries were nowcast based on covariate trends. The impact of mobile phone use was inferred from differences between measured and modelled time series. There is no evidence of an increase in malignant glioma, glioblastoma multiforme, or malignant neoplasms of the parietal lobe not predicted in the 'synthetic England' time series. Malignant neoplasms of the temporal lobe however, have increased faster than expected. A latency period of 10years reflected the earliest latency period when this was measurable and related to mobile phone penetration rates, and indicated an additional increase of 35% (95% Credible Interval 9%:59%) during 2005-2014; corresponding to an additional 188 (95%CI 48-324) cases annually. A causal factor, of which mobile phone use (and possibly other wireless equipment) is in agreement with the hypothesized temporal association, is related to an increased risk of developing malignant neoplasms in the temporal lobe. Copyright © 2016 The Author. Published by Elsevier Ltd.. All rights reserved.

Unconditional cash transfers for clinical and economic outcomes among HIV-affected Ugandan households: a bayesian randomised trial.

PubMed

Mills, Edward J; Adhvaryu, Achyuta; Jakiela, Pamela; Birungi, Josephine; Okoboi, Stephen; Chimulwa, Teddy; Wangisi, Jonathan; Achilla, Tina; Popoff, Evan; Golchi, Shirin; Karlan, Dean

2018-05-28

HIV infection has profound clinical and economic costs at the household level. This is particularly important in low-income settings, where access to additional sources of income or loans may be limited. While several microfinance interventions have been proposed, unconditional cash grants, a strategy to allow participants to choose how to use finances that may improve household security and health, has not previously been evaluated. We examined the effect of an unconditional cash transfer to HIV-infected individuals using a 2 x 2 factorial randomised trial in two rural districts in Uganda. Our primary outcomes were changes in CD4 cell count, sexual behaviors, and adherence to ART. Secondary outcomes were changes in household food security and adult mental health. We applied a Bayesian approach for our primary analysis. We randomized 2170 patients as participatants, with 1081 receiving a cash grant. We found no important intervention effects on CD4 t-cell counts between groups (mean difference [MD] 35.48, 95% Credible Interval [CrI] -59.9-1131.6), food security (odds ratio [OR] 1.22, 95% CrI: 0.47, 3.02), medication adherence (OR 3.15, 95% CrI: 0.58, 18.15), or sexual behavior (OR 0.45 95% CrI: 0.12, 1.55), or health expenditure in the previous 3 weeks (Mean Difference $2.65, 95% CrI: -9.30, 15.69). In secondary analysis, we detected an effect of mental planning on CD4 change between groups (104.2 cells, 9% CrI: 5.99, 202.16). We did not have data on viral load outcomes. Although all outcomes were associated with favorable point estimates, our trial did not demonstrate important effects of unconditional cash grants on health outcomes.

Malaria prevalence metrics in low- and middle-income countries: an assessment of precision in nationally-representative surveys.

PubMed

Alegana, Victor A; Wright, Jim; Bosco, Claudio; Okiro, Emelda A; Atkinson, Peter M; Snow, Robert W; Tatem, Andrew J; Noor, Abdisalan M

2017-11-21

One pillar to monitoring progress towards the Sustainable Development Goals is the investment in high quality data to strengthen the scientific basis for decision-making. At present, nationally-representative surveys are the main source of data for establishing a scientific evidence base, monitoring, and evaluation of health metrics. However, little is known about the optimal precisions of various population-level health and development indicators that remains unquantified in nationally-representative household surveys. Here, a retrospective analysis of the precision of prevalence from these surveys was conducted. Using malaria indicators, data were assembled in nine sub-Saharan African countries with at least two nationally-representative surveys. A Bayesian statistical model was used to estimate between- and within-cluster variability for fever and malaria prevalence, and insecticide-treated bed nets (ITNs) use in children under the age of 5 years. The intra-class correlation coefficient was estimated along with the optimal sample size for each indicator with associated uncertainty. Results suggest that the estimated sample sizes for the current nationally-representative surveys increases with declining malaria prevalence. Comparison between the actual sample size and the modelled estimate showed a requirement to increase the sample size for parasite prevalence by up to 77.7% (95% Bayesian credible intervals 74.7-79.4) for the 2015 Kenya MIS (estimated sample size of children 0-4 years 7218 [7099-7288]), and 54.1% [50.1-56.5] for the 2014-2015 Rwanda DHS (12,220 [11,950-12,410]). This study highlights the importance of defining indicator-relevant sample sizes to achieve the required precision in the current national surveys. While expanding the current surveys would need additional investment, the study highlights the need for improved approaches to cost effective sampling.

Intercalibration of radioisotopic and astrochronologic time scales for the Cenomanian-Turonian boundary interval, western interior Basin, USA

USGS Publications Warehouse

Meyers, S.R.; Siewert, S.E.; Singer, B.S.; Sageman, B.B.; Condon, D.J.; Obradovich, J.D.; Jicha, B.R.; Sawyer, D.A.

2012-01-01

We develop an intercalibrated astrochronologic and radioisotopic time scale for the Cenomanian-Turonian boundary (CTB) interval near the Global Stratotype Section and Point in Colorado, USA, where orbitally influenced rhythmic strata host bentonites that contain sanidine and zircon suitable for 40Ar/ 39Ar and U-Pb dating. Paired 40Ar/ 39Ar and U-Pb ages are determined from four bentonites that span the Vascoceras diartianum to Pseudaspidoceras flexuosum ammonite biozones, utilizing both newly collected material and legacy sanidine samples of J. Obradovich. Comparison of the 40Ar/ 39Ar and U-Pb results underscores the strengths and limitations of each system, and supports an astronomically calibrated Fish Canyon sanidine standard age of 28.201 Ma. The radioisotopic data and published astrochronology are employed to develop a new CTB time scale, using two statistical approaches: (1) a simple integration that yields a CTB age of 93.89 ?? 0.14 Ma (2??; total radioisotopic uncertainty), and (2) a Bayesian intercalibration that explicitly accounts for orbital time scale uncertainty, and yields a CTB age of 93.90 ?? 0.15 Ma (95% credible interval; total radioisotopic and orbital time scale uncertainty). Both approaches firmly anchor the floating orbital time scale, and the Bayesian technique yields astronomically recalibrated radioisotopic ages for individual bentonites, with analytical uncertainties at the permil level of resolution, and total uncertainties below 2???. Using our new results, the duration between the Cenomanian-Turonian and the Cretaceous-Paleogene boundaries is 27.94 ?? 0.16 Ma, with an uncertainty of less than one-half of a long eccentricity cycle. ?? 2012 Geological Society of America.

Health at the borders: Bayesian multilevel analysis of women's malnutrition determinants in Ethiopia.

PubMed

Delbiso, Tefera Darge; Rodriguez-Llanes, Jose Manuel; Altare, Chiara; Masquelier, Bruno; Guha-Sapir, Debarati

2016-01-01

Women's malnutrition, particularly undernutrition, remains an important public health challenge in Ethiopia. Although various studies examined the levels and determinants of women's nutritional status, the influence of living close to an international border on women's nutrition has not been investigated. Yet, Ethiopian borders are regularly affected by conflict and refugee flows, which might ultimately impact health. To investigate the impact of living close to borders in the nutritional status of women in Ethiopia, while considering other important covariates. Our analysis was based on the body mass index (BMI) of 6,334 adult women aged 20-49 years, obtained from the 2011 Ethiopian Demographic and Health Survey (EDHS). A Bayesian multilevel multinomial logistic regression analysis was used to capture the clustered structure of the data and the possible correlation that may exist within and between clusters. After controlling for potential confounders, women living close to borders (i.e. ≤100 km) in Ethiopia were 59% more likely to be underweight (posterior odds ratio [OR]=1.59; 95% credible interval [CrI]: 1.32-1.90) than their counterparts living far from the borders. This result was robust to different choices of border delineation (i.e. ≤50, ≤75, ≤125, and ≤150 km). Women from poor families, those who have no access to improved toilets, reside in lowland areas, and are Muslim, were independently associated with underweight. In contrast, more wealth, higher education, older age, access to improved toilets, being married, and living in urban or lowlands were independently associated with overweight. The problem of undernutrition among women in Ethiopia is most worrisome in the border areas. Targeted interventions to improve nutritional status in these areas, such as improved access to sanitation, economic and livelihood support, are recommended.

Semisupervised learning using Bayesian interpretation: application to LS-SVM.

PubMed

Adankon, Mathias M; Cheriet, Mohamed; Biem, Alain

2011-04-01

Bayesian reasoning provides an ideal basis for representing and manipulating uncertain knowledge, with the result that many interesting algorithms in machine learning are based on Bayesian inference. In this paper, we use the Bayesian approach with one and two levels of inference to model the semisupervised learning problem and give its application to the successful kernel classifier support vector machine (SVM) and its variant least-squares SVM (LS-SVM). Taking advantage of Bayesian interpretation of LS-SVM, we develop a semisupervised learning algorithm for Bayesian LS-SVM using our approach based on two levels of inference. Experimental results on both artificial and real pattern recognition problems show the utility of our method.

Predicting the effect of maternal docosahexaenoic acid (DHA) supplementation to reduce early preterm birth in Australia and the United States using results of within country randomized controlled trials.

PubMed

Yelland, L N; Gajewski, B J; Colombo, J; Gibson, R A; Makrides, M; Carlson, S E

2016-09-01

The DHA to Optimize Mother Infant Outcome (DOMInO) and Kansas DHA Outcomes Study (KUDOS) were randomized controlled trials that supplemented mothers with 800 and 600mg DHA/day, respectively, or a placebo during pregnancy. DOMInO was conducted in Australia and KUDOS in the United States. Both trials found an unanticipated and statistically significant reduction in early preterm birth (ePTB; i.e., birth before 34 weeks gestation). However, in each trial, the number of ePTBs were small. We used a novel Bayesian approach to estimate statistically derived low, moderate or high risk for ePTB, and to test for differences between the DHA and placebo groups. In both trials, the model predicted DHA would significantly reduce the expected proportion of deliveries in the high risk group under the trial conditions of the parent studies. Among the next 300,000 births in Australia we estimated that 1112 ePTB (95% credible interval 51-2189) could be avoided by providing DHA. And in the USA we estimated that 106,030 ePTB (95% credible interval 6400 to 175,700) could be avoided with DHA. Copyright © 2016 Elsevier Ltd. All rights reserved.

First oscillation analysis using neutrino and antineutrino data at T2K

NASA Astrophysics Data System (ADS)

Duffy, Kirsty

2017-09-01

We present details of the first T2K neutrino and antineutrino oscillation results, in which data collected using both a muon neutrino-enhanced neutrino beam and a muon antineutrino-enhanced neutrino beam are analysed, equating to 7.002×1020 protons on target (POT) and 7.471×1020 POT respectively. Both {ν }μ /{\\bar{ν }}μ disappearance and {ν }e/{\\bar{ν }}e appearance data are analysed using a Bayesian Markov Chain Monte Carlo method, providing the first ever sensitivity to the CP-violating phase δCP from T2K data alone. The T2K data favour near-maximal mixing, with sin2 θ 23 and Δ {m}322 consistent with previous T2K measurements, a value of sin2 θ 13 consistent with measurements by reactor experiments, and δCP close to -π/2. When fitting with T2K data alone, the 90% credible interval for δCP disfavours values around π/2: δ CP ∉ [0.38, 2.60] rad. When using a prior on sin2 2θ 13 from reactor measurements, the 90% credible interval contains δCP ∉ [-3.10, -0.17] rad, disfavouring the CP-conserving values 0 and ±π. The effect on this result of the δCP prior is also investigated and presented.

Credibility assessment in child sexual abuse investigations: A descriptive analysis.

PubMed

Melkman, Eran P; Hershkowitz, Irit; Zur, Ronit

2017-05-01

A major challenge in cases of child sexual abuse (CSA) is determining the credibility of children's reports. Consequently cases may be misclassified as false or deemed 'no judgment possible'. Based on a large national sample of reports of CSA made in Israel in 2014, the study examines child and event characteristics contributing to the probability that reports of abuse would be judged credible. National data files of all children aged 3-14, who were referred for investigation following suspected victimization of sexual abuse, and had disclosed sexual abuse, were analyzed. Cases were classified as either 'credible' or 'no judgment possible'. The probability of reaching a 'credible' judgment was examined in relation to characteristics of the child (age, gender, cognitive delay, marital status of the parents,) and of the abusive event (abuse severity, frequency, perpetrator-victim relationship, perpetrator's use of grooming, and perpetrator's use of coercion), controlling for investigator's identity at the cluster level of the analysis. Of 1563 cases analyzed, 57.9% were assessed as credible. The most powerful predictors of a credible judgment were older age and absence of a cognitive delay. Reports of children to married parents, who experienced a single abusive event that involved perpetrator's use of grooming, were also more likely to be judged as credible. Rates of credible judgments found are lower than expected suggesting under-identification of truthful reports of CSA. In particular, those cases of severe and multiple abuse involving younger and cognitively delayed children are the ones with the lowest chances of being assessed as credible. Copyright © 2017 Elsevier Ltd. All rights reserved.

Empirical Bayes estimation of proportions with application to cowbird parasitism rates

USGS Publications Warehouse

Link, W.A.; Hahn, D.C.

1996-01-01

Bayesian models provide a structure for studying collections of parameters such as are considered in the investigation of communities, ecosystems, and landscapes. This structure allows for improved estimation of individual parameters, by considering them in the context of a group of related parameters. Individual estimates are differentially adjusted toward an overall mean, with the magnitude of their adjustment based on their precision. Consequently, Bayesian estimation allows for a more credible identification of extreme values in a collection of estimates. Bayesian models regard individual parameters as values sampled from a specified probability distribution, called a prior. The requirement that the prior be known is often regarded as an unattractive feature of Bayesian analysis and may be the reason why Bayesian analyses are not frequently applied in ecological studies. Empirical Bayes methods provide an alternative approach that incorporates the structural advantages of Bayesian models while requiring a less stringent specification of prior knowledge. Rather than requiring that the prior distribution be known, empirical Bayes methods require only that it be in a certain family of distributions, indexed by hyperparameters that can be estimated from the available data. This structure is of interest per se, in addition to its value in allowing for improved estimation of individual parameters; for example, hypotheses regarding the existence of distinct subgroups in a collection of parameters can be considered under the empirical Bayes framework by allowing the hyperparameters to vary among subgroups. Though empirical Bayes methods have been applied in a variety of contexts, they have received little attention in the ecological literature. We describe the empirical Bayes approach in application to estimation of proportions, using data obtained in a community-wide study of cowbird parasitism rates for illustration. Since observed proportions based on small sample sizes are heavily adjusted toward the mean, extreme values among empirical Bayes estimates identify those species for which there is the greatest evidence of extreme parasitism rates. Applying a subgroup analysis to our data on cowbird parasitism rates, we conclude that parasitism rates for Neotropical Migrants as a group are no greater than those of Resident/Short-distance Migrant species in this forest community. Our data and analyses demonstrate that the parasitism rates for certain Neotropical Migrant species are remarkably low (Wood Thrush and Rose-breasted Grosbeak) while those for others are remarkably high (Ovenbird and Red-eyed Vireo).

Notional Scoring for Technical Review Weighting As Applied to Simulation Credibility Assessment

NASA Technical Reports Server (NTRS)

Hale, Joseph Peter; Hartway, Bobby; Thomas, Danny

2008-01-01

NASA's Modeling and Simulation Standard requires a credibility assessment for critical engineering data produced by models and simulations. Credibility assessment is thus a "qualifyingfactor" in reporting results from simulation-based analysis. The degree to which assessors should be independent of the simulation developers, users and decision makers is a recurring question. This paper provides alternative "weighting algorithms" for calculating the value-added for independence of the levels of technical review defined for the NASA Modeling and Simulation Standard.

Bayesian Inversion of 2D Models from Airborne Transient EM Data

NASA Astrophysics Data System (ADS)

Blatter, D. B.; Key, K.; Ray, A.

2016-12-01

The inherent non-uniqueness in most geophysical inverse problems leads to an infinite number of Earth models that fit observed data to within an adequate tolerance. To resolve this ambiguity, traditional inversion methods based on optimization techniques such as the Gauss-Newton and conjugate gradient methods rely on an additional regularization constraint on the properties that an acceptable model can possess, such as having minimal roughness. While allowing such an inversion scheme to converge on a solution, regularization makes it difficult to estimate the uncertainty associated with the model parameters. This is because regularization biases the inversion process toward certain models that satisfy the regularization constraint and away from others that don't, even when both may suitably fit the data. By contrast, a Bayesian inversion framework aims to produce not a single `most acceptable' model but an estimate of the posterior likelihood of the model parameters, given the observed data. In this work, we develop a 2D Bayesian framework for the inversion of transient electromagnetic (TEM) data. Our method relies on a reversible-jump Markov Chain Monte Carlo (RJ-MCMC) Bayesian inverse method with parallel tempering. Previous gradient-based inversion work in this area used a spatially constrained scheme wherein individual (1D) soundings were inverted together and non-uniqueness was tackled by using lateral and vertical smoothness constraints. By contrast, our work uses a 2D model space of Voronoi cells whose parameterization (including number of cells) is fully data-driven. To make the problem work practically, we approximate the forward solution for each TEM sounding using a local 1D approximation where the model is obtained from the 2D model by retrieving a vertical profile through the Voronoi cells. The implicit parsimony of the Bayesian inversion process leads to the simplest models that adequately explain the data, obviating the need for explicit smoothness constraints. In addition, credible intervals in model space are directly obtained, resolving some of the uncertainty introduced by regularization. An example application shows how the method can be used to quantify the uncertainty in airborne EM soundings for imaging subglacial brine channels and groundwater systems.

Modelling heterogeneity variances in multiple treatment comparison meta-analysis--are informative priors the better solution?

PubMed

Thorlund, Kristian; Thabane, Lehana; Mills, Edward J

2013-01-11

Multiple treatment comparison (MTC) meta-analyses are commonly modeled in a Bayesian framework, and weakly informative priors are typically preferred to mirror familiar data driven frequentist approaches. Random-effects MTCs have commonly modeled heterogeneity under the assumption that the between-trial variance for all involved treatment comparisons are equal (i.e., the 'common variance' assumption). This approach 'borrows strength' for heterogeneity estimation across treatment comparisons, and thus, ads valuable precision when data is sparse. The homogeneous variance assumption, however, is unrealistic and can severely bias variance estimates. Consequently 95% credible intervals may not retain nominal coverage, and treatment rank probabilities may become distorted. Relaxing the homogeneous variance assumption may be equally problematic due to reduced precision. To regain good precision, moderately informative variance priors or additional mathematical assumptions may be necessary. In this paper we describe four novel approaches to modeling heterogeneity variance - two novel model structures, and two approaches for use of moderately informative variance priors. We examine the relative performance of all approaches in two illustrative MTC data sets. We particularly compare between-study heterogeneity estimates and model fits, treatment effect estimates and 95% credible intervals, and treatment rank probabilities. In both data sets, use of moderately informative variance priors constructed from the pair wise meta-analysis data yielded the best model fit and narrower credible intervals. Imposing consistency equations on variance estimates, assuming variances to be exchangeable, or using empirically informed variance priors also yielded good model fits and narrow credible intervals. The homogeneous variance model yielded high precision at all times, but overall inadequate estimates of between-trial variances. Lastly, treatment rankings were similar among the novel approaches, but considerably different when compared with the homogenous variance approach. MTC models using a homogenous variance structure appear to perform sub-optimally when between-trial variances vary between comparisons. Using informative variance priors, assuming exchangeability or imposing consistency between heterogeneity variances can all ensure sufficiently reliable and realistic heterogeneity estimation, and thus more reliable MTC inferences. All four approaches should be viable candidates for replacing or supplementing the conventional homogeneous variance MTC model, which is currently the most widely used in practice.

Determinants of medication adherence in older people with dementia from the caregivers' perspective.

PubMed

El-Saifi, Najwan; Moyle, Wendy; Jones, Cindy; Alston-Knox, Clair

2018-05-11

ABSTRACTBackground:Adherence to treatment is a primary determinant of treatment success. Caregiver support can influence medication adherence in people with cognitive impairment. This study sought to characterize medication adherence in older people with dementia from the caregivers' perspective, and to identify influencing factors. Caregivers caring for a person with dementia and living in the community were eligible to complete the survey. Bayesian profile regression was applied to identify determinants of medication adherence measured using the Adherence to Refills and Medication Scale. Out of the 320 caregivers who participated in the survey, Bayesian profile regression on 221 participants identified two groups: Profile 1 (55 caregivers) with a mean adherence rate of 0.69 (80% Credible Interval (CrI): 0.61-0.77), and Profile 2 (166 caregivers) with a mean adherence rate of 0.80 (80% CrI: 0.77-0.84). Caregivers in Profile 1 were characterized with below data average scores for the following: cognitive functioning, commitment or intention, self-efficacy, and health knowledge, which were all above the data average in Profile 2, except for health knowledge. Caregivers in Profile 1 had a greater proportion of care recipients taking more than five medications and with late-stage dementia. Trade, technical, or vocational training was more common among the caregivers in Profile 1. Profile 2 caregivers had a better patient-provider relationship and less medical problems. Bayesian profile regression was useful in understanding caregiver factors that influence medication adherence. Tailored interventions to the determinants of medication adherence can guide the development of evidence-based interventions.

Simulation-based estimation of mean and standard deviation for meta-analysis via Approximate Bayesian Computation (ABC).

PubMed

Kwon, Deukwoo; Reis, Isildinha M

2015-08-12

When conducting a meta-analysis of a continuous outcome, estimated means and standard deviations from the selected studies are required in order to obtain an overall estimate of the mean effect and its confidence interval. If these quantities are not directly reported in the publications, they must be estimated from other reported summary statistics, such as the median, the minimum, the maximum, and quartiles. We propose a simulation-based estimation approach using the Approximate Bayesian Computation (ABC) technique for estimating mean and standard deviation based on various sets of summary statistics found in published studies. We conduct a simulation study to compare the proposed ABC method with the existing methods of Hozo et al. (2005), Bland (2015), and Wan et al. (2014). In the estimation of the standard deviation, our ABC method performs better than the other methods when data are generated from skewed or heavy-tailed distributions. The corresponding average relative error (ARE) approaches zero as sample size increases. In data generated from the normal distribution, our ABC performs well. However, the Wan et al. method is best for estimating standard deviation under normal distribution. In the estimation of the mean, our ABC method is best regardless of assumed distribution. ABC is a flexible method for estimating the study-specific mean and standard deviation for meta-analysis, especially with underlying skewed or heavy-tailed distributions. The ABC method can be applied using other reported summary statistics such as the posterior mean and 95 % credible interval when Bayesian analysis has been employed.

A Risk Assessment of Antibiotic Pan-Drug-Resistance in the UK: Bayesian Analysis of an Expert Elicitation Study

PubMed Central

Carter, Daniel; Charlett, André; Conti, Stefano; Robotham, Julie V.; Johnson, Alan P.; Livermore, David M.; Fowler, Tom; Sharland, Mike; Hopkins, Susan; Woodford, Neil; Burgess, Philip; Dobra, Stephen

2017-01-01

To inform the UK antimicrobial resistance strategy, a risk assessment was undertaken of the likelihood, over a five-year time-frame, of the emergence and widespread dissemination of pan-drug-resistant (PDR) Gram-negative bacteria that would pose a major public health threat by compromising effective healthcare delivery. Subsequent impact over five- and 20-year time-frames was assessed in terms of morbidity and mortality attributable to PDR Gram-negative bacteraemia. A Bayesian approach, combining available data with expert prior opinion, was used to determine the probability of the emergence, persistence and spread of PDR bacteria. Overall probability was modelled using Monte Carlo simulation. Estimates of impact were also obtained using Bayesian methods. The estimated probability of widespread occurrence of PDR pathogens within five years was 0.2 (95% credibility interval (CrI): 0.07–0.37). Estimated annual numbers of PDR Gram-negative bacteraemias at five and 20 years were 6800 (95% CrI: 400–58,600) and 22,800 (95% CrI: 1500–160,000), respectively; corresponding estimates of excess deaths were 1900 (95% CrI: 0–23,000) and 6400 (95% CrI: 0–64,000). Over 20 years, cumulative estimates indicate 284,000 (95% CrI: 17,000–1,990,000) cases of PDR Gram-negative bacteraemia, leading to an estimated 79,000 (95% CrI: 0–821,000) deaths. This risk assessment reinforces the need for urgent national and international action to tackle antibiotic resistance. PMID:28272350

First search for exotic Z Boson decays into photons and neutral pions in hadron collisions.

PubMed

Aaltonen, T; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Apollinari, G; Appel, J A; Arisawa, T; Artikov, A; Asaadi, J; Ashmanskas, W; Auerbach, B; Aurisano, A; Azfar, F; Badgett, W; Bae, T; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Barria, P; Bartos, P; Bauce, M; Bedeschi, F; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Bhatti, A; Bland, K R; Blumenfeld, B; Bocci, A; Bodek, A; Bortoletto, D; Boudreau, J; Boveia, A; Brigliadori, L; Bromberg, C; Brucken, E; Budagov, J; Budd, H S; Burkett, K; Busetto, G; Bussey, P; Butti, P; Buzatu, A; Calamba, A; Camarda, S; Campanelli, M; Canelli, F; Carls, B; Carlsmith, D; Carosi, R; Carrillo, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cavalli-Sforza, M; Cerri, A; Cerrito, L; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Cho, K; Chokheli, D; Clark, A; Clarke, C; Convery, M E; Conway, J; Corbo, M; Cordelli, M; Cox, C A; Cox, D J; Cremonesi, M; Cruz, D; Cuevas, J; Culbertson, R; d'Ascenzo, N; Datta, M; de Barbaro, P; Demortier, L; Deninno, M; D'Errico, M; Devoto, F; Di Canto, A; Di Ruzza, B; Dittmann, J R; Donati, S; D'Onofrio, M; Dorigo, M; Driutti, A; Ebina, K; Edgar, R; Elagin, A; Erbacher, R; Errede, S; Esham, B; Farrington, S; Fernández Ramos, J P; Field, R; Flanagan, G; Forrest, R; Franklin, M; Freeman, J C; Frisch, H; Funakoshi, Y; Galloni, C; Garfinkel, A F; Garosi, P; Gerberich, H; Gerchtein, E; Giagu, S; Giakoumopoulou, V; Gibson, K; Ginsburg, C M; Giokaris, N; Giromini, P; Giurgiu, G; Glagolev, V; Glenzinski, D; Gold, M; Goldin, D; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González López, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gramellini, E; Grinstein, S; Grosso-Pilcher, C; Group, R C; Guimaraes da Costa, J; Hahn, S R; Han, J Y; Happacher, F; Hara, K; Hare, M; Harr, R F; Harrington-Taber, T; Hatakeyama, K; Hays, C; Heinrich, J; Herndon, M; Hocker, A; Hong, Z; Hopkins, W; Hou, S; Hughes, R E; Husemann, U; Hussein, M; Huston, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jang, D; Jayatilaka, B; Jeon, E J; Jindariani, S; Jones, M; Joo, K K; Jun, S Y; Junk, T R; Kambeitz, M; Kamon, T; Karchin, P E; Kasmi, A; Kato, Y; Ketchum, W; Keung, J; Kilminster, B; Kim, D H; Kim, H S; Kim, J E; Kim, M J; Kim, S H; Kim, S B; Kim, Y J; Kim, Y K; Kimura, N; Kirby, M; Knoepfel, K; Kondo, K; Kong, D J; Konigsberg, J; Kotwal, A V; Kreps, M; Kroll, J; Kruse, M; Kuhr, T; Kurata, M; Laasanen, A T; Lammel, S; Lancaster, M; Lannon, K; Latino, G; Lee, H S; Lee, J S; Leo, S; Leone, S; Lewis, J D; Limosani, A; Lipeles, E; Lister, A; Liu, H; Liu, Q; Liu, T; Lockwitz, S; Loginov, A; Lucchesi, D; Lucà, A; Lueck, J; Lujan, P; Lukens, P; Lungu, G; Lys, J; Lysak, R; Madrak, R; Maestro, P; Malik, S; Manca, G; Manousakis-Katsikakis, A; Marchese, L; Margaroli, F; Marino, P; Martínez, M; Matera, K; Mattson, M E; Mazzacane, A; Mazzanti, P; McNulty, R; Mehta, A; Mehtala, P; Mesropian, C; Miao, T; Mietlicki, D; Mitra, A; Miyake, H; Moed, S; Moggi, N; Moon, C S; Moore, R; Morello, M J; Mukherjee, A; Muller, Th; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Naganoma, J; Nakano, I; Napier, A; Nett, J; Neu, C; Nigmanov, T; Nodulman, L; Noh, S Y; Norniella, O; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Ortolan, L; Pagliarone, C; Palencia, E; Palni, P; Papadimitriou, V; Parker, W; Pauletta, G; Paulini, M; Paus, C; Phillips, T J; Piacentino, G; Pianori, E; Pilot, J; Pitts, K; Plager, C; Pondrom, L; Poprocki, S; Potamianos, K; Pranko, A; Prokoshin, F; Ptohos, F; Punzi, G; Ranjan, N; Redondo Fernández, I; Renton, P; Rescigno, M; Rimondi, F; Ristori, L; Robson, A; Rodriguez, T; Rolli, S; Ronzani, M; Roser, R; Rosner, J L; Ruffini, F; Ruiz, A; Russ, J; Rusu, V; Sakumoto, W K; Sakurai, Y; Santi, L; Sato, K; Saveliev, V; Savoy-Navarro, A; Schlabach, P; Schmidt, E E; Schwarz, T; Scodellaro, L; Scuri, F; Seidel, S; Seiya, Y; Semenov, A; Sforza, F; Shalhout, S Z; Shears, T; Shepard, P F; Shimojima, M; Shochet, M; Shreyber-Tecker, I; Simonenko, A; Sliwa, K; Smith, J R; Snider, F D; Song, H; Sorin, V; St Denis, R; Stancari, M; Stentz, D; Strologas, J; Sudo, Y; Sukhanov, A; Suslov, I; Takemasa, K; Takeuchi, Y; Tang, J; Tecchio, M; Teng, P K; Thom, J; Thomson, E; Thukral, V; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Trovato, M; Ukegawa, F; Uozumi, S; Vázquez, F; Velev, G; Vellidis, C; Vernieri, C; Vidal, M; Vilar, R; Vizán, J; Vogel, M; Volpi, G; Wagner, P; Wallny, R; Wang, S M; Waters, D; Wester Iii, W C; Whiteson, D; Wicklund, A B; Wilbur, S; Williams, H H; Wilson, J S; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, H; Wright, T; Wu, X; Wu, Z; Yamamoto, K; Yamato, D; Yang, T; Yang, U K; Yang, Y C; Yao, W-M; Yeh, G P; Yi, K; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Zanetti, A M; Zeng, Y; Zhou, C; Zucchelli, S

2014-03-21

A search for forbidden and exotic Z boson decays in the diphoton mass spectrum is presented for the first time in hadron collisions, based on data corresponding to 10.0 fb(-1) of integrated luminosity from proton-antiproton collisions at √s = 1.96 TeV collected by the CDF experiment. No evidence of signal is observed, and 95% credibility level Bayesian upper limits are set on the branching ratios of decays of the Z boson to a photon and neutral pion (which is detected as a photon), a pair of photons, and a pair of neutral pions. The observed branching ratio limits are 2.01 × 10(-5) for Z → π(0)γ, 1.46 × 10(-5) for Z → γγ, and 1.52 × 10(-5) for Z → π(0)π(0). The Z → π(0)γ and Z → γγ limits improve the most stringent results from other experiments by factors of 2.6 and 3.6, respectively. The Z → π(0)π(0) branching ratio limit is the first experimental result on this decay.

Performance of informative priors skeptical of large treatment effects in clinical trials: A simulation study.

PubMed

Pedroza, Claudia; Han, Weilu; Thanh Truong, Van Thi; Green, Charles; Tyson, Jon E

2018-01-01

One of the main advantages of Bayesian analyses of clinical trials is their ability to formally incorporate skepticism about large treatment effects through the use of informative priors. We conducted a simulation study to assess the performance of informative normal, Student- t, and beta distributions in estimating relative risk (RR) or odds ratio (OR) for binary outcomes. Simulation scenarios varied the prior standard deviation (SD; level of skepticism of large treatment effects), outcome rate in the control group, true treatment effect, and sample size. We compared the priors with regards to bias, mean squared error (MSE), and coverage of 95% credible intervals. Simulation results show that the prior SD influenced the posterior to a greater degree than the particular distributional form of the prior. For RR, priors with a 95% interval of 0.50-2.0 performed well in terms of bias, MSE, and coverage under most scenarios. For OR, priors with a wider 95% interval of 0.23-4.35 had good performance. We recommend the use of informative priors that exclude implausibly large treatment effects in analyses of clinical trials, particularly for major outcomes such as mortality.

The impact of the rate prior on Bayesian estimation of divergence times with multiple Loci.

PubMed

Dos Reis, Mario; Zhu, Tianqi; Yang, Ziheng

2014-07-01

Bayesian methods provide a powerful way to estimate species divergence times by combining information from molecular sequences with information from the fossil record. With the explosive increase of genomic data, divergence time estimation increasingly uses data of multiple loci (genes or site partitions). Widely used computer programs to estimate divergence times use independent and identically distributed (i.i.d.) priors on the substitution rates for different loci. The i.i.d. prior is problematic. As the number of loci (L) increases, the prior variance of the average rate across all loci goes to zero at the rate 1/L. As a consequence, the rate prior dominates posterior time estimates when many loci are analyzed, and if the rate prior is misspecified, the estimated divergence times will converge to wrong values with very narrow credibility intervals. Here we develop a new prior on the locus rates based on the Dirichlet distribution that corrects the problematic behavior of the i.i.d. prior. We use computer simulation and real data analysis to highlight the differences between the old and new priors. For a dataset for six primate species, we show that with the old i.i.d. prior, if the prior rate is too high (or too low), the estimated divergence times are too young (or too old), outside the bounds imposed by the fossil calibrations. In contrast, with the new Dirichlet prior, posterior time estimates are insensitive to the rate prior and are compatible with the fossil calibrations. We re-analyzed a phylogenomic data set of 36 mammal species and show that using many fossil calibrations can alleviate the adverse impact of a misspecified rate prior to some extent. We recommend the use of the new Dirichlet prior in Bayesian divergence time estimation. [Bayesian inference, divergence time, relaxed clock, rate prior, partition analysis.]. © The Author(s) 2014. Published by Oxford University Press, on behalf of the Society of Systematic Biologists.

An economic growth model based on financial credits distribution to the government economy priority sectors of each regency in Indonesia using hierarchical Bayesian method

NASA Astrophysics Data System (ADS)

Yasmirullah, Septia Devi Prihastuti; Iriawan, Nur; Sipayung, Feronika Rosalinda

2017-11-01

The success of regional economic establishment could be measured by economic growth. Since the Act No. 32 of 2004 has been implemented, unbalance economic among the regency in Indonesia is increasing. This condition is contrary different with the government goal to build society welfare through the economic activity development in each region. This research aims to examine economic growth through the distribution of bank credits to each Indonesia's regency. The data analyzed in this research is hierarchically structured data which follow normal distribution in first level. Two modeling approaches are employed in this research, a global-one level Bayesian approach and two-level hierarchical Bayesian approach. The result shows that hierarchical Bayesian has succeeded to demonstrate a better estimation than a global-one level Bayesian. It proves that the different economic growth in each province is significantly influenced by the variations of micro level characteristics in each province. These variations are significantly affected by cities and province characteristics in second level.

The Chandra Source Catalog: X-ray Aperture Photometry

NASA Astrophysics Data System (ADS)

Kashyap, Vinay; Primini, F. A.; Glotfelty, K. J.; Anderson, C. S.; Bonaventura, N. R.; Chen, J. C.; Davis, J. E.; Doe, S. M.; Evans, I. N.; Evans, J. D.; Fabbiano, G.; Galle, E.; Gibbs, D. G.; Grier, J. D.; Hain, R.; Hall, D. M.; Harbo, P. N.; He, X.; Houck, J. C.; Karovska, M.; Lauer, J.; McCollough, M. L.; McDowell, J. C.; Miller, J. B.; Mitschang, A. W.; Morgan, D. L.; Nichols, J. S.; Nowak, M. A.; Plummer, D. A.; Refsdal, B. L.; Rots, A. H.; Siemiginowska, A. L.; Sundheim, B. A.; Tibbetts, M. S.; Van Stone, D. W.; Winkelman, S. L.; Zografou, P.

2009-01-01

The Chandra Source Catalog represents a reanalysis of the entire ACIS and HRC imaging observations over the 9-year Chandra mission. Source detection is carried out on a uniform basis, using the CIAO tool wavdetect, and source fluxes are estimated post-facto using a Bayesian method that accounts for background, spatial resolution effects, and contamination from nearby sources. We use gamma-function prior distributions, which could be either non-informative, or in case there exist previous observations of the same source, strongly informative. The resulting posterior probability density functions allow us to report the flux and a robust credible range on it. We also determine limiting sensitivities at arbitrary locations in the field using the same formulation. This work was supported by CXC NASA contracts NAS8-39073 (VK) and NAS8-03060 (CSC).

Neutron multiplicity counting: Confidence intervals for reconstruction parameters

DOE PAGES

Verbeke, Jerome M.

2016-03-09

From nuclear materials accountability to homeland security, the need for improved nuclear material detection, assay, and authentication has grown over the past decades. Starting in the 1940s, neutron multiplicity counting techniques have enabled quantitative evaluation of masses and multiplications of fissile materials. In this paper, we propose a new method to compute uncertainties on these parameters using a model-based sequential Bayesian processor, resulting in credible regions in the fissile material mass and multiplication space. These uncertainties will enable us to evaluate quantitatively proposed improvements to the theoretical fission chain model. Additionally, because the processor can calculate uncertainties in real time,more » it is a useful tool in applications such as portal monitoring: monitoring can stop as soon as a preset confidence of non-threat is reached.« less

Tutorial: Asteroseismic Stellar Modelling with AIMS

NASA Astrophysics Data System (ADS)

Lund, Mikkel N.; Reese, Daniel R.

The goal of aims (Asteroseismic Inference on a Massive Scale) is to estimate stellar parameters and credible intervals/error bars in a Bayesian manner from a set of asteroseismic frequency data and so-called classical constraints. To achieve reliable parameter estimates and computational efficiency, it searches through a grid of pre-computed models using an MCMC algorithm—interpolation within the grid of models is performed by first tessellating the grid using a Delaunay triangulation and then doing a linear barycentric interpolation on matching simplexes. Inputs for the modelling consist of individual frequencies from peak-bagging, which can be complemented with classical spectroscopic constraints. aims is mostly written in Python with a modular structure to facilitate contributions from the community. Only a few computationally intensive parts have been rewritten in Fortran in order to speed up calculations.

A Comparison of Metamodeling Techniques via Numerical Experiments

NASA Technical Reports Server (NTRS)

Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.

2016-01-01

This paper presents a comparative analysis of a few metamodeling techniques using numerical experiments for the single input-single output case. These experiments enable comparing the models' predictions with the phenomenon they are aiming to describe as more data is made available. These techniques include (i) prediction intervals associated with a least squares parameter estimate, (ii) Bayesian credible intervals, (iii) Gaussian process models, and (iv) interval predictor models. Aspects being compared are computational complexity, accuracy (i.e., the degree to which the resulting prediction conforms to the actual Data Generating Mechanism), reliability (i.e., the probability that new observations will fall inside the predicted interval), sensitivity to outliers, extrapolation properties, ease of use, and asymptotic behavior. The numerical experiments describe typical application scenarios that challenge the underlying assumptions supporting most metamodeling techniques.

Can Simulation Credibility Be Improved Using Sensitivity Analysis to Understand Input Data Effects on Model Outcome?

NASA Technical Reports Server (NTRS)

Myers, Jerry G.; Young, M.; Goodenow, Debra A.; Keenan, A.; Walton, M.; Boley, L.

2015-01-01

Model and simulation (MS) credibility is defined as, the quality to elicit belief or trust in MS results. NASA-STD-7009 [1] delineates eight components (Verification, Validation, Input Pedigree, Results Uncertainty, Results Robustness, Use History, MS Management, People Qualifications) that address quantifying model credibility, and provides guidance to the model developers, analysts, and end users for assessing the MS credibility. Of the eight characteristics, input pedigree, or the quality of the data used to develop model input parameters, governing functions, or initial conditions, can vary significantly. These data quality differences have varying consequences across the range of MS application. NASA-STD-7009 requires that the lowest input data quality be used to represent the entire set of input data when scoring the input pedigree credibility of the model. This requirement provides a conservative assessment of model inputs, and maximizes the communication of the potential level of risk of using model outputs. Unfortunately, in practice, this may result in overly pessimistic communication of the MS output, undermining the credibility of simulation predictions to decision makers. This presentation proposes an alternative assessment mechanism, utilizing results parameter robustness, also known as model input sensitivity, to improve the credibility scoring process for specific simulations.

Motivation and Treatment Credibility Predicts Dropout, Treatment Adherence, and Clinical Outcomes in an Internet-Based Cognitive Behavioral Relaxation Program: A Randomized Controlled Trial.

PubMed

Alfonsson, Sven; Olsson, Erik; Hursti, Timo

2016-03-08

In previous research, variables such as age, education, treatment credibility, and therapeutic alliance have shown to affect patients' treatment adherence and outcome in Internet-based psychotherapy. A more detailed understanding of how such variables are associated with different measures of adherence and clinical outcomes may help in designing more effective online therapy. The aims of this study were to investigate demographical, psychological, and treatment-specific variables that could predict dropout, treatment adherence, and treatment outcomes in a study of online relaxation for mild to moderate stress symptoms. Participant dropout and attrition as well as data from self-report instruments completed before, during, and after the online relaxation program were analyzed. Multiple linear and logistical regression analyses were conducted to predict early dropout, overall attrition, online treatment progress, number of registered relaxation exercises, posttreatment symptom levels, and reliable improvement. Dropout was significantly predicted by treatment credibility, whereas overall attrition was associated with reporting a focus on immediate consequences and experiencing a low level of intrinsic motivation for the treatment. Treatment progress was predicted by education level and treatment credibility, whereas number of registered relaxation exercises was associated with experiencing intrinsic motivation for the treatment. Posttreatment stress symptoms were positively predicted by feeling external pressure to participate in the treatment and negatively predicted by treatment credibility. Reporting reliable symptom improvement after treatment was predicted by treatment credibility and therapeutic bond. This study confirmed that treatment credibility and a good working alliance are factors associated with successful Internet-based psychotherapy. Further, the study showed that measuring adherence in different ways provides somewhat different results, which underscore the importance of carefully defining treatment adherence in psychotherapy research. Lastly, the results suggest that finding the treatment interesting and engaging may help patients carry through with the intervention and complete prescribed assignments, a result that may help guide the design of future interventions. Clinicaltrials.gov NCT02535598; http://clinicaltrials.gov/ct2/show/NCT02535598 (Archived by WebCite at http://www.webcitation.org/6fl38ms7y).

Policing and risk of overdose mortality in urban neighborhoods

PubMed Central

Bohnert, Amy S.B.; Nandi, Arijit; Tracy, Melissa; Cerdá, Magdalena; Tardiff, Kenneth J; Vlahov, David; Galea, Sandro

2010-01-01

Background Accidental drug overdose is a major cause of mortality among drug users. Fears of police arrest may deter witnesses of drug overdose from calling for medical help and may be a determinant of drug overdose mortality. To our knowledge, no studies have empirically assessed the relation between levels of policing and drug overdose mortality. We hypothesized that levels of police activity, congruent with fears of police arrest, are positively associated with drug overdose mortality. Methods We assembled cross-sectional time-series data for 74 New York City (NYC) police precincts over the period 1990–1999 using data collected from the Office of the Chief Medical Examiner of NYC, the NYC Police Department, and the US Census Bureau. Misdemeanor arrest rate—reflecting police activity—was our primary independent variable of interest, and overdose rate our primary dependent variable of interest. Results The mean overdose rate per 100,000 among police precincts in NYC between 1990 and 1999 was 10.8 (standard deviation = 10.0). In a Bayesian hierarchical model that included random spatial and temporal effects and a space-time interaction, the misdemeanor arrest rate per 1,000 was associated with higher overdose mortality (posterior median = 0.003, 95% Credible Interval = 0.001, 0.005) after adjustment for overall drug use in the precinct and demographic characteristics. Conclusions Levels of police activity in a precinct are associated with accidental drug overdose mortality. Future research should examine aspects of police-community interactions that contribute to higher overdose mortality. PMID:20727684

Neurobehavioral performance in adolescents is inversely associated with traffic exposure.

PubMed

Kicinski, Michal; Vermeir, Griet; Van Larebeke, Nicolas; Den Hond, Elly; Schoeters, Greet; Bruckers, Liesbeth; Sioen, Isabelle; Bijnens, Esmée; Roels, Harry A; Baeyens, Willy; Viaene, Mineke K; Nawrot, Tim S

2015-02-01

On the basis of animal research and epidemiological studies in children and elderly there is a growing concern that traffic exposure may affect the brain. The aim of our study was to investigate the association between traffic exposure and neurobehavioral performance in adolescents. We examined 606 adolescents. To model the exposure, we constructed a traffic exposure factor based on a biomarker of benzene (urinary trans,trans-muconic acid) and the amount of contact with traffic preceding the neurobehavioral examination (using distance-weighted traffic density and time spent in traffic). We used a Bayesian structural equation model to investigate the association between traffic exposure and three neurobehavioral domains: sustained attention, short-term memory, and manual motor speed. A one standard deviation increase in traffic exposure was associated with a 0.26 standard deviation decrease in sustained attention (95% credible interval: -0.02 to -0.51), adjusting for gender, age, smoking, passive smoking, level of education of the mother, socioeconomic status, time of the day, and day of the week. The associations between traffic exposure and the other neurobehavioral domains studied had the same direction but did not reach the level of statistical significance. The results remained consistent in the sensitivity analysis excluding smokers and passive smokers. The inverse association between sustained attention and traffic exposure was independent of the blood lead level. Our study in adolescents supports the recent findings in children and elderly suggesting that traffic exposure adversely affects the neurobehavioral function. Copyright © 2014 Elsevier Ltd. All rights reserved.

Associations between neighbourhood walkability and daily steps in adults: a systematic review and meta-analysis.

PubMed

Hajna, Samantha; Ross, Nancy A; Brazeau, Anne-Sophie; Bélisle, Patrick; Joseph, Lawrence; Dasgupta, Kaberi

2015-08-11

Higher street connectivity, land use mix and residential density (collectively referred to as neighbourhood walkability) have been linked to higher levels of walking. The objective of our study was to summarize the current body of knowledge on the association between neighbourhood walkability and biosensor-assessed daily steps in adults. We conducted a systematic search of PubMed, SCOPUS, and Embase (Ovid) for articles published prior to May 2014 on the association between walkability (based on Geographic Information Systems-derived street connectivity, land use mix, and/or residential density) and daily steps (pedometer or accelerometer-assessed) in adults. The mean differences in daily steps between adults living in high versus low walkable neighbourhoods were pooled across studies using a Bayesian hierarchical model. The search strategy yielded 8,744 unique abstracts. Thirty of these underwent full article review of which six met the inclusion criteria. Four of these studies were conducted in Europe and two were conducted in Asia. A meta-analysis of four of these six studies indicates that participants living in high compared to low walkable neighbourhoods accumulate 766 more steps per day (95 % credible interval 250, 1271). This accounts for approximately 8 % of recommended daily steps. The results of European and Asian studies support the hypothesis that higher neighbourhood walkability is associated with higher levels of biosensor-assessed walking in adults. More studies on this association are needed in North America.

Evaluation of uncertainty in the adjustment of fundamental constants

NASA Astrophysics Data System (ADS)

Bodnar, Olha; Elster, Clemens; Fischer, Joachim; Possolo, Antonio; Toman, Blaza

2016-02-01

Combining multiple measurement results for the same quantity is an important task in metrology and in many other areas. Examples include the determination of fundamental constants, the calculation of reference values in interlaboratory comparisons, or the meta-analysis of clinical studies. However, neither the GUM nor its supplements give any guidance for this task. Various approaches are applied such as weighted least-squares in conjunction with the Birge ratio or random effects models. While the former approach, which is based on a location-scale model, is particularly popular in metrology, the latter represents a standard tool used in statistics for meta-analysis. We investigate the reliability and robustness of the location-scale model and the random effects model with particular focus on resulting coverage or credible intervals. The interval estimates are obtained by adopting a Bayesian point of view in conjunction with a non-informative prior that is determined by a currently favored principle for selecting non-informative priors. Both approaches are compared by applying them to simulated data as well as to data for the Planck constant and the Newtonian constant of gravitation. Our results suggest that the proposed Bayesian inference based on the random effects model is more reliable and less sensitive to model misspecifications than the approach based on the location-scale model.

Bayesian inference for OPC modeling

NASA Astrophysics Data System (ADS)

Burbine, Andrew; Sturtevant, John; Fryer, David; Smith, Bruce W.

2016-03-01

The use of optical proximity correction (OPC) demands increasingly accurate models of the photolithographic process. Model building and inference techniques in the data science community have seen great strides in the past two decades which make better use of available information. This paper aims to demonstrate the predictive power of Bayesian inference as a method for parameter selection in lithographic models by quantifying the uncertainty associated with model inputs and wafer data. Specifically, the method combines the model builder's prior information about each modelling assumption with the maximization of each observation's likelihood as a Student's t-distributed random variable. Through the use of a Markov chain Monte Carlo (MCMC) algorithm, a model's parameter space is explored to find the most credible parameter values. During parameter exploration, the parameters' posterior distributions are generated by applying Bayes' rule, using a likelihood function and the a priori knowledge supplied. The MCMC algorithm used, an affine invariant ensemble sampler (AIES), is implemented by initializing many walkers which semiindependently explore the space. The convergence of these walkers to global maxima of the likelihood volume determine the parameter values' highest density intervals (HDI) to reveal champion models. We show that this method of parameter selection provides insights into the data that traditional methods do not and outline continued experiments to vet the method.

The improved business valuation model for RFID company based on the community mining method.

PubMed

Li, Shugang; Yu, Zhaoxu

2017-01-01

Nowadays, the appetite for the investment and mergers and acquisitions (M&A) activity in RFID companies is growing rapidly. Although the huge number of papers have addressed the topic of business valuation models based on statistical methods or neural network methods, only a few are dedicated to constructing a general framework for business valuation that improves the performance with network graph (NG) and the corresponding community mining (CM) method. In this study, an NG based business valuation model is proposed, where real options approach (ROA) integrating CM method is designed to predict the company's net profit as well as estimate the company value. Three improvements are made in the proposed valuation model: Firstly, our model figures out the credibility of the node belonging to each community and clusters the network according to the evolutionary Bayesian method. Secondly, the improved bacterial foraging optimization algorithm (IBFOA) is adopted to calculate the optimized Bayesian posterior probability function. Finally, in IBFOA, bi-objective method is used to assess the accuracy of prediction, and these two objectives are combined into one objective function using a new Pareto boundary method. The proposed method returns lower forecasting error than 10 well-known forecasting models on 3 different time interval valuing tasks for the real-life simulation of RFID companies.

The improved business valuation model for RFID company based on the community mining method

PubMed Central

Li, Shugang; Yu, Zhaoxu

2017-01-01

Nowadays, the appetite for the investment and mergers and acquisitions (M&A) activity in RFID companies is growing rapidly. Although the huge number of papers have addressed the topic of business valuation models based on statistical methods or neural network methods, only a few are dedicated to constructing a general framework for business valuation that improves the performance with network graph (NG) and the corresponding community mining (CM) method. In this study, an NG based business valuation model is proposed, where real options approach (ROA) integrating CM method is designed to predict the company’s net profit as well as estimate the company value. Three improvements are made in the proposed valuation model: Firstly, our model figures out the credibility of the node belonging to each community and clusters the network according to the evolutionary Bayesian method. Secondly, the improved bacterial foraging optimization algorithm (IBFOA) is adopted to calculate the optimized Bayesian posterior probability function. Finally, in IBFOA, bi-objective method is used to assess the accuracy of prediction, and these two objectives are combined into one objective function using a new Pareto boundary method. The proposed method returns lower forecasting error than 10 well-known forecasting models on 3 different time interval valuing tasks for the real-life simulation of RFID companies. PMID:28459815

Robust Bayesian linear regression with application to an analysis of the CODATA values for the Planck constant

NASA Astrophysics Data System (ADS)

Wübbeler, Gerd; Bodnar, Olha; Elster, Clemens

2018-02-01

Weighted least-squares estimation is commonly applied in metrology to fit models to measurements that are accompanied with quoted uncertainties. The weights are chosen in dependence on the quoted uncertainties. However, when data and model are inconsistent in view of the quoted uncertainties, this procedure does not yield adequate results. When it can be assumed that all uncertainties ought to be rescaled by a common factor, weighted least-squares estimation may still be used, provided that a simple correction of the uncertainty obtained for the estimated model is applied. We show that these uncertainties and credible intervals are robust, as they do not rely on the assumption of a Gaussian distribution of the data. Hence, common software for weighted least-squares estimation may still safely be employed in such a case, followed by a simple modification of the uncertainties obtained by that software. We also provide means of checking the assumptions of such an approach. The Bayesian regression procedure is applied to analyze the CODATA values for the Planck constant published over the past decades in terms of three different models: a constant model, a straight line model and a spline model. Our results indicate that the CODATA values may not have yet stabilized.

Simulating Terrorism: Credible Commitment, Costly Signaling, and Strategic Behavior

ERIC Educational Resources Information Center

Siegel, David A.; Young, Joseph K.

2009-01-01

We present two simulations designed to convey the strategic nature of terrorism and counterterrorism. The first is a simulated hostage crisis, designed primarily to illustrate the concepts of credible commitment and costly signaling. The second explores high-level decision making of both a terrorist group and the state, and is designed to…

Credibility judgments of narratives: language, plausibility, and absorption.

PubMed

Nahari, Galit; Glicksohn, Joseph; Nachson, Israel

2010-01-01

Two experiments were conducted in order to find out whether textual features of narratives differentially affect credibility judgments made by judges having different levels of absorption (a disposition associated with rich visual imagination). Participants in both experiments were exposed to a textual narrative and requested to judge whether the narrator actually experienced the event he described in his story. In Experiment 1, the narrative varied in terms of language (literal, figurative) and plausibility (ordinary, anomalous). In Experiment 2, the narrative varied in terms of language only. The participants' perceptions of the plausibility of the story described and the extent to which they were absorbed in reading were measured. The data from both experiments together suggest that the groups applied entirely different criteria in credibility judgments. For high-absorption individuals, their credibility judgment depends on the degree to which the text can be assimilated into their own vivid imagination, whereas for low-absorption individuals it depends mainly on plausibility. That is, high-absorption individuals applied an experiential mental set while judging the credibility of the narrator, whereas low-absorption individuals applied an instrumental mental set. Possible cognitive mechanisms and implications for credibility judgments are discussed.

Bayesian model reduction and empirical Bayes for group (DCM) studies

PubMed Central

Friston, Karl J.; Litvak, Vladimir; Oswal, Ashwini; Razi, Adeel; Stephan, Klaas E.; van Wijk, Bernadette C.M.; Ziegler, Gabriel; Zeidman, Peter

2016-01-01

This technical note describes some Bayesian procedures for the analysis of group studies that use nonlinear models at the first (within-subject) level – e.g., dynamic causal models – and linear models at subsequent (between-subject) levels. Its focus is on using Bayesian model reduction to finesse the inversion of multiple models of a single dataset or a single (hierarchical or empirical Bayes) model of multiple datasets. These applications of Bayesian model reduction allow one to consider parametric random effects and make inferences about group effects very efficiently (in a few seconds). We provide the relatively straightforward theoretical background to these procedures and illustrate their application using a worked example. This example uses a simulated mismatch negativity study of schizophrenia. We illustrate the robustness of Bayesian model reduction to violations of the (commonly used) Laplace assumption in dynamic causal modelling and show how its recursive application can facilitate both classical and Bayesian inference about group differences. Finally, we consider the application of these empirical Bayesian procedures to classification and prediction. PMID:26569570

Dimensions of Credibility in Models and Simulations

NASA Technical Reports Server (NTRS)

Steele, Martin J.

2008-01-01

Based on the National Aeronautics and Space Administration's (NASA's) work in developing a standard for models and simulations (M&S), the subject of credibility in M&S became a distinct focus. This is an indirect result from the Space Shuttle Columbia Accident Investigation Board (CAIB), which eventually resulted in an action, among others, to improve the rigor in NASA's M&S practices. The focus of this action came to mean a standardized method for assessing and reporting results from any type of M&S. As is typical in the standards development process, this necessarily developed into defming a common terminology base, common documentation requirements (especially for M&S used in critical decision making), and a method for assessing the credibility of M&S results. What surfaced in the development of the NASA Standard was the various dimensions credibility to consider when accepting the results from any model or simulation analysis. The eight generally relevant factors of credibility chosen in the NASA Standard proved only one aspect in the dimensionality of M&S credibility. At the next level of detail, the full comprehension of some of the factors requires an understanding along a couple of dimensions as well. Included in this discussion are the prerequisites for the appropriate use of a given M&S, the choice of factors in credibility assessment with their inherent dimensionality, and minimum requirements for fully reporting M&S results.

Measuring the radius of PSR J0437 -4715 using NICER observations of X-ray oscillations

NASA Astrophysics Data System (ADS)

Lamb, Frederick; Miller, M. Coleman

2017-01-01

The Neutron Star Interior Composition Explorer (NICER) will launch early in 2017. Its first scientific objective is to precisely and reliably measure the radius of several neutron stars, thereby constraining the properties of cold matter at supranuclear densities. This will be done by fitting energy-dependent waveform models to the observed thermal X-ray waveforms of selected rotation-powered millisecond pulsars. A key target is the 174-Hz pulsar PSR J0437 -4715. Using synthetic waveform data and Bayesian methods, we have estimated the precisions with which its mass M and radius R can be measured by NICER. When generating the synthetic data, we assumed M = 1 . 4M⊙ and R = 13 km. When generating the data and when analyzing it, we assumed the X-ray spectrum and radiation beaming pattern given by models with cool hydrogen atmospheres and two hot spots. Assuming NICER observations lasting a total of 1.0 Msec, current knowledge of M and the distance, and knowledge of the pulsar's spin axis to within 1°, the 1 σ credible region in R extends from 11.83 to 13.73 km (7.4%) and in M, from 1.307 to 1.567 M⊙ (9.1%). Marginalizing over M, we find the 1 σ credible interval for R alone extends from 12.62 to 13.68 km (4%).

Teaching Bayesian Statistics in a Health Research Methodology Program

ERIC Educational Resources Information Center

Pullenayegum, Eleanor M.; Thabane, Lehana

2009-01-01

Despite the appeal of Bayesian methods in health research, they are not widely used. This is partly due to a lack of courses in Bayesian methods at an appropriate level for non-statisticians in health research. Teaching such a course can be challenging because most statisticians have been taught Bayesian methods using a mathematical approach, and…

The impact of using informative priors in a Bayesian cost-effectiveness analysis: an application of endovascular versus open surgical repair for abdominal aortic aneurysms in high-risk patients.

PubMed

McCarron, C Elizabeth; Pullenayegum, Eleanor M; Thabane, Lehana; Goeree, Ron; Tarride, Jean-Eric

2013-04-01

Bayesian methods have been proposed as a way of synthesizing all available evidence to inform decision making. However, few practical applications of the use of Bayesian methods for combining patient-level data (i.e., trial) with additional evidence (e.g., literature) exist in the cost-effectiveness literature. The objective of this study was to compare a Bayesian cost-effectiveness analysis using informative priors to a standard non-Bayesian nonparametric method to assess the impact of incorporating additional information into a cost-effectiveness analysis. Patient-level data from a previously published nonrandomized study were analyzed using traditional nonparametric bootstrap techniques and bivariate normal Bayesian models with vague and informative priors. Two different types of informative priors were considered to reflect different valuations of the additional evidence relative to the patient-level data (i.e., "face value" and "skeptical"). The impact of using different distributions and valuations was assessed in a sensitivity analysis. Models were compared in terms of incremental net monetary benefit (INMB) and cost-effectiveness acceptability frontiers (CEAFs). The bootstrapping and Bayesian analyses using vague priors provided similar results. The most pronounced impact of incorporating the informative priors was the increase in estimated life years in the control arm relative to what was observed in the patient-level data alone. Consequently, the incremental difference in life years originally observed in the patient-level data was reduced, and the INMB and CEAF changed accordingly. The results of this study demonstrate the potential impact and importance of incorporating additional information into an analysis of patient-level data, suggesting this could alter decisions as to whether a treatment should be adopted and whether more information should be acquired.

Timing and effect of a safe routes to school program on child pedestrian injury risk during school travel hours: Bayesian changepoint and difference-in-differences analysis.

PubMed

DiMaggio, Charles; Chen, Qixuan; Muennig, Peter A; Li, Guohua

2014-12-01

In 2005, the US Congress allocated $612 million for a national Safe Routes to School (SRTS) program to encourage walking and bicycling to schools. We evaluated the effectiveness of a SRTS in controlling pedestrian injuries among school-age children. Bayesian changepoint analysis was applied to model the quarterly counts of pedestrian injuries among 5- to 19-year old children in New York City between 2001 and 2010 during school-travel hours in census tracts with and without SRTS. Overdispersed Poisson model was used to estimate difference-in-differences in injury risk between census tracts with and without SRTS following the changepoint. In SRTS-intervention census tracts, a change point in the quarterly counts of injuries was identified in the second quarter of 2008, which was consistent with the timing of the implementation of SRTS interventions. In census tracts with SRTS interventions, the estimated quarterly rates of pedestrian injury per 10,000 population among school-age children during school-travel hours were 3.47 (95% Credible Interval [CrI] 2.67, 4.39) prior to the changepoint, and 0.74 (95% CrI 0.30, 1.50) after the changepoint. There was no change in the average number of quarterly injuries in non-SRTS census tracts. Overdispersed Poisson modeling revealed that SRTS implementation was associated with a 44% reduction (95% Confidence Interval [CI] 87% decrease to 130% increase) in school-age pedestrian injury risk during school-travel hours. Bayesian changepoint analysis of quarterly counts of school-age pedestrian injuries successfully identified the timing of SRTS intervention in New York City. Implementation of the SRTS program in New York City appears to be effective in reducing school-age pedestrian injuries during school-travel hours.

qPR: An adaptive partial-report procedure based on Bayesian inference.

PubMed

Baek, Jongsoo; Lesmes, Luis Andres; Lu, Zhong-Lin

2016-08-01

Iconic memory is best assessed with the partial report procedure in which an array of letters appears briefly on the screen and a poststimulus cue directs the observer to report the identity of the cued letter(s). Typically, 6-8 cue delays or 600-800 trials are tested to measure the iconic memory decay function. Here we develop a quick partial report, or qPR, procedure based on a Bayesian adaptive framework to estimate the iconic memory decay function with much reduced testing time. The iconic memory decay function is characterized by an exponential function and a joint probability distribution of its three parameters. Starting with a prior of the parameters, the method selects the stimulus to maximize the expected information gain in the next test trial. It then updates the posterior probability distribution of the parameters based on the observer's response using Bayesian inference. The procedure is reiterated until either the total number of trials or the precision of the parameter estimates reaches a certain criterion. Simulation studies showed that only 100 trials were necessary to reach an average absolute bias of 0.026 and a precision of 0.070 (both in terms of probability correct). A psychophysical validation experiment showed that estimates of the iconic memory decay function obtained with 100 qPR trials exhibited good precision (the half width of the 68.2% credible interval = 0.055) and excellent agreement with those obtained with 1,600 trials of the conventional method of constant stimuli procedure (RMSE = 0.063). Quick partial-report relieves the data collection burden in characterizing iconic memory and makes it possible to assess iconic memory in clinical populations.

Effects of Green Tea Gargling on the Prevention of Influenza Infection: An Analysis Using Bayesian Approaches.

PubMed

Ide, Kazuki; Kawasaki, Yohei; Akutagawa, Maiko; Yamada, Hiroshi

2017-02-01

The aim of this study is to analyze the data obtained from a randomized trial on the prevention of influenza by gargling with green tea, which gave nonsignificant results based on frequentist approaches, by using Bayesian approaches. The posterior proportion, with 95% credible interval (CrI), of influenza in each group was calculated. The Bayesian index θ is the probability that a hypothesis is true. In this case, θ is the probability that the hypothesis that green tea gargling reduced influenza compared with water gargling is true. Univariate and multivariate logistic regression analyses were also performed by using the Markov chain Monte Carlo method. The full analysis set included 747 participants. During the study period, influenza occurred in 44 participants (5.9%). The difference between the two independent binominal proportions was -0.019 (95% CrI, -0.054 to 0.015; θ = 0.87). The partial regression coefficients in the univariate analysis were -0.35 (95% CrI, -1.00 to 0.24) with use of a uniform prior and -0.34 (95% CrI, -0.96 to 0.27) with use of a Jeffreys prior. In the multivariate analysis, the values were -0.37 (95% CrI, -0.96 to 0.30) and -0.36 (95% CrI, -1.03 to 0.21), respectively. The difference between the two independent binominal proportions was less than 0, and θ was greater than 0.85. Therefore, green tea gargling may slightly reduce influenza compared with water gargling. This analysis suggests that green tea gargling can be an additional preventive measure for use with other pharmaceutical and nonpharmaceutical measures and indicates the need for additional studies to confirm the effect of green tea gargling.

qPR: An adaptive partial-report procedure based on Bayesian inference

PubMed Central

Baek, Jongsoo; Lesmes, Luis Andres; Lu, Zhong-Lin

2016-01-01

Iconic memory is best assessed with the partial report procedure in which an array of letters appears briefly on the screen and a poststimulus cue directs the observer to report the identity of the cued letter(s). Typically, 6–8 cue delays or 600–800 trials are tested to measure the iconic memory decay function. Here we develop a quick partial report, or qPR, procedure based on a Bayesian adaptive framework to estimate the iconic memory decay function with much reduced testing time. The iconic memory decay function is characterized by an exponential function and a joint probability distribution of its three parameters. Starting with a prior of the parameters, the method selects the stimulus to maximize the expected information gain in the next test trial. It then updates the posterior probability distribution of the parameters based on the observer's response using Bayesian inference. The procedure is reiterated until either the total number of trials or the precision of the parameter estimates reaches a certain criterion. Simulation studies showed that only 100 trials were necessary to reach an average absolute bias of 0.026 and a precision of 0.070 (both in terms of probability correct). A psychophysical validation experiment showed that estimates of the iconic memory decay function obtained with 100 qPR trials exhibited good precision (the half width of the 68.2% credible interval = 0.055) and excellent agreement with those obtained with 1,600 trials of the conventional method of constant stimuli procedure (RMSE = 0.063). Quick partial-report relieves the data collection burden in characterizing iconic memory and makes it possible to assess iconic memory in clinical populations. PMID:27580045

Inhaled Cannabis for Chronic Neuropathic Pain: A Meta-analysis of Individual Patient Data.

PubMed

Andreae, Michael H; Carter, George M; Shaparin, Naum; Suslov, Kathryn; Ellis, Ronald J; Ware, Mark A; Abrams, Donald I; Prasad, Hannah; Wilsey, Barth; Indyk, Debbie; Johnson, Matthew; Sacks, Henry S

2015-12-01

Chronic neuropathic pain, the most frequent condition affecting the peripheral nervous system, remains underdiagnosed and difficult to treat. Inhaled cannabis may alleviate chronic neuropathic pain. Our objective was to synthesize the evidence on the use of inhaled cannabis for chronic neuropathic pain. We performed a systematic review and a meta-analysis of individual patient data. We registered our protocol with PROSPERO CRD42011001182. We searched in Cochrane Central, PubMed, EMBASE, and AMED. We considered all randomized controlled trials investigating chronic painful neuropathy and comparing inhaled cannabis with placebo. We pooled treatment effects following a hierarchical random-effects Bayesian responder model for the population-averaged subject-specific effect. Our evidence synthesis of individual patient data from 178 participants with 405 observed responses in 5 randomized controlled trials following patients for days to weeks provides evidence that inhaled cannabis results in short-term reductions in chronic neuropathic pain for 1 in every 5 to 6 patients treated (number needed to treat = 5.6 with a Bayesian 95% credible interval ranging between 3.4 and 14). Our inferences were insensitive to model assumptions, priors, and parameter choices. We caution that the small number of studies and participants, the short follow-up, shortcomings in allocation concealment, and considerable attrition limit the conclusions that can be drawn from the review. The Bayes factor is 332, corresponding to a posterior probability of effect of 99.7%. This novel Bayesian meta-analysis of individual patient data from 5 randomized trials suggests that inhaled cannabis may provide short-term relief for 1 in 5 to 6 patients with neuropathic pain. Pragmatic trials are needed to evaluate the long-term benefits and risks of this treatment. Copyright © 2015 American Pain Society. Published by Elsevier Inc. All rights reserved.

Evaluation of calibration efficacy under different levels of uncertainty

DOE PAGES

Heo, Yeonsook; Graziano, Diane J.; Guzowski, Leah; ...

2014-06-10

This study examines how calibration performs under different levels of uncertainty in model input data. It specifically assesses the efficacy of Bayesian calibration to enhance the reliability of EnergyPlus model predictions. A Bayesian approach can be used to update uncertain values of parameters, given measured energy-use data, and to quantify the associated uncertainty.We assess the efficacy of Bayesian calibration under a controlled virtual-reality setup, which enables rigorous validation of the accuracy of calibration results in terms of both calibrated parameter values and model predictions. Case studies demonstrate the performance of Bayesian calibration of base models developed from audit data withmore » differing levels of detail in building design, usage, and operation.« less

Quantitative Decision Support Requires Quantitative User Guidance

NASA Astrophysics Data System (ADS)

Smith, L. A.

2009-12-01

Is it conceivable that models run on 2007 computer hardware could provide robust and credible probabilistic information for decision support and user guidance at the ZIP code level for sub-daily meteorological events in 2060? In 2090? Retrospectively, how informative would output from today’s models have proven in 2003? or the 1930’s? Consultancies in the United Kingdom, including the Met Office, are offering services to “future-proof” their customers from climate change. How is a US or European based user or policy maker to determine the extent to which exciting new Bayesian methods are relevant here? or when a commercial supplier is vastly overselling the insights of today’s climate science? How are policy makers and academic economists to make the closely related decisions facing them? How can we communicate deep uncertainty in the future at small length-scales without undermining the firm foundation established by climate science regarding global trends? Three distinct aspects of the communication of the uses of climate model output targeting users and policy makers, as well as other specialist adaptation scientists, are discussed. First, a brief scientific evaluation of the length and time scales at which climate model output is likely to become uninformative is provided, including a note on the applicability the latest Bayesian methodology to current state-of-the-art general circulation models output. Second, a critical evaluation of the language often employed in communication of climate model output, a language which accurately states that models are “better”, have “improved” and now “include” and “simulate” relevant meteorological processed, without clearly identifying where the current information is thought to be uninformative and misleads, both for the current climate and as a function of the state of the (each) climate simulation. And thirdly, a general approach for evaluating the relevance of quantitative climate model output for a given problem is presented. Based on climate science, meteorology, and the details of the question in hand, this approach identifies necessary (never sufficient) conditions required for the rational use of climate model output in quantitative decision support tools. Inasmuch as climate forecasting is a problem of extrapolation, there will always be harsh limits on our ability to establish where a model is fit for purpose, this does not, however, limit us from identifying model noise as such, and thereby avoiding some cases of the misapplication and over interpretation of model output. It is suggested that failure to clearly communicate the limits of today’s climate model in providing quantitative decision relevant climate information to today’s users of climate information, would risk the credibility of tomorrow’s climate science and science based policy more generally.

A Bayesian Approach to More Stable Estimates of Group-Level Effects in Contextual Studies.

PubMed

Zitzmann, Steffen; Lüdtke, Oliver; Robitzsch, Alexander

2015-01-01

Multilevel analyses are often used to estimate the effects of group-level constructs. However, when using aggregated individual data (e.g., student ratings) to assess a group-level construct (e.g., classroom climate), the observed group mean might not provide a reliable measure of the unobserved latent group mean. In the present article, we propose a Bayesian approach that can be used to estimate a multilevel latent covariate model, which corrects for the unreliable assessment of the latent group mean when estimating the group-level effect. A simulation study was conducted to evaluate the choice of different priors for the group-level variance of the predictor variable and to compare the Bayesian approach with the maximum likelihood approach implemented in the software Mplus. Results showed that, under problematic conditions (i.e., small number of groups, predictor variable with a small ICC), the Bayesian approach produced more accurate estimates of the group-level effect than the maximum likelihood approach did.

Bayesian model reduction and empirical Bayes for group (DCM) studies.

PubMed

Friston, Karl J; Litvak, Vladimir; Oswal, Ashwini; Razi, Adeel; Stephan, Klaas E; van Wijk, Bernadette C M; Ziegler, Gabriel; Zeidman, Peter

2016-03-01

This technical note describes some Bayesian procedures for the analysis of group studies that use nonlinear models at the first (within-subject) level - e.g., dynamic causal models - and linear models at subsequent (between-subject) levels. Its focus is on using Bayesian model reduction to finesse the inversion of multiple models of a single dataset or a single (hierarchical or empirical Bayes) model of multiple datasets. These applications of Bayesian model reduction allow one to consider parametric random effects and make inferences about group effects very efficiently (in a few seconds). We provide the relatively straightforward theoretical background to these procedures and illustrate their application using a worked example. This example uses a simulated mismatch negativity study of schizophrenia. We illustrate the robustness of Bayesian model reduction to violations of the (commonly used) Laplace assumption in dynamic causal modelling and show how its recursive application can facilitate both classical and Bayesian inference about group differences. Finally, we consider the application of these empirical Bayesian procedures to classification and prediction. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Fibroblast growth factor 23: associations with antiretroviral therapy in patients co-infected with HIV and hepatitis C.

PubMed

Young, J; Mucsi, I; Rollet-Kurhajec, K C; Klein, M B

2016-05-01

Fibroblast growth factor 23 (FGF23) has been associated with cardiovascular mortality. We estimate associations between the level of plasma FGF23 and exposure to abacavir (ABC) and to other components of antiretroviral therapy in patients co-infected with HIV and hepatitis C. Both intact and c-terminal FGF23 were measured in plasma using commercial assays for a sub-cohort of 295 patients selected at random from the 1150 patients enrolled in the Canadian Co-infection Cohort. The multiplicative effects of antiretroviral drug exposures and covariates on median FGF23 were then estimated using a hierarchical Bayesian model. The median level of intact FGF23 was independent of either past or recent exposure to abacavir, with multiplicative ratios of 1.00 and 1.07, 95% credible intervals 0.90-1.12 and 0.94-1.23, respectively. Median intact FGF23 tended to increase with past use of both nonnucleoside reverse-transcriptase inhibitors and protease inhibitors, but tended to decrease with recent use of either tenofovir, efavirenz or lopinavir. There were no obvious associations between the median level of c-terminal FGF23 and individual drugs or drug classes. Age, female gender, smoking and the aspartate aminotransferase to platelet ratio index were all associated with a higher median c-terminal FGF23 but not with a higher median intact FGF23. The level of FGF23 in plasma was independent of exposure to ABC. Lower levels of intact FGF23 with recent use of tenofovir, efavirenz or lopinavir may reflect their adverse effects on bone and vitamin D metabolism relative to other drugs in their respective drug classes. © 2015 British HIV Association.

The Effect of Task and Personal Relevance on Credibility Judgements while Searching on the Internet

ERIC Educational Resources Information Center

Kirkyla, Adrius Viktoras

2010-01-01

People can view the Internet as an endless source of information although it is not known how individuals might evaluate the credibility of information that is presented on websites. A methodology is needed to incorporate how the information seeking task, as well as the level of personal relevance, influences the criteria individuals use to…

Human health risk constrained naphthalene-contaminated groundwater remediation management through an improved credibility method.

PubMed

Li, Jing; Lu, Hongwei; Fan, Xing; Chen, Yizhong

2017-07-01

In this study, a human health risk constrained groundwater remediation management program based on the improved credibility is developed for naphthalene contamination. The program integrates simulation, multivariate regression analysis, health risk assessment, uncertainty analysis, and nonlinear optimization into a general framework. The improved credibility-based optimization model for groundwater remediation management with consideration of human health risk (ICOM-HHR) is capable of not only effectively addressing parameter uncertainties and risk-exceeding possibility in human health risk but also providing a credibility level that indicates the satisfaction of the optimal groundwater remediation strategies with multiple contributions of possibility and necessity. The capabilities and effectiveness of ICOM-HHR are illustrated through a real-world case study in Anhui Province, China. Results indicate that the ICOM-HHR would generate double remediation cost yet reduce approximately 10 times of the naphthalene concentrations at monitoring wells, i.e., mostly less than 1 μg/L, which implies that the ICOM-HHR usually results in better environmental and health risk benefits. And it is acceptable to obtain a better environmental quality and a lower health risk level with sacrificing a certain economic benefit.

Filling gaps in notification data: a model-based approach applied to travel related campylobacteriosis cases in New Zealand.

PubMed

Amene, E; Horn, B; Pirie, R; Lake, R; Döpfer, D

2016-09-06

Data containing notified cases of disease are often compromised by incomplete or partial information related to individual cases. In an effort to enhance the value of information from enteric disease notifications in New Zealand, this study explored the use of Bayesian and Multiple Imputation (MI) models to fill risk factor data gaps. As a test case, overseas travel as a risk factor for infection with campylobacteriosis has been examined. Two methods, namely Bayesian Specification (BAS) and Multiple Imputation (MI), were compared regarding predictive performance for various levels of artificially induced missingness of overseas travel status in campylobacteriosis notification data. Predictive performance of the models was assessed through the Brier Score, the Area Under the ROC Curve and the Percent Bias of regression coefficients. Finally, the best model was selected and applied to predict missing overseas travel status of campylobacteriosis notifications. While no difference was observed in the predictive performance of the BAS and MI methods at a lower rate of missingness (<10 %), but the BAS approach performed better than MI at a higher rate of missingness (50 %, 65 %, 80 %). The estimated proportion (95 % Credibility Intervals) of travel related cases was greatest in highly urban District Health Boards (DHBs) in Counties Manukau, Auckland and Waitemata, at 0.37 (0.12, 0.57), 0.33 (0.13, 0.55) and 0.28 (0.10, 0.49), whereas the lowest proportion was estimated for more rural West Coast, Northland and Tairawhiti DHBs at 0.02 (0.01, 0.05), 0.03 (0.01, 0.08) and 0.04 (0.01, 0.06), respectively. The national rate of travel related campylobacteriosis cases was estimated at 0.16 (0.02, 0.48). The use of BAS offers a flexible approach to data augmentation particularly when the missing rate is very high and when the Missing At Random (MAR) assumption holds. High rates of travel associated cases in urban regions of New Zealand predicted by this approach are plausible given the high rate of travel in these regions, including destinations with higher risk of infection. The added advantage of using a Bayesian approach is that the model's prediction can be improved whenever new information becomes available.

Modelling heterogeneity variances in multiple treatment comparison meta-analysis – Are informative priors the better solution?

PubMed Central

2013-01-01

Background Multiple treatment comparison (MTC) meta-analyses are commonly modeled in a Bayesian framework, and weakly informative priors are typically preferred to mirror familiar data driven frequentist approaches. Random-effects MTCs have commonly modeled heterogeneity under the assumption that the between-trial variance for all involved treatment comparisons are equal (i.e., the ‘common variance’ assumption). This approach ‘borrows strength’ for heterogeneity estimation across treatment comparisons, and thus, ads valuable precision when data is sparse. The homogeneous variance assumption, however, is unrealistic and can severely bias variance estimates. Consequently 95% credible intervals may not retain nominal coverage, and treatment rank probabilities may become distorted. Relaxing the homogeneous variance assumption may be equally problematic due to reduced precision. To regain good precision, moderately informative variance priors or additional mathematical assumptions may be necessary. Methods In this paper we describe four novel approaches to modeling heterogeneity variance - two novel model structures, and two approaches for use of moderately informative variance priors. We examine the relative performance of all approaches in two illustrative MTC data sets. We particularly compare between-study heterogeneity estimates and model fits, treatment effect estimates and 95% credible intervals, and treatment rank probabilities. Results In both data sets, use of moderately informative variance priors constructed from the pair wise meta-analysis data yielded the best model fit and narrower credible intervals. Imposing consistency equations on variance estimates, assuming variances to be exchangeable, or using empirically informed variance priors also yielded good model fits and narrow credible intervals. The homogeneous variance model yielded high precision at all times, but overall inadequate estimates of between-trial variances. Lastly, treatment rankings were similar among the novel approaches, but considerably different when compared with the homogenous variance approach. Conclusions MTC models using a homogenous variance structure appear to perform sub-optimally when between-trial variances vary between comparisons. Using informative variance priors, assuming exchangeability or imposing consistency between heterogeneity variances can all ensure sufficiently reliable and realistic heterogeneity estimation, and thus more reliable MTC inferences. All four approaches should be viable candidates for replacing or supplementing the conventional homogeneous variance MTC model, which is currently the most widely used in practice. PMID:23311298

A Bayesian network to predict vulnerability to sea-level rise: data report

USGS Publications Warehouse

Gutierrez, Benjamin T.; Plant, Nathaniel G.; Thieler, E. Robert

2011-01-01

During the 21st century, sea-level rise is projected to have a wide range of effects on coastal environments, development, and infrastructure. Consequently, there has been an increased focus on developing modeling or other analytical approaches to evaluate potential impacts to inform coastal management. This report provides the data that were used to develop and evaluate the performance of a Bayesian network designed to predict long-term shoreline change due to sea-level rise. The data include local rates of relative sea-level rise, wave height, tide range, geomorphic classification, coastal slope, and shoreline-change rate compiled as part of the U.S. Geological Survey Coastal Vulnerability Index for the U.S. Atlantic coast. In this project, the Bayesian network is used to define relationships among driving forces, geologic constraints, and coastal responses. Using this information, the Bayesian network is used to make probabilistic predictions of shoreline change in response to different future sea-level-rise scenarios.

Using Bayesian variable selection to analyze regular resolution IV two-level fractional factorial designs

DOE PAGES

Chipman, Hugh A.; Hamada, Michael S.

2016-06-02

Regular two-level fractional factorial designs have complete aliasing in which the associated columns of multiple effects are identical. Here, we show how Bayesian variable selection can be used to analyze experiments that use such designs. In addition to sparsity and hierarchy, Bayesian variable selection naturally incorporates heredity . This prior information is used to identify the most likely combinations of active terms. We also demonstrate the method on simulated and real experiments.

Using Bayesian variable selection to analyze regular resolution IV two-level fractional factorial designs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chipman, Hugh A.; Hamada, Michael S.

Regular two-level fractional factorial designs have complete aliasing in which the associated columns of multiple effects are identical. Here, we show how Bayesian variable selection can be used to analyze experiments that use such designs. In addition to sparsity and hierarchy, Bayesian variable selection naturally incorporates heredity . This prior information is used to identify the most likely combinations of active terms. We also demonstrate the method on simulated and real experiments.

Ancestral sequence reconstruction in primate mitochondrial DNA: compositional bias and effect on functional inference.

PubMed

Krishnan, Neeraja M; Seligmann, Hervé; Stewart, Caro-Beth; De Koning, A P Jason; Pollock, David D

2004-10-01

Reconstruction of ancestral DNA and amino acid sequences is an important means of inferring information about past evolutionary events. Such reconstructions suggest changes in molecular function and evolutionary processes over the course of evolution and are used to infer adaptation and convergence. Maximum likelihood (ML) is generally thought to provide relatively accurate reconstructed sequences compared to parsimony, but both methods lead to the inference of multiple directional changes in nucleotide frequencies in primate mitochondrial DNA (mtDNA). To better understand this surprising result, as well as to better understand how parsimony and ML differ, we constructed a series of computationally simple "conditional pathway" methods that differed in the number of substitutions allowed per site along each branch, and we also evaluated the entire Bayesian posterior frequency distribution of reconstructed ancestral states. We analyzed primate mitochondrial cytochrome b (Cyt-b) and cytochrome oxidase subunit I (COI) genes and found that ML reconstructs ancestral frequencies that are often more different from tip sequences than are parsimony reconstructions. In contrast, frequency reconstructions based on the posterior ensemble more closely resemble extant nucleotide frequencies. Simulations indicate that these differences in ancestral sequence inference are probably due to deterministic bias caused by high uncertainty in the optimization-based ancestral reconstruction methods (parsimony, ML, Bayesian maximum a posteriori). In contrast, ancestral nucleotide frequencies based on an average of the Bayesian set of credible ancestral sequences are much less biased. The methods involving simpler conditional pathway calculations have slightly reduced likelihood values compared to full likelihood calculations, but they can provide fairly unbiased nucleotide reconstructions and may be useful in more complex phylogenetic analyses than considered here due to their speed and flexibility. To determine whether biased reconstructions using optimization methods might affect inferences of functional properties, ancestral primate mitochondrial tRNA sequences were inferred and helix-forming propensities for conserved pairs were evaluated in silico. For ambiguously reconstructed nucleotides at sites with high base composition variability, ancestral tRNA sequences from Bayesian analyses were more compatible with canonical base pairing than were those inferred by other methods. Thus, nucleotide bias in reconstructed sequences apparently can lead to serious bias and inaccuracies in functional predictions.

Diagnostic performance of ELISA, IFAT and Western blot for the detection of anti-Leishmania infantum antibodies in cats using a Bayesian analysis without a gold standard.

PubMed

Persichetti, Maria Flaminia; Solano-Gallego, Laia; Vullo, Angela; Masucci, Marisa; Marty, Pierre; Delaunay, Pascal; Vitale, Fabrizio; Pennisi, Maria Grazia

2017-03-13

Anti-Leishmania antibodies are increasingly investigated in cats for epidemiological studies or for the diagnosis of clinical feline leishmaniosis. The immunofluorescent antibody test (IFAT), the enzyme-linked immunosorbent assay (ELISA) and western blot (WB) are the serological tests more frequently used. The aim of the present study was to assess diagnostic performance of IFAT, ELISA and WB to detect anti-L. infantum antibodies in feline serum samples obtained from endemic (n = 76) and non-endemic (n = 64) areas and from cats affected by feline leishmaniosis (n = 21) by a Bayesian approach without a gold standard. Cut-offs were set at 80 titre for IFAT and 40 ELISA units for ELISA. WB was considered positive in presence of at least a 18 KDa band. Statistical analysis was performed through a written routine with MATLAB software in the Bayesian framework. The latent data and observations from the joint posterior were simulated in the Bayesian approach by an iterative Markov Chain Monte Carlo technique using the Gibbs sampler for estimating sensitivity and specificity of the three tests. The median seroprevalence in the sample used for evaluating the performance of tests was estimated at 0.27 [credible interval (CI) = 0.20-0.34]. The median sensitivity of the three different methods was 0.97 (CI: 0.86-1.00), 0.75 (CI: 0.61-0.87) and 0.70 (CI: 0.56-0.83) for WB, IFAT and ELISA, respectively. Median specificity reached 0.99 (CI: 0.96-1.00) with WB, 0.97 (CI: 0.93-0.99) with IFAT and 0.98 (CI: 0.94-1.00) with ELISA. IFAT was more sensitive than ELISA (75 vs 70%) for the detection of subclinical infection while ELISA was better for diagnosing clinical leishmaniosis when compared with IFAT (98 vs 97%). The overall performance of all serological techniques was good and the most accurate test for anti-Leishmania antibody detection in feline serum samples was WB.

The intervention effect of local alcohol licensing policies on hospital admission and crime: a natural experiment using a novel Bayesian synthetictime-series method.

PubMed

de Vocht, Frank; Tilling, Kate; Pliakas, Triantafyllos; Angus, Colin; Egan, Matt; Brennan, Alan; Campbell, Rona; Hickman, Matthew

2017-09-01

Control of alcohol licensing at local government level is a key component of alcohol policy in England. There is, however, only weak evidence of any public health improvement. We used a novel natural experiment design to estimate the impact of new local alcohol licensing policies on hospital admissions and crime. We used Home Office licensing data (2007-2012) to identify (1) interventions: local areas where both a cumulative impact zone and increased licensing enforcement were introduced in 2011; and (2) controls: local areas with neither. Outcomes were 2009-2015 alcohol-related hospital admissions, violent and sexual crimes, and antisocial behaviour. Bayesian structural time series were used to create postintervention synthetic time series (counterfactuals) based on weighted time series in control areas. Intervention effects were calculated from differences between measured and expected trends. Validation analyses were conducted using randomly selected controls. 5 intervention and 86 control areas were identified. Intervention was associated with an average reduction in alcohol-related hospital admissions of 6.3% (95% credible intervals (CI) -12.8% to 0.2%) and to lesser extent with a reduced in violent crimes, especially up to 2013 (-4.6%, 95% CI -10.7% to 1.4%). There was weak evidence of an effect on sexual crimes up 2013 (-8.4%, 95% CI -21.4% to 4.6%) and insufficient evidence of an effect on antisocial behaviour as a result of a change in reporting. Moderate reductions in alcohol-related hospital admissions and violent and sexual crimes were associated with introduction of local alcohol licensing policies. This novel methodology holds promise for use in other natural experiments in public health. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Bayesian estimation of the dynamics of pandemic (H1N1) 2009 influenza transmission in Queensland: A space-time SIR-based model.

PubMed

Huang, Xiaodong; Clements, Archie C A; Williams, Gail; Mengersen, Kerrie; Tong, Shilu; Hu, Wenbiao

2016-04-01

A pandemic strain of influenza A spread rapidly around the world in 2009, now referred to as pandemic (H1N1) 2009. This study aimed to examine the spatiotemporal variation in the transmission rate of pandemic (H1N1) 2009 associated with changes in local socio-environmental conditions from May 7-December 31, 2009, at a postal area level in Queensland, Australia. We used the data on laboratory-confirmed H1N1 cases to examine the spatiotemporal dynamics of transmission using a flexible Bayesian, space-time, Susceptible-Infected-Recovered (SIR) modelling approach. The model incorporated parameters describing spatiotemporal variation in H1N1 infection and local socio-environmental factors. The weekly transmission rate of pandemic (H1N1) 2009 was negatively associated with the weekly area-mean maximum temperature at a lag of 1 week (LMXT) (posterior mean: -0.341; 95% credible interval (CI): -0.370--0.311) and the socio-economic index for area (SEIFA) (posterior mean: -0.003; 95% CI: -0.004--0.001), and was positively associated with the product of LMXT and the weekly area-mean vapour pressure at a lag of 1 week (LVAP) (posterior mean: 0.008; 95% CI: 0.007-0.009). There was substantial spatiotemporal variation in transmission rate of pandemic (H1N1) 2009 across Queensland over the epidemic period. High random effects of estimated transmission rates were apparent in remote areas and some postal areas with higher proportion of indigenous populations and smaller overall populations. Local SEIFA and local atmospheric conditions were associated with the transmission rate of pandemic (H1N1) 2009. The more populated regions displayed consistent and synchronized epidemics with low average transmission rates. The less populated regions had high average transmission rates with more variations during the H1N1 epidemic period. Copyright © 2016 Elsevier Inc. All rights reserved.

Predicting the multi-domain progression of Parkinson's disease: a Bayesian multivariate generalized linear mixed-effect model.

PubMed

Wang, Ming; Li, Zheng; Lee, Eun Young; Lewis, Mechelle M; Zhang, Lijun; Sterling, Nicholas W; Wagner, Daymond; Eslinger, Paul; Du, Guangwei; Huang, Xuemei

2017-09-25

It is challenging for current statistical models to predict clinical progression of Parkinson's disease (PD) because of the involvement of multi-domains and longitudinal data. Past univariate longitudinal or multivariate analyses from cross-sectional trials have limited power to predict individual outcomes or a single moment. The multivariate generalized linear mixed-effect model (GLMM) under the Bayesian framework was proposed to study multi-domain longitudinal outcomes obtained at baseline, 18-, and 36-month. The outcomes included motor, non-motor, and postural instability scores from the MDS-UPDRS, and demographic and standardized clinical data were utilized as covariates. The dynamic prediction was performed for both internal and external subjects using the samples from the posterior distributions of the parameter estimates and random effects, and also the predictive accuracy was evaluated based on the root of mean square error (RMSE), absolute bias (AB) and the area under the receiver operating characteristic (ROC) curve. First, our prediction model identified clinical data that were differentially associated with motor, non-motor, and postural stability scores. Second, the predictive accuracy of our model for the training data was assessed, and improved prediction was gained in particularly for non-motor (RMSE and AB: 2.89 and 2.20) compared to univariate analysis (RMSE and AB: 3.04 and 2.35). Third, the individual-level predictions of longitudinal trajectories for the testing data were performed, with ~80% observed values falling within the 95% credible intervals. Multivariate general mixed models hold promise to predict clinical progression of individual outcomes in PD. The data was obtained from Dr. Xuemei Huang's NIH grant R01 NS060722 , part of NINDS PD Biomarker Program (PDBP). All data was entered within 24 h of collection to the Data Management Repository (DMR), which is publically available ( https://pdbp.ninds.nih.gov/data-management ).

Bayesian evidence synthesis to estimate HIV prevalence in men who have sex with men in Poland at the end of 2009.

PubMed

Rosinska, M; Gwiazda, P; De Angelis, D; Presanis, A M

2016-04-01

HIV spread in men who have sex with men (MSM) is an increasing problem in Poland. Despite the existence of a surveillance system, there is no direct evidence to allow estimation of HIV prevalence and the proportion undiagnosed in MSM. We extracted data on HIV and the MSM population in Poland, including case-based surveillance data, diagnostic testing prevalence data and behavioural data relating to self-reported prior diagnosis, stratified by age (⩽35, >35 years) and region (Mazowieckie including the capital city of Warsaw; other regions). They were integrated into one model based on a Bayesian evidence synthesis approach. The posterior distributions for HIV prevalence and the undiagnosed fraction were estimated by Markov Chain Monte Carlo methods. To improve the model fit we repeated the analysis, introducing bias parameters to account for potential lack of representativeness in data. By placing additional constraints on bias parameters we obtained precisely identified estimates. This family of models indicates a high undiagnosed fraction [68·3%, 95% credibility interval (CrI) 53·9-76·1] and overall low prevalence (2·3%, 95% CrI 1·4-4·1) of HIV in MSM. Additional data are necessary in order to produce more robust epidemiological estimates. More effort is urgently needed to ensure timely diagnosis of HIV in Poland.

Prevalence of tuberculosis infection in healthcare workers of the public hospital network in Medellín, Colombia: a Bayesian approach.

PubMed

Ochoa, J; León, A L; Ramírez, I C; Lopera, C M; Bernal, E; Arbeláez, M P

2017-04-01

A latent tuberculosis infection (LTBI) prevalence survey was conducted using tuberculin skin test (TST) and Quantiferon test (QFT) in 1218 healthcare workers (HCWs) in Medellín, Colombia. In order to improve the prevalence estimates, a latent class model was built using a Bayesian approach with informative priors on the sensitivity and specificity of the TST. The proportion of concordant results (TST+,QFT+) was 41% and the discordant results contributed 27%. The marginal estimate of the prevalence P(LTBI+) was 62·1% [95% credible interval (CrI) 53·0-68·2]. The probability of LTBI+ given positive results for both tests was 99·6% (95% CrI 98·1-99·9). Sensitivity was 88·5 for TST and 74·3 for QFT, and specificity was 87·8 for TST and 97·6 for QFT. A high LTBI prevalence was found in HCWs with time-accumulated exposure in hospitals that lack control plans. In a context of intermediate tuberculosis (TB) incidence it is recommended to use only one test (either QFT or TST) in prevalence surveys or as pre-employment tests. Results will be useful to help implement TB infection control plans in hospitals where HCWs may be repeatedly exposed to unnoticed TB patients, and to inform the design of TB control policies.

Geographical Heterogeneity of Multiple Sclerosis Prevalence in France.

PubMed

Pivot, Diane; Debouverie, Marc; Grzebyk, Michel; Brassat, David; Clanet, Michel; Clavelou, Pierre; Confavreux, Christian; Edan, Gilles; Leray, Emmanuelle; Moreau, Thibault; Vukusic, Sandra; Hédelin, Guy; Guillemin, Francis

2016-01-01

Geographical variation in the prevalence of multiple sclerosis (MS) is controversial. Heterogeneity is important to acknowledge to adapt the provision of care within the healthcare system. We aimed to investigate differences in prevalence of MS in departments in the French territory. We estimated MS prevalence on October 31, 2004 in 21 administrative departments in France (22% of the metropolitan departments) by using multiple data sources: the main French health insurance systems, neurologist networks devoted to MS and the Technical Information Agency of Hospitalization. We used a spatial Bayesian approach based on estimating the number of MS cases from 2005 and 2008 capture-recapture studies to analyze differences in prevalence. The age- and sex-standardized prevalence of MS per 100,000 inhabitants ranged from 68.1 (95% credible interval 54.6, 84.4) in Hautes-Pyrénées (southwest France) to 296.5 (258.8, 338.9) in Moselle (northeast France). The greatest prevalence was in the northeast departments, and the other departments showed great variability. By combining multiple data sources into a spatial Bayesian model, we found heterogeneity in MS prevalence among the 21 departments of France, some with higher prevalence than anticipated from previous publications. No clear explanation related to health insurance coverage and hospital facilities can be advanced. Population migration, socioeconomic status of the population studied and environmental effects are suspected.

Bayesian modeling of Clostridium perfringens growth in beef-in-sauce products.

PubMed

Jaloustre, S; Cornu, M; Morelli, E; Noël, V; Delignette-Muller, M L

2011-04-01

Models on Clostridium perfringens growth which have been published to date have all been deterministic. A probabilistic model describing growth under non-isothermal conditions was thus proposed for predicting C. perfringens growth in beef-in-sauce products cooked and distributed in a French hospital. Model parameters were estimated from different types of data from various studies. A Bayesian approach was proposed to model the overall uncertainty regarding parameters and potential variability on the 'work to be done' (h(0)) during the germination, outgrowth and lag phase. Three models which differed according to their description of this parameter h(0) were tested. The model with inter-curve variability on h(0) was found to be the best one, on the basis of goodness-of-fit assessment and validation with literature data on results obtained under non-isothermal conditions. This model was used in two-dimensional Monte Carlo simulations to predict C. perfringens growth throughout the preparation of beef-in-sauce products, using temperature profiles recorded in a hospital kitchen. The median predicted growth was 7.8×10(-2) log(10) cfu·g(-1) (95% credibility interval [2.4×10(-2), 0.8]) despite the fact that for more than 50% of the registered temperature profiles cooling steps were longer than those required by French regulations. Copyright © 2010 Elsevier Ltd. All rights reserved.

A Bayesian Multi-Level Factor Analytic Model of Consumer Price Sensitivities across Categories

ERIC Educational Resources Information Center

Duvvuri, Sri Devi; Gruca, Thomas S.

2010-01-01

Identifying price sensitive consumers is an important problem in marketing. We develop a Bayesian multi-level factor analytic model of the covariation among household-level price sensitivities across product categories that are substitutes. Based on a multivariate probit model of category incidence, this framework also allows the researcher to…

What Is the Probability You Are a Bayesian?

ERIC Educational Resources Information Center

Wulff, Shaun S.; Robinson, Timothy J.

2014-01-01

Bayesian methodology continues to be widely used in statistical applications. As a result, it is increasingly important to introduce students to Bayesian thinking at early stages in their mathematics and statistics education. While many students in upper level probability courses can recite the differences in the Frequentist and Bayesian…

Using Alien Coins to Test Whether Simple Inference Is Bayesian

ERIC Educational Resources Information Center

Cassey, Peter; Hawkins, Guy E.; Donkin, Chris; Brown, Scott D.

2016-01-01

Reasoning and inference are well-studied aspects of basic cognition that have been explained as statistically optimal Bayesian inference. Using a simplified experimental design, we conducted quantitative comparisons between Bayesian inference and human inference at the level of individuals. In 3 experiments, with more than 13,000 participants, we…

Bayesian Correlation Analysis for Sequence Count Data

PubMed Central

Lau, Nelson; Perkins, Theodore J.

2016-01-01

Evaluating the similarity of different measured variables is a fundamental task of statistics, and a key part of many bioinformatics algorithms. Here we propose a Bayesian scheme for estimating the correlation between different entities’ measurements based on high-throughput sequencing data. These entities could be different genes or miRNAs whose expression is measured by RNA-seq, different transcription factors or histone marks whose expression is measured by ChIP-seq, or even combinations of different types of entities. Our Bayesian formulation accounts for both measured signal levels and uncertainty in those levels, due to varying sequencing depth in different experiments and to varying absolute levels of individual entities, both of which affect the precision of the measurements. In comparison with a traditional Pearson correlation analysis, we show that our Bayesian correlation analysis retains high correlations when measurement confidence is high, but suppresses correlations when measurement confidence is low—especially for entities with low signal levels. In addition, we consider the influence of priors on the Bayesian correlation estimate. Perhaps surprisingly, we show that naive, uniform priors on entities’ signal levels can lead to highly biased correlation estimates, particularly when different experiments have widely varying sequencing depths. However, we propose two alternative priors that provably mitigate this problem. We also prove that, like traditional Pearson correlation, our Bayesian correlation calculation constitutes a kernel in the machine learning sense, and thus can be used as a similarity measure in any kernel-based machine learning algorithm. We demonstrate our approach on two RNA-seq datasets and one miRNA-seq dataset. PMID:27701449

Quantifying Uncertainty in the Greenland Surface Mass Balance Elevation Feedback

NASA Astrophysics Data System (ADS)

Edwards, T.

2015-12-01

As the shape of the Greenland ice sheet responds to changes in surface mass balance (SMB) and dynamics, it affects the surface mass balance through the atmospheric lapse rate and by altering atmospheric circulation patterns. Positive degree day models include simplified representations of this feedback, but it is difficult to simulate with state-of-the-art models because it requires coupling of regional climate models with dynamical ice sheet models, which is technically challenging. This difficulty, along with the high computational expense of regional climate models, also drastically limits opportunities for exploring the impact of modelling uncertainties on sea level projections. We present a parameterisation of the SMB-elevation feedback in the MAR regional climate model that provides a far easier and quicker estimate than atmosphere-ice sheet model coupling, which can be used with any ice sheet model. This allows us to use ensembles of different parameter values and ice sheet models to assess the effect of uncertainty in the feedback and ice sheet model structure on future sea level projections. We take a Bayesian approach to uncertainty in the feedback parameterisation, scoring the results from multiple possible "SMB lapse rates" according to how well they reproduce a MAR simulation with altered ice sheet topography. We test the impact of the resulting parameterisation on sea level projections using five ice sheet models forced by MAR (in turned forced by two different global climate models) under the emissions scenario A1B. The estimated additional sea level contribution due to the SMB-elevation feedback is 4.3% at 2100 (95% credibility interval 1.8-6.9%), and 9.6% at 2200 (3.6-16.0%).

The Efficacy of Consensus Tree Methods for Summarizing Phylogenetic Relationships from a Posterior Sample of Trees Estimated from Morphological Data.

PubMed

O'Reilly, Joseph E; Donoghue, Philip C J

2018-03-01

Consensus trees are required to summarize trees obtained through MCMC sampling of a posterior distribution, providing an overview of the distribution of estimated parameters such as topology, branch lengths, and divergence times. Numerous consensus tree construction methods are available, each presenting a different interpretation of the tree sample. The rise of morphological clock and sampled-ancestor methods of divergence time estimation, in which times and topology are coestimated, has increased the popularity of the maximum clade credibility (MCC) consensus tree method. The MCC method assumes that the sampled, fully resolved topology with the highest clade credibility is an adequate summary of the most probable clades, with parameter estimates from compatible sampled trees used to obtain the marginal distributions of parameters such as clade ages and branch lengths. Using both simulated and empirical data, we demonstrate that MCC trees, and trees constructed using the similar maximum a posteriori (MAP) method, often include poorly supported and incorrect clades when summarizing diffuse posterior samples of trees. We demonstrate that the paucity of information in morphological data sets contributes to the inability of MCC and MAP trees to accurately summarise of the posterior distribution. Conversely, majority-rule consensus (MRC) trees represent a lower proportion of incorrect nodes when summarizing the same posterior samples of trees. Thus, we advocate the use of MRC trees, in place of MCC or MAP trees, in attempts to summarize the results of Bayesian phylogenetic analyses of morphological data.

The Efficacy of Consensus Tree Methods for Summarizing Phylogenetic Relationships from a Posterior Sample of Trees Estimated from Morphological Data

PubMed Central

O’Reilly, Joseph E; Donoghue, Philip C J

2018-01-01

Abstract Consensus trees are required to summarize trees obtained through MCMC sampling of a posterior distribution, providing an overview of the distribution of estimated parameters such as topology, branch lengths, and divergence times. Numerous consensus tree construction methods are available, each presenting a different interpretation of the tree sample. The rise of morphological clock and sampled-ancestor methods of divergence time estimation, in which times and topology are coestimated, has increased the popularity of the maximum clade credibility (MCC) consensus tree method. The MCC method assumes that the sampled, fully resolved topology with the highest clade credibility is an adequate summary of the most probable clades, with parameter estimates from compatible sampled trees used to obtain the marginal distributions of parameters such as clade ages and branch lengths. Using both simulated and empirical data, we demonstrate that MCC trees, and trees constructed using the similar maximum a posteriori (MAP) method, often include poorly supported and incorrect clades when summarizing diffuse posterior samples of trees. We demonstrate that the paucity of information in morphological data sets contributes to the inability of MCC and MAP trees to accurately summarise of the posterior distribution. Conversely, majority-rule consensus (MRC) trees represent a lower proportion of incorrect nodes when summarizing the same posterior samples of trees. Thus, we advocate the use of MRC trees, in place of MCC or MAP trees, in attempts to summarize the results of Bayesian phylogenetic analyses of morphological data. PMID:29106675

Association between the Severity of Influenza A(H7N9) Virus Infections and Length of the Incubation Period.

PubMed

Virlogeux, Victor; Yang, Juan; Fang, Vicky J; Feng, Luzhao; Tsang, Tim K; Jiang, Hui; Wu, Peng; Zheng, Jiandong; Lau, Eric H Y; Qin, Ying; Peng, Zhibin; Peiris, J S Malik; Yu, Hongjie; Cowling, Benjamin J

2016-01-01

In early 2013, a novel avian-origin influenza A(H7N9) virus emerged in China, and has caused sporadic human infections. The incubation period is the delay from infection until onset of symptoms, and varies from person to person. Few previous studies have examined whether the duration of the incubation period correlates with subsequent disease severity. We analyzed data of period of exposure on 395 human cases of laboratory-confirmed influenza A(H7N9) virus infection in China in a Bayesian framework using a Weibull distribution. We found a longer incubation period for the 173 fatal cases with a mean of 3.7 days (95% credibility interval, CrI: 3.4-4.1), compared to a mean of 3.3 days (95% CrI: 2.9-3.6) for the 222 non-fatal cases, and the difference in means was marginally significant at 0.47 days (95% CrI: -0.04, 0.99). There was a statistically significant correlation between a longer incubation period and an increased risk of death after adjustment for age, sex, geographical location and underlying medical conditions (adjusted odds ratio 1.70 per day increase in incubation period; 95% credibility interval 1.47-1.97). We found a significant association between a longer incubation period and a greater risk of death among human H7N9 cases. The underlying biological mechanisms leading to this association deserve further exploration.

Search for two-neutrino double electron capture of 124Xe with XENON100

NASA Astrophysics Data System (ADS)

Aprile, E.; Aalbers, J.; Agostini, F.; Alfonsi, M.; Amaro, F. D.; Anthony, M.; Arneodo, F.; Barrow, P.; Baudis, L.; Bauermeister, B.; Benabderrahmane, M. L.; Berger, T.; Breur, P. A.; Brown, A.; Brown, E.; Bruenner, S.; Bruno, G.; Budnik, R.; Bütikofer, L.; Calvén, J.; Cardoso, J. M. R.; Cervantes, M.; Cichon, D.; Coderre, D.; Colijn, A. P.; Conrad, J.; Cussonneau, J. P.; Decowski, M. P.; de Perio, P.; di Gangi, P.; di Giovanni, A.; Diglio, S.; Duchovni, E.; Fei, J.; Ferella, A. D.; Fieguth, A.; Franco, D.; Fulgione, W.; Gallo Rosso, A.; Galloway, M.; Gao, F.; Garbini, M.; Geis, C.; Goetzke, L. W.; Greene, Z.; Grignon, C.; Hasterok, C.; Hogenbirk, E.; Itay, R.; Kaminsky, B.; Kessler, G.; Kish, A.; Landsman, H.; Lang, R. F.; Lellouch, D.; Levinson, L.; Le Calloch, M.; Levy, C.; Lin, Q.; Lindemann, S.; Lindner, M.; Lopes, J. A. M.; Manfredini, A.; Marrodán Undagoitia, T.; Masbou, J.; Massoli, F. V.; Masson, D.; Mayani, D.; Meng, Y.; Messina, M.; Micheneau, K.; Miguez, B.; Molinario, A.; Murra, M.; Naganoma, J.; Ni, K.; Oberlack, U.; Orrigo, S. E. A.; Pakarha, P.; Pelssers, B.; Persiani, R.; Piastra, F.; Pienaar, J.; Piro, M.-C.; Plante, G.; Priel, N.; Rauch, L.; Reichard, S.; Reuter, C.; Rizzo, A.; Rosendahl, S.; Rupp, N.; Dos Santos, J. M. F.; Sartorelli, G.; Scheibelhut, M.; Schindler, S.; Schreiner, J.; Schumann, M.; Scotto Lavina, L.; Selvi, M.; Shagin, P.; Silva, M.; Simgen, H.; Sivers, M. V.; Stein, A.; Thers, D.; Tiseni, A.; Trinchero, G.; Tunnell, C. D.; Wall, R.; Wang, H.; Weber, M.; Wei, Y.; Weinheimer, C.; Wulf, J.; Zhang, Y.; Xenon Collaboration

2017-02-01

Two-neutrino double electron capture is a rare nuclear decay where two electrons are simultaneously captured from the atomic shell. For 124Xe this process has not yet been observed and its detection would provide a new reference for nuclear matrix element calculations. We have conducted a search for two-neutrino double electron capture from the K shell of 124Xe using 7636 kg d of data from the XENON100 dark matter detector. Using a Bayesian analysis we observed no significant excess above background, leading to a lower 90% credibility limit on the half-life T1 /2>6.5 ×1020 yr. We have also evaluated the sensitivity of the XENON1T experiment, which is currently being commissioned, and found a sensitivity of T1 /2>6.1 ×1022 yr after an exposure of 2 t yr .

What’s Driving Uncertainty? The Model or the Model Parameters (What’s Driving Uncertainty? The influences of model and model parameters in data analysis)

DOE PAGES

Anderson-Cook, Christine Michaela

2017-03-01

Here, one of the substantial improvements to the practice of data analysis in recent decades is the change from reporting just a point estimate for a parameter or characteristic, to now including a summary of uncertainty for that estimate. Understanding the precision of the estimate for the quantity of interest provides better understanding of what to expect and how well we are able to predict future behavior from the process. For example, when we report a sample average as an estimate of the population mean, it is good practice to also provide a confidence interval (or credible interval, if youmore » are doing a Bayesian analysis) to accompany that summary. This helps to calibrate what ranges of values are reasonable given the variability observed in the sample and the amount of data that were included in producing the summary.« less

Search for a low-mass neutral Higgs boson with suppressed couplings to fermions using events with multiphoton final states

NASA Astrophysics Data System (ADS)

Aaltonen, T.; Amerio, S.; Amidei, D.; Anastassov, A.; Annovi, A.; Antos, J.; Apollinari, G.; Appel, J. A.; Arisawa, T.; Artikov, A.; Asaadi, J.; Ashmanskas, W.; Auerbach, B.; Aurisano, A.; Azfar, F.; Badgett, W.; Bae, T.; Barbaro-Galtieri, A.; Barnes, V. E.; Barnett, B. A.; Barria, P.; Bartos, P.; Bauce, M.; Bedeschi, F.; Behari, S.; Bellettini, G.; Bellinger, J.; Benjamin, D.; Beretvas, A.; Bhatti, A.; Bland, K. R.; Blumenfeld, B.; Bocci, A.; Bodek, A.; Bortoletto, D.; Boudreau, J.; Boveia, A.; Brigliadori, L.; Bromberg, C.; Brucken, E.; Budagov, J.; Budd, H. S.; Burkett, K.; Busetto, G.; Bussey, P.; Butti, P.; Buzatu, A.; Calamba, A.; Camarda, S.; Campanelli, M.; Canelli, F.; Carls, B.; Carlsmith, D.; Carosi, R.; Carrillo, S.; Casal, B.; Casarsa, M.; Castro, A.; Catastini, P.; Cauz, D.; Cavaliere, V.; Cerri, A.; Cerrito, L.; Chen, Y. C.; Chertok, M.; Chiarelli, G.; Chlachidze, G.; Cho, K.; Chokheli, D.; Clark, A.; Clarke, C.; Convery, M. E.; Conway, J.; Corbo, M.; Cordelli, M.; Cox, C. A.; Cox, D. J.; Cremonesi, M.; Cruz, D.; Cuevas, J.; Culbertson, R.; d'Ascenzo, N.; Datta, M.; de Barbaro, P.; Demortier, L.; Deninno, M.; D'Errico, M.; Devoto, F.; Di Canto, A.; Di Ruzza, B.; Dittmann, J. R.; Donati, S.; D'Onofrio, M.; Dorigo, M.; Driutti, A.; Ebina, K.; Edgar, R.; Erbacher, R.; Errede, S.; Esham, B.; Farrington, S.; Fernández Ramos, J. P.; Field, R.; Flanagan, G.; Forrest, R.; Franklin, M.; Freeman, J. C.; Frisch, H.; Funakoshi, Y.; Galloni, C.; Garfinkel, A. F.; Garosi, P.; Gerberich, H.; Gerchtein, E.; Giagu, S.; Giakoumopoulou, V.; Gibson, K.; Ginsburg, C. M.; Giokaris, N.; Giromini, P.; Glagolev, V.; Glenzinski, D.; Gold, M.; Goldin, D.; Golossanov, A.; Gomez, G.; Gomez-Ceballos, G.; Goncharov, M.; González López, O.; Gorelov, I.; Goshaw, A. T.; Goulianos, K.; Gramellini, E.; Grosso-Pilcher, C.; Guimaraes da Costa, J.; Hahn, S. R.; Han, J. Y.; Happacher, F.; Hara, K.; Hare, M.; Harr, R. F.; Harrington-Taber, T.; Hatakeyama, K.; Hays, C.; Heinrich, J.; Herndon, M.; Hocker, A.; Hong, Z.; Hopkins, W.; Hou, S.; Hughes, R. E.; Husemann, U.; Hussein, M.; Huston, J.; Introzzi, G.; Iori, M.; Ivanov, A.; James, E.; Jang, D.; Jayatilaka, B.; Jeon, E. J.; Jindariani, S.; Jones, M.; Joo, K. K.; Jun, S. Y.; Junk, T. R.; Kambeitz, M.; Kamon, T.; Karchin, P. E.; Kasmi, A.; Kato, Y.; Ketchum, W.; Keung, J.; Kilminster, B.; Kim, D. H.; Kim, H. S.; Kim, J. E.; Kim, M. J.; Kim, S. H.; Kim, S. B.; Kim, Y. J.; Kim, Y. K.; Kimura, N.; Kirby, M.; Knoepfel, K.; Kondo, K.; Kong, D. J.; Konigsberg, J.; Kotwal, A. V.; Kreps, M.; Kroll, J.; Kruse, M.; Kuhr, T.; Kurata, M.; Laasanen, A. T.; Lammel, S.; Lancaster, M.; Lannon, K.; Latino, G.; Lee, H. S.; Lee, J. S.; Leo, S.; Leone, S.; Lewis, J. D.; Limosani, A.; Lipeles, E.; Lister, A.; Liu, Q.; Liu, T.; Lockwitz, S.; Loginov, A.; Lucchesi, D.; Lucà, A.; Lueck, J.; Lujan, P.; Lukens, P.; Lungu, G.; Lys, J.; Lysak, R.; Madrak, R.; Maestro, P.; Malik, S.; Manca, G.; Manousakis-Katsikakis, A.; Marchese, L.; Margaroli, F.; Marino, P.; Matera, K.; Mattson, M. E.; Mazzacane, A.; Mazzanti, P.; McNulty, R.; Mehta, A.; Mehtala, P.; Mesropian, C.; Miao, T.; Mietlicki, D.; Mitra, A.; Miyake, H.; Moed, S.; Moggi, N.; Moon, C. S.; Moore, R.; Morello, M. J.; Mukherjee, A.; Muller, Th.; Murat, P.; Mussini, M.; Nachtman, J.; Nagai, Y.; Naganoma, J.; Nakano, I.; Napier, A.; Nett, J.; Nigmanov, T.; Nodulman, L.; Noh, S. Y.; Norniella, O.; Oakes, L.; Oh, S. H.; Oh, Y. D.; Okusawa, T.; Orava, R.; Ortolan, L.; Pagliarone, C.; Palencia, E.; Palni, P.; Papadimitriou, V.; Parker, W.; Pauletta, G.; Paulini, M.; Paus, C.; Phillips, T. J.; Piacentino, G.; Pianori, E.; Pilot, J.; Pitts, K.; Plager, C.; Pondrom, L.; Poprocki, S.; Potamianos, K.; Pranko, A.; Prokoshin, F.; Ptohos, F.; Punzi, G.; Redondo Fernández, I.; Renton, P.; Rescigno, M.; Rimondi, F.; Ristori, L.; Robson, A.; Rodriguez, T.; Rolli, S.; Ronzani, M.; Roser, R.; Rosner, J. L.; Ruffini, F.; Ruiz, A.; Russ, J.; Rusu, V.; Sakumoto, W. K.; Sakurai, Y.; Santi, L.; Sato, K.; Saveliev, V.; Savoy-Navarro, A.; Schlabach, P.; Schmidt, E. E.; Schwarz, T.; Scodellaro, L.; Scuri, F.; Seidel, S.; Seiya, Y.; Semenov, A.; Sforza, F.; Shalhout, S. Z.; Shears, T.; Shepard, P. F.; Shimojima, M.; Shochet, M.; Shreyber-Tecker, I.; Simonenko, A.; Sliwa, K.; Smith, J. R.; Snider, F. D.; Song, H.; Sorin, V.; St. Denis, R.; Stancari, M.; Stentz, D.; Strologas, J.; Sudo, Y.; Sukhanov, A.; Suslov, I.; Takemasa, K.; Takeuchi, Y.; Tang, J.; Tecchio, M.; Teng, P. K.; Thom, J.; Thomson, E.; Thukral, V.; Toback, D.; Tokar, S.; Tollefson, K.; Tomura, T.; Tonelli, D.; Torre, S.; Torretta, D.; Totaro, P.; Trovato, M.; Ukegawa, F.; Uozumi, S.; Vázquez, F.; Velev, G.; Vellidis, C.; Vernieri, C.; Vidal, M.; Vilar, R.; Vizán, J.; Vogel, M.; Volpi, G.; Wagner, P.; Wallny, R.; Wang, S. M.; Waters, D.; Wester, W. C.; Whiteson, D.; Wicklund, A. B.; Wilbur, S.; Williams, H. H.; Wilson, J. S.; Wilson, P.; Winer, B. L.; Wittich, P.; Wolbers, S.; Wolfe, H.; Wright, T.; Wu, X.; Wu, Z.; Yamamoto, K.; Yamato, D.; Yang, T.; Yang, U. K.; Yang, Y. C.; Yao, W.-M.; Yeh, G. P.; Yi, K.; Yoh, J.; Yorita, K.; Yoshida, T.; Yu, G. B.; Yu, I.; Zanetti, A. M.; Zeng, Y.; Zhou, C.; Zucchelli, S.; CDF Collaboration

2016-06-01

A search for a Higgs boson with suppressed couplings to fermions, hf, assumed to be the neutral, lower-mass partner of the Higgs boson discovered at the Large Hadron Collider, is reported. Such a Higgs boson could exist in extensions of the standard model with two Higgs doublets, and could be produced via p p ¯→H±hf→W*hfhf→4 γ +X , where H± is a charged Higgs boson. This analysis uses all events with at least three photons in the final state from proton-antiproton collisions at a center-of-mass energy of 1.96 TeV collected by the Collider Detector at Fermilab, corresponding to an integrated luminosity of 9.2 fb-1. No evidence of a signal is observed in the data. Values of Higgs-boson masses between 10 and 100 GeV /c2 are excluded at 95% Bayesian credibility.

A Cross-Classified CFA-MTMM Model for Structurally Different and Nonindependent Interchangeable Methods.

PubMed

Koch, Tobias; Schultze, Martin; Jeon, Minjeong; Nussbeck, Fridtjof W; Praetorius, Anna-Katharina; Eid, Michael

2016-01-01

Multirater (multimethod, multisource) studies are increasingly applied in psychology. Eid and colleagues (2008) proposed a multilevel confirmatory factor model for multitrait-multimethod (MTMM) data combining structurally different and multiple independent interchangeable methods (raters). In many studies, however, different interchangeable raters (e.g., peers, subordinates) are asked to rate different targets (students, supervisors), leading to violations of the independence assumption and to cross-classified data structures. In the present work, we extend the ML-CFA-MTMM model by Eid and colleagues (2008) to cross-classified multirater designs. The new C4 model (Cross-Classified CTC[M-1] Combination of Methods) accounts for nonindependent interchangeable raters and enables researchers to explicitly model the interaction between targets and raters as a latent variable. Using a real data application, it is shown how credibility intervals of model parameters and different variance components can be obtained using Bayesian estimation techniques.

How to Develop and Interpret a Credibility Assessment of Numerical Models for Human Research: NASA-STD-7009 Demystified

NASA Technical Reports Server (NTRS)

Nelson, Emily S.; Mulugeta, Lealem; Walton, Marlei; Myers, Jerry G.

2014-01-01

In the wake of the Columbia accident, the NASA-STD-7009 [1] credibility assessment was developed as a unifying platform to describe model credibility and the uncertainties in its modeling predictions. This standard is now being adapted by NASAs Human Research Program to cover a wide range of numerical models for human research. When used properly, the standard can improve the process of code development by encouraging the use of best practices. It can also give management more insight in making informed decisions through a better understanding of the models capabilities and limitations.To a newcomer, the abstractions presented in NASA-STD-7009 and the sheer volume of information that must be absorbed can be overwhelming. This talk is aimed at describing the credibility assessment, which is the heart of the standard, in plain terms. It will outline how to develop a credibility assessment under the standard. It will also show how to quickly interpret the graphs and tables that result from the assessment and how to drill down from the top-level view to the foundation of the assessment. Finally, it will highlight some of the resources that are available for further study.

Bayesian Group Bridge for Bi-level Variable Selection.

PubMed

Mallick, Himel; Yi, Nengjun

2017-06-01

A Bayesian bi-level variable selection method (BAGB: Bayesian Analysis of Group Bridge) is developed for regularized regression and classification. This new development is motivated by grouped data, where generic variables can be divided into multiple groups, with variables in the same group being mechanistically related or statistically correlated. As an alternative to frequentist group variable selection methods, BAGB incorporates structural information among predictors through a group-wise shrinkage prior. Posterior computation proceeds via an efficient MCMC algorithm. In addition to the usual ease-of-interpretation of hierarchical linear models, the Bayesian formulation produces valid standard errors, a feature that is notably absent in the frequentist framework. Empirical evidence of the attractiveness of the method is illustrated by extensive Monte Carlo simulations and real data analysis. Finally, several extensions of this new approach are presented, providing a unified framework for bi-level variable selection in general models with flexible penalties.

Bayesian Fundamentalism or Enlightenment? On the explanatory status and theoretical contributions of Bayesian models of cognition.

PubMed

Jones, Matt; Love, Bradley C

2011-08-01

The prominence of Bayesian modeling of cognition has increased recently largely because of mathematical advances in specifying and deriving predictions from complex probabilistic models. Much of this research aims to demonstrate that cognitive behavior can be explained from rational principles alone, without recourse to psychological or neurological processes and representations. We note commonalities between this rational approach and other movements in psychology - namely, Behaviorism and evolutionary psychology - that set aside mechanistic explanations or make use of optimality assumptions. Through these comparisons, we identify a number of challenges that limit the rational program's potential contribution to psychological theory. Specifically, rational Bayesian models are significantly unconstrained, both because they are uninformed by a wide range of process-level data and because their assumptions about the environment are generally not grounded in empirical measurement. The psychological implications of most Bayesian models are also unclear. Bayesian inference itself is conceptually trivial, but strong assumptions are often embedded in the hypothesis sets and the approximation algorithms used to derive model predictions, without a clear delineation between psychological commitments and implementational details. Comparing multiple Bayesian models of the same task is rare, as is the realization that many Bayesian models recapitulate existing (mechanistic level) theories. Despite the expressive power of current Bayesian models, we argue they must be developed in conjunction with mechanistic considerations to offer substantive explanations of cognition. We lay out several means for such an integration, which take into account the representations on which Bayesian inference operates, as well as the algorithms and heuristics that carry it out. We argue this unification will better facilitate lasting contributions to psychological theory, avoiding the pitfalls that have plagued previous theoretical movements.

A close look at why one social norms campaign did not reduce student drinking.

PubMed

Thombs, Dennis L; Dotterer, Scott; Olds, R Scott; Sharp, Katherine E; Raub, Carrie Giovannone

2004-01-01

The authors examined 3 possible explanations for the failure of a social norms campaign at a large public university. They administered an anonymous survey to 2 random samples of undergraduate classes: a baseline assessment of 616 students before the campaign's implementation and a follow-up survey of 723 students 4 academic years later. At follow-up, 66.5% of the students were aware of the campaign, yet the survey revealed no reduction in perceived drinking norms or alcohol use in this group. An analysis of the postcampaign sample revealed that (1) a majority of the students did not find the statistics used in the campaign messages credible, (2) higher levels of alcohol use predicted lower levels of perceived campaign credibility, and (3) only 38.5% of the students understood the campaign's intended purpose. If they are to influence personally relevant drinking norms, these campaigns must undergo further development to enhance message credibility and participants' understanding.

A Bayesian Approach for Analyzing Longitudinal Structural Equation Models

ERIC Educational Resources Information Center

Song, Xin-Yuan; Lu, Zhao-Hua; Hser, Yih-Ing; Lee, Sik-Yum

2011-01-01

This article considers a Bayesian approach for analyzing a longitudinal 2-level nonlinear structural equation model with covariates, and mixed continuous and ordered categorical variables. The first-level model is formulated for measures taken at each time point nested within individuals for investigating their characteristics that are dynamically…

The attractiveness-positivity link: Let's contextualize it.

PubMed

Mello, Joana; Garcia-Marques, Teresa

2018-02-27

The statement "what is beautiful is good" reflects a persuasive heuristic that may be supported either by a general association of attractiveness with positivity or by a specific association with the perceived credibility of an attractive source. In one study (N = 58), we approach this question using an explicit and an implicit measure (Stroop Task) to assess whether attractiveness is more likely associated with valenced words when these are related (vs. unrelated) to credibility. Results show that this effect occurs but only for the implicit measure. When the word-face associations were made at an explicit level, we found a general association between positivity and attractiveness, unrestricted to the dimension of credibility. We discuss how these results inform about attractiveness as a shortcut to judgments of validity.

Spatial heterogeneity and risk factors for stunting among children under age five in Ethiopia: A Bayesian geo-statistical model.

PubMed

Hagos, Seifu; Hailemariam, Damen; WoldeHanna, Tasew; Lindtjørn, Bernt

2017-01-01

Understanding the spatial distribution of stunting and underlying factors operating at meso-scale is of paramount importance for intervention designing and implementations. Yet, little is known about the spatial distribution of stunting and some discrepancies are documented on the relative importance of reported risk factors. Therefore, the present study aims at exploring the spatial distribution of stunting at meso- (district) scale, and evaluates the effect of spatial dependency on the identification of risk factors and their relative contribution to the occurrence of stunting and severe stunting in a rural area of Ethiopia. A community based cross sectional study was conducted to measure the occurrence of stunting and severe stunting among children aged 0-59 months. Additionally, we collected relevant information on anthropometric measures, dietary habits, parent and child-related demographic and socio-economic status. Latitude and longitude of surveyed households were also recorded. Local Anselin Moran's I was calculated to investigate the spatial variation of stunting prevalence and identify potential local pockets (hotspots) of high prevalence. Finally, we employed a Bayesian geo-statistical model, which accounted for spatial dependency structure in the data, to identify potential risk factors for stunting in the study area. Overall, the prevalence of stunting and severe stunting in the district was 43.7% [95%CI: 40.9, 46.4] and 21.3% [95%CI: 19.5, 23.3] respectively. We identified statistically significant clusters of high prevalence of stunting (hotspots) in the eastern part of the district and clusters of low prevalence (cold spots) in the western. We found out that the inclusion of spatial structure of the data into the Bayesian model has shown to improve the fit for stunting model. The Bayesian geo-statistical model indicated that the risk of stunting increased as the child's age increased (OR 4.74; 95% Bayesian credible interval [BCI]:3.35-6.58) and among boys (OR 1.28; 95%BCI; 1.12-1.45). However, maternal education and household food security were found to be protective against stunting and severe stunting. Stunting prevalence may vary across space at different scale. For this, it's important that nutrition studies and, more importantly, control interventions take into account this spatial heterogeneity in the distribution of nutritional deficits and their underlying associated factors. The findings of this study also indicated that interventions integrating household food insecurity in nutrition programs in the district might help to avert the burden of stunting.

Clinic accessibility and clinic-level predictors of the geographic variation in 2009 pandemic influenza vaccine coverage in Montreal, Canada

PubMed Central

Charland, Katia M; de Montigny, Luc; Brownstein, John S; Buckeridge, David L

2014-01-01

Background Nineteen mass vaccination clinics were established in Montreal, Canada, as part of the 2009 influenza A/H1N1p vaccination campaign. Although approximately 50% of the population was vaccinated, there was a considerable variation in clinic performance and community vaccine coverage. Objective To identify community- and clinic-level predictors of vaccine uptake, while accounting for the accessibility of clinics from the community of residence. Methods All records of influenza A/H1N1p vaccinations administered in Montreal were obtained from a vaccine registry. Multivariable regression models, specifically Bayesian gravity models, were used to assess the relationship between vaccination rates and clinic accessibility, clinic-level factors, and community-level factors. Results Relative risks compare the vaccination rates at the variable's upper quartile to the lower quartile. All else being equal, clinics in areas with high violent crime rates, high residential density, and high levels of material deprivation tended to perform poorly (adjusted relative risk [ARR]: 0·917, 95% CI [credible interval]: 0·915, 0·918; ARR: 0·663, 95% CI: 0·660, 0·666, ARR: 0·649, 95% CI: 0·645, 0·654, respectively). Even after controlling for accessibility and clinic-level predictors, communities with a greater proportion of new immigrants and families living below the poverty level tended to have lower rates (ARR: 0·936, 95% CI: 0·913, 0·959; ARR: 0·918, 95% CI: 0·893, 0·946, respectively), while communities with a higher proportion speaking English or French tended to have higher rates (ARR: 1·034, 95% CI: 1·012, 1·059). Conclusion In planning future mass vaccination campaigns, the gravity model could be used to compare expected vaccine uptake for different clinic location strategies. PMID:24382000

Clinic accessibility and clinic-level predictors of the geographic variation in 2009 pandemic influenza vaccine coverage in Montreal, Canada.

PubMed

Charland, Katia M; de Montigny, Luc; Brownstein, John S; Buckeridge, David L

2014-05-01

Nineteen mass vaccination clinics were established in Montreal, Canada, as part of the 2009 influenza A/H1N1p vaccination campaign. Although approximately 50% of the population was vaccinated, there was a considerable variation in clinic performance and community vaccine coverage. To identify community- and clinic-level predictors of vaccine uptake, while accounting for the accessibility of clinics from the community of residence. All records of influenza A/H1N1p vaccinations administered in Montreal were obtained from a vaccine registry. Multivariable regression models, specifically Bayesian gravity models, were used to assess the relationship between vaccination rates and clinic accessibility, clinic-level factors, and community-level factors. Relative risks compare the vaccination rates at the variable's upper quartile to the lower quartile. All else being equal, clinics in areas with high violent crime rates, high residential density, and high levels of material deprivation tended to perform poorly (adjusted relative risk [ARR]: 0·917, 95% CI [credible interval]: 0·915, 0·918; ARR: 0·663, 95% CI: 0·660, 0·666, ARR: 0·649, 95% CI: 0·645, 0·654, respectively). Even after controlling for accessibility and clinic-level predictors, communities with a greater proportion of new immigrants and families living below the poverty level tended to have lower rates (ARR: 0·936, 95% CI: 0·913, 0·959; ARR: 0·918, 95% CI: 0·893, 0·946, respectively), while communities with a higher proportion speaking English or French tended to have higher rates (ARR: 1·034, 95% CI: 1·012, 1·059). In planning future mass vaccination campaigns, the gravity model could be used to compare expected vaccine uptake for different clinic location strategies. © 2014 The Authors. Influenza and Other Respiratory Viruses Published by John Wiley & Sons Ltd.

Moving beyond qualitative evaluations of Bayesian models of cognition.

PubMed

Hemmer, Pernille; Tauber, Sean; Steyvers, Mark

2015-06-01

Bayesian models of cognition provide a powerful way to understand the behavior and goals of individuals from a computational point of view. Much of the focus in the Bayesian cognitive modeling approach has been on qualitative model evaluations, where predictions from the models are compared to data that is often averaged over individuals. In many cognitive tasks, however, there are pervasive individual differences. We introduce an approach to directly infer individual differences related to subjective mental representations within the framework of Bayesian models of cognition. In this approach, Bayesian data analysis methods are used to estimate cognitive parameters and motivate the inference process within a Bayesian cognitive model. We illustrate this integrative Bayesian approach on a model of memory. We apply the model to behavioral data from a memory experiment involving the recall of heights of people. A cross-validation analysis shows that the Bayesian memory model with inferred subjective priors predicts withheld data better than a Bayesian model where the priors are based on environmental statistics. In addition, the model with inferred priors at the individual subject level led to the best overall generalization performance, suggesting that individual differences are important to consider in Bayesian models of cognition.

Effects of argument quality, source credibility and self-reported diabetes knowledge on message attitudes: an experiment using diabetes related messages.

PubMed

Lin, Tung-Cheng; Hwang, Lih-Lian; Lai, Yung-Jye

2017-05-17

Previous studies have reported that credibility and content (argument quality) are the most critical factors affecting the quality of health information and its acceptance and use; however, this causal relationship merits further investigation in the context of health education. Moreover, message recipients' prior knowledge may moderate these relationships. This study used the elaboration likelihood model to determine the main effects of argument quality, source credibility and the moderating effect of self-reported diabetes knowledge on message attitudes. A between-subjects experimental design using an educational message concerning diabetes for manipulation was applied to validate the effects empirically. A total of 181 participants without diabetes were recruited from the Department of Health, Taipei City Government. Four group messages were manipulated in terms of argument quality (high and low) × source credibility (high and low). Argument quality and source credibility of health information significantly influenced the attitude of message recipients. The participants with high self-reported knowledge participants exhibited significant disapproval for messages with low argument quality. Effective health information should provide objective descriptions and cite reliable sources; in addition, it should provide accurate, customised messages for recipients who have high background knowledge level and ability to discern message quality. © 2017 Health Libraries Group Health Information & Libraries Journal.

An enhanced export coefficient based optimization model for supporting agricultural nonpoint source pollution mitigation under uncertainty.

PubMed

Rong, Qiangqiang; Cai, Yanpeng; Chen, Bing; Yue, Wencong; Yin, Xin'an; Tan, Qian

2017-02-15

In this research, an export coefficient based dual inexact two-stage stochastic credibility constrained programming (ECDITSCCP) model was developed through integrating an improved export coefficient model (ECM), interval linear programming (ILP), fuzzy credibility constrained programming (FCCP) and a fuzzy expected value equation within a general two stage programming (TSP) framework. The proposed ECDITSCCP model can effectively address multiple uncertainties expressed as random variables, fuzzy numbers, pure and dual intervals. Also, the model can provide a direct linkage between pre-regulated management policies and the associated economic implications. Moreover, the solutions under multiple credibility levels can be obtained for providing potential decision alternatives for decision makers. The proposed model was then applied to identify optimal land use structures for agricultural NPS pollution mitigation in a representative upstream subcatchment of the Miyun Reservoir watershed in north China. Optimal solutions of the model were successfully obtained, indicating desired land use patterns and nutrient discharge schemes to get a maximum agricultural system benefits under a limited discharge permit. Also, numerous results under multiple credibility levels could provide policy makers with several options, which could help get an appropriate balance between system benefits and pollution mitigation. The developed ECDITSCCP model can be effectively applied to addressing the uncertain information in agricultural systems and shows great applicability to the land use adjustment for agricultural NPS pollution mitigation. Copyright © 2016 Elsevier B.V. All rights reserved.

Diagnostic accuracy of a bayesian latent group analysis for the detection of malingering-related poor effort.

PubMed

Ortega, Alonso; Labrenz, Stephan; Markowitsch, Hans J; Piefke, Martina

2013-01-01

In the last decade, different statistical techniques have been introduced to improve assessment of malingering-related poor effort. In this context, we have recently shown preliminary evidence that a Bayesian latent group model may help to optimize classification accuracy using a simulation research design. In the present study, we conducted two analyses. Firstly, we evaluated how accurately this Bayesian approach can distinguish between participants answering in an honest way (honest response group) and participants feigning cognitive impairment (experimental malingering group). Secondly, we tested the accuracy of our model in the differentiation between patients who had real cognitive deficits (cognitively impaired group) and participants who belonged to the experimental malingering group. All Bayesian analyses were conducted using the raw scores of a visual recognition forced-choice task (2AFC), the Test of Memory Malingering (TOMM, Trial 2), and the Word Memory Test (WMT, primary effort subtests). The first analysis showed 100% accuracy for the Bayesian model in distinguishing participants of both groups with all effort measures. The second analysis showed outstanding overall accuracy of the Bayesian model when estimates were obtained from the 2AFC and the TOMM raw scores. Diagnostic accuracy of the Bayesian model diminished when using the WMT total raw scores. Despite, overall diagnostic accuracy can still be considered excellent. The most plausible explanation for this decrement is the low performance in verbal recognition and fluency tasks of some patients of the cognitively impaired group. Additionally, the Bayesian model provides individual estimates, p(zi |D), of examinees' effort levels. In conclusion, both high classification accuracy levels and Bayesian individual estimates of effort may be very useful for clinicians when assessing for effort in medico-legal settings.

Optimal Cutoff and Accuracy of an IgM Enzyme-Linked Immunosorbent Assay for Diagnosis of Acute Scrub Typhus in Northern Thailand: an Alternative Reference Method to the IgM Immunofluorescence Assay

PubMed Central

Blacksell, Stuart D.; Tanganuchitcharnchai, Ampai; Jintaworn, Suthatip; Kantipong, Pacharee; Richards, Allen L.; Day, Nicholas P. J.

2016-01-01

The enzyme-linked immunosorbent assay (ELISA) has been proposed as an alternative serologic diagnostic test to the indirect immunofluorescence assay (IFA) for scrub typhus. Here, we systematically determine the optimal sample dilution and cutoff optical density (OD) and estimate the accuracy of IgM ELISA using Bayesian latent class models (LCMs). Data from 135 patients with undifferentiated fever were reevaluated using Bayesian LCMs. Every patient was evaluated for the presence of an eschar and tested with a blood culture for Orientia tsutsugamushi, three different PCR assays, and an IgM IFA. The IgM ELISA was performed for every sample at sample dilutions from 1:100 to 1:102,400 using crude whole-cell antigens of the Karp, Kato, and Gilliam strains of O. tsutsugamushi developed by the Naval Medical Research Center. We used Bayesian LCMs to generate unbiased receiver operating characteristic curves and found that the sample dilution of 1:400 was optimal for the IgM ELISA. With the optimal cutoff OD of 1.474 at a sample dilution of 1:400, the IgM ELISA had a sensitivity of 85.7% (95% credible interval [CrI], 77.4% to 86.7%) and a specificity of 98.1% (95% CrI, 97.2% to 100%) using paired samples. For the ELISA, the OD could be determined objectively and quickly, in contrast to the reading of IFA slides, which was both subjective and labor-intensive. The IgM ELISA for scrub typhus has high diagnostic accuracy and is less subjective than the IgM IFA. We suggest that the IgM ELISA may be used as an alternative reference test to the IgM IFA for the serological diagnosis of scrub typhus. PMID:27008880

Incremental Value (Bayesian Framework) of Thoracic Ultrasonography over Thoracic Auscultation for Diagnosis of Bronchopneumonia in Preweaned Dairy Calves.

PubMed

Buczinski, S; Ménard, J; Timsit, E

2016-07-01

Thoracic ultrasonography (TUS) is a specific and relatively sensitive method to diagnose bronchopneumonia (BP) in dairy calves. Unfortunately, as it requires specific training and equipment, veterinarians typically base their diagnosis on thoracic auscultation (AUSC), which is rapid and easy to perform. We hypothesized that the use of TUS, in addition to AUSC, can significantly increase accuracy of BP diagnosis. Therefore, the objectives were to (i) determine the incremental value of TUS over AUSC for diagnosis of BP in preweaned dairy calves and (ii) assess diagnostic accuracy of AUSC. Two hundred and nine dairy calves (<1 month of age) were enrolled in this cross-sectional study. Prospective cross-sectional study. All calves from a veal calves unit were examined (independent operators) using the Wisconsin Calf Respiratory Scoring Criteria (CRSC), AUSC, and TUS. A Bayesian latent class approach was used to estimate the incremental value of AUSC over TUS (integrated discrimination improvement [IDI]) and the diagnostic accuracy of AUSC. Abnormal CRSC, AUSC, and TUS were recorded in 3.3, 53.1, and 23.9% of calves, respectively. AUSC was sensitive (72.9%; 95% Bayesian credible interval [BCI]: 50.1-96.4%), but not specific (53.3%; 95% BCI: 43.3-64.0%) to diagnose BP. Compared to AUSC, TUS was more specific (92.9%; 95% BCI: 86.5-97.1%), but had similar sensitivity (76.5%; 95% BCI: 60.2-88.8%). The incremental value of TUS over AUSC was high (IDI = 43.7%; 5% BCI: 22.0-63.0%) significantly improving proportions of sick and healthy calves appropriately classified. The use of TUS over AUSC significantly improved accuracy of BP diagnosis in dairy calves. Copyright © 2016 The Authors. Journal of Veterinary Internal Medicine published by Wiley Periodicals, Inc. on behalf of the American College of Veterinary Internal Medicine.

Variation in ventilation time after coronary artery bypass grafting: an analysis from the society of thoracic surgeons adult cardiac surgery database.

PubMed

Jacobs, Jeffrey P; He, Xia; O'Brien, Sean M; Welke, Karl F; Filardo, Giovanni; Han, Jane M; Ferraris, Victor A; Prager, Richard L; Shahian, David M

2013-09-01

Short postoperative ventilation times are accepted as a marker of quality. This analysis assesses center level variation in postoperative ventilation time in a subset of patients undergoing isolated coronary artery bypass grafting (CABG). In 2009 and 2010, 325,129 patients in the STS Adult Cardiac Surgery Database underwent isolated CABG. Patients were excluded if they were intubated before entering the operating room, required ventilation for greater than 24 hours, or had missing data on key covariates. The final study cohort was 274,231 isolated CABG patients from 1,008 centers. Bayesian hierarchical models were used to assess between-center variation in ventilation time and to explore the effect of center-level covariates. Analyses were performed with and without adjusting for case mix. After adjusting for case mix, the ratio of median ventilator time at the 90th percentile of the center-level distribution compared with the tenth percentile was 9.0:5.0=1.8 (95% credible interval: 1.79 to 1.85). This ratio illustrates the scale of between-center differences: centers above the 90th percentile have a ventilation time of at least 1.8 times that of centers below the tenth percentile. Smaller hospital volume, presence of a residency program, and some census regions were associated with longer ventilation times. After adjustment for severity of illness, substantial inter-center variation exists in postoperative ventilation time in this subset of patients undergoing isolated CABG. This finding represents an opportunity for multi-institutional quality improvement initiatives designed to limit variations in ventilator management and achieve the shortest possible ventilation times for all patients, thus benefiting both clinical outcomes and resource utilization. Copyright © 2013 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Statistical surrogate models for prediction of high-consequence climate change.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Constantine, Paul; Field, Richard V., Jr.; Boslough, Mark Bruce Elrick

2011-09-01

In safety engineering, performance metrics are defined using probabilistic risk assessments focused on the low-probability, high-consequence tail of the distribution of possible events, as opposed to best estimates based on central tendencies. We frame the climate change problem and its associated risks in a similar manner. To properly explore the tails of the distribution requires extensive sampling, which is not possible with existing coupled atmospheric models due to the high computational cost of each simulation. We therefore propose the use of specialized statistical surrogate models (SSMs) for the purpose of exploring the probability law of various climate variables of interest.more » A SSM is different than a deterministic surrogate model in that it represents each climate variable of interest as a space/time random field. The SSM can be calibrated to available spatial and temporal data from existing climate databases, e.g., the Program for Climate Model Diagnosis and Intercomparison (PCMDI), or to a collection of outputs from a General Circulation Model (GCM), e.g., the Community Earth System Model (CESM) and its predecessors. Because of its reduced size and complexity, the realization of a large number of independent model outputs from a SSM becomes computationally straightforward, so that quantifying the risk associated with low-probability, high-consequence climate events becomes feasible. A Bayesian framework is developed to provide quantitative measures of confidence, via Bayesian credible intervals, in the use of the proposed approach to assess these risks.« less

Approximate Bayesian algorithm to estimate the basic reproduction number in an influenza pandemic using arrival times of imported cases.

PubMed

Chong, Ka Chun; Zee, Benny Chung Ying; Wang, Maggie Haitian

2018-04-10

In an influenza pandemic, arrival times of cases are a proxy of the epidemic size and disease transmissibility. Because of intense surveillance of travelers from infected countries, detection is more rapid and complete than on local surveillance. Travel information can provide a more reliable estimation of transmission parameters. We developed an Approximate Bayesian Computation algorithm to estimate the basic reproduction number (R 0 ) in addition to the reporting rate and unobserved epidemic start time, utilizing travel, and routine surveillance data in an influenza pandemic. A simulation was conducted to assess the sampling uncertainty. The estimation approach was further applied to the 2009 influenza A/H1N1 pandemic in Mexico as a case study. In the simulations, we showed that the estimation approach was valid and reliable in different simulation settings. We also found estimates of R 0 and the reporting rate to be 1.37 (95% Credible Interval [CI]: 1.26-1.42) and 4.9% (95% CI: 0.1%-18%), respectively, in the 2009 influenza pandemic in Mexico, which were robust to variations in the fixed parameters. The estimated R 0 was consistent with that in the literature. This method is useful for officials to obtain reliable estimates of disease transmissibility for strategic planning. We suggest that improvements to the flow of reporting for confirmed cases among patients arriving at different countries are required. Copyright © 2018 Elsevier Ltd. All rights reserved.

Bayesian Source Attribution of Salmonellosis in South Australia.

PubMed

Glass, K; Fearnley, E; Hocking, H; Raupach, J; Veitch, M; Ford, L; Kirk, M D

2016-03-01

Salmonellosis is a significant cause of foodborne gastroenteritis in Australia, and rates of illness have increased over recent years. We adopt a Bayesian source attribution model to estimate the contribution of different animal reservoirs to illness due to Salmonella spp. in South Australia between 2000 and 2010, together with 95% credible intervals (CrI). We excluded known travel associated cases and those of rare subtypes (fewer than 20 human cases or fewer than 10 isolates from included sources over the 11-year period), and the remaining 76% of cases were classified as sporadic or outbreak associated. Source-related parameters were included to allow for different handling and consumption practices. We attributed 35% (95% CrI: 20-49) of sporadic cases to chicken meat and 37% (95% CrI: 23-53) of sporadic cases to eggs. Of outbreak-related cases, 33% (95% CrI: 20-62) were attributed to chicken meat and 59% (95% CrI: 29-75) to eggs. A comparison of alternative model assumptions indicated that biases due to possible clustering of samples from sources had relatively minor effects on these estimates. Analysis of source-related parameters showed higher risk of illness from contaminated eggs than from contaminated chicken meat, suggesting that consumption and handling practices potentially play a bigger role in illness due to eggs, considering low Salmonella prevalence on eggs. Our results strengthen the evidence that eggs and chicken meat are important vehicles for salmonellosis in South Australia. © 2015 Society for Risk Analysis.

Disentangling the effects of climate, density dependence, and harvest on an iconic large herbivore's population dynamics.

PubMed

Koons, David N; Colchero, Fernando; Hersey, Kent; Gimenez, Olivier

2015-06-01

Understanding the relative effects of climate, harvest, and density dependence on population dynamics is critical for guiding sound population management, especially for ungulates in arid and semiarid environments experiencing climate change. To address these issues for bison in southern Utah, USA, we applied a Bayesian state-space model to a 72-yr time series of abundance counts. While accounting for known harvest (as well as live removal) from the population, we found that the bison population in southern Utah exhibited a strong potential to grow from low density (β0 = 0.26; Bayesian credible interval based on 95% of the highest posterior density [BCI] = 0.19-0.33), and weak but statistically significant density dependence (β1 = -0.02, BCI = -0.04 to -0.004). Early spring temperatures also had strong positive effects on population growth (Pfat1 = 0.09, BCI = 0.04-0.14), much more so than precipitation and other temperature-related variables (model weight > three times more than that for other climate variables). Although we hypothesized that harvest is the primary driving force of bison population dynamics in southern Utah, our elasticity analysis indicated that changes in early spring temperature could have a greater relative effect on equilibrium abundance than either harvest or. the strength of density dependence. Our findings highlight the utility of incorporating elasticity analyses into state-space population models, and the need to include climatic processes in wildlife management policies and planning.

A Bayesian method for characterizing distributed micro-releases: II. inference under model uncertainty with short time-series data.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Marzouk, Youssef; Fast P.; Kraus, M.

2006-01-01

Terrorist attacks using an aerosolized pathogen preparation have gained credibility as a national security concern after the anthrax attacks of 2001. The ability to characterize such attacks, i.e., to estimate the number of people infected, the time of infection, and the average dose received, is important when planning a medical response. We address this question of characterization by formulating a Bayesian inverse problem predicated on a short time-series of diagnosed patients exhibiting symptoms. To be of relevance to response planning, we limit ourselves to 3-5 days of data. In tests performed with anthrax as the pathogen, we find that thesemore » data are usually sufficient, especially if the model of the outbreak used in the inverse problem is an accurate one. In some cases the scarcity of data may initially support outbreak characterizations at odds with the true one, but with sufficient data the correct inferences are recovered; in other words, the inverse problem posed and its solution methodology are consistent. We also explore the effect of model error-situations for which the model used in the inverse problem is only a partially accurate representation of the outbreak; here, the model predictions and the observations differ by more than a random noise. We find that while there is a consistent discrepancy between the inferred and the true characterizations, they are also close enough to be of relevance when planning a response.« less

Estimation of the diagnostic performance of two ELISAs to detect PCV2 antibodies in pig sera using a Bayesian method.

PubMed

Fablet, C; Rose, N; Bernard, C; Messager, I; Piel, Y; Grasland, B

2017-11-01

This study was designed to assess the diagnostic characteristics of two PCV2 ELISAs without a gold standard. Four hundred and sixty-five serum samples from finishing pigs (25 herds) not vaccinated against PCV2 were used. Samples were tested by two ELISAs: an in-house ELISA (I-ELISA) and the commercial SERELISA ® PCV2 Ab Mono Blocking kit (S-ELISA). A ROC curve was used to assess the S-ELISA's optimal threshold by taking the I-ELISA as a reference and using the cut-off previously determined by comparison to an cccmonolayer assay (IPMA). This led to an S-ELISA result ≥170 being considered as positive. The sensitivity (Se) and specificity (Sp) of each ELISA were then estimated without a gold standard using a Bayesian approach. The mean Se and Sp values of the I-ELISA were slightly higher than those of the S-ELISA (mean Se I-ELISA=0.90 vs. mean Se S-ELISA=0.86; mean Sp I-ELISA=0.92 vs. mean Sp S-ELISA=0.85). However, the 95% credibility intervals (CI95%) overlapped (Se I-ELISA CI95%=0.85-0.95 vs. Se S-ELISA CI95%=0.82-0.90; Sp I-ELISA CI95%=0.82-0.98 vs. Sp S-ELISA CI95%=0.75-0.94). Both ELISAs appeared to be valuable tools for detecting PCV2 antibodies. Copyright © 2017 Elsevier B.V. All rights reserved.

Lung cancer mortality in France. Trend analysis and projection between 1975 and 2012, using a Bayesian age-period-cohort model.

PubMed

Eilstein, Daniel; Uhry, Zoé; Lim, Tek-Ang; Bloch, Juliette

2008-03-01

Lung cancer is currently the most common cancer in the world and as such is an important public health concern. One of the main challenges is to foresee the evolution of trends in lung cancer mortality rates in order to anticipate the future burden of this disease as well as to plan the supply of adequate health care. The aim of this study is to propose a quantification of future lung cancer mortality rates by gender in France until the year 2012. Lung cancer mortality data in France (1978-2002) were extracted from the National Statistics of Death and analyzed by 5-year age-groups and periods, using a Bayesian age-period-cohort model. Between 1978 and 2002, female lung cancer mortality rate rises by 3.3%year(-1). For men, a slow increase is observed until 1988-1992 followed by a declining trend. In 1998-2002, age-standardized mortality rates were, respectively, 45.5 and 7.6 per 100000 for males and for females. By 2008-2012 these figures would reach 40.8 (95% credibility interval (CI): 32.7, 50.0) and 12.1 (CI: 11.7, 12.6) per 100000, respectively, which represents among women a 4.7% annual increase (CI: 4.5, 5.0). Our results highlight the relevance of pursuing public health measures in order to cope more actively with tobacco smoking in the prevention strategy against lung cancer specifically among women.

Spatial vulnerability of fine particulate matter relative to the prevalence of diabetes in the United States.

PubMed

Chien, Lung-Chang; Alamgir, Hasanat; Yu, Hwa-Lung

2015-03-01

Recent research supports a link between diabetes and fine particulate matter (≤ 2.5μg in diameter; PM2.5) in both laboratory and epidemiology studies. However, research investigating the potential relationship of the spatial vulnerability of diabetes to concomitant PM2.5 levels is still sparse, and the level of diabetes geographic disparities attributed to PM2.5 levels has yet to be evaluated. We conducted a Bayesian structured additive regression modeling approach to determine whether long-term exposure to PM2.5 is spatially associated with diabetes prevalence after adjusting for the socioeconomic status of county residents. This study utilizes the following data sources from 2004 to 2010: the Behavioral Risk Factor Surveillance System, the American Community Survey, and the Environmental Protection Agency. We also conducted spatial comparisons with low, median-low, median-high, and high levels of PM2.5 concentrations. When PM2.5 concentrations increased 1 μg/m(3), the increase in the relative risk percentage for diabetes ranged from -5.47% (95% credible interval = -6.14, -4.77) to 2.34% (95% CI = 2.01, 2.70), where 1323 of 3109 counties (42.55%) displayed diabetes vulnerability with significantly positive relative risk percentages. These vulnerable counties are more likely located in the Southeast, Central, and South Regions of the U.S. A similar spatial vulnerability pattern for concentrations of low PM2.5 levels was also present in these same three regions. A clear cluster of vulnerable counties at median-high PM2.5 level was found in Michigan. This study identifies the spatial vulnerability of diabetes prevalence associated with PM2.5, and thereby provides the evidence needed to prompt and establish enhanced surveillance that can monitor diabetes vulnerability in areas with low PM2.5 pollution. Copyright © 2014 Elsevier B.V. All rights reserved.

Spatial vulnerability of fine particulate matter relative to the geographic disparities of adult's diabetes prevalence in the United States

NASA Astrophysics Data System (ADS)

Chien, Lung-Chang; Alamgir, Hassanat; Yu, Hwa-Lung

2015-04-01

Potentially larger regional effects of climate change have been revealed on the elevation of fine particulate matter (≤ 2.5 µg in diameter; PM2.5) in the U.S. In addition, recent research supports a link between diabetes and PM2.5 in both laboratory and epidemiology studies. However, research investigating the potential relationship of the spatial vulnerability of diabetes to concomitant PM2.5 levels is still sparse, and the level of diabetes geographic disparities attributed to PM2.5 levels has yet to be evaluated. We conducted a Bayesian structured additive regression modeling approach to determine whether long-term exposure to PM2.5 is spatially associated with diabetes prevalence after adjusting for the socioeconomic status of county residents. This study utilizes the following data sources from 2004-2010: the Behavioral Risk Factor Surveillance System, the American Community Survey, and the Environmental Protection Agency. We also conducted spatial comparisons with low, median-low, median-high, and high levels of PM2.5 concentrations. When PM2.5 concentrations increased 1 µg/m3, the increase in the relative risk percentage for diabetes ranged from -5.47% (95% credible interval = -6.14, -4.77) to 2.34% (95% CI = 2.01, 2.70), where 1,323 of 3,109 counties (42.55%) displayed diabetes vulnerability with significantly positive relative risk percentages. These vulnerable counties are more likely located in the Southeast, Central, and South Regions of the U.S. A similar spatial vulnerability pattern for concentrations of low PM2.5 levels was also present in these same three regions. A clear cluster of vulnerable counties at median-high PM2.5 level was found in Michigan. This study identifies the spatial vulnerability of diabetes prevalence associated with PM2.5, and thereby provides the evidence needed to prompt and establish enhanced surveillance that can monitor diabetes vulnerability in areas with low PM2.5 pollution.

Modeling the occurrence of Mycobacterium avium subsp. paratuberculosis in bulk raw milk and the impact of management options for exposure mitigation.

PubMed

Boulais, Christophe; Wacker, Ron; Augustin, Jean-Christophe; Cheikh, Mohamed Hedi Ben; Peladan, Fabrice

2011-07-01

Mycobacterium avium subsp. paratuberculosis (MAP) is the causal agent of paratuberculosis (Johne's disease) in cattle and other farm ruminants. The potential role of MAP in Crohn's disease in humans and the contribution of dairy products to human exposure to MAP continue to be the subject of scientific debate. The occurrence of MAP in bulk raw milk from dairy herds was assessed using a stochastic modeling approach. Raw milk samples were collected from bulk tanks in dairy plants and tested for the presence of MAP. Results from this analytical screening were used in a Bayesian network to update the model prediction. Of the 83 raw milk samples tested, 4 were positive for MAP by culture and PCR. We estimated that the level of MAP in bulk tanks ranged from 0 CFU/ml for the 2.5th percentile to 65 CFU/ml for the 97.5th percentile, with 95% credibility intervals of [0, 0] and [16, 326], respectively. The model was used to evaluate the effect of measures aimed at reducing the occurrence of MAP in raw milk. Reducing the prevalence of paratuberculosis has less of an effect on the occurrence of MAP in bulk raw milk than does managing clinically infected animals through good farming practices. Copyright ©, International Association for Food Protection

Lion (Panthera leo) populations are declining rapidly across Africa, except in intensively managed areas.

PubMed

Bauer, Hans; Chapron, Guillaume; Nowell, Kristin; Henschel, Philipp; Funston, Paul; Hunter, Luke T B; Macdonald, David W; Packer, Craig

2015-12-01

We compiled all credible repeated lion surveys and present time series data for 47 lion (Panthera leo) populations. We used a Bayesian state space model to estimate growth rate-λ for each population and summed these into three regional sets to provide conservation-relevant estimates of trends since 1990. We found a striking geographical pattern: African lion populations are declining everywhere, except in four southern countries (Botswana, Namibia, South Africa, and Zimbabwe). Population models indicate a 67% chance that lions in West and Central Africa decline by one-half, while estimating a 37% chance that lions in East Africa also decline by one-half over two decades. We recommend separate regional assessments of the lion in the World Conservation Union (IUCN) Red List of Threatened Species: already recognized as critically endangered in West Africa, our analysis supports listing as regionally endangered in Central and East Africa and least concern in southern Africa. Almost all lion populations that historically exceeded ∼ 500 individuals are declining, but lion conservation is successful in southern Africa, in part because of the proliferation of reintroduced lions in small, fenced, intensively managed, and funded reserves. If management budgets for wild lands cannot keep pace with mounting levels of threat, the species may rely increasingly on these southern African areas and may no longer be a flagship species of the once vast natural ecosystems across the rest of the continent.

Sequential updating of a new dynamic pharmacokinetic model for caffeine in premature neonates.

PubMed

Micallef, Sandrine; Amzal, Billy; Bach, Véronique; Chardon, Karen; Tourneux, Pierre; Bois, Frédéric Y

2007-01-01

Caffeine treatment is widely used in nursing care to reduce the risk of apnoea in premature neonates. To check the therapeutic efficacy of the treatment against apnoea, caffeine concentration in blood is an important indicator. The present study was aimed at building a pharmacokinetic model as a basis for a medical decision support tool. In the proposed model, time dependence of physiological parameters is introduced to describe rapid growth of neonates. To take into account the large variability in the population, the pharmacokinetic model is embedded in a population structure. The whole model is inferred within a Bayesian framework. To update caffeine concentration predictions as data of an incoming patient are collected, we propose a fast method that can be used in a medical context. This involves the sequential updating of model parameters (at individual and population levels) via a stochastic particle algorithm. Our model provides better predictions than the ones obtained with models previously published. We show, through an example, that sequential updating improves predictions of caffeine concentration in blood (reduce bias and length of credibility intervals). The update of the pharmacokinetic model using body mass and caffeine concentration data is studied. It shows how informative caffeine concentration data are in contrast to body mass data. This study provides the methodological basis to predict caffeine concentration in blood, after a given treatment if data are collected on the treated neonate.

Message propagation in the network based on node credibility

NASA Astrophysics Data System (ADS)

Nian, Fuzhong; Dang, Zhongkai

2018-04-01

In the propagation efficiency point of view, the node credibility is introduced in this paper. For the message receiver, the node would partially believe the message according to the credibility of the propagator. For a node, the credibility is variable. The more the true message spread, the higher the credibility, and vice versa, the credibility becomes smaller. Based on the idea, a new network was established with the node credibility. Finally, a comparing experiment between the fully trusted network and the network with the node credibility was implemented. The results indicate that the spread effect of messages is better in the network with the node credibility.

Implementation of an Adaptive Learning System Using a Bayesian Network

ERIC Educational Resources Information Center

Yasuda, Keiji; Kawashima, Hiroyuki; Hata, Yoko; Kimura, Hiroaki

2015-01-01

An adaptive learning system is proposed that incorporates a Bayesian network to efficiently gauge learners' understanding at the course-unit level. Also, learners receive content that is adapted to their measured level of understanding. The system works on an iPad via the Edmodo platform. A field experiment using the system in an elementary school…

The relationship between electronic gaming machine accessibility and police-recorded domestic violence: A spatio-temporal analysis of 654 postcodes in Victoria, Australia, 2005-2014.

PubMed

Markham, Francis; Doran, Bruce; Young, Martin

2016-08-01

An emerging body of research has documented an association between problem gambling and domestic violence in a range of study populations and locations. Yet little research has analysed this relationship at ecological scales. This study investigates the proposition that gambling accessibility and the incidence of domestic violence might be linked. The association between police-recorded domestic violence and electronic gaming machine accessibility is described at the postcode level. Police recorded family incidents per 10,000 and domestic-violence related physical assault offenses per 10,000 were used as outcome variables. Electronic gaming machine accessibility was measured as electronic gaming machines per 10,000 and gambling venues per 100,000. Bayesian spatio-temporal mixed-effects models were used to estimate the associations between gambling accessibility and domestic violence, using annual postcode-level data in Victoria, Australia between 2005 and 2014, adjusting for a range of covariates. Significant associations of policy-relevant magnitudes were found between all domestic violence and EGM accessibility variables. Postcodes with no electronic gaming machines were associated with 20% (95% credibility interval [C.I.]: 15%, 24%) fewer family incidents per 10,000 and 30% (95% C.I.: 24%, 35%) fewer domestic-violence assaults per 10,000, when compared with postcodes with 75 electronic gaming machine per 10,000. The causal relations underlying these associations are unclear. Quasi-experimental research is required to determine if reducing gambling accessibility is likely to reduce the incidence of domestic violence. Copyright © 2016 Elsevier Ltd. All rights reserved.

Neighbourhood Walkability and Daily Steps in Adults with Type 2 Diabetes.

PubMed

Hajna, Samantha; Ross, Nancy A; Joseph, Lawrence; Harper, Sam; Dasgupta, Kaberi

2016-01-01

There is evidence that greater neighbourhood walkability (i.e., neighbourhoods with more amenities and well-connected streets) is associated with higher levels of total walking in Europe and in Asia, but it remains unclear if this association holds in the Canadian context and in chronic disease populations. We examined the relationships of different walkability measures to biosensor-assessed total walking (i.e., steps/day) in adults with type 2 diabetes living in Montreal (QC, Canada). Participants (60.5±10.4 years; 48.1% women) were recruited through McGill University-affiliated clinics (June 2006 to May 2008). Steps/day were assessed once per season for one year with pedometers. Neighbourhood walkability was evaluated through participant reports, in-field audits, Geographic Information Systems (GIS)-derived measures, and the Walk Score®. Relationships between walkability and daily steps were estimated using Bayesian longitudinal hierarchical linear regression models (n = 131). Participants who reported living in the most compared to the least walkable neighbourhoods completed 1345 more steps/day (95% Credible Interval: 718, 1976; Quartiles 4 versus 1). Those living in the most compared to the least walkable neighbourhoods (based on GIS-derived walkability) completed 606 more steps per day (95% CrI: 8, 1203). No statistically significant associations with steps were observed for audit-assessed walkability or the Walk Score®. Adults with type 2 diabetes who perceived their neighbourhoods as more walkable accumulated more daily steps. This suggests that knowledge of local neighborhood features that enhance walking is a meaningful predictor of higher levels of walking and an important component of neighbourhood walkability.

Association between the Severity of Influenza A(H7N9) Virus Infections and Length of the Incubation Period

PubMed Central

Fang, Vicky J.; Feng, Luzhao; Tsang, Tim K.; Jiang, Hui; Wu, Peng; Zheng, Jiandong; Lau, Eric H. Y.; Qin, Ying; Peng, Zhibin; Peiris, J. S. Malik; Yu, Hongjie; Cowling, Benjamin J.

2016-01-01

Background In early 2013, a novel avian-origin influenza A(H7N9) virus emerged in China, and has caused sporadic human infections. The incubation period is the delay from infection until onset of symptoms, and varies from person to person. Few previous studies have examined whether the duration of the incubation period correlates with subsequent disease severity. Methods and Findings We analyzed data of period of exposure on 395 human cases of laboratory-confirmed influenza A(H7N9) virus infection in China in a Bayesian framework using a Weibull distribution. We found a longer incubation period for the 173 fatal cases with a mean of 3.7 days (95% credibility interval, CrI: 3.4–4.1), compared to a mean of 3.3 days (95% CrI: 2.9–3.6) for the 222 non-fatal cases, and the difference in means was marginally significant at 0.47 days (95% CrI: -0.04, 0.99). There was a statistically significant correlation between a longer incubation period and an increased risk of death after adjustment for age, sex, geographical location and underlying medical conditions (adjusted odds ratio 1.70 per day increase in incubation period; 95% credibility interval 1.47–1.97). Conclusions We found a significant association between a longer incubation period and a greater risk of death among human H7N9 cases. The underlying biological mechanisms leading to this association deserve further exploration. PMID:26885816

Select tissue mineral concentrations and chronic wasting disease status in mule deer from North-central Colorado.

PubMed

Wolfe, Lisa L; Conner, Mary M; Bedwell, Cathy L; Lukacs, Paul M; Miller, Michael W

2010-07-01

Trace mineral imbalances have been suggested as having a causative or contributory role in chronic wasting disease (CWD), a prion disease of several North American cervid species. To begin exploring relationships between tissue mineral concentrations and CWD in natural systems, we measured liver tissue concentrations of copper, manganese, and molybdenum in samples from 447 apparently healthy, adult (> or = 2 yr old) mule deer (Odocoileus hemionus) culled or vehicle killed from free-ranging populations in north-central Colorado, United States, where CWD occurs naturally; we also measured copper concentrations in brain-stem (medulla oblongata at the obex) tissue from 181 of these deer. Analyses revealed a wide range of concentrations of all three minerals among sampled deer (copper: 5.6-331 ppm in liver, 1.5-31.9 ppm in obex; manganese: 0.1-21.4 ppm in liver; molybdenum: 0.5-4.0 ppm in liver). Bayesian multiple regression analysis revealed a negative association between obex copper (-0.097; 95% credible interval -0.192 to -0.006) and the probability of sampled deer also being infected with CWD, as well as a positive association between liver manganese (0.158; 95% credible interval 0.066 to 0.253) and probability of infection. We could not discern whether the tendencies toward lower brain-stem copper concentrations or higher systemic manganese concentrations in infected deer preceded prion infection or rather were the result of infection and its subsequent effects, although the distribution of trace mineral concentrations in infected deer seemed more suggestive of the latter.

Credibility analysis of risk classes by generalized linear model

NASA Astrophysics Data System (ADS)

Erdemir, Ovgucan Karadag; Sucu, Meral

2016-06-01

In this paper generalized linear model (GLM) and credibility theory which are frequently used in nonlife insurance pricing are combined for reliability analysis. Using full credibility standard, GLM is associated with limited fluctuation credibility approach. Comparison criteria such as asymptotic variance and credibility probability are used to analyze the credibility of risk classes. An application is performed by using one-year claim frequency data of a Turkish insurance company and results of credible risk classes are interpreted.

Bayesian learning of visual chunks by human observers

PubMed Central

Orbán, Gergő; Fiser, József; Aslin, Richard N.; Lengyel, Máté

2008-01-01

Efficient and versatile processing of any hierarchically structured information requires a learning mechanism that combines lower-level features into higher-level chunks. We investigated this chunking mechanism in humans with a visual pattern-learning paradigm. We developed an ideal learner based on Bayesian model comparison that extracts and stores only those chunks of information that are minimally sufficient to encode a set of visual scenes. Our ideal Bayesian chunk learner not only reproduced the results of a large set of previous empirical findings in the domain of human pattern learning but also made a key prediction that we confirmed experimentally. In accordance with Bayesian learning but contrary to associative learning, human performance was well above chance when pair-wise statistics in the exemplars contained no relevant information. Thus, humans extract chunks from complex visual patterns by generating accurate yet economical representations and not by encoding the full correlational structure of the input. PMID:18268353

Abstract Mindsets Increase Believability of Spatially Distant Online Messages

PubMed Central

Sungur, Hande; Hartmann, Tilo; van Koningsbruggen, Guido M.

2016-01-01

Growing evidence from online credibility research reveals that online users rely on heuristic processes to evaluate the credibility of online information. The current paper, which is based on the construal level theory (CLT), proposes that congruency between the psychological distance of a stimulus and the way it is mentally construed can act as a heuristic for believability. According to CLT, psychologically close (e.g., spatially, temporally, socially) stimuli are represented concretely whereas psychologically distant stimuli are represented abstractly. The level of mental construals and the psychological distance of information have been shown to influence people’s truth judgments in offline contexts. This study tests whether congruency between the construal level of people’s mindsets (abstract vs. concrete) and the psychological distance implied in an online message (far vs. close) enhances message believability. By partially confirming CLT predictions, we found that believability of an online news item about a distant location increased when people maintained an abstract mindset rather than a concrete one. The effect of a concrete mindset on believability was not significant for the close psychological distance condition. Our findings provide initial evidence that congruency between the construal level of people’s mindsets and psychological distance cues in online messages can act as a heuristic for believability. We discuss the potential of applying the CLT framework to the growing literature on online cognitive heuristics in the area of online information credibility. PMID:27468272

Global mean sea-level rise in a world agreed upon in Paris

NASA Astrophysics Data System (ADS)

Bittermann, Klaus; Rahmstorf, Stefan; Kopp, Robert E.; Kemp, Andrew C.

2017-12-01

Although the 2015 Paris Agreement seeks to hold global average temperature to ‘well below 2 °C above pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5 °C above pre-industrial levels’, projections of global mean sea-level (GMSL) rise commonly focus on scenarios in which there is a high probability that warming exceeds 1.5 °C. Using a semi-empirical model, we project GMSL changes between now and 2150 CE under a suite of temperature scenarios that satisfy the Paris Agreement temperature targets. The projected magnitude and rate of GMSL rise varies among these low emissions scenarios. Stabilizing temperature at 1.5 °C instead of 2 °C above preindustrial reduces GMSL in 2150 CE by 17 cm (90% credible interval: 14-21 cm) and reduces peak rates of rise by 1.9 mm yr-1 (90% credible interval: 1.4-2.6 mm yr-1). Delaying the year of peak temperature has little long-term influence on GMSL, but does reduce the maximum rate of rise. Stabilizing at 2 °C in 2080 CE rather than 2030 CE reduces the peak rate by 2.7 mm yr-1 (90% credible interval: 2.0-4.0 mm yr-1).

Producer-level benefits of sustainability certification.

PubMed

Blackman, Allen; Rivera, Jorge

2011-12-01

Initiatives certifying that producers of goods and services adhere to defined environmental and social-welfare production standards are increasingly popular. According to proponents, these initiatives create financial incentives for producers to improve their environmental, social, and economic performance. We reviewed the evidence on whether these initiatives have such benefits. We identified peer-reviewed, ex post, producer-level studies in economic sectors in which certification is particularly prevalent (bananas, coffee, fish products, forest products, and tourism operations), classified these studies on the basis of whether their design and methods likely generated credible results, summarized findings from the studies with credible results, and considered how these findings might guide future research. We found 46 relevant studies, most of which focused on coffee and forest products and examined fair-trade and Forest Stewardship Council certification. The methods used in 11 studies likely generated credible results. Of these 11 studies, nine examined the economic effects and two the environmental effects of certification. The results of four of the 11 studies, all of which examined economic effects, showed that certification has producer-level benefits. Hence, the evidence to support the hypothesis that certification benefits the environment or producers is limited. More evidence could be generated by incorporating rigorous, independent evaluation into the design and implementation of projects promoting certification. ©2011 Society for Conservation Biology.

Comparison of credible patients of very low intelligence and non-credible patients on neurocognitive performance validity indicators.

PubMed

Smith, Klayton; Boone, Kyle; Victor, Tara; Miora, Deborah; Cottingham, Maria; Ziegler, Elizabeth; Zeller, Michelle; Wright, Matthew

2014-01-01

The purpose of this archival study was to identify performance validity tests (PVTs) and standard IQ and neurocognitive test scores, which singly or in combination, differentiate credible patients of low IQ (FSIQ ≤ 75; n = 55) from non-credible patients. We compared the credible participants against a sample of 74 non-credible patients who appeared to have been attempting to feign low intelligence specifically (FSIQ ≤ 75), as well as a larger non-credible sample (n = 383) unselected for IQ. The entire non-credible group scored significantly higher than the credible participants on measures of verbal crystallized intelligence/semantic memory and manipulation of overlearned information, while the credible group performed significantly better on many processing speed and memory tests. Additionally, credible women showed faster finger-tapping speeds than non-credible women. The credible group also scored significantly higher than the non-credible subgroup with low IQ scores on measures of attention, visual perceptual/spatial tasks, processing speed, verbal learning/list learning, and visual memory, and credible women continued to outperform non-credible women on finger tapping. When cut-offs were selected to maintain approximately 90% specificity in the credible group, sensitivity rates were highest for verbal and visual memory measures (i.e., TOMM trials 1 and 2; Warrington Words correct and time; Rey Word Recognition Test total; RAVLT Effort Equation, Trial 5, total across learning trials, short delay, recognition, and RAVLT/RO discriminant function; and Digit Symbol recognition), followed by select attentional PVT scores (i.e., b Test omissions and time to recite four digits forward). When failure rates were tabulated across seven most sensitive scores, a cut-off of ≥ 2 failures was associated with 85.4% specificity and 85.7% sensitivity, while a cut-off of ≥ 3 failures resulted in 95.1% specificity and 66.0% sensitivity. Results are discussed in light of extant literature and directions for future research.

Uncovering robust patterns of microRNA co-expression across cancers using Bayesian Relevance Networks

PubMed Central

2017-01-01

Co-expression networks have long been used as a tool for investigating the molecular circuitry governing biological systems. However, most algorithms for constructing co-expression networks were developed in the microarray era, before high-throughput sequencing—with its unique statistical properties—became the norm for expression measurement. Here we develop Bayesian Relevance Networks, an algorithm that uses Bayesian reasoning about expression levels to account for the differing levels of uncertainty in expression measurements between highly- and lowly-expressed entities, and between samples with different sequencing depths. It combines data from groups of samples (e.g., replicates) to estimate group expression levels and confidence ranges. It then computes uncertainty-moderated estimates of cross-group correlations between entities, and uses permutation testing to assess their statistical significance. Using large scale miRNA data from The Cancer Genome Atlas, we show that our Bayesian update of the classical Relevance Networks algorithm provides improved reproducibility in co-expression estimates and lower false discovery rates in the resulting co-expression networks. Software is available at www.perkinslab.ca. PMID:28817636

Uncovering robust patterns of microRNA co-expression across cancers using Bayesian Relevance Networks.

PubMed

Ramachandran, Parameswaran; Sánchez-Taltavull, Daniel; Perkins, Theodore J

2017-01-01

Co-expression networks have long been used as a tool for investigating the molecular circuitry governing biological systems. However, most algorithms for constructing co-expression networks were developed in the microarray era, before high-throughput sequencing-with its unique statistical properties-became the norm for expression measurement. Here we develop Bayesian Relevance Networks, an algorithm that uses Bayesian reasoning about expression levels to account for the differing levels of uncertainty in expression measurements between highly- and lowly-expressed entities, and between samples with different sequencing depths. It combines data from groups of samples (e.g., replicates) to estimate group expression levels and confidence ranges. It then computes uncertainty-moderated estimates of cross-group correlations between entities, and uses permutation testing to assess their statistical significance. Using large scale miRNA data from The Cancer Genome Atlas, we show that our Bayesian update of the classical Relevance Networks algorithm provides improved reproducibility in co-expression estimates and lower false discovery rates in the resulting co-expression networks. Software is available at www.perkinslab.ca.

From individual to population level effects of toxicants in the tubicifid Branchiura sowerbyi using threshold effect models in a Bayesian framework.

PubMed

Ducrot, Virginie; Billoir, Elise; Péry, Alexandre R R; Garric, Jeanne; Charles, Sandrine

2010-05-01

Effects of zinc were studied in the freshwater worm Branchiura sowerbyi using partial and full life-cycle tests. Only newborn and juveniles were sensitive to zinc, displaying effects on survival, growth, and age at first brood at environmentally relevant concentrations. Threshold effect models were proposed to assess toxic effects on individuals. They were fitted to life-cycle test data using Bayesian inference and adequately described life-history trait data in exposed organisms. The daily asymptotic growth rate of theoretical populations was then simulated with a matrix population model, based upon individual-level outputs. Population-level outputs were in accordance with existing literature for controls. Working in a Bayesian framework allowed incorporating parameter uncertainty in the simulation of the population-level response to zinc exposure, thus increasing the relevance of test results in the context of ecological risk assessment.

Bayesian analyses of time-interval data for environmental radiation monitoring.

PubMed

Luo, Peng; Sharp, Julia L; DeVol, Timothy A

2013-01-01

Time-interval (time difference between two consecutive pulses) analysis based on the principles of Bayesian inference was investigated for online radiation monitoring. Using experimental and simulated data, Bayesian analysis of time-interval data [Bayesian (ti)] was compared with Bayesian and a conventional frequentist analysis of counts in a fixed count time [Bayesian (cnt) and single interval test (SIT), respectively]. The performances of the three methods were compared in terms of average run length (ARL) and detection probability for several simulated detection scenarios. Experimental data were acquired with a DGF-4C system in list mode. Simulated data were obtained using Monte Carlo techniques to obtain a random sampling of the Poisson distribution. All statistical algorithms were developed using the R Project for statistical computing. Bayesian analysis of time-interval information provided a similar detection probability as Bayesian analysis of count information, but the authors were able to make a decision with fewer pulses at relatively higher radiation levels. In addition, for the cases with very short presence of the source (< count time), time-interval information is more sensitive to detect a change than count information since the source data is averaged by the background data over the entire count time. The relationships of the source time, change points, and modifications to the Bayesian approach for increasing detection probability are presented.

Integrative Approaches to Evaluating Neurotoxicity Data for Risk Assessment.

EPA Science Inventory

Risk assessment classically has been based on single adverse outcomes identified as the Lowest Observable Adverse Effect Level (LOAEL) or the highest dose level in a credible study producing a No Observable Adverse Effect Level (NOAEL). While this approach has been useful overal...

Search for a Low-Mass Neutral Higgs Boson with Suppressed Couplings to Fermions Using Events with Multiphoton Final States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aaltonen, Timo Antero

A search for a Higgs boson with suppressed couplings to fermions,more » $$h_f$$, assumed to be the neutral, lower-mass partner of the Higgs boson discovered at the Large Hadron Collider, is reported. Such a Higgs boson could exist in extensions of the standard model with two Higgs doublets, and could be produced via $$p\\bar{p} \\to H^\\pm h_f \\to W^* h_f h_f \\to 4\\gamma + X$$, where $$H^\\pm$$ is a charged Higgs boson. This analysis uses all events with at least three photons in the final state from proton-antiproton collisions at a center-of-mass energy of 1.96~TeV collected by the Collider Detector at Fermilab, corresponding to an integrated luminosity of 9.2~$${\\rm fb}^{-1}$$. No evidence of a signal is observed in the data. Values of Higgs-boson masses between 10 and 100 GeV/$c^2$ are excluded at 95\\% Bayesian credibility.« less

Bayesian analysis of multimethod ego-depletion studies favours the null hypothesis.

PubMed

Etherton, Joseph L; Osborne, Randall; Stephenson, Katelyn; Grace, Morgan; Jones, Chas; De Nadai, Alessandro S

2018-04-01

Ego-depletion refers to the purported decrease in performance on a task requiring self-control after engaging in a previous task involving self-control, with self-control proposed to be a limited resource. Despite many published studies consistent with this hypothesis, recurrent null findings within our laboratory and indications of publication bias have called into question the validity of the depletion effect. This project used three depletion protocols involved three different depleting initial tasks followed by three different self-control tasks as dependent measures (total n = 840). For each method, effect sizes were not significantly different from zero When data were aggregated across the three different methods and examined meta-analytically, the pooled effect size was not significantly different from zero (for all priors evaluated, Hedges' g = 0.10 with 95% credibility interval of [-0.05, 0.24]) and Bayes factors reflected strong support for the null hypothesis (Bayes factor > 25 for all priors evaluated). © 2018 The British Psychological Society.

Attributing foodborne salmonellosis in humans to animal reservoirs in the European Union using a multi-country stochastic model.

PubMed

DE Knegt, L V; Pires, S M; Hald, T

2015-04-01

A Bayesian modelling approach comparing the occurrence of Salmonella serovars in animals and humans was used to attribute salmonellosis cases to broilers, turkeys, pigs, laying hens, travel and outbreaks in 24 European Union countries. Salmonella data for animals and humans, covering the period from 2007 to 2009, were mainly obtained from studies and reports published by the European Food Safety Authority. Availability of food sources for consumption was derived from trade and production data from the European Statistical Office. Results showed layers as the most important reservoir of human salmonellosis in Europe, with 42·4% (7 903 000 cases, 95% credibility interval 4 181 000-14 510 000) of cases, 95·9% of which was caused by S. Enteritidis. In Finland and Sweden, most cases were travel-related, while in most other countries the main sources were related to the laying hen or pig reservoir, highlighting differences in the epidemiology of Salmonella, surveillance focus and eating habits across the European Union.

Back to Normal! Gaussianizing posterior distributions for cosmological probes

NASA Astrophysics Data System (ADS)

Schuhmann, Robert L.; Joachimi, Benjamin; Peiris, Hiranya V.

2014-05-01

We present a method to map multivariate non-Gaussian posterior probability densities into Gaussian ones via nonlinear Box-Cox transformations, and generalizations thereof. This is analogous to the search for normal parameters in the CMB, but can in principle be applied to any probability density that is continuous and unimodal. The search for the optimally Gaussianizing transformation amongst the Box-Cox family is performed via a maximum likelihood formalism. We can judge the quality of the found transformation a posteriori: qualitatively via statistical tests of Gaussianity, and more illustratively by how well it reproduces the credible regions. The method permits an analytical reconstruction of the posterior from a sample, e.g. a Markov chain, and simplifies the subsequent joint analysis with other experiments. Furthermore, it permits the characterization of a non-Gaussian posterior in a compact and efficient way. The expression for the non-Gaussian posterior can be employed to find analytic formulae for the Bayesian evidence, and consequently be used for model comparison.

Search for a Low-Mass Neutral Higgs Boson with Suppressed Couplings to Fermions Using Events with Multiphoton Final States

DOE PAGES

Aaltonen, Timo Antero

2016-06-20

A search for a Higgs boson with suppressed couplings to fermions,more » $$h_f$$, assumed to be the neutral, lower-mass partner of the Higgs boson discovered at the Large Hadron Collider, is reported. Such a Higgs boson could exist in extensions of the standard model with two Higgs doublets, and could be produced via $$p\\bar{p} \\to H^\\pm h_f \\to W^* h_f h_f \\to 4\\gamma + X$$, where $$H^\\pm$$ is a charged Higgs boson. This analysis uses all events with at least three photons in the final state from proton-antiproton collisions at a center-of-mass energy of 1.96~TeV collected by the Collider Detector at Fermilab, corresponding to an integrated luminosity of 9.2~$${\\rm fb}^{-1}$$. No evidence of a signal is observed in the data. Values of Higgs-boson masses between 10 and 100 GeV/$c^2$ are excluded at 95\\% Bayesian credibility.« less

Evaluating a fish monitoring protocol using state-space hierarchical models

USGS Publications Warehouse

Russell, Robin E.; Schmetterling, David A.; Guy, Chris S.; Shepard, Bradley B.; McFarland, Robert; Skaar, Donald

2012-01-01

Using data collected from three river reaches in Montana, we evaluated our ability to detect population trends and predict fish future fish abundance. Data were collected as part of a long-term monitoring program conducted by Montana Fish, Wildlife and Parks to primarily estimate rainbow (Oncorhynchus mykiss) and brown trout (Salmo trutta) abundance in numerous rivers across Montana. We used a hierarchical Bayesian mark-recapture model to estimate fish abundance over time in each of the three river reaches. We then fit a state-space Gompertz model to estimate current trends and future fish populations. Density dependent effects were detected in 1 of the 6 fish populations. Predictions of future fish populations displayed wide credible intervals. Our simulations indicated that given the observed variation in the abundance estimates, the probability of detecting a 30% decline in fish populations over a five-year period was less than 50%. We recommend a monitoring program that is closely tied to management objectives and reflects the precision necessary to make informed management decisions.

Search for Resonances Decaying to Top and Bottom Quarks with the CDF Experiment.

PubMed

Aaltonen, T; Amerio, S; Amidei, D; Anastassov, A; Annovi, A; Antos, J; Anzà, F; Apollinari, G; Appel, J A; Arisawa, T; Artikov, A; Asaadi, J; Ashmanskas, W; Auerbach, B; Aurisano, A; Azfar, F; Badgett, W; Bae, T; Barbaro-Galtieri, A; Barnes, V E; Barnett, B A; Barria, P; Bartos, P; Bauce, M; Bedeschi, F; Behari, S; Bellettini, G; Bellinger, J; Benjamin, D; Beretvas, A; Bhatti, A; Bianchi, L; Bland, K R; Blumenfeld, B; Bocci, A; Bodek, A; Bortoletto, D; Boudreau, J; Boveia, A; Brigliadori, L; Bromberg, C; Brucken, E; Budagov, J; Budd, H S; Burkett, K; Busetto, G; Bussey, P; Butti, P; Buzatu, A; Calamba, A; Camarda, S; Campanelli, M; Canelli, F; Carls, B; Carlsmith, D; Carosi, R; Carrillo, S; Casal, B; Casarsa, M; Castro, A; Catastini, P; Cauz, D; Cavaliere, V; Cerri, A; Cerrito, L; Chen, Y C; Chertok, M; Chiarelli, G; Chlachidze, G; Cho, K; Chokheli, D; Clark, A; Clarke, C; Convery, M E; Conway, J; Corbo, M; Cordelli, M; Cox, C A; Cox, D J; Cremonesi, M; Cruz, D; Cuevas, J; Culbertson, R; d'Ascenzo, N; Datta, M; de Barbaro, P; Demortier, L; Deninno, M; D'Errico, M; Devoto, F; Di Canto, A; Di Ruzza, B; Dittmann, J R; Donati, S; D'Onofrio, M; Dorigo, M; Driutti, A; Ebina, K; Edgar, R; Elagin, A; Erbacher, R; Errede, S; Esham, B; Farrington, S; Fernández Ramos, J P; Field, R; Flanagan, G; Forrest, R; Franklin, M; Freeman, J C; Frisch, H; Funakoshi, Y; Galloni, C; Garfinkel, A F; Garosi, P; Gerberich, H; Gerchtein, E; Giagu, S; Giakoumopoulou, V; Gibson, K; Ginsburg, C M; Giokaris, N; Giromini, P; Glagolev, V; Glenzinski, D; Gold, M; Goldin, D; Golossanov, A; Gomez, G; Gomez-Ceballos, G; Goncharov, M; González López, O; Gorelov, I; Goshaw, A T; Goulianos, K; Gramellini, E; Grosso-Pilcher, C; Group, R C; Guimaraes da Costa, J; Hahn, S R; Han, J Y; Happacher, F; Hara, K; Hare, M; Harr, R F; Harrington-Taber, T; Hatakeyama, K; Hays, C; Heinrich, J; Herndon, M; Hocker, A; Hong, Z; Hopkins, W; Hou, S; Hughes, R E; Husemann, U; Hussein, M; Huston, J; Introzzi, G; Iori, M; Ivanov, A; James, E; Jang, D; Jayatilaka, B; Jeon, E J; Jindariani, S; Jones, M; Joo, K K; Jun, S Y; Junk, T R; Kambeitz, M; Kamon, T; Karchin, P E; Kasmi, A; Kato, Y; Ketchum, W; Keung, J; Kilminster, B; Kim, D H; Kim, H S; Kim, J E; Kim, M J; Kim, S H; Kim, S B; Kim, Y J; Kim, Y K; Kimura, N; Kirby, M; Knoepfel, K; Kondo, K; Kong, D J; Konigsberg, J; Kotwal, A V; Kreps, M; Kroll, J; Kruse, M; Kuhr, T; Kurata, M; Laasanen, A T; Lammel, S; Lancaster, M; Lannon, K; Latino, G; Lee, H S; Lee, J S; Leo, S; Leone, S; Lewis, J D; Limosani, A; Lipeles, E; Lister, A; Liu, H; Liu, Q; Liu, T; Lockwitz, S; Loginov, A; Lucchesi, D; Lucà, A; Lueck, J; Lujan, P; Lukens, P; Lungu, G; Lys, J; Lysak, R; Madrak, R; Maestro, P; Malik, S; Manca, G; Manousakis-Katsikakis, A; Marchese, L; Margaroli, F; Marino, P; Matera, K; Mattson, M E; Mazzacane, A; Mazzanti, P; McNulty, R; Mehta, A; Mehtala, P; Mesropian, C; Miao, T; Mietlicki, D; Mitra, A; Miyake, H; Moed, S; Moggi, N; Moon, C S; Moore, R; Morello, M J; Mukherjee, A; Muller, Th; Murat, P; Mussini, M; Nachtman, J; Nagai, Y; Naganoma, J; Nakano, I; Napier, A; Nett, J; Neu, C; Nigmanov, T; Nodulman, L; Noh, S Y; Norniella, O; Oakes, L; Oh, S H; Oh, Y D; Oksuzian, I; Okusawa, T; Orava, R; Ortolan, L; Pagliarone, C; Palencia, E; Palni, P; Papadimitriou, V; Parker, W; Pauletta, G; Paulini, M; Paus, C; Phillips, T J; Piacentino, G; Pianori, E; Pilot, J; Pitts, K; Plager, C; Pondrom, L; Poprocki, S; Potamianos, K; Pranko, A; Prokoshin, F; Ptohos, F; Punzi, G; Redondo Fernández, I; Renton, P; Rescigno, M; Rimondi, F; Ristori, L; Robson, A; Rodriguez, T; Rolli, S; Ronzani, M; Roser, R; Rosner, J L; Ruffini, F; Ruiz, A; Russ, J; Rusu, V; Sakumoto, W K; Sakurai, Y; Santi, L; Sato, K; Saveliev, V; Savoy-Navarro, A; Schlabach, P; Schmidt, E E; Schwarz, T; Scodellaro, L; Scuri, F; Seidel, S; Seiya, Y; Semenov, A; Sforza, F; Shalhout, S Z; Shears, T; Shepard, P F; Shimojima, M; Shochet, M; Shreyber-Tecker, I; Simonenko, A; Sliwa, K; Smith, J R; Snider, F D; Song, H; Sorin, V; St Denis, R; Stancari, M; Stentz, D; Strologas, J; Sudo, Y; Sukhanov, A; Suslov, I; Takemasa, K; Takeuchi, Y; Tang, J; Tecchio, M; Teng, P K; Thom, J; Thomson, E; Thukral, V; Toback, D; Tokar, S; Tollefson, K; Tomura, T; Tonelli, D; Torre, S; Torretta, D; Totaro, P; Trovato, M; Ukegawa, F; Uozumi, S; Vázquez, F; Velev, G; Vellidis, C; Vernieri, C; Vidal, M; Vilar, R; Vizán, J; Vogel, M; Volpi, G; Wagner, P; Wallny, R; Wang, S M; Waters, D; Wester, W C; Whiteson, D; Wicklund, A B; Wilbur, S; Williams, H H; Wilson, J S; Wilson, P; Winer, B L; Wittich, P; Wolbers, S; Wolfe, H; Wright, T; Wu, X; Wu, Z; Yamamoto, K; Yamato, D; Yang, T; Yang, U K; Yang, Y C; Yao, W-M; Yeh, G P; Yi, K; Yoh, J; Yorita, K; Yoshida, T; Yu, G B; Yu, I; Zanetti, A M; Zeng, Y; Zhou, C; Zucchelli, S

2015-08-07

We report on a search for charged massive resonances decaying to top (t) and bottom (b) quarks in the full data set of proton-antiproton collisions at a center-of-mass energy of √[s]=1.96  TeV collected by the CDF II detector at the Tevatron, corresponding to an integrated luminosity of 9.5  fb(-1). No significant excess above the standard model background prediction is observed. We set 95% Bayesian credibility mass-dependent upper limits on the heavy charged-particle production cross section times branching ratio to tb. Using a standard model extension with a W'→tb and left-right-symmetric couplings as a benchmark model, we constrain the W' mass and couplings in the 300-900  GeV/c(2) range. The limits presented here are the most stringent for a charged resonance with mass in the range 300-600  GeV/c(2) decaying to top and bottom quarks.

Introducing Computed Tomography Standards for Age Estimation of Modern Australian Subadults Using Postnatal Ossification Timings of Select Cranial and Cervical Sites(.).

PubMed

Lottering, Nicolene; MacGregor, Donna M; Alston, Clair L; Watson, Debbie; Gregory, Laura S

2016-01-01

Contemporary, population-specific ossification timings of the cranium are lacking in current literature due to challenges in obtaining large repositories of documented subadult material, forcing Australian practitioners to rely on North American, arguably antiquated reference standards for age estimation. This study assessed the temporal pattern of ossification of the cranium and provides recalibrated probabilistic information for age estimation of modern Australian children. Fusion status of the occipital and frontal bones, atlas, and axis was scored using a modified two- to four-tier system from cranial/cervical DICOM datasets of 585 children aged birth to 10 years. Transition analysis was applied to elucidate maximum-likelihood estimates between consecutive fusion stages, in conjunction with Bayesian statistics to calculate credible intervals for age estimation. Results demonstrate significant sex differences in skeletal maturation (p < 0.05) and earlier timings in comparison with major literary sources, underscoring the requisite of updated standards for age estimation of modern individuals. © 2015 American Academy of Forensic Sciences.

Restricted spatial regression in practice: Geostatistical models, confounding, and robustness under model misspecification

USGS Publications Warehouse

Hanks, Ephraim M.; Schliep, Erin M.; Hooten, Mevin B.; Hoeting, Jennifer A.

2015-01-01

In spatial generalized linear mixed models (SGLMMs), covariates that are spatially smooth are often collinear with spatially smooth random effects. This phenomenon is known as spatial confounding and has been studied primarily in the case where the spatial support of the process being studied is discrete (e.g., areal spatial data). In this case, the most common approach suggested is restricted spatial regression (RSR) in which the spatial random effects are constrained to be orthogonal to the fixed effects. We consider spatial confounding and RSR in the geostatistical (continuous spatial support) setting. We show that RSR provides computational benefits relative to the confounded SGLMM, but that Bayesian credible intervals under RSR can be inappropriately narrow under model misspecification. We propose a posterior predictive approach to alleviating this potential problem and discuss the appropriateness of RSR in a variety of situations. We illustrate RSR and SGLMM approaches through simulation studies and an analysis of malaria frequencies in The Gambia, Africa.

A statistical approach to rank multiple priorities in environmental epidemiology: an example from high-risk areas in Sardinia, Italy.

PubMed

Catelan, Dolores; Biggeri, Annibale

2008-11-01

In environmental epidemiology, long lists of relative risk estimates from exposed populations are compared to a reference to scrutinize the dataset for extremes. Here, inference on disease profiles for given areas, or for fixed disease population signatures, are of interest and summaries can be obtained averaging over areas or diseases. We have developed a multivariate hierarchical Bayesian approach to estimate posterior rank distributions and we show how to produce league tables of ranks with credibility intervals useful to address the above mentioned inferential problems. Applying the procedure to a real dataset from the report "Environment and Health in Sardinia (Italy)" we selected 18 areas characterized by high environmental pressure for industrial, mining or military activities investigated for 29 causes of deaths among male residents. Ranking diseases highlighted the increased burdens of neoplastic (cancerous), and non-neoplastic respiratory diseases in the heavily polluted area of Portoscuso. The averaged ranks by disease over areas showed lung cancer among the three highest positions.

Search for resonances decaying to top and bottom quarks with the CDF experiment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Aaltonen, Timo Antero

2015-08-03

We report on a search for charged massive resonances decaying to top (t) and bottom (b) quarks in the full data set of proton-antiproton collisions at a center-of-mass energy of √s = 1.96 TeV collected by the CDF II detector at the Tevatron, corresponding to an integrated luminosity of 9.5 fb –1. No significant excess above the standard model background prediction is observed. We set 95% Bayesian credibility mass-dependent upper limits on the heavy charged-particle production cross section times branching ratio to tb. Using a standard model extension with a W' → tb and left-right-symmetric couplings as a benchmark model,more » we constrain the W' mass and couplings in the 300–900 GeV/c 2 range. As a result, the limits presented here are the most stringent for a charged resonance with mass in the range 300–600 GeV/c 2 decaying to top and bottom quarks.« less

Bayesian network modeling applied to coastal geomorphology: lessons learned from a decade of experimentation and application

NASA Astrophysics Data System (ADS)

Plant, N. G.; Thieler, E. R.; Gutierrez, B.; Lentz, E. E.; Zeigler, S. L.; Van Dongeren, A.; Fienen, M. N.

2016-12-01

We evaluate the strengths and weaknesses of Bayesian networks that have been used to address scientific and decision-support questions related to coastal geomorphology. We will provide an overview of coastal geomorphology research that has used Bayesian networks and describe what this approach can do and when it works (or fails to work). Over the past decade, Bayesian networks have been formulated to analyze the multi-variate structure and evolution of coastal morphology and associated human and ecological impacts. The approach relates observable system variables to each other by estimating discrete correlations. The resulting Bayesian-networks make predictions that propagate errors, conduct inference via Bayes rule, or both. In scientific applications, the model results are useful for hypothesis testing, using confidence estimates to gage the strength of tests while applications to coastal resource management are aimed at decision-support, where the probabilities of desired ecosystems outcomes are evaluated. The range of Bayesian-network applications to coastal morphology includes emulation of high-resolution wave transformation models to make oceanographic predictions, morphologic response to storms and/or sea-level rise, groundwater response to sea-level rise and morphologic variability, habitat suitability for endangered species, and assessment of monetary or human-life risk associated with storms. All of these examples are based on vast observational data sets, numerical model output, or both. We will discuss the progression of our experiments, which has included testing whether the Bayesian-network approach can be implemented and is appropriate for addressing basic and applied scientific problems and evaluating the hindcast and forecast skill of these implementations. We will present and discuss calibration/validation tests that are used to assess the robustness of Bayesian-network models and we will compare these results to tests of other models. This will demonstrate how Bayesian networks are used to extract new insights about coastal morphologic behavior, assess impacts to societal and ecological systems, and communicate probabilistic predictions to decision makers.

Colorectal cancer mortality and industrial pollution in Spain

PubMed Central

2012-01-01

Background Records kept as a result of the implementation of Integrated Pollution Prevention and Control (IPPC) and the European Pollutant Release and Transfer Register (E-PRTR) constitute a public inventory of industries, created by the European Commission, which is a valuable resource for monitoring industrial pollution. Our objective is to ascertain whether there might be excess colorectal cancer mortality among populations residing in the vicinity of Spanish industrial installations that are governed by the IPPC Directive and E-PRTR Regulation and report their emissions to air. Methods An ecological study was designed to examine colorectal cancer mortality at a municipal level (8098 Spanish towns), over the period 1997–2006. We conducted an exploratory "near vs. far" analysis to estimate the relative risks (RR) of towns situated at a distance of less than 2 km from industrial installations. The analysis was repeated for each of the 24 industrial groups. RR and their 95% credible/confidence intervals (95%CI) were estimated on the basis of Poisson regression models, using two types of modelling: a) the conditional autoregressive Bayesian model proposed by Besag, York and Mollié, with explanatory variables; and b) a mixed regression model. Integrated nested Laplace approximations were used as a Bayesian inference tool. Results Statistically significant RRs were detected in the vicinity of mining industry (RR 1.258; 95%CI 1.082 - 1.463), paper and wood production (RR 1.071; 95%CI 1.007 – 1.140), food and beverage sector (RR 1.069; 95%CI 1.029 - 1.111), metal production and processing installations (RR 1.065; 95% CI 1.011 – 1.123) and ceramics (RR 1.050 ; 95%CI 1.004 – 1.099). Conclusions Given the exploratory nature of this study, it would seem advisable to check in other countries or with other designs, if the proximity of industries that emit pollutants into the air could be an added risk factor for colorectal cancer mortality. Nevertheless, some of the differences between men and women observed in the analyses of the industrial groups suggest that there may be a component of occupational exposure, little-studied in the case of cancers of the digestive system. PMID:22852770

Direct benefit of vaccinating boys along with girls against oncogenic human papillomavirus: bayesian evidence synthesis.

PubMed

Bogaards, Johannes A; Wallinga, Jacco; Brakenhoff, Ruud H; Meijer, Chris J L M; Berkhof, Johannes

2015-05-12

To assess the reduction in the vaccine preventable burden of cancer in men if boys are vaccinated along with girls against oncogenic human papillomavirus (HPV). Bayesian evidence synthesis approach used to evaluate the impact of vaccination against HPV types 16 and 18 on the burden of anal, penile, and oropharyngeal carcinomas among heterosexual men and men who have sex with men. The reduced transmission of vaccine-type HPV from vaccination of girls was assumed to lower the risk of HPV associated cancer in all men but not to affect the excess risk of HPV associated cancers among men who have sex with men. General population in the Netherlands. Inclusion of boys aged 12 into HPV vaccination programmes. Quality adjusted life years (QALYs) and numbers needed to vaccinate. Before HPV vaccination, 14.9 (95% credible interval 12.2 to 18.1) QALYs per thousand men were lost to vaccine preventable cancers associated with HPV in the Netherlands. This burden would be reduced by 37% (28% to 48%) if the vaccine uptake among girls remains at the current level of 60%. To prevent one additional case of cancer among men, 795 boys (660 to 987) would need to be vaccinated; with tumour specific numbers for anal, penile, and oropharyngeal cancer of 2162, 3486, and 1975, respectively. The burden of HPV related cancer in men would be reduced by 66% (53% to 805) if vaccine uptake among girls increases to 90%. In that case, 1735 boys (1240 to 2900) would need to be vaccinated to prevent an additional case; with tumour specific numbers for anal, penile, and oropharyngeal cancer of 2593, 29107, and 6484, respectively. Men will benefit indirectly from vaccination of girls but remain at risk of cancers associated with HPV. The incremental benefit of vaccinating boys when vaccine uptake among girls is high is driven by the prevention of anal carcinomas, which underscores the relevance of HPV prevention efforts for men who have sex with men. © Bogaards et al 2015.

Direct benefit of vaccinating boys along with girls against oncogenic human papillomavirus: bayesian evidence synthesis

PubMed Central

Wallinga, Jacco; Brakenhoff, Ruud H; Meijer, Chris J L M; Berkhof, Johannes

2015-01-01

Objective To assess the reduction in the vaccine preventable burden of cancer in men if boys are vaccinated along with girls against oncogenic human papillomavirus (HPV). Design Bayesian evidence synthesis approach used to evaluate the impact of vaccination against HPV types 16 and 18 on the burden of anal, penile, and oropharyngeal carcinomas among heterosexual men and men who have sex with men. The reduced transmission of vaccine-type HPV from vaccination of girls was assumed to lower the risk of HPV associated cancer in all men but not to affect the excess risk of HPV associated cancers among men who have sex with men. Setting General population in the Netherlands. Intervention Inclusion of boys aged 12 into HPV vaccination programmes. Main outcome measures Quality adjusted life years (QALYs) and numbers needed to vaccinate. Results Before HPV vaccination, 14.9 (95% credible interval 12.2 to 18.1) QALYs per thousand men were lost to vaccine preventable cancers associated with HPV in the Netherlands. This burden would be reduced by 37% (28% to 48%) if the vaccine uptake among girls remains at the current level of 60%. To prevent one additional case of cancer among men, 795 boys (660 to 987) would need to be vaccinated; with tumour specific numbers for anal, penile, and oropharyngeal cancer of 2162, 3486, and 1975, respectively. The burden of HPV related cancer in men would be reduced by 66% (53% to 805) if vaccine uptake among girls increases to 90%. In that case, 1735 boys (1240 to 2900) would need to be vaccinated to prevent an additional case; with tumour specific numbers for anal, penile, and oropharyngeal cancer of 2593, 29107, and 6484, respectively. Conclusions Men will benefit indirectly from vaccination of girls but remain at risk of cancers associated with HPV. The incremental benefit of vaccinating boys when vaccine uptake among girls is high is driven by the prevention of anal carcinomas, which underscores the relevance of HPV prevention efforts for men who have sex with men. PMID:25985328

A Surrogate-based Adaptive Sampling Approach for History Matching and Uncertainty Quantification

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Weixuan; Zhang, Dongxiao; Lin, Guang

A critical procedure in reservoir simulations is history matching (or data assimilation in a broader sense), which calibrates model parameters such that the simulation results are consistent with field measurements, and hence improves the credibility of the predictions given by the simulations. Often there exist non-unique combinations of parameter values that all yield the simulation results matching the measurements. For such ill-posed history matching problems, Bayesian theorem provides a theoretical foundation to represent different solutions and to quantify the uncertainty with the posterior PDF. Lacking an analytical solution in most situations, the posterior PDF may be characterized with a samplemore » of realizations, each representing a possible scenario. A novel sampling algorithm is presented here for the Bayesian solutions to history matching problems. We aim to deal with two commonly encountered issues: 1) as a result of the nonlinear input-output relationship in a reservoir model, the posterior distribution could be in a complex form, such as multimodal, which violates the Gaussian assumption required by most of the commonly used data assimilation approaches; 2) a typical sampling method requires intensive model evaluations and hence may cause unaffordable computational cost. In the developed algorithm, we use a Gaussian mixture model as the proposal distribution in the sampling process, which is simple but also flexible to approximate non-Gaussian distributions and is particularly efficient when the posterior is multimodal. Also, a Gaussian process is utilized as a surrogate model to speed up the sampling process. Furthermore, an iterative scheme of adaptive surrogate refinement and re-sampling ensures sampling accuracy while keeping the computational cost at a minimum level. The developed approach is demonstrated with an illustrative example and shows its capability in handling the above-mentioned issues. Multimodal posterior of the history matching problem is captured and are used to give a reliable production prediction with uncertainty quantification. The new algorithm reveals a great improvement in terms of computational efficiency comparing previously studied approaches for the sample problem.« less

Spatial analysis of MODIS aerosol optical depth, PM2.5, and chronic coronary heart disease.

PubMed

Hu, Zhiyong

2009-05-12

Numerous studies have found adverse health effects of acute and chronic exposure to fine particulate matter (PM2.5). Air pollution epidemiological studies relying on ground measurements provided by monitoring networks are often limited by sparse and unbalanced spatial distribution of the monitors. Studies have found correlations between satellite aerosol optical depth (AOD) and PM2.5 in some land regions. Satellite aerosol data may be used to extend the spatial coverage of PM2.5 exposure assessment. This study was to investigate correlation between PM2.5 and AOD in the conterminous USA, to derive a spatially complete PM2.5 surface by merging satellite AOD data and ground measurements based on the potential correlation, and to examine if there is an association of coronary heart disease with PM2.5. Years 2003 and 2004 daily MODIS (Moderate Resolution Imaging Spectrometer) Level 2 AOD images were collated with US EPA PM2.5 data covering the conterminous USA. Pearson's correlation analysis and geographically weighted regression (GWR) found that the relationship between PM2.5 and AOD is not spatially consistent across the conterminous states. The average correlation is 0.67 in the east and 0.22 in the west. GWR predicts well in the east and poorly in the west. The GWR model was used to derive a PM2.5 grid surface using the mean AOD raster calculated using the daily AOD data (RMSE = 1.67 microg/m3). Fitting of a Bayesian hierarchical model linking PM2.5 with age-race standardized mortality rates (SMRs) of chronic coronary heart disease found that areas with higher values of PM2.5 also show high rates of CCHD mortality: = 0.802, posterior 95% Bayesian credible interval (CI) = (0.386, 1.225). There is a spatial variation of the relationship between PM2.5 and AOD in the conterminous USA. In the eastern USA where AOD correlates well with PM2.5, AOD can be merged with ground PM2.5 data to derive a PM2.5 surface for epidemiological study. The study found that chronic coronary heart disease mortality rate increases with exposure to PM2.5.

Measuring Credibility Perceptions in CSR Communication: A Scale Development to Test Readers’ Perceived Credibility of CSR Reports

PubMed Central

Lock, Irina; Seele, Peter

2017-01-01

Credibility is central to communication but often jeopardized by “credibility gaps.” This is especially true for communication about corporate social responsibility (CSR). To date, no tool has been available to analyze stakeholders’ credibility perceptions of CSR communication. This article presents a series of studies conducted to develop a scale to assess the perceived credibility of CSR reports, one of CSR communication’s most important tools. The scale provides a novel operationalization of credibility using validity claims of Habermas’s ideal speech situation as subdimensions. The scale development process, carried out in five studies including a literature review, a Delphi study, and three validation studies applying confirmatory factor analysis, resulted in the 16-item Perceived Credibility (PERCRED) scale. The scale shows convergent, discriminant, concurrent, and nomological validity and is the first validated measure for analyzing credibility perceptions of CSR reports. PMID:29278260

Measuring Credibility Perceptions in CSR Communication: A Scale Development to Test Readers' Perceived Credibility of CSR Reports.

PubMed

Lock, Irina; Seele, Peter

2017-11-01

Credibility is central to communication but often jeopardized by "credibility gaps." This is especially true for communication about corporate social responsibility (CSR). To date, no tool has been available to analyze stakeholders' credibility perceptions of CSR communication. This article presents a series of studies conducted to develop a scale to assess the perceived credibility of CSR reports, one of CSR communication's most important tools. The scale provides a novel operationalization of credibility using validity claims of Habermas's ideal speech situation as subdimensions. The scale development process, carried out in five studies including a literature review, a Delphi study, and three validation studies applying confirmatory factor analysis, resulted in the 16-item Perceived Credibility (PERCRED) scale. The scale shows convergent, discriminant, concurrent, and nomological validity and is the first validated measure for analyzing credibility perceptions of CSR reports.

Source Credibility in Tobacco Control Messaging

PubMed Central

Schmidt, Allison M.; Ranney, Leah M.; Pepper, Jessica K.; Goldstein, Adam O.

2016-01-01

Objectives Perceived credibility of a message’s source can affect persuasion. This paper reviews how beliefs about the source of tobacco control messages may encourage attitude and behavior change. Methods We conducted a series of searches of the peer-reviewed literature using terms from communication and public health fields. We reviewed research on source credibility, its underlying concepts, and its relation to the persuasiveness of tobacco control messages. Results We recommend an agenda for future research to bridge the gaps between communication literature on source credibility and tobacco control research. Our recommendations are to study the impact of source credibility on persuasion with long-term behavior change outcomes, in different populations and demographic groups, by developing new credibility measures that are topic- and organization-specific, by measuring how credibility operates across media platforms, and by identifying factors that enhance credibility and persuasion. Conclusions This manuscript reviews the state of research on source credibility and identifies gaps that are maximally relevant to tobacco control communication. Knowing first whether a source is perceived as credible, and second, how to enhance perceived credibility, can inform the development of future tobacco control campaigns and regulatory communications. PMID:27525298

Bayesian estimation of differential transcript usage from RNA-seq data.

PubMed

Papastamoulis, Panagiotis; Rattray, Magnus

2017-11-27

Next generation sequencing allows the identification of genes consisting of differentially expressed transcripts, a term which usually refers to changes in the overall expression level. A specific type of differential expression is differential transcript usage (DTU) and targets changes in the relative within gene expression of a transcript. The contribution of this paper is to: (a) extend the use of cjBitSeq to the DTU context, a previously introduced Bayesian model which is originally designed for identifying changes in overall expression levels and (b) propose a Bayesian version of DRIMSeq, a frequentist model for inferring DTU. cjBitSeq is a read based model and performs fully Bayesian inference by MCMC sampling on the space of latent state of each transcript per gene. BayesDRIMSeq is a count based model and estimates the Bayes Factor of a DTU model against a null model using Laplace's approximation. The proposed models are benchmarked against the existing ones using a recent independent simulation study as well as a real RNA-seq dataset. Our results suggest that the Bayesian methods exhibit similar performance with DRIMSeq in terms of precision/recall but offer better calibration of False Discovery Rate.

Testing adaptive toolbox models: a Bayesian hierarchical approach.

PubMed

Scheibehenne, Benjamin; Rieskamp, Jörg; Wagenmakers, Eric-Jan

2013-01-01

Many theories of human cognition postulate that people are equipped with a repertoire of strategies to solve the tasks they face. This theoretical framework of a cognitive toolbox provides a plausible account of intra- and interindividual differences in human behavior. Unfortunately, it is often unclear how to rigorously test the toolbox framework. How can a toolbox model be quantitatively specified? How can the number of toolbox strategies be limited to prevent uncontrolled strategy sprawl? How can a toolbox model be formally tested against alternative theories? The authors show how these challenges can be met by using Bayesian inference techniques. By means of parameter recovery simulations and the analysis of empirical data across a variety of domains (i.e., judgment and decision making, children's cognitive development, function learning, and perceptual categorization), the authors illustrate how Bayesian inference techniques allow toolbox models to be quantitatively specified, strategy sprawl to be contained, and toolbox models to be rigorously tested against competing theories. The authors demonstrate that their approach applies at the individual level but can also be generalized to the group level with hierarchical Bayesian procedures. The suggested Bayesian inference techniques represent a theoretical and methodological advancement for toolbox theories of cognition and behavior.

Techniques for Conducting Effective Concept Design and Design-to-Cost Trade Studies

NASA Technical Reports Server (NTRS)

Di Pietro, David A.

2015-01-01

Concept design plays a central role in project success as its product effectively locks the majority of system life cycle cost. Such extraordinary leverage presents a business case for conducting concept design in a credible fashion, particularly for first-of-a-kind systems that advance the state of the art and that have high design uncertainty. A key challenge, however, is to know when credible design convergence has been achieved in such systems. Using a space system example, this paper characterizes the level of convergence needed for concept design in the context of technical and programmatic resource margins available in preliminary design and highlights the importance of design and cost evaluation learning curves in determining credible convergence. It also provides techniques for selecting trade study cases that promote objective concept evaluation, help reveal unknowns, and expedite convergence within the trade space and conveys general practices for conducting effective concept design-to-cost studies.

Bayesian modeling of flexible cognitive control

PubMed Central

Jiang, Jiefeng; Heller, Katherine; Egner, Tobias

2014-01-01

“Cognitive control” describes endogenous guidance of behavior in situations where routine stimulus-response associations are suboptimal for achieving a desired goal. The computational and neural mechanisms underlying this capacity remain poorly understood. We examine recent advances stemming from the application of a Bayesian learner perspective that provides optimal prediction for control processes. In reviewing the application of Bayesian models to cognitive control, we note that an important limitation in current models is a lack of a plausible mechanism for the flexible adjustment of control over conflict levels changing at varying temporal scales. We then show that flexible cognitive control can be achieved by a Bayesian model with a volatility-driven learning mechanism that modulates dynamically the relative dependence on recent and remote experiences in its prediction of future control demand. We conclude that the emergent Bayesian perspective on computational mechanisms of cognitive control holds considerable promise, especially if future studies can identify neural substrates of the variables encoded by these models, and determine the nature (Bayesian or otherwise) of their neural implementation. PMID:24929218

The function of credibility in information processing for risk perception.

PubMed

Trumbo, Craig W; McComas, Katherine A

2003-04-01

This study examines how credibility affects the way people process information and how they subsequently perceive risk. Three conceptual areas are brought together in this analysis: the psychometric model of risk perception, Eagly and Chaiken's heuristic-systematic information processing model, and Meyer's credibility index. Data come from a study of risk communication in the circumstance of state health department investigations of suspected cancer clusters (five cases, N = 696). Credibility is assessed for three information sources: state health departments, citizen groups, and industries involved in each case. Higher credibility for industry and the state directly predicts lower risk perception, whereas high credibility for citizen groups predicts greater risk perception. A path model shows that perceiving high credibility for industry and state-and perceiving low credibility for citizen groups-promotes heuristic processing, which in turn is a strong predictor of lower risk perception. Alternately, perceiving industry and the state to have low credibility also promotes greater systematic processing, which consistently leads to perception of greater risk. Between a one-fifth and one-third of the effect of credibility on risk perception is shown to be indirectly transmitted through information processing.

Treatment strategies for coronary in-stent restenosis: systematic review and hierarchical Bayesian network meta-analysis of 24 randomised trials and 4880 patients

PubMed Central

Giacoppo, Daniele; Gargiulo, Giuseppe; Aruta, Patrizia; Capranzano, Piera; Tamburino, Corrado

2015-01-01

Study question What is the most safe and effective interventional treatment for coronary in-stent restenosis? Methods In a hierarchical Bayesian network meta-analysis, PubMed, Embase, Scopus, Cochrane Library, Web of Science, ScienceDirect, and major scientific websites were screened up to 10 August 2015. Randomised controlled trials of patients with any type of coronary in-stent restenosis (either of bare metal stents or drug eluting stents; and either first or recurrent instances) were included. Trials including multiple treatments at the same time in the same group or comparing variants of the same intervention were excluded. Primary endpoints were target lesion revascularisation and late lumen loss, both at six to 12 months. The main analysis was complemented by network subanalyses, standard pairwise comparisons, and subgroup and sensitivity analyses. Study answer and limitations Twenty four trials (4880 patients), including seven interventional treatments, were identified. Compared with plain balloons, bare metal stents, brachytherapy, rotational atherectomy, and cutting balloons, drug coated balloons and drug eluting stents were associated with a reduced risk of target lesion revascularisation and major adverse cardiac events, and with reduced late lumen loss. Treatment ranking indicated that drug eluting stents had the highest probability (61.4%) of being the most effective for target lesion vascularisation; drug coated balloons were similarly indicated as the most effective treatment for late lumen loss (probability 70.3%). The comparative efficacy of drug coated balloons and drug eluting stents was similar for target lesion revascularisation (summary odds ratio 1.10, 95% credible interval 0.59 to 2.01) and late lumen loss reduction (mean difference in minimum lumen diameter 0.04 mm, 95% credible interval −0.20 to 0.10). Risks of death, myocardial infarction, and stent thrombosis were comparable across all treatments, but these analyses were limited by a low number of events. Trials had heterogeneity regarding investigation periods, baseline characteristics, and endpoint reporting, with a lack of information at long term follow-up. Direct and indirect evidence was also inconsistent for the comparison between drug eluting stents and drug coated balloons. What this study adds Compared with other currently available interventional treatments for coronary in-stent restenosis, drug coated balloons and drug eluting stents are associated with superior clinical and angiographic outcomes, with a similar comparative efficacy. Funding, competing interests, data sharing This study received no external funding. The authors declare no competing interests. No additional data available. PMID:26537292

Bayesian validation of a serum and milk ELISA for antibodies against Mycobacterium avium subspecies paratuberculosis in Greek dairy goats across lactation.

PubMed

Angelidou, E; Kostoulas, P; Leontides, L

2014-02-01

We validated a commercial (Idexx Pourquier, Montpellier, France) serum and milk indirect ELISA that detects antibodies against Mycobacterium avium ssp. paratuberculosis (MAP) in Greek dairy goats. Each goat was sampled 4 times, starting from kidding and covering early, mid, and late lactation. A total of 1,268 paired milk (or colostrum) and serum samples were collected during the 7-mo lactation period. Bayesian latent class models, which allow for the continuous interpretation of test results, were used to derive the distribution of the serum and milk ELISA response for healthy and MAP-infected individuals at each lactation stage. Both serum and milk ELISA, in all lactation stages, had average and similar overall discriminatory ability as measured by the area under the curve (AUC). For each test, the smallest overlap between the distribution of the healthy and MAP-infected does was in late lactation. At this stage, the AUC was 0.89 (95% credible interval: 0.70; 0.98) and 0.92 (0.74; 0.99) for the milk and serum ELISA, respectively. Both tests had comparable sensitivities and specificities at the recommended cutoffs across lactation. Lowering the cutoffs led to an increase in sensitivity without serious loss in specificity. In conclusion, the milk ELISA was as accurate as the serum ELISA. Therefore, it could serve as the diagnostic tool of choice, especially during the implementation of MAP control programs that require frequent testing, because milk sampling is a noninvasive, rapid, and easy process. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Assessing the association between natural food folate intake and blood folate concentrations: a systematic review and Bayesian meta-analysis of trials and observational studies.

PubMed

Marchetta, Claire M; Devine, Owen J; Crider, Krista S; Tsang, Becky L; Cordero, Amy M; Qi, Yan Ping; Guo, Jing; Berry, Robert J; Rosenthal, Jorge; Mulinare, Joseph; Mersereau, Patricia; Hamner, Heather C

2015-04-10

Folate is found naturally in foods or as synthetic folic acid in dietary supplements and fortified foods. Adequate periconceptional folic acid intake can prevent neural tube defects. Folate intake impacts blood folate concentration; however, the dose-response between natural food folate and blood folate concentrations has not been well described. We estimated this association among healthy females. A systematic literature review identified studies (1 1992-3 2014) with both natural food folate intake alone and blood folate concentration among females aged 12-49 years. Bayesian methods were used to estimate regression model parameters describing the association between natural food folate intake and subsequent blood folate concentration. Seven controlled trials and 29 observational studies met the inclusion criteria. For the six studies using microbiologic assay (MA) included in the meta-analysis, we estimate that a 6% (95% Credible Interval (CrI): 4%, 9%) increase in red blood cell (RBC) folate concentration and a 7% (95% CrI: 1%, 12%) increase in serum/plasma folate concentration can occur for every 10% increase in natural food folate intake. Using modeled results, we estimate that a natural food folate intake of ≥ 450 μg dietary folate equivalents (DFE)/day could achieve the lower bound of an RBC folate concentration (~ 1050 nmol/L) associated with the lowest risk of a neural tube defect. Natural food folate intake affects blood folate concentration and adequate intakes could help women achieve a RBC folate concentration associated with a risk of 6 neural tube defects/10,000 live births.

A comparison of discontinuation rates of tofacitinib and biologic disease-modifying anti-rheumatic drugs in rheumatoid arthritis: a systematic review and Bayesian network meta-analysis.

PubMed

Park, Sun-Kyeong; Lee, Min-Young; Jang, Eun-Jin; Kim, Hye-Lin; Ha, Dong-Mun; Lee, Eui-Kyung

2017-01-01

The purpose of this study was to compare the discontinuation rates of tofacitinib and biologics (tumour necrosis factor inhibitors (TNFi), abatacept, rituximab, and tocilizumab) in rheumatoid arthritis (RA) patients considering inadequate responses (IRs) to previous treatment(s). Randomised controlled trials of tofacitinib and biologics - reporting at least one total discontinuation, discontinuation due to lack of efficacy (LOE), and discontinuation due to adverse events (AEs) - were identified through systematic review. The analyses were conducted for patients with IRs to conventional synthetic disease-modifying anti-rheumatic drugs (cDMARDs) and for patients with biologics-IR, separately. Bayesian network meta-analysis was used to estimate rate ratio (RR) of a biologic relative to tofacitinib with 95% credible interval (CrI), and probability of RR being <1 (P[RR<1]). The analyses of 34 studies showed no significant differences in discontinuation rates between tofacitinib and biologics in the cDMARDs-IR group. In the biologics-IR group, however, TNFi (RR 0.17, 95% CrI 0.01-3.61, P[RR<1] 92.0%) and rituximab (RR 0.20, 95% CrI 0.01-2.91, P[RR<1] 92.3%) showed significantly lower total discontinuation rates than tofacitinib did. Despite the difference, discontinuation cases owing to LOE and AEs revealed that tofacitinib was comparable to the biologics. The comparability of discontinuation rate between tofacitinib and biologics was different based on previous treatments and discontinuation reasons: LOE, AEs, and total (due to other reasons). Therefore, those factors need to be considered to decide the optimal treatment strategy.

Bayesian estimation of the accuracy of the calf respiratory scoring chart and ultrasonography for the diagnosis of bovine respiratory disease in pre-weaned dairy calves.

PubMed

Buczinski, Sébastien; L Ollivett, Terri; Dendukuri, Nandini

2015-05-01

There is currently no gold standard method for the diagnosis of bovine respiratory disease (BRD) complex in Holstein pre-weaned dairy calves. Systematic thoracic ultrasonography (TUS) has been used as a proxy for BRD, but cannot be directly used by producers. The Wisconsin calf respiratory scoring chart (CRSC) is a simpler alternative, but with unknown accuracy. Our objective was to estimate the accuracy of CRSC, while adjusting for the lack of a gold standard. Two cross sectional study populations with a high BRD prevalence (n=106 pre-weaned Holstein calves) and an average BRD prevalence (n=85 pre-weaned Holstein calves) from North America were studied. All calves were simultaneously assessed using CRSC (cutoff used ≥ 5) and TUS (cutoff used ≥ 1cm of lung consolidation). Bayesian latent class models allowing for conditional dependence were used with informative priors for BRD prevalence and TUS accuracy (sensitivity (Se) and specificity (Sp)) and non-informative priors for CRSC accuracies. Robustness of the model was tested by relaxing priors for prevalence or TUS accuracy. The SeCRSC (95% credible interval (CI)) and SpCRSC were 62.4% (47.9-75.8) and 74.1% (64.9-82.8) respectively. The SeTUS was 79.4% (66.4-90.9) and SpTUS was 93.9% (88.0-97.6). The imperfect accuracy of CRSC and TUS should be taken into account when using those tools to assess BRD status. Copyright © 2015 Elsevier B.V. All rights reserved.

Bayesian probabilities for Mw 9.0+ earthquakes in the Aleutian Islands from a regionally scaled global rate

NASA Astrophysics Data System (ADS)

Butler, Rhett; Frazer, L. Neil; Templeton, William J.

2016-05-01

We use the global rate of Mw ≥ 9.0 earthquakes, and standard Bayesian procedures, to estimate the probability of such mega events in the Aleutian Islands, where they pose a significant risk to Hawaii. We find that the probability of such an earthquake along the Aleutians island arc is 6.5% to 12% over the next 50 years (50% credibility interval) and that the annualized risk to Hawai'i is about $30 M. Our method (the regionally scaled global rate method or RSGR) is to scale the global rate of Mw 9.0+ events in proportion to the fraction of global subduction (units of area per year) that takes place in the Aleutians. The RSGR method assumes that Mw 9.0+ events are a Poisson process with a rate that is both globally and regionally stationary on the time scale of centuries, and it follows the principle of Burbidge et al. (2008) who used the product of fault length and convergence rate, i.e., the area being subducted per annum, to scale the Poisson rate for the GSS to sections of the Indonesian subduction zone. Before applying RSGR to the Aleutians, we first apply it to five other regions of the global subduction system where its rate predictions can be compared with those from paleotsunami, paleoseismic, and geoarcheology data. To obtain regional rates from paleodata, we give a closed-form solution for the probability density function of the Poisson rate when event count and observation time are both uncertain.

Parameter Estimation for Compact Binaries with Ground-Based Gravitational-Wave Observations Using the LALInference

NASA Technical Reports Server (NTRS)

Veitch, J.; Raymond, V.; Farr, B.; Farr, W.; Graff, P.; Vitale, S.; Aylott, B.; Blackburn, K.; Christensen, N.; Coughlin, M.

2015-01-01

The Advanced LIGO and Advanced Virgo gravitational wave (GW) detectors will begin operation in the coming years, with compact binary coalescence events a likely source for the first detections. The gravitational waveforms emitted directly encode information about the sources, including the masses and spins of the compact objects. Recovering the physical parameters of the sources from the GW observations is a key analysis task. This work describes the LALInference software library for Bayesian parameter estimation of compact binary signals, which builds on several previous methods to provide a well-tested toolkit which has already been used for several studies. We show that our implementation is able to correctly recover the parameters of compact binary signals from simulated data from the advanced GW detectors. We demonstrate this with a detailed comparison on three compact binary systems: a binary neutron star (BNS), a neutron star - black hole binary (NSBH) and a binary black hole (BBH), where we show a cross-comparison of results obtained using three independent sampling algorithms. These systems were analysed with non-spinning, aligned spin and generic spin configurations respectively, showing that consistent results can be obtained even with the full 15-dimensional parameter space of the generic spin configurations. We also demonstrate statistically that the Bayesian credible intervals we recover correspond to frequentist confidence intervals under correct prior assumptions by analysing a set of 100 signals drawn from the prior. We discuss the computational cost of these algorithms, and describe the general and problem-specific sampling techniques we have used to improve the efficiency of sampling the compact binary coalescence (CBC) parameter space.

Assessing the social and environmental determinants of pertussis epidemics in Queensland, Australia: a Bayesian spatio-temporal analysis.

PubMed

Huang, X; Lambert, S; Lau, C; Soares Magalhaes, R J; Marquess, J; Rajmokan, M; Milinovich, G; Hu, W

2017-04-01

Pertussis epidemics have displayed substantial spatial heterogeneity in countries with high socioeconomic conditions and high vaccine coverage. This study aims to investigate the relationship between pertussis risk and socio-environmental factors on the spatio-temporal variation underlying pertussis infection. We obtained daily case numbers of pertussis notifications from Queensland Health, Australia by postal area, for the period January 2006 to December 2012. A Bayesian spatio-temporal model was used to quantify the relationship between monthly pertussis incidence and socio-environmental factors. The socio-environmental factors included monthly mean minimum temperature (MIT), monthly mean vapour pressure (VAP), Queensland school calendar pattern (SCP), and socioeconomic index for area (SEIFA). An increase in pertussis incidence was observed from 2006 to 2010 and a slight decrease from 2011 to 2012. Spatial analyses showed pertussis incidence across Queensland postal area to be low and more spatially homogeneous during 2006-2008; incidence was higher and more spatially heterogeneous after 2009. The results also showed that the average decrease in monthly pertussis incidence was 3·1% [95% credible interval (CrI) 1·3-4·8] for each 1 °C increase in monthly MIT, while average increase in monthly pertussis incidences were 6·2% (95% CrI 0·4-12·4) and 2% (95% CrI 1-3) for SCP periods and for each 10-unit increase in SEIFA, respectively. This study demonstrated that pertussis transmission is significantly associated with MIT, SEIFA, and SCP. Mapping derived from this work highlights the potential for future investigation and areas for focusing future control strategies.

Readability, credibility and quality of patient information for hypogonadism and testosterone replacement therapy on the Internet.

PubMed

McBride, J A; Carson, C C; Coward, R M

2017-05-01

The incidence of hypogonadism and use of testosterone replacement therapy (TRT) are rising, while data evaluating the complexity and quality of health-care information available to patients on the Internet for hypogonadism or TRT are lacking. This study focuses on characterizing the readability, credibility and quality of patient-centered information for hypogonadism on the Internet. A Google search was performed to identify top-ranked websites offering patient-centered information on hypogonadism and TRT. Readability was quantified by reading grade level using several validated instruments. Credibility and quality were determined by several additional criteria, including authorship, references, health-care information quality certification and breadth of topic discussion. Twenty of 75 total sites identified (27%) met the inclusion and exclusion criteria and were evaluated. The mean reading grade level was 13.1 (interquartile range 11.7-15.1), with all websites demonstrating reading levels significantly above recommended levels. Less than half (45%) of the sites were neither authored nor reviewed by a physician, 60% contained at least one reference and 40% were certified for displaying quality health-care information. Over half (55%) did not comprehensively discuss management of hypogonadism or mention treatment-associated risks. In conclusion, the majority of patient-centered information available on the Internet regarding hypogonadism or TRT is of poor quality and too complex for the average patient to comprehend. These results highlight a critical shortage in easily accessible, high-quality, comprehensible online patient health-care information on hypogonadism and TRT.

Revised standards for statistical evidence.

PubMed

Johnson, Valen E

2013-11-26

Recent advances in Bayesian hypothesis testing have led to the development of uniformly most powerful Bayesian tests, which represent an objective, default class of Bayesian hypothesis tests that have the same rejection regions as classical significance tests. Based on the correspondence between these two classes of tests, it is possible to equate the size of classical hypothesis tests with evidence thresholds in Bayesian tests, and to equate P values with Bayes factors. An examination of these connections suggest that recent concerns over the lack of reproducibility of scientific studies can be attributed largely to the conduct of significance tests at unjustifiably high levels of significance. To correct this problem, evidence thresholds required for the declaration of a significant finding should be increased to 25-50:1, and to 100-200:1 for the declaration of a highly significant finding. In terms of classical hypothesis tests, these evidence standards mandate the conduct of tests at the 0.005 or 0.001 level of significance.

Bayesian Analysis of the Association between Family-Level Factors and Siblings' Dental Caries.

PubMed

Wen, A; Weyant, R J; McNeil, D W; Crout, R J; Neiswanger, K; Marazita, M L; Foxman, B

2017-07-01

We conducted a Bayesian analysis of the association between family-level socioeconomic status and smoking and the prevalence of dental caries among siblings (children from infant to 14 y) among children living in rural and urban Northern Appalachia using data from the Center for Oral Health Research in Appalachia (COHRA). The observed proportion of siblings sharing caries was significantly different from predicted assuming siblings' caries status was independent. Using a Bayesian hierarchical model, we found the inclusion of a household factor significantly improved the goodness of fit. Other findings showed an inverse association between parental education and siblings' caries and a positive association between households with smokers and siblings' caries. Our study strengthens existing evidence suggesting that increased parental education and decreased parental cigarette smoking are associated with reduced childhood caries in the household. Our results also demonstrate the value of a Bayesian approach, which allows us to include household as a random effect, thereby providing more accurate estimates than obtained using generalized linear mixed models.

A New Paradigm for Credibly Administering Placebo Alcohol to Underage Drinkers

PubMed Central

Bernstein, Michael H.; Colby, Suzanne M.

2015-01-01

Background The primary goal of this study was to establish a paradigm for credibly administering placebo alcohol to underage drinkers. We also sought to create a new, valid procedure for establishing placebo alcohol believability. Method Participants were 138 American college students (66.7% female) predominantly (90.0%) under the legal drinking age. Groups of 2–3 participants and one same-sex confederate consumed mixed drinks, purportedly containing alcohol, ad-lib in a naturalistic bar-laboratory for 20 minutes. All beverages, however, were non-alcoholic but we used visual, olfactory, and taste cues to maximize placebo credibility. Also, the confederate made two scripted statements designed to increase the perception of drinking real alcohol. After the drinking portion, participants responded to survey items related to alcohol consumption and intoxication. Next, they were individually debriefed, with open-ended responses used to make a determination of whether the participant was deceived with respect to placebo alcohol. Results All participants estimated consuming some amount of alcohol. However, using a more conservative criteria for estimating alcohol believability based on the debrief, 89.1% of participants were classified as deceived. Deceived participants were much more likely to estimate having a positive Blood Alcohol Content, and to say their current level of intoxication was typical given the amount of alcohol consumed than non-deceived participants. Discussion Credibly administering placebo alcohol to underage drinkers is possible. This approach carries great potential for future laboratory work. In addition, the methodology used here to classify participants as deceived or not deceived appears valid based on self-reported BAC estimation and intoxication levels. PMID:26334562

A new paradigm for credibly administering placebo alcohol to underage drinkers.

PubMed

Bernstein, Michael H; Wood, Mark D; Colby, Suzanne M

2016-01-01

The primary goal of this study was to establish a paradigm for credibly administering placebo alcohol to underage drinkers. We also sought to create a new, valid procedure for establishing placebo alcohol believability. Participants were 138 American college students (66.7% female) predominantly (90.0%) under the legal drinking age. Groups of 2-3 participants and one same-sex confederate consumed mixed drinks, purportedly containing alcohol, ad-lib in a naturalistic bar-laboratory for 20 min. All beverages, however, were non-alcoholic but we used visual, olfactory, and taste cues to maximize placebo credibility. Also, the confederate made two scripted statements designed to increase the perception of drinking real alcohol. After the drinking portion, participants responded to survey items related to alcohol consumption and intoxication. Next, they were individually debriefed, with open-ended responses used to make a determination of whether the participant was deceived with respect to placebo alcohol. All participants estimated consuming some amount of alcohol. However, using a more conservative criteria for estimating alcohol believability based on the debrief, 89.1% of participants were classified as deceived. Deceived participants were much more likely to estimate having a positive blood alcohol content and to say that their current level of intoxication was typical given the amount of alcohol consumed than non-deceived participants. Credibly administering placebo alcohol to underage drinkers is possible. This approach carries great potential for future laboratory work. In addition, the methodology used here to classify participants as deceived or not deceived appears valid based on self-reported BAC estimation and intoxication levels. Copyright © 2015. Published by Elsevier Ltd.

Collinear Latent Variables in Multilevel Confirmatory Factor Analysis: A Comparison of Maximum Likelihood and Bayesian Estimations.

PubMed

Can, Seda; van de Schoot, Rens; Hox, Joop

2015-06-01

Because variables may be correlated in the social and behavioral sciences, multicollinearity might be problematic. This study investigates the effect of collinearity manipulated in within and between levels of a two-level confirmatory factor analysis by Monte Carlo simulation. Furthermore, the influence of the size of the intraclass correlation coefficient (ICC) and estimation method; maximum likelihood estimation with robust chi-squares and standard errors and Bayesian estimation, on the convergence rate are investigated. The other variables of interest were rate of inadmissible solutions and the relative parameter and standard error bias on the between level. The results showed that inadmissible solutions were obtained when there was between level collinearity and the estimation method was maximum likelihood. In the within level multicollinearity condition, all of the solutions were admissible but the bias values were higher compared with the between level collinearity condition. Bayesian estimation appeared to be robust in obtaining admissible parameters but the relative bias was higher than for maximum likelihood estimation. Finally, as expected, high ICC produced less biased results compared to medium ICC conditions.

On the applicability of surrogate-based Markov chain Monte Carlo-Bayesian inversion to the Community Land Model: Case studies at flux tower sites: SURROGATE-BASED MCMC FOR CLM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Maoyi; Ray, Jaideep; Hou, Zhangshuan

2016-07-04

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesianmore » model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically-average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. Analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.« less

The Performance of the Date-Randomization Test in Phylogenetic Analyses of Time-Structured Virus Data.

PubMed

Duchêne, Sebastián; Duchêne, David; Holmes, Edward C; Ho, Simon Y W

2015-07-01

Rates and timescales of viral evolution can be estimated using phylogenetic analyses of time-structured molecular sequences. This involves the use of molecular-clock methods, calibrated by the sampling times of the viral sequences. However, the spread of these sampling times is not always sufficient to allow the substitution rate to be estimated accurately. We conducted Bayesian phylogenetic analyses of simulated virus data to evaluate the performance of the date-randomization test, which is sometimes used to investigate whether time-structured data sets have temporal signal. An estimate of the substitution rate passes this test if its mean does not fall within the 95% credible intervals of rate estimates obtained using replicate data sets in which the sampling times have been randomized. We find that the test sometimes fails to detect rate estimates from data with no temporal signal. This error can be minimized by using a more conservative criterion, whereby the 95% credible interval of the estimate with correct sampling times should not overlap with those obtained with randomized sampling times. We also investigated the behavior of the test when the sampling times are not uniformly distributed throughout the tree, which sometimes occurs in empirical data sets. The test performs poorly in these circumstances, such that a modification to the randomization scheme is needed. Finally, we illustrate the behavior of the test in analyses of nucleotide sequences of cereal yellow dwarf virus. Our results validate the use of the date-randomization test and allow us to propose guidelines for interpretation of its results. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

On the applicability of surrogate-based MCMC-Bayesian inversion to the Community Land Model: Case studies at Flux tower sites

DOE PAGES

Huang, Maoyi; Ray, Jaideep; Hou, Zhangshuan; ...

2016-06-01

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesianmore » model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. As a result, analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.« less

On the applicability of surrogate-based MCMC-Bayesian inversion to the Community Land Model: Case studies at Flux tower sites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Maoyi; Ray, Jaideep; Hou, Zhangshuan

The Community Land Model (CLM) has been widely used in climate and Earth system modeling. Accurate estimation of model parameters is needed for reliable model simulations and predictions under current and future conditions, respectively. In our previous work, a subset of hydrological parameters has been identified to have significant impact on surface energy fluxes at selected flux tower sites based on parameter screening and sensitivity analysis, which indicate that the parameters could potentially be estimated from surface flux observations at the towers. To date, such estimates do not exist. In this paper, we assess the feasibility of applying a Bayesianmore » model calibration technique to estimate CLM parameters at selected flux tower sites under various site conditions. The parameters are estimated as a joint probability density function (PDF) that provides estimates of uncertainty of the parameters being inverted, conditional on climatologically average latent heat fluxes derived from observations. We find that the simulated mean latent heat fluxes from CLM using the calibrated parameters are generally improved at all sites when compared to those obtained with CLM simulations using default parameter sets. Further, our calibration method also results in credibility bounds around the simulated mean fluxes which bracket the measured data. The modes (or maximum a posteriori values) and 95% credibility intervals of the site-specific posterior PDFs are tabulated as suggested parameter values for each site. As a result, analysis of relationships between the posterior PDFs and site conditions suggests that the parameter values are likely correlated with the plant functional type, which needs to be confirmed in future studies by extending the approach to more sites.« less

Trial-by-Trial Changes in a Priori Informational Value of External Cues and Subjective Expectancies in Human Auditory Attention

PubMed Central

Arjona, Antonio; Gómez, Carlos M.

2011-01-01

Background Preparatory activity based on a priori probabilities generated in previous trials and subjective expectancies would produce an attentional bias. However, preparation can be correct (valid) or incorrect (invalid) depending on the actual target stimulus. The alternation effect refers to the subjective expectancy that a target will not be repeated in the same position, causing RTs to increase if the target location is repeated. The present experiment, using the Posner's central cue paradigm, tries to demonstrate that not only the credibility of the cue, but also the expectancy about the next position of the target are changedin a trial by trial basis. Sequences of trials were analyzed. Results The results indicated an increase in RT benefits when sequences of two and three valid trials occurred. The analysis of errors indicated an increase in anticipatory behavior which grows as the number of valid trials is increased. On the other hand, there was also an RT benefit when a trial was preceded by trials in which the position of the target changed with respect to the current trial (alternation effect). Sequences of two alternations or two repetitions were faster than sequences of trials in which a pattern of repetition or alternation is broken. Conclusions Taken together, these results suggest that in Posner's central cue paradigm, and with regard to the anticipatory activity, the credibility of the external cue and of the endogenously anticipated patterns of target location are constantly updated. The results suggest that Bayesian rules are operating in the generation of anticipatory activity as a function of the previous trial's outcome, but also on biases or prior beliefs like the “gambler fallacy”. PMID:21698164

On Correlated-noise Analyses Applied to Exoplanet Light Curves

NASA Astrophysics Data System (ADS)

Cubillos, Patricio; Harrington, Joseph; Loredo, Thomas J.; Lust, Nate B.; Blecic, Jasmina; Stemm, Madison

2017-01-01

Time-correlated noise is a significant source of uncertainty when modeling exoplanet light-curve data. A correct assessment of correlated noise is fundamental to determine the true statistical significance of our findings. Here, we review three of the most widely used correlated-noise estimators in the exoplanet field, the time-averaging, residual-permutation, and wavelet-likelihood methods. We argue that the residual-permutation method is unsound in estimating the uncertainty of parameter estimates. We thus recommend to refrain from this method altogether. We characterize the behavior of the time averaging’s rms-versus-bin-size curves at bin sizes similar to the total observation duration, which may lead to underestimated uncertainties. For the wavelet-likelihood method, we note errors in the published equations and provide a list of corrections. We further assess the performance of these techniques by injecting and retrieving eclipse signals into synthetic and real Spitzer light curves, analyzing the results in terms of the relative-accuracy and coverage-fraction statistics. Both the time-averaging and wavelet-likelihood methods significantly improve the estimate of the eclipse depth over a white-noise analysis (a Markov-chain Monte Carlo exploration assuming uncorrelated noise). However, the corrections are not perfect when retrieving the eclipse depth from Spitzer data sets, these methods covered the true (injected) depth within the 68% credible region in only ˜45%-65% of the trials. Lastly, we present our open-source model-fitting tool, Multi-Core Markov-Chain Monte Carlo (MC3). This package uses Bayesian statistics to estimate the best-fitting values and the credible regions for the parameters for a (user-provided) model. MC3 is a Python/C code, available at https://github.com/pcubillos/MCcubed.

Adalimumab versus infliximab for the treatment of moderate to severe ulcerative colitis in adult patients naïve to anti-TNF therapy: an indirect treatment comparison meta-analysis.

PubMed

Thorlund, Kristian; Druyts, Eric; Mills, Edward J; Fedorak, Richard N; Marshall, John K

2014-07-01

To compare the efficacy of adalimumab and infliximab for the treatment of moderate to severe ulcerative colitis using indirect treatment comparison meta-analysis. A systematic review and Bayesian indirect treatment comparison meta-analyses were performed for seven patient-important clinical outcomes at 8 weeks and 52 weeks. Odds ratio (OR) estimates and associated 95% credible intervals (CrIs) were produced. Five eligible RCTs informed clinical remission, response, mucosal healing, quality of life, colectomy, serious adverse events, and discontinuation due to adverse events at 8 weeks and 52 weeks. At 8 weeks of induction therapy, clinical remission (OR=0.42, 95% CrI 0.17-0.97), clinical response (OR=0.45, 95% CrI 0.23-0.89) and mucosal healing (OR=0.46, 95% CrI 0.25-0.86) statistically favored infliximab. However, after 52 weeks of maintenance therapy OR estimates showed no significant difference between infliximab and adalimumab. For serious adverse events and discontinuations due to adverse events, adalimumab and infliximab were similar to placebo. Further, the indirect treatment comparison of adalimumab and infliximab yielded odds ratios close to 1.00 with wide credible intervals. The findings of this indirect treatment comparison meta-analysis suggest that both infliximab and adalimumab are superior to placebo in the treatment of moderate to moderately severe ulcerative colitis. While infliximab is statistically more effective than adalimumab in the induction of remission, response and mucosal healing at 8 weeks, infliximab and adalimumab are comparable in efficacy at 52 weeks of maintenance treatment. Copyright © 2014 European Crohn's and Colitis Organisation. Published by Elsevier B.V. All rights reserved.

Integrated System Health Management (ISHM): Systematic Capability Implementation

NASA Technical Reports Server (NTRS)

Figueroa, Fernando; Holland, Randy; Schmalzwel, John; Duncavage, Dan

2006-01-01

This paper provides a credible approach for implementation of ISHM capability in any system. The requirements and processes to implement ISHM capability are unique in that a credible capability is initially implemented at a low level, and it evolves to achieve higher levels by incremental augmentation. In contrast, typical capabilities, such as thrust of an engine, are implemented once at full Functional Capability Level (FCL), which is not designed to change during the life of the product. The approach will describe core ingredients (e.g. technologies, architectures, etc.) and when and how ISHM capabilities may be implemented. A specific architecture/taxonomy/ontology will be described, as well as a prototype software environment that supports development of ISHM capability. This paper will address implementation of system-wide ISHM as a core capability, and ISHM for specific subsystems as expansions and evolution, but always focusing on achieving an integrated capability.

A FAST BAYESIAN METHOD FOR UPDATING AND FORECASTING HOURLY OZONE LEVELS

EPA Science Inventory

A Bayesian hierarchical space-time model is proposed by combining information from real-time ambient AIRNow air monitoring data, and output from a computer simulation model known as the Community Multi-scale Air Quality (Eta-CMAQ) forecast model. A model validation analysis shows...

The role of corporate credibility in legitimizing disease promotion.

PubMed

McDaniel, Patricia A; Malone, Ruth E

2009-03-01

We explored what corporate "credibility" means to tobacco companies to determine why it matters to companies and what a lack of credibility means to them. We collected documents from an online tobacco industry document archive and analyzed them with an interpretive approach. Tobacco companies conceptualized credibility not as being worthy of belief or confidence but as inspiring it. Thus, credibility was understood primarily as altering public perception of the industry. "Truth" was largely absent from tobacco industry conceptualizations of credibility, which were linked with "responsibility" and "reasonableness." However, industry research found that the public regarded credibility and responsibility differently, expecting these to entail truth telling, advertising reductions, less harmful products, apologies for deception, making amends, or exiting the tobacco business altogether. Overall, industry credibility-building projects failed repeatedly. Public health discourse increasingly attends to the roles of corporations in promoting disease. Industries such as tobacco and alcohol have been identified as profiting from harmful products. Yet corporations' ability to continue business as usual requires sustaining an implicit societal assent to their activities that depends on corporate credibility. For public health to address corporate disease promotion effectively, undermining corporate credibility may be strategically important.

Effect of Patient Experience on Bypassing a Primary Care Gatekeeper: a Multicenter Prospective Cohort Study in Japan.

PubMed

Aoki, Takuya; Yamamoto, Yosuke; Ikenoue, Tatsuyoshi; Kaneko, Makoto; Kise, Morito; Fujinuma, Yasuki; Fukuhara, Shunichi

2018-05-01

To discuss how best to implement the gatekeeping functionality of primary care; identifying the factors that cause patients to bypass their primary care gatekeepers when seeking care should be beneficial. To examine the association between patient experience with their primary care physicians and bypassing them to directly obtain care from higher-level healthcare facilities. This prospective cohort study was conducted in 13 primary care clinics in Japan. We assessed patient experience of primary care using the Japanese version of Primary Care Assessment Tool (JPCAT), which comprises six domains: first contact, longitudinality, coordination, comprehensiveness (services available), comprehensiveness (services provided), and community orientation. The primary outcome was the patient bypassing their usual primary care physician to seek care at a hospital, with this occurring at least once in a year. We used a Bayesian hierarchical model to adjust clustering within clinics and individual covariates. Data were analyzed from 205 patients for whom a physician at a clinic served as their usual primary care physician. The patient follow-up rate was 80.1%. After adjustment for patients' sociodemographic and health status characteristics, the JPCAT total score was found to be inversely associated with patient bypass behavior (odds ratio per 1 SD increase, 0.44; 95% credible interval, 0.21-0.88). The results of various sensitivity analyses were consistent with those of the primary analysis. We found that patient experience of primary care in Japan was inversely associated with bypassing a primary care gatekeeper to seek care at higher-level healthcare facilities, such as hospitals. Our findings suggest that primary care providers' efforts to improve patient experience should help to ensure appropriate use of healthcare services under loosely regulated gatekeeping systems; further studies are warranted.

Neighbourhood Walkability and Daily Steps in Adults with Type 2 Diabetes

PubMed Central

Hajna, Samantha; Ross, Nancy A.; Joseph, Lawrence; Harper, Sam; Dasgupta, Kaberi

2016-01-01

Introduction There is evidence that greater neighbourhood walkability (i.e., neighbourhoods with more amenities and well-connected streets) is associated with higher levels of total walking in Europe and in Asia, but it remains unclear if this association holds in the Canadian context and in chronic disease populations. We examined the relationships of different walkability measures to biosensor-assessed total walking (i.e., steps/day) in adults with type 2 diabetes living in Montreal (QC, Canada). Materials and Methods Participants (60.5±10.4 years; 48.1% women) were recruited through McGill University-affiliated clinics (June 2006 to May 2008). Steps/day were assessed once per season for one year with pedometers. Neighbourhood walkability was evaluated through participant reports, in-field audits, Geographic Information Systems (GIS)-derived measures, and the Walk Score®. Relationships between walkability and daily steps were estimated using Bayesian longitudinal hierarchical linear regression models (n = 131). Results Participants who reported living in the most compared to the least walkable neighbourhoods completed 1345 more steps/day (95% Credible Interval: 718, 1976; Quartiles 4 versus 1). Those living in the most compared to the least walkable neighbourhoods (based on GIS-derived walkability) completed 606 more steps per day (95% CrI: 8, 1203). No statistically significant associations with steps were observed for audit-assessed walkability or the Walk Score®. Conclusions Adults with type 2 diabetes who perceived their neighbourhoods as more walkable accumulated more daily steps. This suggests that knowledge of local neighborhood features that enhance walking is a meaningful predictor of higher levels of walking and an important component of neighbourhood walkability. PMID:26991308

Cross-validation of the Dot Counting Test in a large sample of credible and non-credible patients referred for neuropsychological testing.

PubMed

McCaul, Courtney; Boone, Kyle B; Ermshar, Annette; Cottingham, Maria; Victor, Tara L; Ziegler, Elizabeth; Zeller, Michelle A; Wright, Matthew

2018-01-18

To cross-validate the Dot Counting Test in a large neuropsychological sample. Dot Counting Test scores were compared in credible (n = 142) and non-credible (n = 335) neuropsychology referrals. Non-credible patients scored significantly higher than credible patients on all Dot Counting Test scores. While the original E-score cut-off of ≥17 achieved excellent specificity (96.5%), it was associated with mediocre sensitivity (52.8%). However, the cut-off could be substantially lowered to ≥13.80, while still maintaining adequate specificity (≥90%), and raising sensitivity to 70.0%. Examination of non-credible subgroups revealed that Dot Counting Test sensitivity in feigned mild traumatic brain injury (mTBI) was 55.8%, whereas sensitivity was 90.6% in patients with non-credible cognitive dysfunction in the context of claimed psychosis, and 81.0% in patients with non-credible cognitive performance in depression or severe TBI. Thus, the Dot Counting Test may have a particular role in detection of non-credible cognitive symptoms in claimed psychiatric disorders. Alternative to use of the E-score, failure on ≥1 cut-offs applied to individual Dot Counting Test scores (≥6.0″ for mean grouped dot counting time, ≥10.0″ for mean ungrouped dot counting time, and ≥4 errors), occurred in 11.3% of the credible sample, while nearly two-thirds (63.6%) of the non-credible sample failed one of more of these cut-offs. An E-score cut-off of 13.80, or failure on ≥1 individual score cut-offs, resulted in few false positive identifications in credible patients, and achieved high sensitivity (64.0-70.0%), and therefore appear appropriate for use in identifying neurocognitive performance invalidity.

Toward an ecological analysis of Bayesian inferences: how task characteristics influence responses

PubMed Central

Hafenbrädl, Sebastian; Hoffrage, Ulrich

2015-01-01

In research on Bayesian inferences, the specific tasks, with their narratives and characteristics, are typically seen as exchangeable vehicles that merely transport the structure of the problem to research participants. In the present paper, we explore whether, and possibly how, task characteristics that are usually ignored influence participants’ responses in these tasks. We focus on both quantitative dimensions of the tasks, such as their base rates, hit rates, and false-alarm rates, as well as qualitative characteristics, such as whether the task involves a norm violation or not, whether the stakes are high or low, and whether the focus is on the individual case or on the numbers. Using a data set of 19 different tasks presented to 500 different participants who provided a total of 1,773 responses, we analyze these responses in two ways: first, on the level of the numerical estimates themselves, and second, on the level of various response strategies, Bayesian and non-Bayesian, that might have produced the estimates. We identified various contingencies, and most of the task characteristics had an influence on participants’ responses. Typically, this influence has been stronger when the numerical information in the tasks was presented in terms of probabilities or percentages, compared to natural frequencies – and this effect cannot be fully explained by a higher proportion of Bayesian responses when natural frequencies were used. One characteristic that did not seem to influence participants’ response strategy was the numerical value of the Bayesian solution itself. Our exploratory study is a first step toward an ecological analysis of Bayesian inferences, and highlights new avenues for future research. PMID:26300791

A Bayesian hierarchical model for mortality data from cluster-sampling household surveys in humanitarian crises.

PubMed

Heudtlass, Peter; Guha-Sapir, Debarati; Speybroeck, Niko

2018-05-31

The crude death rate (CDR) is one of the defining indicators of humanitarian emergencies. When data from vital registration systems are not available, it is common practice to estimate the CDR from household surveys with cluster-sampling design. However, sample sizes are often too small to compare mortality estimates to emergency thresholds, at least in a frequentist framework. Several authors have proposed Bayesian methods for health surveys in humanitarian crises. Here, we develop an approach specifically for mortality data and cluster-sampling surveys. We describe a Bayesian hierarchical Poisson-Gamma mixture model with generic (weakly informative) priors that could be used as default in absence of any specific prior knowledge, and compare Bayesian and frequentist CDR estimates using five different mortality datasets. We provide an interpretation of the Bayesian estimates in the context of an emergency threshold and demonstrate how to interpret parameters at the cluster level and ways in which informative priors can be introduced. With the same set of weakly informative priors, Bayesian CDR estimates are equivalent to frequentist estimates, for all practical purposes. The probability that the CDR surpasses the emergency threshold can be derived directly from the posterior of the mean of the mixing distribution. All observation in the datasets contribute to the estimation of cluster-level estimates, through the hierarchical structure of the model. In a context of sparse data, Bayesian mortality assessments have advantages over frequentist ones already when using only weakly informative priors. More informative priors offer a formal and transparent way of combining new data with existing data and expert knowledge and can help to improve decision-making in humanitarian crises by complementing frequentist estimates.

The Bayesian boom: good thing or bad?

PubMed Central

Hahn, Ulrike

2014-01-01

A series of high-profile critiques of Bayesian models of cognition have recently sparked controversy. These critiques question the contribution of rational, normative considerations in the study of cognition. The present article takes central claims from these critiques and evaluates them in light of specific models. Closer consideration of actual examples of Bayesian treatments of different cognitive phenomena allows one to defuse these critiques showing that they cannot be sustained across the diversity of applications of the Bayesian framework for cognitive modeling. More generally, there is nothing in the Bayesian framework that would inherently give rise to the deficits that these critiques perceive, suggesting they have been framed at the wrong level of generality. At the same time, the examples are used to demonstrate the different ways in which consideration of rationality uniquely benefits both theory and practice in the study of cognition. PMID:25152738

A Tutorial in Bayesian Potential Outcomes Mediation Analysis.

PubMed

Miočević, Milica; Gonzalez, Oscar; Valente, Matthew J; MacKinnon, David P

2018-01-01

Statistical mediation analysis is used to investigate intermediate variables in the relation between independent and dependent variables. Causal interpretation of mediation analyses is challenging because randomization of subjects to levels of the independent variable does not rule out the possibility of unmeasured confounders of the mediator to outcome relation. Furthermore, commonly used frequentist methods for mediation analysis compute the probability of the data given the null hypothesis, which is not the probability of a hypothesis given the data as in Bayesian analysis. Under certain assumptions, applying the potential outcomes framework to mediation analysis allows for the computation of causal effects, and statistical mediation in the Bayesian framework gives indirect effects probabilistic interpretations. This tutorial combines causal inference and Bayesian methods for mediation analysis so the indirect and direct effects have both causal and probabilistic interpretations. Steps in Bayesian causal mediation analysis are shown in the application to an empirical example.

Hierarchical Bayesian Models of Subtask Learning

ERIC Educational Resources Information Center

Anglim, Jeromy; Wynton, Sarah K. A.

2015-01-01

The current study used Bayesian hierarchical methods to challenge and extend previous work on subtask learning consistency. A general model of individual-level subtask learning was proposed focusing on power and exponential functions with constraints to test for inconsistency. To study subtask learning, we developed a novel computer-based booking…

Spatio-Temporal History of HIV-1 CRF35_AD in Afghanistan and Iran.

PubMed

Eybpoosh, Sana; Bahrampour, Abbas; Karamouzian, Mohammad; Azadmanesh, Kayhan; Jahanbakhsh, Fatemeh; Mostafavi, Ehsan; Zolala, Farzaneh; Haghdoost, Ali Akbar

2016-01-01

HIV-1 Circulating Recombinant Form 35_AD (CRF35_AD) has an important position in the epidemiological profile of Afghanistan and Iran. Despite the presence of this clade in Afghanistan and Iran for over a decade, our understanding of its origin and dissemination patterns is limited. In this study, we performed a Bayesian phylogeographic analysis to reconstruct the spatio-temporal dispersion pattern of this clade using eligible CRF35_AD gag and pol sequences available in the Los Alamos HIV database (432 sequences available from Iran, 16 sequences available from Afghanistan, and a single CRF35_AD-like pol sequence available from USA). Bayesian Markov Chain Monte Carlo algorithm was implemented in BEAST v1.8.1. Between-country dispersion rates were tested with Bayesian stochastic search variable selection method and were considered significant where Bayes factor values were greater than three. The findings suggested that CRF35_AD sequences were genetically similar to parental sequences from Kenya and Uganda, and to a set of subtype A1 sequences available from Afghan refugees living in Pakistan. Our results also showed that across all phylogenies, Afghan and Iranian CRF35_AD sequences formed a monophyletic cluster (posterior clade credibility> 0.7). The divergence date of this cluster was estimated to be between 1990 and 1992. Within this cluster, a bidirectional dispersion of the virus was observed across Afghanistan and Iran. We could not clearly identify if Afghanistan or Iran first established or received this epidemic, as the root location of this cluster could not be robustly estimated. Three CRF35_AD sequences from Afghan refugees living in Pakistan nested among Afghan and Iranian CRF35_AD branches. However, the CRF35_AD-like sequence available from USA diverged independently from Kenyan subtype A1 sequences, suggesting it not to be a true CRF35_AD lineage. Potential factors contributing to viral exchange between Afghanistan and Iran could be injection drug networks and mass migration of Afghan refugees and labours to Iran, which calls for extensive preventive efforts.

Efficient estimation of abundance for patchily distributed populations via two-phase, adaptive sampling.

USGS Publications Warehouse

Conroy, M.J.; Runge, J.P.; Barker, R.J.; Schofield, M.R.; Fonnesbeck, C.J.

2008-01-01

Many organisms are patchily distributed, with some patches occupied at high density, others at lower densities, and others not occupied. Estimation of overall abundance can be difficult and is inefficient via intensive approaches such as capture-mark-recapture (CMR) or distance sampling. We propose a two-phase sampling scheme and model in a Bayesian framework to estimate abundance for patchily distributed populations. In the first phase, occupancy is estimated by binomial detection samples taken on all selected sites, where selection may be of all sites available, or a random sample of sites. Detection can be by visual surveys, detection of sign, physical captures, or other approach. At the second phase, if a detection threshold is achieved, CMR or other intensive sampling is conducted via standard procedures (grids or webs) to estimate abundance. Detection and CMR data are then used in a joint likelihood to model probability of detection in the occupancy sample via an abundance-detection model. CMR modeling is used to estimate abundance for the abundance-detection relationship, which in turn is used to predict abundance at the remaining sites, where only detection data are collected. We present a full Bayesian modeling treatment of this problem, in which posterior inference on abundance and other parameters (detection, capture probability) is obtained under a variety of assumptions about spatial and individual sources of heterogeneity. We apply the approach to abundance estimation for two species of voles (Microtus spp.) in Montana, USA. We also use a simulation study to evaluate the frequentist properties of our procedure given known patterns in abundance and detection among sites as well as design criteria. For most population characteristics and designs considered, bias and mean-square error (MSE) were low, and coverage of true parameter values by Bayesian credibility intervals was near nominal. Our two-phase, adaptive approach allows efficient estimation of abundance of rare and patchily distributed species and is particularly appropriate when sampling in all patches is impossible, but a global estimate of abundance is required.

Risk mapping of clonorchiasis in the People’s Republic of China: A systematic review and Bayesian geostatistical analysis

PubMed Central

Lai, Ying-Si; Zhou, Xiao-Nong; Pan, Zhi-Heng; Utzinger, Jürg; Vounatsou, Penelope

2017-01-01

Background Clonorchiasis, one of the most important food-borne trematodiases, affects more than 12 million people in the People’s Republic of China (P.R. China). Spatially explicit risk estimates of Clonorchis sinensis infection are needed in order to target control interventions. Methodology Georeferenced survey data pertaining to infection prevalence of C. sinensis in P.R. China from 2000 onwards were obtained via a systematic review in PubMed, ISI Web of Science, Chinese National Knowledge Internet, and Wanfang Data from January 1, 2000 until January 10, 2016, with no restriction of language or study design. Additional disease data were provided by the National Institute of Parasitic Diseases, Chinese Center for Diseases Control and Prevention in Shanghai. Environmental and socioeconomic proxies were extracted from remote-sensing and other data sources. Bayesian variable selection was carried out to identify the most important predictors of C. sinensis risk. Geostatistical models were applied to quantify the association between infection risk and the predictors of the disease, and to predict the risk of infection across P.R. China at high spatial resolution (over a grid with grid cell size of 5×5 km). Principal findings We obtained clonorchiasis survey data at 633 unique locations in P.R. China. We observed that the risk of C. sinensis infection increased over time, particularly from 2005 onwards. We estimate that around 14.8 million (95% Bayesian credible interval 13.8–15.8 million) people in P.R. China were infected with C. sinensis in 2010. Highly endemic areas (≥ 20%) were concentrated in southern and northeastern parts of the country. The provinces with the highest risk of infection and the largest number of infected people were Guangdong, Guangxi, and Heilongjiang. Conclusions/Significance Our results provide spatially relevant information for guiding clonorchiasis control interventions in P.R. China. The trend toward higher risk of C. sinensis infection in the recent past urges the Chinese government to pay more attention to the public health importance of clonorchiasis and to target interventions to high-risk areas. PMID:28253272

Spatio-Temporal History of HIV-1 CRF35_AD in Afghanistan and Iran

PubMed Central

Eybpoosh, Sana; Bahrampour, Abbas; Karamouzian, Mohammad; Azadmanesh, Kayhan; Jahanbakhsh, Fatemeh; Mostafavi, Ehsan; Zolala, Farzaneh; Haghdoost, Ali Akbar

2016-01-01

HIV-1 Circulating Recombinant Form 35_AD (CRF35_AD) has an important position in the epidemiological profile of Afghanistan and Iran. Despite the presence of this clade in Afghanistan and Iran for over a decade, our understanding of its origin and dissemination patterns is limited. In this study, we performed a Bayesian phylogeographic analysis to reconstruct the spatio-temporal dispersion pattern of this clade using eligible CRF35_AD gag and pol sequences available in the Los Alamos HIV database (432 sequences available from Iran, 16 sequences available from Afghanistan, and a single CRF35_AD-like pol sequence available from USA). Bayesian Markov Chain Monte Carlo algorithm was implemented in BEAST v1.8.1. Between-country dispersion rates were tested with Bayesian stochastic search variable selection method and were considered significant where Bayes factor values were greater than three. The findings suggested that CRF35_AD sequences were genetically similar to parental sequences from Kenya and Uganda, and to a set of subtype A1 sequences available from Afghan refugees living in Pakistan. Our results also showed that across all phylogenies, Afghan and Iranian CRF35_AD sequences formed a monophyletic cluster (posterior clade credibility> 0.7). The divergence date of this cluster was estimated to be between 1990 and 1992. Within this cluster, a bidirectional dispersion of the virus was observed across Afghanistan and Iran. We could not clearly identify if Afghanistan or Iran first established or received this epidemic, as the root location of this cluster could not be robustly estimated. Three CRF35_AD sequences from Afghan refugees living in Pakistan nested among Afghan and Iranian CRF35_AD branches. However, the CRF35_AD-like sequence available from USA diverged independently from Kenyan subtype A1 sequences, suggesting it not to be a true CRF35_AD lineage. Potential factors contributing to viral exchange between Afghanistan and Iran could be injection drug networks and mass migration of Afghan refugees and labours to Iran, which calls for extensive preventive efforts. PMID:27280293

Bayesian estimation of extreme flood quantiles using a rainfall-runoff model and a stochastic daily rainfall generator

NASA Astrophysics Data System (ADS)

Costa, Veber; Fernandes, Wilson

2017-11-01

Extreme flood estimation has been a key research topic in hydrological sciences. Reliable estimates of such events are necessary as structures for flood conveyance are continuously evolving in size and complexity and, as a result, their failure-associated hazards become more and more pronounced. Due to this fact, several estimation techniques intended to improve flood frequency analysis and reducing uncertainty in extreme quantile estimation have been addressed in the literature in the last decades. In this paper, we develop a Bayesian framework for the indirect estimation of extreme flood quantiles from rainfall-runoff models. In the proposed approach, an ensemble of long daily rainfall series is simulated with a stochastic generator, which models extreme rainfall amounts with an upper-bounded distribution function, namely, the 4-parameter lognormal model. The rationale behind the generation model is that physical limits for rainfall amounts, and consequently for floods, exist and, by imposing an appropriate upper bound for the probabilistic model, more plausible estimates can be obtained for those rainfall quantiles with very low exceedance probabilities. Daily rainfall time series are converted into streamflows by routing each realization of the synthetic ensemble through a conceptual hydrologic model, the Rio Grande rainfall-runoff model. Calibration of parameters is performed through a nonlinear regression model, by means of the specification of a statistical model for the residuals that is able to accommodate autocorrelation, heteroscedasticity and nonnormality. By combining the outlined steps in a Bayesian structure of analysis, one is able to properly summarize the resulting uncertainty and estimating more accurate credible intervals for a set of flood quantiles of interest. The method for extreme flood indirect estimation was applied to the American river catchment, at the Folsom dam, in the state of California, USA. Results show that most floods, including exceptionally large non-systematic events, were reasonably estimated with the proposed approach. In addition, by accounting for uncertainties in each modeling step, one is able to obtain a better understanding of the influential factors in large flood formation dynamics.

Transmission potential of influenza A/H7N9, February to May 2013, China

PubMed Central

2013-01-01

Background On 31 March 2013, the first human infections with the novel influenza A/H7N9 virus were reported in Eastern China. The outbreak expanded rapidly in geographic scope and size, with a total of 132 laboratory-confirmed cases reported by 3 June 2013, in 10 Chinese provinces and Taiwan. The incidence of A/H7N9 cases has stalled in recent weeks, presumably as a consequence of live bird market closures in the most heavily affected areas. Here we compare the transmission potential of influenza A/H7N9 with that of other emerging pathogens and evaluate the impact of intervention measures in an effort to guide pandemic preparedness. Methods We used a Bayesian approach combined with a SEIR (Susceptible-Exposed-Infectious-Removed) transmission model fitted to daily case data to assess the reproduction number (R) of A/H7N9 by province and to evaluate the impact of live bird market closures in April and May 2013. Simulation studies helped quantify the performance of our approach in the context of an emerging pathogen, where human-to-human transmission is limited and most cases arise from spillover events. We also used alternative approaches to estimate R based on individual-level information on prior exposure and compared the transmission potential of influenza A/H7N9 with that of other recent zoonoses. Results Estimates of R for the A/H7N9 outbreak were below the epidemic threshold required for sustained human-to-human transmission and remained near 0.1 throughout the study period, with broad 95% credible intervals by the Bayesian method (0.01 to 0.49). The Bayesian estimation approach was dominated by the prior distribution, however, due to relatively little information contained in the case data. We observe a statistically significant deceleration in growth rate after 6 April 2013, which is consistent with a reduction in A/H7N9 transmission associated with the preemptive closure of live bird markets. Although confidence intervals are broad, the estimated transmission potential of A/H7N9 appears lower than that of recent zoonotic threats, including avian influenza A/H5N1, swine influenza H3N2sw and Nipah virus. Conclusion Although uncertainty remains high in R estimates for H7N9 due to limited epidemiological information, all available evidence points to a low transmission potential. Continued monitoring of the transmission potential of A/H7N9 is critical in the coming months as intervention measures may be relaxed and seasonal factors could promote disease transmission in colder months. PMID:24083506

Developing Large-Scale Bayesian Networks by Composition: Fault Diagnosis of Electrical Power Systems in Aircraft and Spacecraft

NASA Technical Reports Server (NTRS)

Mengshoel, Ole Jakob; Poll, Scott; Kurtoglu, Tolga

2009-01-01

This CD contains files that support the talk (see CASI ID 20100021404). There are 24 models that relate to the ADAPT system and 1 Excel worksheet. In the paper an investigation into the use of Bayesian networks to construct large-scale diagnostic systems is described. The high-level specifications, Bayesian networks, clique trees, and arithmetic circuits representing 24 different electrical power systems are described in the talk. The data in the CD are the models of the 24 different power systems.

Bayesian Decision Support

NASA Astrophysics Data System (ADS)

Berliner, M.

2017-12-01

Bayesian statistical decision theory offers a natural framework for decision-policy making in the presence of uncertainty. Key advantages of the approach include efficient incorporation of information and observations. However, in complicated settings it is very difficult, perhaps essentially impossible, to formalize the mathematical inputs needed in the approach. Nevertheless, using the approach as a template is useful for decision support; that is, organizing and communicating our analyses. Bayesian hierarchical modeling is valuable in quantifying and managing uncertainty such cases. I review some aspects of the idea emphasizing statistical model development and use in the context of sea-level rise.

Argumentative Men: Expectations of Success.

ERIC Educational Resources Information Center

Schullery, Nancy M.

1999-01-01

Considers how argumentativeness is linked with several managerial qualities, such as group leadership, better decision-making, and enhanced credibility. Surveys nearly 300 full-time employed men. Shows that men at all levels exhibit the full range of argumentativeness. Finds the mean argumentativeness of supervisors at all levels is significantly…

The Validity of Left Ventricular Mass as a Surrogate End Point for All-Cause and Cardiovascular Mortality Outcomes in People With CKD: A Systematic Review and Meta-analysis.

PubMed

Badve, Sunil V; Palmer, Suetonia C; Strippoli, Giovanni F M; Roberts, Matthew A; Teixeira-Pinto, Armando; Boudville, Neil; Cass, Alan; Hawley, Carmel M; Hiremath, Swapnil S; Pascoe, Elaine M; Perkovic, Vlado; Whalley, Gillian A; Craig, Jonathan C; Johnson, David W

2016-10-01

Left ventricular mass (LVM) is a widely used surrogate end point in randomized trials involving people with chronic kidney disease (CKD) because treatment-induced LVM reductions are assumed to lower cardiovascular risk. The aim of this study was to assess the validity of LVM as a surrogate end point for all-cause and cardiovascular mortality in CKD. Systematic review and meta-analysis. Participants with any stages of CKD. Randomized controlled trials with 3 or more months' follow-up that reported LVM data. Any pharmacologic or nonpharmacologic intervention. The surrogate outcome of interest was LVM change from baseline to last measurement, and clinical outcomes of interest were all-cause and cardiovascular mortality. Standardized mean differences (SMDs) of LVM change and relative risk for mortality were estimated using pairwise random-effects meta-analysis. Correlations between surrogate and clinical outcomes were summarized across all interventions combined using bivariate random-effects Bayesian models, and 95% credible intervals were computed. 73 trials (6,732 participants) covering 25 intervention classes were included in the meta-analysis. Overall, risk of bias was uncertain or high. Only 3 interventions reduced LVM: erythropoiesis-stimulating agents (9 trials; SMD, -0.13; 95% CI, -0.23 to -0.03), renin-angiotensin-aldosterone system inhibitors (13 trials; SMD, -0.28; 95% CI, -0.45 to -0.12), and isosorbide mononitrate (2 trials; SMD, -0.43; 95% CI, -0.72 to -0.14). All interventions had uncertain effects on all-cause and cardiovascular mortality. There were weak and imprecise associations between the effects of interventions on LVM change and all-cause (32 trials; 5,044 participants; correlation coefficient, 0.28; 95% credible interval, -0.13 to 0.59) and cardiovascular mortality (13 trials; 2,327 participants; correlation coefficient, 0.30; 95% credible interval, -0.54 to 0.76). Limited long-term data, suboptimal quality of included studies. There was no clear and consistent association between intervention-induced LVM change and mortality. Evidence for LVM as a valid surrogate end point in CKD is currently lacking. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Simulation Credibility: Advances in Verification, Validation, and Uncertainty Quantification

NASA Technical Reports Server (NTRS)

Mehta, Unmeel B. (Editor); Eklund, Dean R.; Romero, Vicente J.; Pearce, Jeffrey A.; Keim, Nicholas S.

2016-01-01

Decision makers and other users of simulations need to know quantified simulation credibility to make simulation-based critical decisions and effectively use simulations, respectively. The credibility of a simulation is quantified by its accuracy in terms of uncertainty, and the responsibility of establishing credibility lies with the creator of the simulation. In this volume, we present some state-of-the-art philosophies, principles, and frameworks. The contributing authors involved in this publication have been dedicated to advancing simulation credibility. They detail and provide examples of key advances over the last 10 years in the processes used to quantify simulation credibility: verification, validation, and uncertainty quantification. The philosophies and assessment methods presented here are anticipated to be useful to other technical communities conducting continuum physics-based simulations; for example, issues related to the establishment of simulation credibility in the discipline of propulsion are discussed. We envision that simulation creators will find this volume very useful to guide and assist them in quantitatively conveying the credibility of their simulations.

Monitoring Human Development Goals: A Straightforward (Bayesian) Methodology for Cross-National Indices

ERIC Educational Resources Information Center

Abayomi, Kobi; Pizarro, Gonzalo

2013-01-01

We offer a straightforward framework for measurement of progress, across many dimensions, using cross-national social indices, which we classify as linear combinations of multivariate country level data onto a univariate score. We suggest a Bayesian approach which yields probabilistic (confidence type) intervals for the point estimates of country…

Bayesian mixture modeling for blood sugar levels of diabetes mellitus patients (case study in RSUD Saiful Anwar Malang Indonesia)

NASA Astrophysics Data System (ADS)

Budi Astuti, Ani; Iriawan, Nur; Irhamah; Kuswanto, Heri; Sasiarini, Laksmi

2017-10-01

Bayesian statistics proposes an approach that is very flexible in the number of samples and distribution of data. Bayesian Mixture Model (BMM) is a Bayesian approach for multimodal models. Diabetes Mellitus (DM) is more commonly known in the Indonesian community as sweet pee. This disease is one type of chronic non-communicable diseases but it is very dangerous to humans because of the effects of other diseases complications caused. WHO reports in 2013 showed DM disease was ranked 6th in the world as the leading causes of human death. In Indonesia, DM disease continues to increase over time. These research would be studied patterns and would be built the BMM models of the DM data through simulation studies where the simulation data built on cases of blood sugar levels of DM patients in RSUD Saiful Anwar Malang. The results have been successfully demonstrated pattern of distribution of the DM data which has a normal mixture distribution. The BMM models have succeed to accommodate the real condition of the DM data based on the data driven concept.

Credibility and advocacy in conservation science

PubMed Central

Horton, Cristi C.; Peterson, Tarla Rai; Banerjee, Paulami

2015-01-01

Abstract Conservation policy sits at the nexus of natural science and politics. On the one hand, conservation scientists strive to maintain scientific credibility by emphasizing that their research findings are the result of disinterested observations of reality. On the other hand, conservation scientists are committed to conservation even if they do not advocate a particular policy. The professional conservation literature offers guidance on negotiating the relationship between scientific objectivity and political advocacy without damaging conservation science's credibility. The value of this guidance, however, may be restricted by limited recognition of credibility's multidimensionality and emergent nature: it emerges through perceptions of expertise, goodwill, and trustworthiness. We used content analysis of the literature to determine how credibility is framed in conservation science as it relates to apparent contradictions between science and advocacy. Credibility typically was framed as a static entity lacking dimensionality. Authors identified expertise or trustworthiness as important, but rarely mentioned goodwill. They usually did not identify expertise, goodwill, or trustworthiness as dimensions of credibility or recognize interactions among these 3 dimensions of credibility. This oversimplification may limit the ability of conservation scientists to contribute to biodiversity conservation. Accounting for the emergent quality and multidimensionality of credibility should enable conservation scientists to advance biodiversity conservation more effectively. PMID:26041036

The Role of Corporate Credibility in Legitimizing Disease Promotion

PubMed Central

Malone, Ruth E.

2009-01-01

Objectives. We explored what corporate “credibility” means to tobacco companies to determine why it matters to companies and what a lack of credibility means to them. Methods. We collected documents from an online tobacco industry document archive and analyzed them with an interpretive approach. Results. Tobacco companies conceptualized credibility not as being worthy of belief or confidence but as inspiring it. Thus, credibility was understood primarily as altering public perception of the industry. “Truth” was largely absent from tobacco industry conceptualizations of credibility, which were linked with “responsibility” and “reasonableness.” However, industry research found that the public regarded credibility and responsibility differently, expecting these to entail truth telling, advertising reductions, less harmful products, apologies for deception, making amends, or exiting the tobacco business altogether. Overall, industry credibility-building projects failed repeatedly. Conclusions. Public health discourse increasingly attends to the roles of corporations in promoting disease. Industries such as tobacco and alcohol have been identified as profiting from harmful products. Yet corporations' ability to continue business as usual requires sustaining an implicit societal assent to their activities that depends on corporate credibility. For public health to address corporate disease promotion effectively, undermining corporate credibility may be strategically important. PMID:19106419

Statistical comparison of a hybrid approach with approximate and exact inference models for Fusion 2+

NASA Astrophysics Data System (ADS)

Lee, K. David; Wiesenfeld, Eric; Gelfand, Andrew

2007-04-01

One of the greatest challenges in modern combat is maintaining a high level of timely Situational Awareness (SA). In many situations, computational complexity and accuracy considerations make the development and deployment of real-time, high-level inference tools very difficult. An innovative hybrid framework that combines Bayesian inference, in the form of Bayesian Networks, and Possibility Theory, in the form of Fuzzy Logic systems, has recently been introduced to provide a rigorous framework for high-level inference. In previous research, the theoretical basis and benefits of the hybrid approach have been developed. However, lacking is a concrete experimental comparison of the hybrid framework with traditional fusion methods, to demonstrate and quantify this benefit. The goal of this research, therefore, is to provide a statistical analysis on the comparison of the accuracy and performance of hybrid network theory, with pure Bayesian and Fuzzy systems and an inexact Bayesian system approximated using Particle Filtering. To accomplish this task, domain specific models will be developed under these different theoretical approaches and then evaluated, via Monte Carlo Simulation, in comparison to situational ground truth to measure accuracy and fidelity. Following this, a rigorous statistical analysis of the performance results will be performed, to quantify the benefit of hybrid inference to other fusion tools.

Research on software behavior trust based on hierarchy evaluation

NASA Astrophysics Data System (ADS)

Long, Ke; Xu, Haishui

2017-08-01

In view of the correlation software behavior, we evaluate software behavior credibility from two levels of control flow and data flow. In control flow level, method of the software behavior of trace based on support vector machine (SVM) is proposed. In data flow level, behavioral evidence evaluation based on fuzzy decision analysis method is put forward.

Assessing system reliability and allocating resources: a bayesian approach that integrates multi-level data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Graves, Todd L; Hamada, Michael S

2008-01-01

Good estimates of the reliability of a system make use of test data and expert knowledge at all available levels. Furthermore, by integrating all these information sources, one can determine how best to allocate scarce testing resources to reduce uncertainty. Both of these goals are facilitated by modern Bayesian computational methods. We apply these tools to examples that were previously solvable only through the use of ingenious approximations, and use genetic algorithms to guide resource allocation.

Use of Third-Party Credibility in Hostile Situations.

ERIC Educational Resources Information Center

Gorney, Carole M.

A study analyzed the use of third-party credibility as a deliberate and systematic public relations strategy to regain credibility for an organization faced with public hostility. Four types of third-party usage are: citizen participation, outside investigation, adversarial advocacy, and employee dissemination. Third-party credibility as a public…

45 CFR 158.232 - Calculating the credibility adjustment.

Code of Federal Regulations, 2011 CFR

2011-10-01

... experience is zero. (2) The base credibility factor for partially credible experience is determined based on... adjustment for an MLR based on partially credible experience is zero if both of the following conditions are... deductible factor is based on the average per person deductible of policies whose experience is included in...

Opening the doors: building brand awareness.

PubMed

John, Judith; McCartney, Rob

2006-01-01

In search of a credible and cost-effective way to promote Mount Sinai Hospital (Mount Sinai) and educate a broad public, Mount Sinai opened its doors wide to The Globe and Mail (The Globe). The result was a three-part national feature series that told Mount Sinai's compelling story, provided third-party credibility and confirmed the value of proactive media relations. The series engaged our staff, energized our volunteers and reached both stakeholders and the general public on an emotional level. It also generated the more than dollars 6 million worth of equivalent advertising space it would have required for Mount Sinai to reach this national audience.

Spatio-temporal factors associated with meningococcal meningitis annual incidence at the health centre level in Niger, 2004-2010.

PubMed

Paireau, Juliette; Maïnassara, Halima B; Jusot, Jean-François; Collard, Jean-Marc; Idi, Issa; Moulia-Pelat, Jean-Paul; Mueller, Judith E; Fontanet, Arnaud

2014-05-01

Epidemics of meningococcal meningitis (MM) recurrently strike the African Meningitis Belt. This study aimed at investigating factors, still poorly understood, that influence annual incidence of MM serogroup A, the main etiologic agent over 2004-2010, at a fine spatial scale in Niger. To take into account data dependencies over space and time and control for unobserved confounding factors, we developed an explanatory Bayesian hierarchical model over 2004-2010 at the health centre catchment area (HCCA) level. The multivariate model revealed that both climatic and non-climatic factors were important for explaining spatio-temporal variations in incidence: mean relative humidity during November-June over the study region (posterior mean Incidence Rate Ratio (IRR) = 0.656, 95% Credible Interval (CI) 0.405-0.949) and occurrence of early rains in March in a HCCA (IRR = 0.353, 95% CI 0.239-0.502) were protective factors; a higher risk was associated with the percentage of neighbouring HCCAs having at least one MM A case during the same year (IRR = 2.365, 95% CI 2.078-2.695), the presence of a road crossing the HCCA (IRR = 1.743, 95% CI 1.173-2.474) and the occurrence of cases before 31 December in a HCCA (IRR = 6.801, 95% CI 4.004-10.910). At the study region level, higher annual incidence correlated with greater geographic spread and, to a lesser extent, with higher intensity of localized outbreaks. Based on these findings, we hypothesize that spatio-temporal variability of MM A incidence between years and HCCAs result from variations in the intensity or duration of the dry season climatic effects on disease risk, and is further impacted by factors of spatial contacts, representing facilitated pathogen transmission. Additional unexplained factors may contribute to the observed incidence patterns and should be further investigated.

Pathfinding to an optimal strategy of revascularization in primary coronary intervention in patients with multivessel disease: a network meta-analysis of randomized trials.

PubMed

Komócsi, András; Kehl, Dániel; d'Ascenso, Fabrizio; DiNicolantonio, James; Vorobcsuk, András

2017-03-01

In ST-segment elevation myocardial infarction (STEMI), current guidelines discourage treatment of the non-culprit lesions at the time of the primary intervention. Latest trials have challenged this strategy suggesting benefit of early complete revascularization. We performed a Bayesian multiple treatment network meta-analysis of randomized clinical trials (RCTs) in STEMI on culprit-only intervention (CO) versus different timing multivessel revascularization, including immediate (IM), same hospitalization (SH) or later staged (ST). Outcome parameters were pooled with a random-effects model. For multiple-treatment meta-analysis, a Bayesian Markov chain Monte Carlo method was used. Eight RCTs involving 2077 patients were identified. ST and IM revascularization was associated with a decrease in major adverse cardiac events (MACEs) compared to culprit-only approach (risk ratio [RR]: 0.43 credible interval [CrI]: 0.22-0.77 and RR: 0.36 CrI: 0.24-0.54, respectively). IM was superior to SH (RR: 0.49 CrI: 0.29-0.80). With regards to myocardial infarction IM was superior to SH (RR: 0.18 CrI: 0.02-0.99). The posterior probability of being the best choice of treatment regarding the frequency of MACEs was 71.2% for IM, 28.5% for ST, 0.3% for SH and 0.05% for culprit-only approach. Results from RCTs indicate that immediate or staged revascularization of non-culprit lesions reduces major adverse events in patients after primary percutaneous coronary intervention. Differences in MACEs suggest superiority of the immediate or staged intervention; however, further randomized trials are needed to determine the optimal timing of revascularization of the non-culprit lesions.

Long term outcomes of new generation drug eluting stents versus coronary artery bypass grafting for multivessel and/or left main coronary artery disease. A Bayesian network meta-analysis of randomized controlled trials.

PubMed

Mina, George S; Watti, Hussam; Soliman, Demiana; Shewale, Anand; Atkins, Jessica; Reddy, Pratap; Dominic, Paari

2018-01-05

Most data guiding revascularization of multivessel disease (MVD) and/or left main disease (LMD) favor coronary artery bypass grafting (CABG) over percutaneous coronary intervention (PCI). However, those data are based on trials comparing CABG to bare metal stents (BMS) or old generation drug eluting stents (OG-DES). Hence, it is essential to outcomes of CABG to those of new generation drug eluting stents (NG-DES). We searched PUBMED and Cochrane database for trials evaluating revascularization of MVD and/or LMD with CABG and/or PCI. A Bayesian network meta-analysis was performed to calculate odds ratios (OR) and 95% credible intervals (CrI). Primary outcome was major adverse cardiovascular events (MACE) at 3-5 years. Secondary outcomes were mortality, cerebrovascular accidents (CVA), myocardial infarction (MI) and repeat revascularization. We included 10 trials with a total of 9287 patients. CABG was associated with lower MACE when compared to BMS or OG-DES. However, MACE was not significantly different between CABG and NG-DES (OR 0.79, CrI 0.45-1.40). Moreover, there were no significant differences between CABG and NG-DES in mortality (OR 0.78, CrI 0.45-1.37), CVA (OR 0.93 CrI 0.35-2.2) or MI (OR 0.6, CrI 0.17-2.0). On the other hand, CABG was associated with lower repeat revascularization (OR 0.55, CrI 0.36-0.84). Our study suggests that NG-DES is an acceptable alternative to CABG in patients with MVD and/or LMD. However, repeat revascularization remains to be lower with CABG than with PCI. Copyright © 2018. Published by Elsevier Inc.

Low coverage of central point vaccination against dog rabies in Bamako, Mali.

PubMed

Muthiani, Yvonne; Traoré, Abdallah; Mauti, Stephanie; Zinsstag, Jakob; Hattendorf, Jan

2015-06-15

Canine rabies remains an important public-health problem in Africa. Dog mass vaccination is the recommended method for rabies control and elimination. We report on the first small-scale mass dog vaccination campaign trial in Bamako, Mali. Our objective was to estimate coverage of the vaccination campaign and to quantify determinants of intervention effectiveness. In September 2013, a central point vaccination campaign--free of cost for dog owners--was carried out in 17 posts on three consecutive days within Bamako's Commune 1. Vaccination coverage and the proportion of ownerless dogs were estimated by combining mark-recapture household and transect surveys using Bayesian modeling. The estimated vaccination coverage was 17.6% (95% Credibility Interval, CI: 14.4-22.1%) which is far below the World Health Organization (WHO) recommended vaccination coverage of 70%. The Bayesian estimate for the owned dog population of Commune 1 was 3459 dogs (95% CI: 2786-4131) and the proportion of ownerless dogs was about 8%. The low coverage observed is primarily attributed to low participation by dog owners. Dog owners reported several reasons for not bringing their dogs to the vaccination posts. The most frequently reported reasons for non-attendance were lack of information (25%) and the inability to handle the dog (16%). For 37% of respondents, no clear reason was given for non-vaccination. Despite low coverage, the vaccination campaign in Bamako was relatively easy to implement, both in terms of logistics and organization. Almost half of the participating dog owners brought their pets on the first day of the campaign. Participatory stakeholder processes involving communities and local authorities are needed to identify effective communication channels and locally adapted vaccination strategies, which could include both central-point and door-to-door vaccination. Copyright © 2015 Elsevier B.V. All rights reserved.

Using Bayesian Models to Assess the Effects of Under-reporting of Cannabis Use on the Association with Birth Defects, National Birth Defects Prevention Study, 1997–2005

PubMed Central

van Gelder, Marleen M. H. J.; Rogier, A.; Donders, T.; Devine, Owen; Roeleveld, Nel; Reefhuis, Jennita

2015-01-01

Background Studies on associations between periconceptional cannabis exposure and birth defects have mainly relied on self-reported exposure. Therefore, the results may be biased due to underreporting of the exposure. The aim of this study was to quantify the potential effects of this form of exposure misclassification. Methods Using multivariable logistic regression, we re-analyzed associations between periconceptional cannabis use and 20 specific birth defects using data from the National Birth Defects Prevention Study from 1997–2005 for 13 859 case infants and 6556 control infants. For seven birth defects, we implemented four Bayesian models based on various assumptions concerning the sensitivity of self-reported cannabis use to estimate odds ratios (ORs), adjusted for confounding and underreporting of the exposure. We used information on sensitivity of self-reported cannabis use from the literature for prior assumptions. Results The results unadjusted for underreporting of the exposure showed an association between cannabis use and anencephaly (posterior OR 1.9 [95% credible interval (CRI) 1.1, 3.2]) which persisted after adjustment for potential exposure misclassification. Initially, no statistically significant associations were observed between cannabis use and the other birth defect categories studied. Although adjustment for underreporting did not notably change these effect estimates, cannabis use was associated with esophageal atresia (posterior OR 1.7 [95% CRI 1.0, 2.9]), diaphragmatic hernia (posterior OR 1.8 [95% CRI 1.1, 3.0]) and gastroschisis (posterior OR 1.7 [95% CRI 1.2, 2.3]) after correction for exposure misclassification. Conclusions Underreporting of the exposure may have obscured some cannabis-birth defect associations in previous studies. However, the resulting bias is likely to be limited. PMID:25155701

Using bayesian models to assess the effects of under-reporting of cannabis use on the association with birth defects, national birth defects prevention study, 1997-2005.

PubMed

van Gelder, Marleen M H J; Donders, A Rogier T; Devine, Owen; Roeleveld, Nel; Reefhuis, Jennita

2014-09-01

Studies on associations between periconceptional cannabis exposure and birth defects have mainly relied on self-reported exposure. Therefore, the results may be biased due to under-reporting of the exposure. The aim of this study was to quantify the potential effects of this form of exposure misclassification. Using multivariable logistic regression, we re-analysed associations between periconceptional cannabis use and 20 specific birth defects using data from the National Birth Defects Prevention Study from 1997-2005 for 13 859 case infants and 6556 control infants. For seven birth defects, we implemented four Bayesian models based on various assumptions concerning the sensitivity of self-reported cannabis use to estimate odds ratios (ORs), adjusted for confounding and under-reporting of the exposure. We used information on sensitivity of self-reported cannabis use from the literature for prior assumptions. The results unadjusted for under-reporting of the exposure showed an association between cannabis use and anencephaly (posterior OR 1.9 [95% credible interval (CRI) 1.1, 3.2]) which persisted after adjustment for potential exposure misclassification. Initially, no statistically significant associations were observed between cannabis use and the other birth defect categories studied. Although adjustment for under-reporting did not notably change these effect estimates, cannabis use was associated with esophageal atresia (posterior OR 1.7 [95% CRI 1.0, 2.9]), diaphragmatic hernia (posterior OR 1.8 [95% CRI 1.1, 3.0]), and gastroschisis (posterior OR 1.7 [95% CRI 1.2, 2.3]) after correction for exposure misclassification. Under-reporting of the exposure may have obscured some cannabis-birth defect associations in previous studies. However, the resulting bias is likely to be limited. © 2014 John Wiley & Sons Ltd.

Efficacy of nonvenous medications for acute convulsive seizures

PubMed Central

Kothari, Harsh; Zhang, Zongjun; Han, Baoguang; Horn, Paul S.; Glauser, Tracy A.

2015-01-01

Objective: This is a network meta-analysis of nonvenous drugs used in randomized controlled trials (RCTs) for treatment of acute convulsive seizures and convulsive status epilepticus. Methods: Literature was searched according to Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines for RCTs examining treatment of acute convulsive seizures or status epilepticus with at least one of the study arms being a nonvenous medication. After demographic and outcome data extraction, a Bayesian network meta-analysis was performed and efficacy results were summarized using treatment effects and their credible intervals (CrI). We also calculated the probability of each route–drug combination being the most clinically effective for a given outcome, and provided their Bayesian hierarchical ranking. Results: This meta-analysis of 16 studies found that intramuscular midazolam (IM-MDZ) is superior to other nonvenous medications regarding time to seizure termination after administration (2.145 minutes, 95% CrI 1.308–3.489), time to seizure cessation after arrival in the hospital (3.841 minutes, 95% CrI 2.697–5.416), and time to initiate treatment (0.779 minutes, 95% CrI 0.495–1.221). Additionally, intranasal midazolam (IN-MDZ) was adjudged most efficacious for seizure cessation within 10 minutes of administration (90.4% of participants, 95% CrI 79.4%–96.9%), and persistent seizure cessation for ≥1 hour (78.5% of participants, 95% CrI 59.5%–92.1%). Paucity of RCTs produced evidence gaps resulting in small networks, routes/drugs included in some networks but not others, and some trials not being connected to any network. Conclusions: Despite the evidence gaps, IM-MDZ and IN-MDZ exhibit the best efficacy data for the nonvenous treatment of acute convulsive seizures or status epilepticus. PMID:26511448

A Bayesian hierarchical model of Antarctic fur seal foraging and pup growth related to sea ice and prey abundance.

PubMed

Hiruki-Raring, Lisa M; Ver Hoef, Jay M; Boveng, Peter L; Bengtson, John L

2012-03-01

We created a Bayesian hierarchical model (BHM) to investigate ecosystem relationships between the physical ecosystem (sea ice extent), a prey measure (krill density), predator behaviors (diving and foraging effort of female Antarctic fur seals, Arctocephalus gazella, with pups) and predator characteristics (mass of maternal fur seals and pups). We collected data on Antarctic fur seals from 1987/1988 to 1994/1995 at Seal Island, Antarctica. The BHM allowed us to link together predators and prey into a model that uses all the data efficiently and accounts for major sources of uncertainty. Based on the literature, we made hypotheses about the relationships in the model, which we compared with the model outcome after fitting the BHM. For each BHM parameter, we calculated the mean of the posterior density and the 95% credible interval. Our model confirmed others' findings that increased sea ice was related to increased krill density. Higher krill density led to reduced dive intensity of maternal fur seals, as measured by dive depth and duration, and to less time spent foraging by maternal fur seals. Heavier maternal fur seals and lower maternal foraging effort resulted in heavier pups at 22 d. No relationship was found between krill density and maternal mass, or between maternal mass and foraging effort on pup growth rates between 22 and 85 days of age. Maternal mass may have reflected environmental conditions prior to the pup provisioning season, rather than summer prey densities. Maternal mass and foraging effort were not related to pup growth rates between 22 and 85 d, possibly indicating that food was not limiting, food sources other than krill were being used, or differences occurred before pups reached age 22 d.

Comparative Effectiveness of Mesalamine, Sulfasalazine, Corticosteroids, and Budesonide for the Induction of Remission in Crohn's Disease: A Bayesian Network Meta-analysis.

PubMed

Coward, Stephanie; Kuenzig, M Ellen; Hazlewood, Glen; Clement, Fiona; McBrien, Kerry; Holmes, Rebecca; Panaccione, Remo; Ghosh, Subrata; Seow, Cynthia H; Rezaie, Ali; Kaplan, Gilaad G

2017-03-01

Induction treatment of mild-to-moderate Crohn's disease is controversial. To compare the induction of remission between different doses of mesalamine, sulfasalazine, corticosteroids, and budesonide for active Crohn's disease. We identified randomized controlled trials from existing Cochrane reviews and an updated literature search in Medline, EMBASE, and CENTRAL to November 2015. We included randomized controlled trials (n = 22) in adult patients with Crohn's disease that compared budesonide, sulfasalazine, mesalamine, or corticosteroids with placebo or each other, for the induction of remission (8-17 wks). Mesalamine (above and below 2.4 g/d) and budesonide (above and below 6 mg/d) were stratified into low and high doses. Our primary outcome was remission, defined as a Crohn's Disease Activity Index score <150. A Bayesian random-effects network meta-analysis was performed on the proportion in remission. Corticosteroids (odds ratio [OR] = 3.80; 95% credible interval [CrI]: 2.48-5.66), high-dose budesonide (OR = 2.96; 95% CrI: 2.06-4.30), and high-dose mesalamine (OR = 2.29; 95% CrI: 1.58-3.33) were superior to placebo. Corticosteroids were similar to high-dose budesonide (OR = 1.21; 95% CrI: 0.84-1.76), but more effective than high-dose mesalamine (OR = 1.83; 95% CrI: 1.16-2.88). Sulfasalazine was not significantly superior to any therapy including placebo. Randomized controlled trials that use a strict definition of induction of remission and disease severity at enrollment to assess effectiveness in treating mild-to-moderate Crohn's disease are limited. Corticosteroids and high-dose budesonide were effective treatments for inducing remission in mild-to-moderate Crohn's disease. High-dose mesalamine is an option among patients preferring to avoid steroids.

Estimation of Coast-Wide Population Trends of Marbled Murrelets in Canada Using a Bayesian Hierarchical Model

PubMed Central

Schroeder, Bernard K.; Lindsay, David J.; Faust, Deborah A.

2015-01-01

Species at risk with secretive breeding behaviours, low densities, and wide geographic range pose a significant challenge to conservation actions because population trends are difficult to detect. Such is the case with the Marbled Murrelet (Brachyramphus marmoratus), a seabird listed as ‘Threatened’ by the Species at Risk Act in Canada largely due to the loss of its old growth forest nesting habitat. We report the first estimates of population trend of Marbled Murrelets in Canada derived from a monitoring program that uses marine radar to detect birds as they enter forest watersheds during 923 dawn surveys at 58 radar monitoring stations within the six Marbled Murrelet Conservation Regions on coastal British Columbia, Canada, 1996–2013. Temporal trends in radar counts were analyzed with a hierarchical Bayesian multivariate modeling approach that controlled for variation in tilt of the radar unit and day of year, included year-specific deviations from the overall trend (‘year effects’), and allowed for trends to be estimated at three spatial scales. A negative overall trend of -1.6%/yr (95% credibility interval: -3.2%, 0.01%) indicated moderate evidence for a coast-wide decline, although trends varied strongly among the six conservation regions. Negative annual trends were detected in East Vancouver Island (-9%/yr) and South Mainland Coast (-3%/yr) Conservation Regions. Over a quarter of the year effects were significantly different from zero, and the estimated standard deviation in common-shared year effects between sites within each region was about 50% per year. This large common-shared interannual variation in counts may have been caused by regional movements of birds related to changes in marine conditions that affect the availability of prey. PMID:26258803

Modeling Input Errors to Improve Uncertainty Estimates for Sediment Transport Model Predictions

NASA Astrophysics Data System (ADS)

Jung, J. Y.; Niemann, J. D.; Greimann, B. P.

2016-12-01

Bayesian methods using Markov chain Monte Carlo algorithms have recently been applied to sediment transport models to assess the uncertainty in the model predictions due to the parameter values. Unfortunately, the existing approaches can only attribute overall uncertainty to the parameters. This limitation is critical because no model can produce accurate forecasts if forced with inaccurate input data, even if the model is well founded in physical theory. In this research, an existing Bayesian method is modified to consider the potential errors in input data during the uncertainty evaluation process. The input error is modeled using Gaussian distributions, and the means and standard deviations are treated as uncertain parameters. The proposed approach is tested by coupling it to the Sedimentation and River Hydraulics - One Dimension (SRH-1D) model and simulating a 23-km reach of the Tachia River in Taiwan. The Wu equation in SRH-1D is used for computing the transport capacity for a bed material load of non-cohesive material. Three types of input data are considered uncertain: (1) the input flowrate at the upstream boundary, (2) the water surface elevation at the downstream boundary, and (3) the water surface elevation at a hydraulic structure in the middle of the reach. The benefits of modeling the input errors in the uncertainty analysis are evaluated by comparing the accuracy of the most likely forecast and the coverage of the observed data by the credible intervals to those of the existing method. The results indicate that the internal boundary condition has the largest uncertainty among those considered. Overall, the uncertainty estimates from the new method are notably different from those of the existing method for both the calibration and forecast periods.

45 CFR 158.231 - Life-years used to determine credible experience.

Code of Federal Regulations, 2013 CFR

2013-10-01

... 45 Public Welfare 1 2013-10-01 2013-10-01 false Life-years used to determine credible experience... and Providing the Rebate § 158.231 Life-years used to determine credible experience. (a) The life-years used to determine the credibility of an issuer's experience are the life-years for the MLR...

45 CFR 158.231 - Life-years used to determine credible experience.

Code of Federal Regulations, 2014 CFR

2014-10-01

... 45 Public Welfare 1 2014-10-01 2014-10-01 false Life-years used to determine credible experience... and Providing the Rebate § 158.231 Life-years used to determine credible experience. (a) The life-years used to determine the credibility of an issuer's experience are the life-years for the MLR...

A BAYESIAN SPATIAL AND TEMPORAL MODELING APPROACH TO MAPPING GEOGRAPHIC VARIATION IN MORTALITY RATES FOR SUBNATIONAL AREAS WITH R-INLA.

PubMed

Khana, Diba; Rossen, Lauren M; Hedegaard, Holly; Warner, Margaret

2018-01-01

Hierarchical Bayes models have been used in disease mapping to examine small scale geographic variation. State level geographic variation for less common causes of mortality outcomes have been reported however county level variation is rarely examined. Due to concerns about statistical reliability and confidentiality, county-level mortality rates based on fewer than 20 deaths are suppressed based on Division of Vital Statistics, National Center for Health Statistics (NCHS) statistical reliability criteria, precluding an examination of spatio-temporal variation in less common causes of mortality outcomes such as suicide rates (SRs) at the county level using direct estimates. Existing Bayesian spatio-temporal modeling strategies can be applied via Integrated Nested Laplace Approximation (INLA) in R to a large number of rare causes of mortality outcomes to enable examination of spatio-temporal variations on smaller geographic scales such as counties. This method allows examination of spatiotemporal variation across the entire U.S., even where the data are sparse. We used mortality data from 2005-2015 to explore spatiotemporal variation in SRs, as one particular application of the Bayesian spatio-temporal modeling strategy in R-INLA to predict year and county-specific SRs. Specifically, hierarchical Bayesian spatio-temporal models were implemented with spatially structured and unstructured random effects, correlated time effects, time varying confounders and space-time interaction terms in the software R-INLA, borrowing strength across both counties and years to produce smoothed county level SRs. Model-based estimates of SRs were mapped to explore geographic variation.

Credibility and advocacy in conservation science.

PubMed

Horton, Cristi C; Peterson, Tarla Rai; Banerjee, Paulami; Peterson, Markus J

2016-02-01

Conservation policy sits at the nexus of natural science and politics. On the one hand, conservation scientists strive to maintain scientific credibility by emphasizing that their research findings are the result of disinterested observations of reality. On the other hand, conservation scientists are committed to conservation even if they do not advocate a particular policy. The professional conservation literature offers guidance on negotiating the relationship between scientific objectivity and political advocacy without damaging conservation science's credibility. The value of this guidance, however, may be restricted by limited recognition of credibility's multidimensionality and emergent nature: it emerges through perceptions of expertise, goodwill, and trustworthiness. We used content analysis of the literature to determine how credibility is framed in conservation science as it relates to apparent contradictions between science and advocacy. Credibility typically was framed as a static entity lacking dimensionality. Authors identified expertise or trustworthiness as important, but rarely mentioned goodwill. They usually did not identify expertise, goodwill, or trustworthiness as dimensions of credibility or recognize interactions among these 3 dimensions of credibility. This oversimplification may limit the ability of conservation scientists to contribute to biodiversity conservation. Accounting for the emergent quality and multidimensionality of credibility should enable conservation scientists to advance biodiversity conservation more effectively. © 2015 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Would a madman have been so wise as this?" The effects of source credibility and message credibility on validation.

PubMed

Foy, Jeffrey E; LoCasto, Paul C; Briner, Stephen W; Dyar, Samantha

2017-02-01

Readers rapidly check new information against prior knowledge during validation, but research is inconsistent as to whether source credibility affects validation. We argue that readers are likely to accept highly plausible assertions regardless of source, but that high source credibility may boost acceptance of claims that are less plausible based on general world knowledge. In Experiment 1, participants read narratives with assertions for which the plausibility varied depending on the source. For high credibility sources, we found that readers were faster to read information confirming these assertions relative to contradictory information. We found the opposite patterns for low credibility characters. In Experiment 2, readers read claims from the same high or low credibility sources, but the claims were always plausible based on general world knowledge. Readers consistently took longer to read contradictory information, regardless of source. In Experiment 3, participants read modified versions of "The Tell-Tale Heart," which was narrated entirely by an unreliable source. We manipulated the plausibility of a target event, as well as whether high credibility characters within the story provided confirmatory or contradictory information about the narrator's description of the target event. Though readers rated the narrator as being insane, they were more likely to believe the narrator's assertions about the target event when it was plausible and corroborated by other characters. We argue that sourcing research would benefit from focusing on the relationship between source credibility, message credibility, and multiple sources within a text.

Treatment credibility, expectancy, and preference: Prediction of treatment engagement and outcome in a randomized clinical trial of hatha yoga vs. health education as adjunct treatments for depression.

PubMed

Uebelacker, Lisa A; Weinstock, Lauren M; Battle, Cynthia L; Abrantes, Ana M; Miller, Ivan W

2018-06-02

Hatha yoga may be helpful for alleviating depression symptoms. The purpose of this analysis is to determine whether treatment program preference, credibility, or expectancy predict engagement in depression interventions (yoga or a control class) or depression symptom severity over time. This is a secondary analysis of a randomized controlled trial (RCT) of hatha yoga vs. a health education control group for treatment of depression. Depressed participants (n = 122) attended up to 20 classes over a period of 10 weeks, and then completed additional assessments after 3 and 6 months. We assessed treatment preference prior to randomization, and treatment credibility and expectancy after participants attended their first class. Treatment "concordance" indicated that treatment preference matched assigned treatment. Treatment credibility, expectancy, and concordance were not associated with treatment engagement. Treatment expectancy moderated the association between treatment group and depression. Depression severity over time differed by expectancy level for the yoga group but not for the health education group. Controlling for baseline depression, participants in the yoga group with an average or high expectancy for improvement showed lower depression symptoms across the acute intervention and follow-up period than those with a low expectancy for improvement. There was a trend for a similar pattern for credibility. Concordance was not associated with treatment outcome. This is a secondary, post-hoc analysis and should be considered hypothesis-generating. Results suggest that expectancy improves the likelihood of success only for a intervention thought to actively target depression (yoga) and not a control intervention. Copyright © 2018. Published by Elsevier B.V.

Further Validation of the Conner's Adult Attention Deficit/Hyperactivity Rating Scale Infrequency Index (CII) for Detection of Non-Credible Report of Attention Deficit/Hyperactivity Disorder Symptoms.

PubMed

Cook, Carolyn M; Bolinger, Elizabeth; Suhr, Julie

2016-06-01

Attention deficit/hyperactivity disorder (ADHD) can be easily presented in a non-credible manner, through non-credible report of ADHD symptoms and/or by non-credible performance on neuropsychological tests. While most studies have focused on detection of non-credible performance using performance validity tests, there are few studies examining the ability to detect non-credible report of ADHD symptoms. We provide further validation data for a recently developed measure of non-credible ADHD symptom report, the Conner's Adult ADHD Rating Scales (CAARS) Infrequency Index (CII). Using archival data from 86 adults referred for concerns about ADHD, we examined the accuracy of the CII in detecting extreme scores on the CAARS and invalid reporting on validity indices of the Minnesota Multiphasic Personality Inventory-2 Restructured Format (MMPI-2-RF). We also examined the accuracy of the CII in detecting non-credible performance on standalone and embedded performance validity tests. The CII was 52% sensitive to extreme scores on CAARS DSM symptom subscales (with 97% specificity) and 20%-36% sensitive to invalid responding on MMPI-2-RF validity scales (with near 90% specificity), providing further evidence for the interpretation of the CII as an indicator of non-credible ADHD symptom report. However, the CII detected only 18% of individuals who failed a standalone performance validity test (Word Memory Test), with 87.8% specificity, and was not accurate in detecting non-credible performance using embedded digit span cutoffs. Future studies should continue to examine how best to assess for non-credible symptom report in ADHD referrals. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants.

PubMed

Dadaev, Tokhir; Saunders, Edward J; Newcombe, Paul J; Anokian, Ezequiel; Leongamornlert, Daniel A; Brook, Mark N; Cieza-Borrella, Clara; Mijuskovic, Martina; Wakerell, Sarah; Olama, Ali Amin Al; Schumacher, Fredrick R; Berndt, Sonja I; Benlloch, Sara; Ahmed, Mahbubl; Goh, Chee; Sheng, Xin; Zhang, Zhuo; Muir, Kenneth; Govindasami, Koveela; Lophatananon, Artitaya; Stevens, Victoria L; Gapstur, Susan M; Carter, Brian D; Tangen, Catherine M; Goodman, Phyllis; Thompson, Ian M; Batra, Jyotsna; Chambers, Suzanne; Moya, Leire; Clements, Judith; Horvath, Lisa; Tilley, Wayne; Risbridger, Gail; Gronberg, Henrik; Aly, Markus; Nordström, Tobias; Pharoah, Paul; Pashayan, Nora; Schleutker, Johanna; Tammela, Teuvo L J; Sipeky, Csilla; Auvinen, Anssi; Albanes, Demetrius; Weinstein, Stephanie; Wolk, Alicja; Hakansson, Niclas; West, Catharine; Dunning, Alison M; Burnet, Neil; Mucci, Lorelei; Giovannucci, Edward; Andriole, Gerald; Cussenot, Olivier; Cancel-Tassin, Géraldine; Koutros, Stella; Freeman, Laura E Beane; Sorensen, Karina Dalsgaard; Orntoft, Torben Falck; Borre, Michael; Maehle, Lovise; Grindedal, Eli Marie; Neal, David E; Donovan, Jenny L; Hamdy, Freddie C; Martin, Richard M; Travis, Ruth C; Key, Tim J; Hamilton, Robert J; Fleshner, Neil E; Finelli, Antonio; Ingles, Sue Ann; Stern, Mariana C; Rosenstein, Barry; Kerns, Sarah; Ostrer, Harry; Lu, Yong-Jie; Zhang, Hong-Wei; Feng, Ninghan; Mao, Xueying; Guo, Xin; Wang, Guomin; Sun, Zan; Giles, Graham G; Southey, Melissa C; MacInnis, Robert J; FitzGerald, Liesel M; Kibel, Adam S; Drake, Bettina F; Vega, Ana; Gómez-Caamaño, Antonio; Fachal, Laura; Szulkin, Robert; Eklund, Martin; Kogevinas, Manolis; Llorca, Javier; Castaño-Vinyals, Gemma; Penney, Kathryn L; Stampfer, Meir; Park, Jong Y; Sellers, Thomas A; Lin, Hui-Yi; Stanford, Janet L; Cybulski, Cezary; Wokolorczyk, Dominika; Lubinski, Jan; Ostrander, Elaine A; Geybels, Milan S; Nordestgaard, Børge G; Nielsen, Sune F; Weisher, Maren; Bisbjerg, Rasmus; Røder, Martin Andreas; Iversen, Peter; Brenner, Hermann; Cuk, Katarina; Holleczek, Bernd; Maier, Christiane; Luedeke, Manuel; Schnoeller, Thomas; Kim, Jeri; Logothetis, Christopher J; John, Esther M; Teixeira, Manuel R; Paulo, Paula; Cardoso, Marta; Neuhausen, Susan L; Steele, Linda; Ding, Yuan Chun; De Ruyck, Kim; De Meerleer, Gert; Ost, Piet; Razack, Azad; Lim, Jasmine; Teo, Soo-Hwang; Lin, Daniel W; Newcomb, Lisa F; Lessel, Davor; Gamulin, Marija; Kulis, Tomislav; Kaneva, Radka; Usmani, Nawaid; Slavov, Chavdar; Mitev, Vanio; Parliament, Matthew; Singhal, Sandeep; Claessens, Frank; Joniau, Steven; Van den Broeck, Thomas; Larkin, Samantha; Townsend, Paul A; Aukim-Hastie, Claire; Gago-Dominguez, Manuela; Castelao, Jose Esteban; Martinez, Maria Elena; Roobol, Monique J; Jenster, Guido; van Schaik, Ron H N; Menegaux, Florence; Truong, Thérèse; Koudou, Yves Akoli; Xu, Jianfeng; Khaw, Kay-Tee; Cannon-Albright, Lisa; Pandha, Hardev; Michael, Agnieszka; Kierzek, Andrzej; Thibodeau, Stephen N; McDonnell, Shannon K; Schaid, Daniel J; Lindstrom, Sara; Turman, Constance; Ma, Jing; Hunter, David J; Riboli, Elio; Siddiq, Afshan; Canzian, Federico; Kolonel, Laurence N; Le Marchand, Loic; Hoover, Robert N; Machiela, Mitchell J; Kraft, Peter; Freedman, Matthew; Wiklund, Fredrik; Chanock, Stephen; Henderson, Brian E; Easton, Douglas F; Haiman, Christopher A; Eeles, Rosalind A; Conti, David V; Kote-Jarai, Zsofia

2018-06-11

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.

National spatial and temporal patterns of notified dengue cases, Colombia 2007-2010.

PubMed

Restrepo, Angela Cadavid; Baker, Peter; Clements, Archie C A

2014-07-01

To explore the variation in the spatial distribution of notified dengue cases in Colombia from January 2007 to December 2010 and examine associations between the disease and selected environmental risk factors. Data on the number of notified dengue cases in Colombia were obtained from the National Institute of Health (Instituto Nacional de Salud - INS) for the period 1 January 2007 through 31 December 2010. Data on environmental factors were collected from the Worldclim website. A Bayesian spatio-temporal conditional autoregressive model was used to quantify the relationship between monthly dengue cases and temperature, precipitation and elevation. Monthly dengue counts decreased by 18% (95% credible interval (CrI): 17-19%) in 2008 and increased by 30% (95% CrI: 28-31%) and 326% (95% CrI: 322-331%) in 2009 and 2010, respectively, compared to 2007. Additionally, there was a significant, nonlinear effect of monthly average precipitation. The results highlight the role of environmental risk factors in determining the spatial of dengue and show how these factors can be used to develop and refine preventive approaches for dengue in Colombia. © 2014 John Wiley & Sons Ltd.

A Systematic Review of the Literature on Cystic Echinococcosis Frequency Worldwide and Its Associated Clinical Manifestations

PubMed Central

Budke, Christine M.; Carabin, Hélène; Ndimubanzi, Patrick C.; Nguyen, Hai; Rainwater, Elizabeth; Dickey, Mary; Bhattarai, Rachana; Zeziulin, Oleksandr; Qian, Men-Bao

2013-01-01

A systematic literature review of cystic echinoccocosis (CE) frequency and symptoms was conducted. Studies without denominators, original data, or using one serological test were excluded. Random-effect log-binomial models were run for CE frequency and proportion of reported symptoms where appropriate. A total of 45 and 25 articles on CE frequency and symptoms met all inclusion criteria. Prevalence of CE ranged from 1% to 7% in community-based studies and incidence rates ranged from 0 to 32 cases per 100,000 in hospital-based studies. The CE prevalence was higher in females (Prevalence Proportion Ratio: 1.35 [95% Bayesian Credible Interval: 1.16–1.53]) and increased with age. The most common manifestations of hepatic and pulmonary CE were abdominal pain (57.3% [95% confidence interval [CI]: 37.3–76.1%]) and cough (51.3% [95% CI: 35.7–66.7%]), respectively. The results are limited by the small number of unbiased studies. Nonetheless, the age/gender prevalence differences could be used to inform future models of CE burden. PMID:23546806

A systematic review of the literature on cystic echinococcosis frequency worldwide and its associated clinical manifestations.

PubMed

Budke, Christine M; Carabin, Hélène; Ndimubanzi, Patrick C; Nguyen, Hai; Rainwater, Elizabeth; Dickey, Mary; Bhattarai, Rachana; Zeziulin, Oleksandr; Qian, Men-Bao

2013-06-01

A systematic literature review of cystic echinoccocosis (CE) frequency and symptoms was conducted. Studies without denominators, original data, or using one serological test were excluded. Random-effect log-binomial models were run for CE frequency and proportion of reported symptoms where appropriate. A total of 45 and 25 articles on CE frequency and symptoms met all inclusion criteria. Prevalence of CE ranged from 1% to 7% in community-based studies and incidence rates ranged from 0 to 32 cases per 100,000 in hospital-based studies. The CE prevalence was higher in females (Prevalence Proportion Ratio: 1.35 [95% Bayesian Credible Interval: 1.16-1.53]) and increased with age. The most common manifestations of hepatic and pulmonary CE were abdominal pain (57.3% [95% confidence interval [CI]: 37.3-76.1%]) and cough (51.3% [95% CI: 35.7-66.7%]), respectively. The results are limited by the small number of unbiased studies. Nonetheless, the age/gender prevalence differences could be used to inform future models of CE burden.

Number-Knower Levels in Young Children: Insights from Bayesian Modeling

ERIC Educational Resources Information Center

Lee, Michael D.; Sarnecka, Barbara W.

2011-01-01

Lee and Sarnecka (2010) developed a Bayesian model of young children's behavior on the Give-N test of number knowledge. This paper presents two new extensions of the model, and applies the model to new data. In the first extension, the model is used to evaluate competing theories about the conceptual knowledge underlying children's behavior. One,…

Guidelines for developing and updating Bayesian belief networks applied to ecological modeling and conservation.

Treesearch

B.G. Marcot; J.D. Steventon; G.D. Sutherland; R.K. McCann

2006-01-01

We provide practical guidelines for developing, testing, and revising Bayesian belief networks (BBNs). Primary steps in this process include creating influence diagrams of the hypothesized "causal web" of key factors affecting a species or ecological outcome of interest; developing a first, alpha-level BBN model from the influence diagram; revising the model...

Effect of Bayesian Student Modeling on Academic Achievement in Foreign Language Teaching (University Level English Preparatory School Example)

ERIC Educational Resources Information Center

Aslan, Burak Galip; Öztürk, Özlem; Inceoglu, Mustafa Murat

2014-01-01

Considering the increasing importance of adaptive approaches in CALL systems, this study implemented a machine learning based student modeling middleware with Bayesian networks. The profiling approach of the student modeling system is based on Felder and Silverman's Learning Styles Model and Felder and Soloman's Index of Learning Styles…

Bayesian estimation and use of high-throughput remote sensing indices for quantitative genetic analyses of leaf growth.

PubMed

Baker, Robert L; Leong, Wen Fung; An, Nan; Brock, Marcus T; Rubin, Matthew J; Welch, Stephen; Weinig, Cynthia

2018-02-01

We develop Bayesian function-valued trait models that mathematically isolate genetic mechanisms underlying leaf growth trajectories by factoring out genotype-specific differences in photosynthesis. Remote sensing data can be used instead of leaf-level physiological measurements. Characterizing the genetic basis of traits that vary during ontogeny and affect plant performance is a major goal in evolutionary biology and agronomy. Describing genetic programs that specifically regulate morphological traits can be complicated by genotypic differences in physiological traits. We describe the growth trajectories of leaves using novel Bayesian function-valued trait (FVT) modeling approaches in Brassica rapa recombinant inbred lines raised in heterogeneous field settings. While frequentist approaches estimate parameter values by treating each experimental replicate discretely, Bayesian models can utilize information in the global dataset, potentially leading to more robust trait estimation. We illustrate this principle by estimating growth asymptotes in the face of missing data and comparing heritabilities of growth trajectory parameters estimated by Bayesian and frequentist approaches. Using pseudo-Bayes factors, we compare the performance of an initial Bayesian logistic growth model and a model that incorporates carbon assimilation (A max ) as a cofactor, thus statistically accounting for genotypic differences in carbon resources. We further evaluate two remotely sensed spectroradiometric indices, photochemical reflectance (pri2) and MERIS Terrestrial Chlorophyll Index (mtci) as covariates in lieu of A max , because these two indices were genetically correlated with A max across years and treatments yet allow much higher throughput compared to direct leaf-level gas-exchange measurements. For leaf lengths in uncrowded settings, including A max improves model fit over the initial model. The mtci and pri2 indices also outperform direct A max measurements. Of particular importance for evolutionary biologists and plant breeders, hierarchical Bayesian models estimating FVT parameters improve heritabilities compared to frequentist approaches.

Evaluating Multiple Perspectives: Approaching the Synthesis Task through Assessing Credibility

ERIC Educational Resources Information Center

Lafferty, Karen Elizabeth; Summers, Amy; Tanaka, Stephanie; Cavanagh, Jeanne

2016-01-01

Introduction of the Common Core State Standards and assessments like the synthesis performance task pose new challenges for secondary English teachers. As students of all ability levels engage with complex text and in tasks that target higher level cognitive skills, teachers need strategies to support their understanding. This article describes…

Informative Bayesian Type A uncertainty evaluation, especially applicable to a small number of observations

NASA Astrophysics Data System (ADS)

Cox, M.; Shirono, K.

2017-10-01

A criticism levelled at the Guide to the Expression of Uncertainty in Measurement (GUM) is that it is based on a mixture of frequentist and Bayesian thinking. In particular, the GUM’s Type A (statistical) uncertainty evaluations are frequentist, whereas the Type B evaluations, using state-of-knowledge distributions, are Bayesian. In contrast, making the GUM fully Bayesian implies, among other things, that a conventional objective Bayesian approach to Type A uncertainty evaluation for a number n of observations leads to the impractical consequence that n must be at least equal to 4, thus presenting a difficulty for many metrologists. This paper presents a Bayesian analysis of Type A uncertainty evaluation that applies for all n ≥slant 2 , as in the frequentist analysis in the current GUM. The analysis is based on assuming that the observations are drawn from a normal distribution (as in the conventional objective Bayesian analysis), but uses an informative prior based on lower and upper bounds for the standard deviation of the sampling distribution for the quantity under consideration. The main outcome of the analysis is a closed-form mathematical expression for the factor by which the standard deviation of the mean observation should be multiplied to calculate the required standard uncertainty. Metrological examples are used to illustrate the approach, which is straightforward to apply using a formula or look-up table.

An evaluation of Bayesian techniques for controlling model complexity and selecting inputs in a neural network for short-term load forecasting.

PubMed

Hippert, Henrique S; Taylor, James W

2010-04-01

Artificial neural networks have frequently been proposed for electricity load forecasting because of their capabilities for the nonlinear modelling of large multivariate data sets. Modelling with neural networks is not an easy task though; two of the main challenges are defining the appropriate level of model complexity, and choosing the input variables. This paper evaluates techniques for automatic neural network modelling within a Bayesian framework, as applied to six samples containing daily load and weather data for four different countries. We analyse input selection as carried out by the Bayesian 'automatic relevance determination', and the usefulness of the Bayesian 'evidence' for the selection of the best structure (in terms of number of neurones), as compared to methods based on cross-validation. Copyright 2009 Elsevier Ltd. All rights reserved.

Prediction of community prevalence of human onchocerciasis in the Amazonian onchocerciasis focus: Bayesian approach.

PubMed Central

Carabin, Hélène; Escalona, Marisela; Marshall, Clare; Vivas-Martínez, Sarai; Botto, Carlos; Joseph, Lawrence; Basáñez, María-Gloria

2003-01-01

OBJECTIVE: To develop a Bayesian hierarchical model for human onchocerciasis with which to explore the factors that influence prevalence of microfilariae in the Amazonian focus of onchocerciasis and predict the probability of any community being at least mesoendemic (>20% prevalence of microfilariae), and thus in need of priority ivermectin treatment. METHODS: Models were developed with data from 732 individuals aged > or =15 years who lived in 29 Yanomami communities along four rivers of the south Venezuelan Orinoco basin. The models' abilities to predict prevalences of microfilariae in communities were compared. The deviance information criterion, Bayesian P-values, and residual values were used to select the best model with an approximate cross-validation procedure. FINDINGS: A three-level model that acknowledged clustering of infection within communities performed best, with host age and sex included at the individual level, a river-dependent altitude effect at the community level, and additional clustering of communities along rivers. This model correctly classified 25/29 (86%) villages with respect to their need for priority ivermectin treatment. CONCLUSION: Bayesian methods are a flexible and useful approach for public health research and control planning. Our model acknowledges the clustering of infection within communities, allows investigation of links between individual- or community-specific characteristics and infection, incorporates additional uncertainty due to missing covariate data, and informs policy decisions by predicting the probability that a new community is at least mesoendemic. PMID:12973640

Prediction of community prevalence of human onchocerciasis in the Amazonian onchocerciasis focus: Bayesian approach.

PubMed

Carabin, Hélène; Escalona, Marisela; Marshall, Clare; Vivas-Martínez, Sarai; Botto, Carlos; Joseph, Lawrence; Basáñez, María-Gloria

2003-01-01

To develop a Bayesian hierarchical model for human onchocerciasis with which to explore the factors that influence prevalence of microfilariae in the Amazonian focus of onchocerciasis and predict the probability of any community being at least mesoendemic (>20% prevalence of microfilariae), and thus in need of priority ivermectin treatment. Models were developed with data from 732 individuals aged > or =15 years who lived in 29 Yanomami communities along four rivers of the south Venezuelan Orinoco basin. The models' abilities to predict prevalences of microfilariae in communities were compared. The deviance information criterion, Bayesian P-values, and residual values were used to select the best model with an approximate cross-validation procedure. A three-level model that acknowledged clustering of infection within communities performed best, with host age and sex included at the individual level, a river-dependent altitude effect at the community level, and additional clustering of communities along rivers. This model correctly classified 25/29 (86%) villages with respect to their need for priority ivermectin treatment. Bayesian methods are a flexible and useful approach for public health research and control planning. Our model acknowledges the clustering of infection within communities, allows investigation of links between individual- or community-specific characteristics and infection, incorporates additional uncertainty due to missing covariate data, and informs policy decisions by predicting the probability that a new community is at least mesoendemic.

Gender, smiling, and witness credibility in actual trials.

PubMed

Nagle, Jacklyn E; Brodsky, Stanley L; Weeter, Kaycee

2014-01-01

It has been acknowledged that females exhibit more smiling behaviors than males, but there has been little attention to this gender difference in the courtroom. Although both male and female witnesses exhibit smiling behaviors, there has been no research examining the subsequent effect of gender and smiling on witness credibility. This study used naturalistic observation to examine smiling behaviors and credibility in actual witnesses testifying in court. Raters assessed the smiling behaviors and credibility (as measured by the Witness Credibility Scale) of 32 male and female witnesses testifying in trials in a mid-sized Southern city. "Credibility raters" rated the perceived likeability, trustworthiness, confidence, knowledge, and overall credibility of the witnesses using the Witness Credibility Scale. "Smile raters" noted smiling frequency and types, including speaking/expressive and listening/receptive smiles. Gender was found to affect perceived trustworthiness ratings, in which male witnesses were seen as more trustworthy than female witnesses. No significant differences were found in the smiling frequency for male and female witnesses. However, the presence of smiling was found to contribute to perceived likeability of a witness. Smiling female witnesses were found to be more likeable than smiling male and non-smiling female witnesses. Copyright © 2014 John Wiley & Sons, Ltd.

A Bayesian Performance Prediction Model for Mathematics Education: A Prototypical Approach for Effective Group Composition

ERIC Educational Resources Information Center

Bekele, Rahel; McPherson, Maggie

2011-01-01

This research work presents a Bayesian Performance Prediction Model that was created in order to determine the strength of personality traits in predicting the level of mathematics performance of high school students in Addis Ababa. It is an automated tool that can be used to collect information from students for the purpose of effective group…

A simulation study on Bayesian Ridge regression models for several collinearity levels

NASA Astrophysics Data System (ADS)

Efendi, Achmad; Effrihan

2017-12-01

When analyzing data with multiple regression model if there are collinearities, then one or several predictor variables are usually omitted from the model. However, there sometimes some reasons, for instance medical or economic reasons, the predictors are all important and should be included in the model. Ridge regression model is not uncommon in some researches to use to cope with collinearity. Through this modeling, weights for predictor variables are used for estimating parameters. The next estimation process could follow the concept of likelihood. Furthermore, for the estimation nowadays the Bayesian version could be an alternative. This estimation method does not match likelihood one in terms of popularity due to some difficulties; computation and so forth. Nevertheless, with the growing improvement of computational methodology recently, this caveat should not at the moment become a problem. This paper discusses about simulation process for evaluating the characteristic of Bayesian Ridge regression parameter estimates. There are several simulation settings based on variety of collinearity levels and sample sizes. The results show that Bayesian method gives better performance for relatively small sample sizes, and for other settings the method does perform relatively similar to the likelihood method.

Bayesian spatio-temporal modeling of particulate matter concentrations in Peninsular Malaysia

NASA Astrophysics Data System (ADS)

Manga, Edna; Awang, Norhashidah

2016-06-01

This article presents an application of a Bayesian spatio-temporal Gaussian process (GP) model on particulate matter concentrations from Peninsular Malaysia. We analyze daily PM10 concentration levels from 35 monitoring sites in June and July 2011. The spatiotemporal model set in a Bayesian hierarchical framework allows for inclusion of informative covariates, meteorological variables and spatiotemporal interactions. Posterior density estimates of the model parameters are obtained by Markov chain Monte Carlo methods. Preliminary data analysis indicate information on PM10 levels at sites classified as industrial locations could explain part of the space time variations. We include the site-type indicator in our modeling efforts. Results of the parameter estimates for the fitted GP model show significant spatio-temporal structure and positive effect of the location-type explanatory variable. We also compute some validation criteria for the out of sample sites that show the adequacy of the model for predicting PM10 at unmonitored sites.

Bayesian Computation for Log-Gaussian Cox Processes: A Comparative Analysis of Methods

PubMed Central

Teng, Ming; Nathoo, Farouk S.; Johnson, Timothy D.

2017-01-01

The Log-Gaussian Cox Process is a commonly used model for the analysis of spatial point pattern data. Fitting this model is difficult because of its doubly-stochastic property, i.e., it is an hierarchical combination of a Poisson process at the first level and a Gaussian Process at the second level. Various methods have been proposed to estimate such a process, including traditional likelihood-based approaches as well as Bayesian methods. We focus here on Bayesian methods and several approaches that have been considered for model fitting within this framework, including Hamiltonian Monte Carlo, the Integrated nested Laplace approximation, and Variational Bayes. We consider these approaches and make comparisons with respect to statistical and computational efficiency. These comparisons are made through several simulation studies as well as through two applications, the first examining ecological data and the second involving neuroimaging data. PMID:29200537

A hierarchical, ontology-driven Bayesian concept for ubiquitous medical environments--a case study for pulmonary diseases.

PubMed

Maragoudakis, Manolis; Lymberopoulos, Dimitrios; Fakotakis, Nikos; Spiropoulos, Kostas

2008-01-01

The present paper extends work on an existing computer-based Decision Support System (DSS) that aims to provide assistance to physicians as regards to pulmonary diseases. The extension deals with allowing for a hierarchical decomposition of the task, at different levels of domain granularity, using a novel approach, i.e. Hierarchical Bayesian Networks. The proposed framework uses data from various networking appliances such as mobile phones and wireless medical sensors to establish a ubiquitous environment for medical treatment of pulmonary diseases. Domain knowledge is encoded at the upper levels of the hierarchy, thus making the process of generalization easier to accomplish. The experimental results were carried out under the Pulmonary Department, University Regional Hospital Patras, Patras, Greece. They have supported our initial beliefs about the ability of Bayesian networks to provide an effective, yet semantically-oriented, means of prognosis and reasoning under conditions of uncertainty.

Gaussian Process Model for Antarctic Surface Mass Balance and Ice Core Site Selection

NASA Astrophysics Data System (ADS)

White, P. A.; Reese, S.; Christensen, W. F.; Rupper, S.

2017-12-01

Surface mass balance (SMB) is an important factor in the estimation of sea level change, and data are collected to estimate models for prediction of SMB on the Antarctic ice sheet. Using Favier et al.'s (2013) quality-controlled aggregate data set of SMB field measurements, a fully Bayesian spatial model is posed to estimate Antarctic SMB and propose new field measurement locations. Utilizing Nearest-Neighbor Gaussian process (NNGP) models, SMB is estimated over the Antarctic ice sheet. An Antarctic SMB map is rendered using this model and is compared with previous estimates. A prediction uncertainty map is created to identify regions of high SMB uncertainty. The model estimates net SMB to be 2173 Gton yr-1 with 95% credible interval (2021,2331) Gton yr-1. On average, these results suggest lower Antarctic SMB and higher uncertainty than previously purported [Vaughan et al. (1999); Van de Berg et al. (2006); Arthern, Winebrenner and Vaughan (2006); Bromwich et al. (2004); Lenaerts et al. (2012)], even though this model utilizes significantly more observations than previous models. Using the Gaussian process' uncertainty and model parameters, we propose 15 new measurement locations for field study utilizing a maximin space-filling, error-minimizing design; these potential measurements are identied to minimize future estimation uncertainty. Using currently accepted Antarctic mass balance estimates and our SMB estimate, we estimate net mass loss [Shepherd et al. (2012); Jacob et al. (2012)]. Furthermore, we discuss modeling details for both space-time data and combining field measurement data with output from mathematical models using the NNGP framework.

First search at CDF for the Higgs boson decaying to a W-boson pair in proton-antiproton collisions at the center-of-mass energy of 1.96 TeV

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chuang, Shan-Huei S.

2006-01-01

By way of retaining the gauge invariance of the Standard Model (SM) and giving masses to the W ± and Z 0 bosons and the fermions, the Higgs mechanism predicts the existence of a neutral scalar bosonic particle, whose mass is not exactly known. The Higgs boson is the only experimentally unconfirmed SM particle to date. This thesis documents a search for the Higgs boson in pmore » $$\\bar{p}$$ collisions at √s = 1.96 TeV at the Tevatron, using 360 ± pb -1 data collected by the Run II Collider Detector at Fermilab (CDF II), as part of the most important quest for contemporary particle physicists. The search was for a Higgs boson decaying to a pair of W ± bosons, where each W boson decays to an electron, a muon or a tau that further decays to an electron or a muon with associated neutrinos. Events with two charged leptons plus large missing energy were selected in data triggered on a high p$$\\bar{p}$$ lepton and compared to the signal and backgrounds modeled using Monte Carlo and jet data. No signal-like excess was observed in data. Therefore, upper limits on the HWW production cross-section in the analyzed mass range were extracted using the binned likelihood maximum from distributions of dilepton azimuthal angle at 95% Bayesian credibility level (CL), as shown in the table below.« less

Spatial Patterns and Socioecological Drivers of Dengue Fever Transmission in Queensland, Australia

PubMed Central

Clements, Archie; Williams, Gail; Tong, Shilu; Mengersen, Kerrie

2011-01-01

Background: Understanding how socioecological factors affect the transmission of dengue fever (DF) may help to develop an early warning system of DF. Objectives: We examined the impact of socioecological factors on the transmission of DF and assessed potential predictors of locally acquired and overseas-acquired cases of DF in Queensland, Australia. Methods: We obtained data from Queensland Health on the numbers of notified DF cases by local government area (LGA) in Queensland for the period 1 January 2002 through 31 December 2005. Data on weather and the socioeconomic index were obtained from the Australian Bureau of Meteorology and the Australian Bureau of Statistics, respectively. A Bayesian spatial conditional autoregressive model was fitted at the LGA level to quantify the relationship between DF and socioecological factors. Results: Our estimates suggest an increase in locally acquired DF of 6% [95% credible interval (CI): 2%, 11%] and 61% (95% CI: 2%, 241%) in association with a 1-mm increase in average monthly rainfall and a 1°C increase in average monthly maximum temperature between 2002 and 2005, respectively. By contrast, overseas-acquired DF cases increased by 1% (95% CI: 0%, 3%) and by 1% (95% CI: 0%, 2%) in association with a 1-mm increase in average monthly rainfall and a 1-unit increase in average socioeconomic index, respectively. Conclusions: Socioecological factors appear to influence the transmission of DF in Queensland, but the drivers of locally acquired and overseas-acquired DF may differ. DF risk is spatially clustered with different patterns for locally acquired and overseas-acquired cases. PMID:22015625

An analysis of possible applications of fuzzy set theory to the actuarial credibility theory

NASA Technical Reports Server (NTRS)

Ostaszewski, Krzysztof; Karwowski, Waldemar

1992-01-01

In this work, we review the basic concepts of actuarial credibility theory from the point of view of introducing applications of the fuzzy set-theoretic method. We show how the concept of actuarial credibility can be modeled through the fuzzy set membership functions and how fuzzy set methods, especially fuzzy pattern recognition, can provide an alternative tool for estimating credibility.

Comparative Effectiveness of 12 Treatment Strategies for Preventing Contrast-Induced Acute Kidney Injury: A Systematic Review and Bayesian Network Meta-analysis.

PubMed

Su, Xiaole; Xie, Xinfang; Liu, Lijun; Lv, Jicheng; Song, Fujian; Perkovic, Vlado; Zhang, Hong

2017-01-01

To simultaneously evaluate the relative efficacy of multiple pharmacologic strategies for preventing contrast-induced acute kidney injury (AKI). Systematic review containing a Bayesian network meta-analysis of randomized controlled trials. Participants undergoing diagnostic and/or interventional procedures with contrast media. Randomized controlled trials comparing the active drug treatments with each other or with hydration alone. Any of the following drugs in combination with hydration: N-acetylcysteine (NAC), theophylline (aminophylline), fenoldopam, iloprost, alprostadil, prostaglandin E 1 , statins, statins plus NAC, bicarbonate sodium, bicarbonate sodium plus NAC, ascorbic acid (vitamin C), tocopherol (vitamin E), α-lipoic acid, atrial natriuretic peptide, B-type natriuretic peptide, and carperitide. The occurrence of contrast-induced AKI. The trial network included 150 trials with 31,631 participants and 4,182 contrast-induced AKI events assessing 12 different interventions. Compared to hydration, ORs (95% credible intervals) for contrast-induced AKI were 0.31 (0.14-0.60) for high-dose statin plus NAC, 0.37 (0.19-0.64) for high-dose statin alone, 0.37 (0.17-0.72) for prostaglandins, 0.48 (0.26-0.82) for theophylline, 0.62 (0.40-0.88) for bicarbonate sodium plus NAC, 0.67 (0.54-0.81) for NAC alone, 0.64 (0.41-0.95) for vitamins and analogues, 0.70 (0.29-1.37) for natriuretic peptides, 0.69 (0.31-1.37) for fenoldopam, 0.78 (0.59-1.01) for bicarbonate sodium, and 0.98 (0.41-2.07) for low-dose statin. High-dose statin plus NAC or high-dose statin alone were likely to be ranked the best or the second best for preventing contrast-induced AKI. The overall results were not materially changed in metaregressions or subgroup and sensitivity analyses. Patient-level data were unavailable; unable to include some treatment agents; low event rates; imbalanced distribution of participants among treatment strategies. High-dose statins plus hydration with or without NAC might be the preferred treatment strategy to prevent contrast-induced AKI in patients undergoing diagnostic and/or interventional procedures requiring contrast media. Copyright © 2016 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

Establishing Credibility in the Multicultural Classroom: When the Instructor Speaks with an Accent

ERIC Educational Resources Information Center

McLean, Chikako Akamatsu

2007-01-01

Applying theories of cultural dimensions, teacher credibility, and nonverbal immediacy, this chapter explores classroom management techniques used by Asian female teachers to establish credibility. (Contains 1 note.)

Radiofrequency Radiation and Teratogenesis: A Comprehensive Review of the Literature Pertinent to Air Force Operations.

DTIC Science & Technology

1996-06-01

credible evidence that chronic exposure of human mothers during pregnancy or of potential fathers to RFR a levels at or below the current maximum guidelines would cause any anomalies in their offspring.

Overview of an internationally-harmonized program for adverse outcome pathway development

EPA Science Inventory

Adverse outcome pathways (AOPs) are critical frameworks for organizing knowledge concerning the scientifically-credible predictive linkages between toxicological observations made at molecular and cellular levels (e.g., via molecular screening assays, biomarker responses, or chem...

Developing and Evaluating Patient Education Materials.

ERIC Educational Resources Information Center

Monsivais, Diane; Reynolds, Audree

2003-01-01

Discusses the rationale for nurse involvement in the development of patient education materials. Presents guidelines for evaluating existing material, including print and web resources, for credibility and readability. Makes recommendations for rewriting material at an easier-to-read level. (SK)

Menarche and Fatness: Reexamination of the Critical Body Composition Hypothesis

ERIC Educational Resources Information Center

Trussell, James

1978-01-01

Examines the credibility of the theory that, menarche and fecundity require a certain level of fat in the body. Concludes that the evidence does not totally support this hypothesis and that further investigation is warranted. (GA)

A Bayesian Model of the Memory Colour Effect.

PubMed

Witzel, Christoph; Olkkonen, Maria; Gegenfurtner, Karl R

2018-01-01

According to the memory colour effect, the colour of a colour-diagnostic object is not perceived independently of the object itself. Instead, it has been shown through an achromatic adjustment method that colour-diagnostic objects still appear slightly in their typical colour, even when they are colourimetrically grey. Bayesian models provide a promising approach to capture the effect of prior knowledge on colour perception and to link these effects to more general effects of cue integration. Here, we model memory colour effects using prior knowledge about typical colours as priors for the grey adjustments in a Bayesian model. This simple model does not involve any fitting of free parameters. The Bayesian model roughly captured the magnitude of the measured memory colour effect for photographs of objects. To some extent, the model predicted observed differences in memory colour effects across objects. The model could not account for the differences in memory colour effects across different levels of realism in the object images. The Bayesian model provides a particularly simple account of memory colour effects, capturing some of the multiple sources of variation of these effects.

A Bayesian Model of the Memory Colour Effect

PubMed Central

Olkkonen, Maria; Gegenfurtner, Karl R.

2018-01-01

According to the memory colour effect, the colour of a colour-diagnostic object is not perceived independently of the object itself. Instead, it has been shown through an achromatic adjustment method that colour-diagnostic objects still appear slightly in their typical colour, even when they are colourimetrically grey. Bayesian models provide a promising approach to capture the effect of prior knowledge on colour perception and to link these effects to more general effects of cue integration. Here, we model memory colour effects using prior knowledge about typical colours as priors for the grey adjustments in a Bayesian model. This simple model does not involve any fitting of free parameters. The Bayesian model roughly captured the magnitude of the measured memory colour effect for photographs of objects. To some extent, the model predicted observed differences in memory colour effects across objects. The model could not account for the differences in memory colour effects across different levels of realism in the object images. The Bayesian model provides a particularly simple account of memory colour effects, capturing some of the multiple sources of variation of these effects. PMID:29760874

A simple Bayesian approach to quantifying confidence level of adverse event incidence proportion in small samples.

PubMed

Liu, Fang

2016-01-01

In both clinical development and post-marketing of a new therapy or a new treatment, incidence of an adverse event (AE) is always a concern. When sample sizes are small, large sample-based inferential approaches on an AE incidence proportion in a certain time period no longer apply. In this brief discussion, we introduce a simple Bayesian framework to quantify, in small sample studies and the rare AE case, (1) the confidence level that the incidence proportion of a particular AE p is over or below a threshold, (2) the lower or upper bounds on p with a certain level of confidence, and (3) the minimum required number of patients with an AE before we can be certain that p surpasses a specific threshold, or the maximum allowable number of patients with an AE after which we can no longer be certain that p is below a certain threshold, given a certain confidence level. The method is easy to understand and implement; the interpretation of the results is intuitive. This article also demonstrates the usefulness of simple Bayesian concepts when it comes to answering practical questions.

The relationship between gene transcription and combinations of histone modifications

NASA Astrophysics Data System (ADS)

Cui, Xiangjun; Li, Hong; Luo, Liaofu

2012-09-01

Histone modification is an important subject of epigenetics which plays an intrinsic role in transcriptional regulation. It is known that multiple histone modifications act in a combinatorial fashion. In this study, we demonstrated that the pathways within constructed Bayesian networks can give an indication for the combinations among 12 histone modifications which have been studied in the TSS+1kb region in S. cerevisiae. After Bayesian networks for the genes with high transcript levels (H-network) and low transcript levels (L-network) were constructed, the combinations of modifications within the two networks were analyzed from the view of transcript level. The results showed that different combinations played dissimilar roles in the regulation of gene transcription when there exist differences for gene expression at transcription level.

Refining value-at-risk estimates using a Bayesian Markov-switching GJR-GARCH copula-EVT model.

PubMed

Sampid, Marius Galabe; Hasim, Haslifah M; Dai, Hongsheng

2018-01-01

In this paper, we propose a model for forecasting Value-at-Risk (VaR) using a Bayesian Markov-switching GJR-GARCH(1,1) model with skewed Student's-t innovation, copula functions and extreme value theory. A Bayesian Markov-switching GJR-GARCH(1,1) model that identifies non-constant volatility over time and allows the GARCH parameters to vary over time following a Markov process, is combined with copula functions and EVT to formulate the Bayesian Markov-switching GJR-GARCH(1,1) copula-EVT VaR model, which is then used to forecast the level of risk on financial asset returns. We further propose a new method for threshold selection in EVT analysis, which we term the hybrid method. Empirical and back-testing results show that the proposed VaR models capture VaR reasonably well in periods of calm and in periods of crisis.

Source attribution and credibility of health and appearance exercise advertisements: relationship with implicit and explicit attitudes and intentions.

PubMed

Berry, Tanya R; Shields, Chris

2014-02-01

The relationship of attributed source (commercial or nonprofit) and credibility of exercise advertisements to explicit and implicit exercise-related attitudes and intentions was examined. Male and female participants (N = 227) were randomly assigned to watch health or appearance-related advertisements and then completed an implicit attitudes task and questionnaires. Health advertisements and those attributed to a nonprofit source were rated more credible. Appearance condition participants who attributed the advertisement to a nonprofit source also rated the advertisement as more credible. Participants who rated a commercial advertisement as credible reported higher implicit instrumental attitudes. Implications for exercise promotion are discussed.

A Bayesian random effects discrete-choice model for resource selection: Population-level selection inference

USGS Publications Warehouse

Thomas, D.L.; Johnson, D.; Griffith, B.

2006-01-01

Modeling the probability of use of land units characterized by discrete and continuous measures, we present a Bayesian random-effects model to assess resource selection. This model provides simultaneous estimation of both individual- and population-level selection. Deviance information criterion (DIC), a Bayesian alternative to AIC that is sample-size specific, is used for model selection. Aerial radiolocation data from 76 adult female caribou (Rangifer tarandus) and calf pairs during 1 year on an Arctic coastal plain calving ground were used to illustrate models and assess population-level selection of landscape attributes, as well as individual heterogeneity of selection. Landscape attributes included elevation, NDVI (a measure of forage greenness), and land cover-type classification. Results from the first of a 2-stage model-selection procedure indicated that there is substantial heterogeneity among cow-calf pairs with respect to selection of the landscape attributes. In the second stage, selection of models with heterogeneity included indicated that at the population-level, NDVI and land cover class were significant attributes for selection of different landscapes by pairs on the calving ground. Population-level selection coefficients indicate that the pairs generally select landscapes with higher levels of NDVI, but the relationship is quadratic. The highest rate of selection occurs at values of NDVI less than the maximum observed. Results for land cover-class selections coefficients indicate that wet sedge, moist sedge, herbaceous tussock tundra, and shrub tussock tundra are selected at approximately the same rate, while alpine and sparsely vegetated landscapes are selected at a lower rate. Furthermore, the variability in selection by individual caribou for moist sedge and sparsely vegetated landscapes is large relative to the variability in selection of other land cover types. The example analysis illustrates that, while sometimes computationally intense, a Bayesian hierarchical discrete-choice model for resource selection can provide managers with 2 components of population-level inference: average population selection and variability of selection. Both components are necessary to make sound management decisions based on animal selection.

A Bayesian prediction model between a biomarker and the clinical endpoint for dichotomous variables.

PubMed

Jiang, Zhiwei; Song, Yang; Shou, Qiong; Xia, Jielai; Wang, William

2014-12-20

Early biomarkers are helpful for predicting clinical endpoints and for evaluating efficacy in clinical trials even if the biomarker cannot replace clinical outcome as a surrogate. The building and evaluation of an association model between biomarkers and clinical outcomes are two equally important concerns regarding the prediction of clinical outcome. This paper is to address both issues in a Bayesian framework. A Bayesian meta-analytic approach is proposed to build a prediction model between the biomarker and clinical endpoint for dichotomous variables. Compared with other Bayesian methods, the proposed model only requires trial-level summary data of historical trials in model building. By using extensive simulations, we evaluate the link function and the application condition of the proposed Bayesian model under scenario (i) equal positive predictive value (PPV) and negative predictive value (NPV) and (ii) higher NPV and lower PPV. In the simulations, the patient-level data is generated to evaluate the meta-analytic model. PPV and NPV are employed to describe the patient-level relationship between the biomarker and the clinical outcome. The minimum number of historical trials to be included in building the model is also considered. It is seen from the simulations that the logit link function performs better than the odds and cloglog functions under both scenarios. PPV/NPV ≥0.5 for equal PPV and NPV, and PPV + NPV ≥1 for higher NPV and lower PPV are proposed in order to predict clinical outcome accurately and precisely when the proposed model is considered. Twenty historical trials are required to be included in model building when PPV and NPV are equal. For unequal PPV and NPV, the minimum number of historical trials for model building is proposed to be five. A hypothetical example shows an application of the proposed model in global drug development. The proposed Bayesian model is able to predict well the clinical endpoint from the observed biomarker data for dichotomous variables as long as the conditions are satisfied. It could be applied in drug development. But the practical problems in applications have to be studied in further research.

Trust and Credibility in Web-Based Health Information: A Review and Agenda for Future Research

PubMed Central

2017-01-01

Background Internet sources are becoming increasingly important in seeking health information, such that they may have a significant effect on health care decisions and outcomes. Hence, given the wide range of different sources of Web-based health information (WHI) from different organizations and individuals, it is important to understand how information seekers evaluate and select the sources that they use, and more specifically, how they assess their credibility and trustworthiness. Objective The aim of this study was to review empirical studies on trust and credibility in the use of WHI. The article seeks to present a profile of the research conducted on trust and credibility in WHI seeking, to identify the factors that impact judgments of trustworthiness and credibility, and to explore the role of demographic factors affecting trust formation. On this basis, it aimed to identify the gaps in current knowledge and to propose an agenda for future research. Methods A systematic literature review was conducted. Searches were conducted using a variety of combinations of the terms WHI, trust, credibility, and their variants in four multi-disciplinary and four health-oriented databases. Articles selected were published in English from 2000 onwards; this process generated 3827 unique records. After the application of the exclusion criteria, 73 were analyzed fully. Results Interest in this topic has persisted over the last 15 years, with articles being published in medicine, social science, and computer science and originating mostly from the United States and the United Kingdom. Documents in the final dataset fell into 3 categories: (1) those using trust or credibility as a dependent variable, (2) those using trust or credibility as an independent variable, and (3) studies of the demographic factors that influence the role of trust or credibility in WHI seeking. There is a consensus that website design, clear layout, interactive features, and the authority of the owner have a positive effect on trust or credibility, whereas advertising has a negative effect. With regard to content features, authority of the author, ease of use, and content have a positive effect on trust or credibility formation. Demographic factors influencing trust formation are age, gender, and perceived health status. Conclusions There is considerable scope for further research. This includes increased clarity of the interaction between the variables associated with health information seeking, increased consistency on the measurement of trust and credibility, a greater focus on specific WHI sources, and enhanced understanding of the impact of demographic variables on trust and credibility judgments. PMID:28630033

Credibility of the measurement of serum ferritin and transferrin receptor as indicators of iron deficiency anemia in hemodialysis patients.

PubMed

Mahdavi, M R; Makhlough, A; Kosaryan, M; Roshan, P

2011-10-01

Anemia is a common complication in uremic patients. Erythropoietin therapy is prescribed in these cases; however, this treatment is not successful in iron deficient patients. Ferritin-based diagnosis of iron deficiency in these patients is a challenging task, as serum ferritin level may be high due to chronic inflammation and mask iron deficiency. In the current study we evaluated the credibility of another indicator of body iron supply, serum transferrin receptor, in hemodialysis patients in two University-based Hospitals in North of Iran. In a cross-sectional study, 53 hemodialysis patients with a mean age of 56 +/- 18.7 years and 30 persons with iron deficiency and normal renal function with a mean age of 20.1 +/- 14.4 years were examined. All hemodialysis patients were on hemodialysis 2-3 times per week for 3-4 hours. All cases were examined for blood hemoglobin content, serum iron, CRP, serum ferritin and serum transferrin receptor levels. The reference ranges introduced by manufacturers were considered as standard ranges for analysis of the results. Using one sample T-test and Fisher's exact test, data were analyzed. p<0.05 was considered as significant. Hemodialysis patients had blood hemoglobin content below normal range (p<0.05 for men, p<0.001 for women) and CRP levels above normal range (p<0.001). In hemodialysis patients, serum ferritin level was significantly higher than control group (p<0.001), whilst serum transferrin receptor levels in the two groups were not significantly different (p=0.69), and both were above defined normal upper limit (p<0.001 for iron deficient patients; p<0.05 for hemodialysis patients). This study showed measurement of serum ferritin in the presence of chronic inflammation induced by renal failure cannot be a credible indicator of body iron supply, while under this certain condition serum transferrin receptor can more appropriately reflect the amount of body iron supply.

Understanding the complex relationships underlying hot flashes: a Bayesian network approach.

PubMed

Smith, Rebecca L; Gallicchio, Lisa M; Flaws, Jodi A

2018-02-01

The mechanism underlying hot flashes is not well-understood, primarily because of complex relationships between and among hot flashes and their risk factors. We explored those relationships using a Bayesian network approach based on a 2006 to 2015 cohort study of hot flashes among 776 female residents, 45 to 54 years old, in the Baltimore area. Bayesian networks were fit for each outcome (current hot flashes, hot flashes before the end of the study, hot flash severity, hot flash frequency, and age at first hot flashes) separately and together with a list of risk factors (estrogen, progesterone, testosterone, body mass index and obesity, race, income level, education level, smoking history, drinking history, and activity level). Each fitting was conducted separately on all women and only perimenopausal women, at enrollment and 4 years after enrollment. Hormone levels, almost always interrelated, were the most common variable linked to hot flashes; hormone levels were sometimes related to body mass index, but were not directly related to any other risk factors. Smoking was also frequently associated with increased likelihood of severe symptoms, but not through an antiestrogenic pathway. The age at first hot flashes was related only to race. All other factors were either not related to outcomes or were mediated entirely by race, hormone levels, or smoking. These models can serve as a guide for design of studies into the causal network underlying hot flashes.

Heritability and quantitative genetic divergence of serotiny, a fire-persistence plant trait

PubMed Central

Hernández-Serrano, Ana; Verdú, Miguel; Santos-del-Blanco, Luís; Climent, José; González-Martínez, Santiago C.; Pausas, Juli G.

2014-01-01

Background and Aims Although it is well known that fire acts as a selective pressure shaping plant phenotypes, there are no quantitative estimates of the heritability of any trait related to plant persistence under recurrent fires, such as serotiny. In this study, the heritability of serotiny in Pinus halepensis is calculated, and an evaluation is made as to whether fire has left a selection signature on the level of serotiny among populations by comparing the genetic divergence of serotiny with the expected divergence of neutral molecular markers (QST–FST comparison). Methods A common garden of P. halepensis was used, located in inland Spain and composed of 145 open-pollinated families from 29 provenances covering the entire natural range of P. halepensis in the Iberian Peninsula and Balearic Islands. Narrow-sense heritability (h2) and quantitative genetic differentiation among populations for serotiny (QST) were estimated by means of an ‘animal model’ fitted by Bayesian inference. In order to determine whether genetic differentiation for serotiny is the result of differential natural selection, QST estimates for serotiny were compared with FST estimates obtained from allozyme data. Finally, a test was made of whether levels of serotiny in the different provenances were related to different fire regimes, using summer rainfall as a proxy for fire regime in each provenance. Key Results Serotiny showed a significant narrow-sense heritability (h2) of 0·20 (credible interval 0·09–0·40). Quantitative genetic differentiation among provenances for serotiny (QST = 0·44) was significantly higher than expected under a neutral process (FST = 0·12), suggesting adaptive differentiation. A significant negative relationship was found between the serotiny level of trees in the common garden and summer rainfall of their provenance sites. Conclusions Serotiny is a heritable trait in P. halepensis, and selection acts on it, giving rise to contrasting serotiny levels among populations depending on the fire regime, and supporting the role of fire in generating genetic divergence for adaptive traits. PMID:25008363

Wavelet-based 3D reconstruction of microcalcification clusters from two mammographic views: new evidence that fractal tumors are malignant and Euclidean tumors are benign.

PubMed

Batchelder, Kendra A; Tanenbaum, Aaron B; Albert, Seth; Guimond, Lyne; Kestener, Pierre; Arneodo, Alain; Khalil, Andre

2014-01-01

The 2D Wavelet-Transform Modulus Maxima (WTMM) method was used to detect microcalcifications (MC) in human breast tissue seen in mammograms and to characterize the fractal geometry of benign and malignant MC clusters. This was done in the context of a preliminary analysis of a small dataset, via a novel way to partition the wavelet-transform space-scale skeleton. For the first time, the estimated 3D fractal structure of a breast lesion was inferred by pairing the information from two separate 2D projected mammographic views of the same breast, i.e. the cranial-caudal (CC) and mediolateral-oblique (MLO) views. As a novelty, we define the "CC-MLO fractal dimension plot", where a "fractal zone" and "Euclidean zones" (non-fractal) are defined. 118 images (59 cases, 25 malignant and 34 benign) obtained from a digital databank of mammograms with known radiologist diagnostics were analyzed to determine which cases would be plotted in the fractal zone and which cases would fall in the Euclidean zones. 92% of malignant breast lesions studied (23 out of 25 cases) were in the fractal zone while 88% of the benign lesions were in the Euclidean zones (30 out of 34 cases). Furthermore, a Bayesian statistical analysis shows that, with 95% credibility, the probability that fractal breast lesions are malignant is between 74% and 98%. Alternatively, with 95% credibility, the probability that Euclidean breast lesions are benign is between 76% and 96%. These results support the notion that the fractal structure of malignant tumors is more likely to be associated with an invasive behavior into the surrounding tissue compared to the less invasive, Euclidean structure of benign tumors. Finally, based on indirect 3D reconstructions from the 2D views, we conjecture that all breast tumors considered in this study, benign and malignant, fractal or Euclidean, restrict their growth to 2-dimensional manifolds within the breast tissue.

Consistency between direct and indirect trial evidence: is direct evidence always more reliable?

PubMed

Madan, Jason; Stevenson, Matt D; Cooper, Katy L; Ades, A E; Whyte, Sophie; Akehurst, Ron

2011-01-01

To present a case study involving the reduction in incidence of febrile neutropenia (FN) after chemotherapy with granulocyte colony-stimulating factors (G-CSFs), illustrating difficulties that may arise when following the common preference for direct evidence over indirect evidence. Evidence of the efficacy of treatments was identified from two previous systematic reviews. We used Bayesian evidence synthesis to estimate relative treatment effects based on direct evidence, indirect evidence, and both pooled together. We checked for inconsistency between direct and indirect evidence and explored the role of one specific trial using cross-validation. A subsequent review identified further studies not available at the time of the original analysis. We repeated the analyses on the enlarged evidence base. We found substantial inconsistency in the original evidence base. The median odds ratio of FN for primary pegfilgrastim versus no primary G-CSF was 0.06 (95% credible interval: 0.02-0.19) based on direct evidence, but 0.27 (95% credible interval: 0.13-0.53) based on indirect evidence (P value for consistency hypothesis 0.027). The additional trials were consistent with the earlier indirect, rather than the direct, evidence, and there was no inconsistency between direct and indirect estimates in the updated evidence. The earlier inconsistency was due to one trial comparing primary pegfilgrastim with no primary G-CSF. Predictive cross-validation showed that this study was inconsistent with the evidence as a whole and with other trials making this comparison. Both the Cochrane Handbook and the NICE Methods Guide express a preference for direct evidence. A more robust strategy, which is in line with the accepted principles of evidence synthesis, would be to combine all relevant and appropriate information, whether direct or indirect. Copyright © 2011 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Statistical Surrogate Models for Estimating Probability of High-Consequence Climate Change

NASA Astrophysics Data System (ADS)

Field, R.; Constantine, P.; Boslough, M.

2011-12-01

We have posed the climate change problem in a framework similar to that used in safety engineering, by acknowledging that probabilistic risk assessments focused on low-probability, high-consequence climate events are perhaps more appropriate than studies focused simply on best estimates. To properly explore the tails of the distribution requires extensive sampling, which is not possible with existing coupled atmospheric models due to the high computational cost of each simulation. We have developed specialized statistical surrogate models (SSMs) that can be used to make predictions about the tails of the associated probability distributions. A SSM is different than a deterministic surrogate model in that it represents each climate variable of interest as a space/time random field, that is, a random variable for every fixed location in the atmosphere at all times. The SSM can be calibrated to available spatial and temporal data from existing climate databases, or to a collection of outputs from general circulation models. Because of its reduced size and complexity, the realization of a large number of independent model outputs from a SSM becomes computationally straightforward, so that quantifying the risk associated with low-probability, high-consequence climate events becomes feasible. A Bayesian framework was also developed to provide quantitative measures of confidence, via Bayesian credible intervals, to assess these risks. To illustrate the use of the SSM, we considered two collections of NCAR CCSM 3.0 output data. The first collection corresponds to average December surface temperature for years 1990-1999 based on a collection of 8 different model runs obtained from the Program for Climate Model Diagnosis and Intercomparison (PCMDI). We calibrated the surrogate model to the available model data and make various point predictions. We also analyzed average precipitation rate in June, July, and August over a 54-year period assuming a cyclic Y2K ocean model. We applied the calibrated surrogate model to study the probability that the precipitation rate falls below certain thresholds and utilized the Bayesian approach to quantify our confidence in these predictions. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under Contract DE-AC04-94AL85000.

Estimating the sensitivity and specificity of Kato-Katz stool examination technique for detection of hookworms, Ascaris lumbricoides and Trichuris trichiura infections in humans in the absence of a 'gold standard'.

PubMed

Tarafder, M R; Carabin, H; Joseph, L; Balolong, E; Olveda, R; McGarvey, S T

2010-03-15

The accuracy of the Kato-Katz technique in identifying individuals with soil-transmitted helminth (STH) infections is limited by day-to-day variation in helminth egg excretion, confusion with other parasites and the laboratory technicians' experience. We aimed to estimate the sensitivity and specificity of the Kato-Katz technique to detect infection with Ascaris lumbricoides, hookworm and Trichuris trichiura using a Bayesian approach in the absence of a 'gold standard'. Data were obtained from a longitudinal study conducted between January 2004 and December 2005 in Samar Province, the Philippines. Each participant provided between one and three stool samples over consecutive days. Stool samples were examined using the Kato-Katz technique and reported as positive or negative for STHs. In the presence of measurement error, the true status of each individual is considered as latent data. Using a Bayesian method, we calculated marginal posterior densities of sensitivity and specificity parameters from the product of the likelihood function of observed and latent data. A uniform prior distribution was used (beta distribution: alpha=1, beta=1). A total of 5624 individuals provided at least one stool sample. One, two and three stool samples were provided by 1582, 1893 and 2149 individuals, respectively. All STHs showed variation in test results from day to day. Sensitivity estimates of the Kato-Katz technique for one stool sample were 96.9% (95% Bayesian Credible Interval [BCI]: 96.1%, 97.6%), 65.2% (60.0%, 69.8%) and 91.4% (90.5%, 92.3%), for A. lumbricoides, hookworm and T. trichiura, respectively. Specificity estimates for one stool sample were 96.1% (95.5%, 96.7%), 93.8% (92.4%, 95.4%) and 94.4% (93.2%, 95.5%), for A. lumbricoides, hookworm and T. trichiura, respectively. Our results show that the Kato-Katz technique can perform with reasonable accuracy with one day's stool collection for A. lumbricoides and T. trichiura. Low sensitivity of the Kato-Katz for detection of hookworm infection may be related to rapid degeneration of delicate hookworm eggs with time. (c) 2009 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

Relating memory to functional performance in normal aging to dementia using hierarchical Bayesian cognitive processing models.

PubMed

Shankle, William R; Pooley, James P; Steyvers, Mark; Hara, Junko; Mangrola, Tushar; Reisberg, Barry; Lee, Michael D

2013-01-01

Determining how cognition affects functional abilities is important in Alzheimer disease and related disorders. A total of 280 patients (normal or Alzheimer disease and related disorders) received a total of 1514 assessments using the functional assessment staging test (FAST) procedure and the MCI Screen. A hierarchical Bayesian cognitive processing model was created by embedding a signal detection theory model of the MCI Screen-delayed recognition memory task into a hierarchical Bayesian framework. The signal detection theory model used latent parameters of discriminability (memory process) and response bias (executive function) to predict, simultaneously, recognition memory performance for each patient and each FAST severity group. The observed recognition memory data did not distinguish the 6 FAST severity stages, but the latent parameters completely separated them. The latent parameters were also used successfully to transform the ordinal FAST measure into a continuous measure reflecting the underlying continuum of functional severity. Hierarchical Bayesian cognitive processing models applied to recognition memory data from clinical practice settings accurately translated a latent measure of cognition into a continuous measure of functional severity for both individuals and FAST groups. Such a translation links 2 levels of brain information processing and may enable more accurate correlations with other levels, such as those characterized by biomarkers.

Jordanian TEFL Graduate Students' Use of Critical Thinking Skills (as Measured by the Cornell Critical Thinking Test, Level Z)

ERIC Educational Resources Information Center

Bataineh, Ruba Fahmi; Zghoul, Lamma Hmoud

2006-01-01

This study investigates the critical thinking skills of 50 students currently enrolled in the Master's TEFL Programme at Yarmouk University, Jordan. The Cornell Critical Thinking Test, Level Z is utilised to test the students' use, or lack thereof, of the critical thinking skills of deduction, semantics, credibility, induction, definition and…

Evaluation of LLNL BSL-3 Maximum Credible Event Potential Consequence to the General Population and Surrounding Environment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, M.

2010-08-16

The purpose of this evaluation is to establish reproducibility of the analysis and consequence results to the general population and surrounding environment in the LLNL Biosafety Level 3 Facility Environmental Assessment (LLNL 2008).

U.S. EPA. 2000. Science Policy Council Handbook: Peer Review

EPA Pesticide Factsheets

The goal of the Peer Review Policy and this Handbook is to enhance the quality and credibility of Agency decisions by ensuring that the scientific and technical work products underlying these decisions receive appropriate levels of peer review by independe

Using multi-level Bayesian lesion-symptom mapping to probe the body-part-specificity of gesture imitation skills.

PubMed

Achilles, Elisabeth I S; Weiss, Peter H; Fink, Gereon R; Binder, Ellen; Price, Cathy J; Hope, Thomas M H

2017-11-01

Past attempts to identify the neural substrates of hand and finger imitation skills in the left hemisphere of the brain have yielded inconsistent results. Here, we analyse those associations in a large sample of 257 left hemisphere stroke patients. By introducing novel Bayesian methods, we characterise lesion symptom associations at three levels: the voxel-level, the single-region level (using anatomically defined regions), and the region-pair level. The results are inconsistent across those three levels and we argue that each level of analysis makes assumptions which constrain the results it can produce. Regardless of the inconsistencies across levels, and contrary to past studies which implicated differential neural substrates for hand and finger imitation, we find no consistent voxels or regions, where damage affects one imitation skill and not the other, at any of the three analysis levels. Our novel Bayesian approach indicates that any apparent differences appear to be driven by an increased sensitivity of hand imitation skills to lesions that also impair finger imitation. In our analyses, the results of the highest level of analysis (region-pairs) emphasise a role of the primary somatosensory and motor cortices, and the occipital lobe in imitation. We argue that this emphasis supports an account of both imitation tasks based on direct sensor-motor connections, which throws doubt on past accounts which imply the need for an intermediate (e.g. body-part-coding) system of representation. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Individual Uncertainty and the Uncertainty of Science: The Impact of Perceived Conflict and General Self-Efficacy on the Perception of Tentativeness and Credibility of Scientific Information.

PubMed

Flemming, Danny; Feinkohl, Insa; Cress, Ulrike; Kimmerle, Joachim

2015-01-01

We examined in two empirical studies how situational and personal aspects of uncertainty influence laypeople's understanding of the uncertainty of scientific information, with focus on the detection of tentativeness and perception of scientific credibility. In the first study (N = 48), we investigated the impact of a perceived conflict due to contradicting information as a situational, text-inherent aspect of uncertainty. The aim of the second study (N = 61) was to explore the role of general self-efficacy as an intra-personal uncertainty factor. In Study 1, participants read one of two versions of an introductory text in a between-group design. This text provided them with an overview about the neurosurgical procedure of deep brain stimulation (DBS). The text expressed a positive attitude toward DBS in one experimental condition or focused on the negative aspects of this method in the other condition. Then participants in both conditions read the same text that dealt with a study about DBS as experimental treatment in a small sample of patients with major depression. Perceived conflict between the two texts was found to increase the perception of tentativeness and to decrease the perception of scientific credibility, implicating that text-inherent aspects have significant effects on critical appraisal. The results of Study 2 demonstrated that participants with higher general self-efficacy detected the tentativeness to a lesser degree and assumed a higher level of scientific credibility, indicating a more naïve understanding of scientific information. This appears to be contradictory to large parts of previous findings that showed positive effects of high self-efficacy on learning. Both studies showed that perceived tentativeness and perceived scientific credibility of medical information contradicted each other. We conclude that there is a need for supporting laypeople in understanding the uncertainty of scientific information and that scientific writers should consider how to present scientific results when compiling pertinent texts.

Individual Uncertainty and the Uncertainty of Science: The Impact of Perceived Conflict and General Self-Efficacy on the Perception of Tentativeness and Credibility of Scientific Information

PubMed Central

Flemming, Danny; Feinkohl, Insa; Cress, Ulrike; Kimmerle, Joachim

2015-01-01

We examined in two empirical studies how situational and personal aspects of uncertainty influence laypeople’s understanding of the uncertainty of scientific information, with focus on the detection of tentativeness and perception of scientific credibility. In the first study (N = 48), we investigated the impact of a perceived conflict due to contradicting information as a situational, text-inherent aspect of uncertainty. The aim of the second study (N = 61) was to explore the role of general self-efficacy as an intra-personal uncertainty factor. In Study 1, participants read one of two versions of an introductory text in a between-group design. This text provided them with an overview about the neurosurgical procedure of deep brain stimulation (DBS). The text expressed a positive attitude toward DBS in one experimental condition or focused on the negative aspects of this method in the other condition. Then participants in both conditions read the same text that dealt with a study about DBS as experimental treatment in a small sample of patients with major depression. Perceived conflict between the two texts was found to increase the perception of tentativeness and to decrease the perception of scientific credibility, implicating that text-inherent aspects have significant effects on critical appraisal. The results of Study 2 demonstrated that participants with higher general self-efficacy detected the tentativeness to a lesser degree and assumed a higher level of scientific credibility, indicating a more naïve understanding of scientific information. This appears to be contradictory to large parts of previous findings that showed positive effects of high self-efficacy on learning. Both studies showed that perceived tentativeness and perceived scientific credibility of medical information contradicted each other. We conclude that there is a need for supporting laypeople in understanding the uncertainty of scientific information and that scientific writers should consider how to present scientific results when compiling pertinent texts. PMID:26648902

Comparing Families of Dynamic Causal Models

PubMed Central

Penny, Will D.; Stephan, Klaas E.; Daunizeau, Jean; Rosa, Maria J.; Friston, Karl J.; Schofield, Thomas M.; Leff, Alex P.

2010-01-01

Mathematical models of scientific data can be formally compared using Bayesian model evidence. Previous applications in the biological sciences have mainly focussed on model selection in which one first selects the model with the highest evidence and then makes inferences based on the parameters of that model. This “best model” approach is very useful but can become brittle if there are a large number of models to compare, and if different subjects use different models. To overcome this shortcoming we propose the combination of two further approaches: (i) family level inference and (ii) Bayesian model averaging within families. Family level inference removes uncertainty about aspects of model structure other than the characteristic of interest. For example: What are the inputs to the system? Is processing serial or parallel? Is it linear or nonlinear? Is it mediated by a single, crucial connection? We apply Bayesian model averaging within families to provide inferences about parameters that are independent of further assumptions about model structure. We illustrate the methods using Dynamic Causal Models of brain imaging data. PMID:20300649

Credibility engineering in the food industry: linking science, regulation, and marketing in a corporate context.

PubMed

Penders, Bart; Nelis, Annemiek P

2011-12-01

We expand upon the notion of the "credibility cycle" through a study of credibility engineering by the food industry. Research and development (R&D) as well as marketing contribute to the credibility of the food company Unilever and its claims. Innovation encompasses the development, marketing, and sales of products. These are directed towards three distinct audiences: scientific peers, regulators, and consumers. R&D uses scientific articles to create credit for itself amongst peers and regulators. These articles are used to support health claims on products. However, R&D, regulation, and marketing are not separate realms. A single strategy of credibility engineering connects health claims to a specific public through linking that public to a health issue and a food product.

What makes professors appear credible: The effect of demographic characteristics and ideological beliefs.

PubMed

Zhu, Luke Lei; Aquino, Karl; Vadera, Abhijeet K

2016-06-01

Five studies are conducted to examine how ideology and perceptions regarding gender, race, caste, and affiliation status affect how individuals judge researchers' credibility. Support is found for predictions that individuals judge researcher credibility according to their egalitarian or elitist ideologies and according to status cues including race, gender, caste, and university affiliation. Egalitarians evaluate low-status researchers as more credible than high-status researchers. Elitists show the opposite pattern. Credibility judgments affect whether individuals will interpret subsequent ambiguous events in accordance with the researcher's findings. Effects of diffuse status cues and ideological beliefs may be mitigated when specific status cues are presented to override stereotypes. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Tweeting and Eating: The Effect of Links and Likes on Food-Hypersensitive Consumers’ Perceptions of Tweets

PubMed Central

Hamshaw, Richard J. T.; Barnett, Julie; Lucas, Jane S.

2018-01-01

Moving on from literature that focuses on how consumers use social media and the benefits of organizations utilizing platforms for health and risk communication, this study explores how specific characteristics of tweets affect the way in which they are perceived. An online survey with 251 participants with self-reported food hypersensitivity (FH) took part in an online experiment to consider the impact of tweet characteristics on perceptions of source credibility, message credibility, persuasiveness, and intention to act upon the presented information. Positioning the research hypotheses within the framework of the Elaboration Likelihood Model and Uses and Gratifications Theory, the study explored motivations for using social media and tested the impact of the affordances of Twitter—(1) the inclusion of links and (2) the number of social validation indicators (likes and retweets). Having links accompanying tweets significantly increased ratings of the tweets’ message credibility, as well as persuasiveness of their content. Socially validated tweets had no effect on these same variables. Parents of FH children were found to utilize social media for social reasons more than hypersensitive adults; concern level surrounding a reaction did not appear to alter the level of use. Links were considered valuable in obtaining social media users to attend to useful or essential food health and risk information. Future research in this area can usefully consider the nature and the effects of social validation in relation to other social media platforms and with other groups. PMID:29740573

Tweeting and Eating: The Effect of Links and Likes on Food-Hypersensitive Consumers' Perceptions of Tweets.

PubMed

Hamshaw, Richard J T; Barnett, Julie; Lucas, Jane S

2018-01-01

Moving on from literature that focuses on how consumers use social media and the benefits of organizations utilizing platforms for health and risk communication, this study explores how specific characteristics of tweets affect the way in which they are perceived. An online survey with 251 participants with self-reported food hypersensitivity (FH) took part in an online experiment to consider the impact of tweet characteristics on perceptions of source credibility, message credibility, persuasiveness, and intention to act upon the presented information. Positioning the research hypotheses within the framework of the Elaboration Likelihood Model and Uses and Gratifications Theory, the study explored motivations for using social media and tested the impact of the affordances of Twitter-(1) the inclusion of links and (2) the number of social validation indicators (likes and retweets). Having links accompanying tweets significantly increased ratings of the tweets' message credibility, as well as persuasiveness of their content. Socially validated tweets had no effect on these same variables. Parents of FH children were found to utilize social media for social reasons more than hypersensitive adults; concern level surrounding a reaction did not appear to alter the level of use. Links were considered valuable in obtaining social media users to attend to useful or essential food health and risk information. Future research in this area can usefully consider the nature and the effects of social validation in relation to other social media platforms and with other groups.

Bayesian statistical inference enhances the interpretation of contemporary randomized controlled trials.

PubMed

Wijeysundera, Duminda N; Austin, Peter C; Hux, Janet E; Beattie, W Scott; Laupacis, Andreas

2009-01-01

Randomized trials generally use "frequentist" statistics based on P-values and 95% confidence intervals. Frequentist methods have limitations that might be overcome, in part, by Bayesian inference. To illustrate these advantages, we re-analyzed randomized trials published in four general medical journals during 2004. We used Medline to identify randomized superiority trials with two parallel arms, individual-level randomization and dichotomous or time-to-event primary outcomes. Studies with P<0.05 in favor of the intervention were deemed "positive"; otherwise, they were "negative." We used several prior distributions and exact conjugate analyses to calculate Bayesian posterior probabilities for clinically relevant effects. Of 88 included studies, 39 were positive using a frequentist analysis. Although the Bayesian posterior probabilities of any benefit (relative risk or hazard ratio<1) were high in positive studies, these probabilities were lower and variable for larger benefits. The positive studies had only moderate probabilities for exceeding the effects that were assumed for calculating the sample size. By comparison, there were moderate probabilities of any benefit in negative studies. Bayesian and frequentist analyses complement each other when interpreting the results of randomized trials. Future reports of randomized trials should include both.

Bayesian Inference on the Radio-quietness of Gamma-ray Pulsars

NASA Astrophysics Data System (ADS)

Yu, Hoi-Fung; Hui, Chung Yue; Kong, Albert K. H.; Takata, Jumpei

2018-04-01

For the first time we demonstrate using a robust Bayesian approach to analyze the populations of radio-quiet (RQ) and radio-loud (RL) gamma-ray pulsars. We quantify their differences and obtain their distributions of the radio-cone opening half-angle δ and the magnetic inclination angle α by Bayesian inference. In contrast to the conventional frequentist point estimations that might be non-representative when the distribution is highly skewed or multi-modal, which is often the case when data points are scarce, Bayesian statistics displays the complete posterior distribution that the uncertainties can be readily obtained regardless of the skewness and modality. We found that the spin period, the magnetic field strength at the light cylinder, the spin-down power, the gamma-ray-to-X-ray flux ratio, and the spectral curvature significance of the two groups of pulsars exhibit significant differences at the 99% level. Using Bayesian inference, we are able to infer the values and uncertainties of δ and α from the distribution of RQ and RL pulsars. We found that δ is between 10° and 35° and the distribution of α is skewed toward large values.

Developing Large-Scale Bayesian Networks by Composition: Fault Diagnosis of Electrical Power Systems in Aircraft and Spacecraft

NASA Technical Reports Server (NTRS)

Mengshoel, Ole Jakob; Poll, Scott; Kurtoglu, Tolga

2009-01-01

In this paper, we investigate the use of Bayesian networks to construct large-scale diagnostic systems. In particular, we consider the development of large-scale Bayesian networks by composition. This compositional approach reflects how (often redundant) subsystems are architected to form systems such as electrical power systems. We develop high-level specifications, Bayesian networks, clique trees, and arithmetic circuits representing 24 different electrical power systems. The largest among these 24 Bayesian networks contains over 1,000 random variables. Another BN represents the real-world electrical power system ADAPT, which is representative of electrical power systems deployed in aerospace vehicles. In addition to demonstrating the scalability of the compositional approach, we briefly report on experimental results from the diagnostic competition DXC, where the ProADAPT team, using techniques discussed here, obtained the highest scores in both Tier 1 (among 9 international competitors) and Tier 2 (among 6 international competitors) of the industrial track. While we consider diagnosis of power systems specifically, we believe this work is relevant to other system health management problems, in particular in dependable systems such as aircraft and spacecraft. (See CASI ID 20100021910 for supplemental data disk.)

Approaches in highly parameterized inversion: bgaPEST, a Bayesian geostatistical approach implementation with PEST: documentation and instructions

USGS Publications Warehouse

Fienen, Michael N.; D'Oria, Marco; Doherty, John E.; Hunt, Randall J.

2013-01-01

The application bgaPEST is a highly parameterized inversion software package implementing the Bayesian Geostatistical Approach in a framework compatible with the parameter estimation suite PEST. Highly parameterized inversion refers to cases in which parameters are distributed in space or time and are correlated with one another. The Bayesian aspect of bgaPEST is related to Bayesian probability theory in which prior information about parameters is formally revised on the basis of the calibration dataset used for the inversion. Conceptually, this approach formalizes the conditionality of estimated parameters on the specific data and model available. The geostatistical component of the method refers to the way in which prior information about the parameters is used. A geostatistical autocorrelation function is used to enforce structure on the parameters to avoid overfitting and unrealistic results. Bayesian Geostatistical Approach is designed to provide the smoothest solution that is consistent with the data. Optionally, users can specify a level of fit or estimate a balance between fit and model complexity informed by the data. Groundwater and surface-water applications are used as examples in this text, but the possible uses of bgaPEST extend to any distributed parameter applications.

Bayesian logistic regression approaches to predict incorrect DRG assignment.

PubMed

Suleiman, Mani; Demirhan, Haydar; Boyd, Leanne; Girosi, Federico; Aksakalli, Vural

2018-05-07

Episodes of care involving similar diagnoses and treatments and requiring similar levels of resource utilisation are grouped to the same Diagnosis-Related Group (DRG). In jurisdictions which implement DRG based payment systems, DRGs are a major determinant of funding for inpatient care. Hence, service providers often dedicate auditing staff to the task of checking that episodes have been coded to the correct DRG. The use of statistical models to estimate an episode's probability of DRG error can significantly improve the efficiency of clinical coding audits. This study implements Bayesian logistic regression models with weakly informative prior distributions to estimate the likelihood that episodes require a DRG revision, comparing these models with each other and to classical maximum likelihood estimates. All Bayesian approaches had more stable model parameters than maximum likelihood. The best performing Bayesian model improved overall classification per- formance by 6% compared to maximum likelihood, with a 34% gain compared to random classification, respectively. We found that the original DRG, coder and the day of coding all have a significant effect on the likelihood of DRG error. Use of Bayesian approaches has improved model parameter stability and classification accuracy. This method has already lead to improved audit efficiency in an operational capacity.

Enhancing Student Perceptions of Fairness: The Relationship between Instructor Credibility and Classroom Justice

ERIC Educational Resources Information Center

Chory, Rebecca M.

2007-01-01

The present study investigated the relationships between college students' perceptions of instructor credibility (competence, character, and caring) and their perceptions of classroom justice (distributive, procedural, and interactional justice). Results indicate that perceptions of instructor credibility positively predicted perceptions of…

Factors Underlying the Public's Credibility Perceptions in Educational Evaluations

ERIC Educational Resources Information Center

Jacobson, Miriam R.

2016-01-01

Understanding how evaluation audiences perceive credibility can help evaluators design evaluations and reports that support appropriate use. While researchers have studied credibility assessment among various educational stakeholders, little research has been conducted with the broader public. This study explored potential factors affecting the…

Motivation and treatment credibility predict alliance in cognitive behavioral treatment for youth with anxiety disorders in community clinics.

PubMed

Fjermestad, K W; Lerner, M D; McLeod, B D; Wergeland, G J H; Haugland, B S M; Havik, O E; Öst, L-G; Silverman, W K

2017-11-16

We examined whether motivation and treatment credibility predicted alliance in a 10-session cognitive behavioral treatment delivered in community clinics for youth anxiety disorders. Ninety-one clinic-referred youths (mean age  = 11.4 years, standard deviation = 2.1, range 8-15 years, 49.5% boys) with anxiety disorders-rated treatment motivation at pretreatment and perceived treatment credibility after session 1. Youths and therapists (YT) rated alliance after session 3 (early) and session 7 (late). Hierarchical linear models were applied to examine whether motivation and treatment credibility predicted YT early alliance, YT alliance change, and YT alliance agreement. Motivation predicted high early YT alliance, but not YT alliance change or alliance agreement. Youth-rated treatment credibility predicted high early youth alliance and high YT positive alliance change, but not early therapist alliance or alliance agreement. Conclusion Efforts to enhance youth motivation and treatment credibility early in treatment could facilitate the formation of a strong YT alliance. © 2017 Wiley Periodicals, Inc.

Controversy matters: Impacts of topic and solution controversy on the perceived credibility of a scientist who advocates.

PubMed

Beall, Lindsey; Myers, Teresa A; Kotcher, John E; Vraga, Emily K; Maibach, Edward W

2017-01-01

In this article, we focus on the potential influence of a scientist's advocacy position on the public's perceived credibility of scientists as a whole. Further, we examine how the scientist's solution position (information only, non-controversial, and controversial) affects the public's perception of the scientist's motivation for sharing information about specific issues (flu, marijuana, climate change, severe weather). Finally, we assess how perceived motivations mediate the relationship between solution position and credibility. Using data from a quota sample of American adults obtained by Qualtrics (n = 2,453), we found that in some conditions advocating for a solution positively predicted credibility, while in one condition, it negatively predicted scientist credibility. We also found that the influence of solution position on perceived credibility was mediated by several motivation perceptions; most notably through perception that the scientist was motivated to: (a) serve the public and (b) persuade the public. Further results and implications are discussed.

Controversy matters: Impacts of topic and solution controversy on the perceived credibility of a scientist who advocates

PubMed Central

Myers, Teresa A.; Kotcher, John E.; Vraga, Emily K.; Maibach, Edward W.

2017-01-01

In this article, we focus on the potential influence of a scientist’s advocacy position on the public’s perceived credibility of scientists as a whole. Further, we examine how the scientist’s solution position (information only, non-controversial, and controversial) affects the public’s perception of the scientist’s motivation for sharing information about specific issues (flu, marijuana, climate change, severe weather). Finally, we assess how perceived motivations mediate the relationship between solution position and credibility. Using data from a quota sample of American adults obtained by Qualtrics (n = 2,453), we found that in some conditions advocating for a solution positively predicted credibility, while in one condition, it negatively predicted scientist credibility. We also found that the influence of solution position on perceived credibility was mediated by several motivation perceptions; most notably through perception that the scientist was motivated to: (a) serve the public and (b) persuade the public. Further results and implications are discussed. PMID:29136643

When Is a Child's Forensic Statement Deemed Credible? A Comparison of Physical and Sexual Abuse Cases.

PubMed

Hershkowitz, Irit; Melkman, Eran P; Zur, Ronit

2018-05-01

A large national sample of 4,775 reports of child physical and sexual abuse made in Israel in 2014 was analyzed in order to examine whether assessments of credibility would vary according to abuse type, physical or sexual, and whether child and event characteristics contributing to the probability that reports of abuse would be determined as credible would be similar or different in child physical abuse (CPA) and child sexual abuse (CSA) cases. Results revealed that CPA reports were less likely to be viewed as credible (41.9%) compared to CSA reports (56.7%). Multigroup path analysis, however, indicated equivalence in predicting factors. In a unified model for both types of abuse, salient predictors of a credible judgment were older age, lack of a cognitive delay, and the alleged abusive event being a onetime less severe act. Over and beyond the effects of these factors, abuse type significantly contributed to the prediction of credibility judgments.

Trust and Credibility in Web-Based Health Information: A Review and Agenda for Future Research.

PubMed

Sbaffi, Laura; Rowley, Jennifer

2017-06-19

Internet sources are becoming increasingly important in seeking health information, such that they may have a significant effect on health care decisions and outcomes. Hence, given the wide range of different sources of Web-based health information (WHI) from different organizations and individuals, it is important to understand how information seekers evaluate and select the sources that they use, and more specifically, how they assess their credibility and trustworthiness. The aim of this study was to review empirical studies on trust and credibility in the use of WHI. The article seeks to present a profile of the research conducted on trust and credibility in WHI seeking, to identify the factors that impact judgments of trustworthiness and credibility, and to explore the role of demographic factors affecting trust formation. On this basis, it aimed to identify the gaps in current knowledge and to propose an agenda for future research. A systematic literature review was conducted. Searches were conducted using a variety of combinations of the terms WHI, trust, credibility, and their variants in four multi-disciplinary and four health-oriented databases. Articles selected were published in English from 2000 onwards; this process generated 3827 unique records. After the application of the exclusion criteria, 73 were analyzed fully. Interest in this topic has persisted over the last 15 years, with articles being published in medicine, social science, and computer science and originating mostly from the United States and the United Kingdom. Documents in the final dataset fell into 3 categories: (1) those using trust or credibility as a dependent variable, (2) those using trust or credibility as an independent variable, and (3) studies of the demographic factors that influence the role of trust or credibility in WHI seeking. There is a consensus that website design, clear layout, interactive features, and the authority of the owner have a positive effect on trust or credibility, whereas advertising has a negative effect. With regard to content features, authority of the author, ease of use, and content have a positive effect on trust or credibility formation. Demographic factors influencing trust formation are age, gender, and perceived health status. There is considerable scope for further research. This includes increased clarity of the interaction between the variables associated with health information seeking, increased consistency on the measurement of trust and credibility, a greater focus on specific WHI sources, and enhanced understanding of the impact of demographic variables on trust and credibility judgments. ©Laura Sbaffi, Jennifer Rowley. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 19.06.2017.

An exploratory pilot study to design and assess the credibility of a sham kinesiology treatment.

PubMed

Hall, Sue; Lewith, George; Brien, Sarah; Little, Paul

2008-12-01

Kinesiology is a complementary therapy assessing subtle change in manual muscle testing results to select individualised treatments. We report the exploratory 2-stage development and pilot of a sham kinesiology treatment for use in a clinical trial to evaluate the specific effects of this intervention. 1. To design, pilot and assess the credibility of a sham kinesiology treatment in a kinesiology-aware population. 2. To pilot the sham kinesiology in a cross-over study of sham versus real kinesiology, and to make an exploratory assessment of its credibility in a kinesiology-naïve population. 1. 10 kinesiology-aware volunteers received a specially designed sham treatment weekly for 5 weeks which was subject to a credibility assessment. 2. 10 kinesiology-naïve patients with low back pain were randomised to receive 4 real and 4 sham treatments in a cross-over design; the treatments were subject to a credibility assessment. 100% of participants found the sham protocol a credible treatment as measured by the credibility questionnaire. 100% of patients having real treatment first did not recognise that the second set of treatments were sham. Small numbers precluded the use of formal statistical tests. In this small sample it appeared feasible to deliver an apparently credible sham kinesiology treatment. This feasibility study has allowed us to develop a sham treatment for use in a larger prospective clinical trial of kinesiology in patients with low back pain. 2008 S. Karger AG, Basel.

8 CFR 208.2 - Jurisdiction

Code of Federal Regulations, 2010 CFR

2010-01-01

... jurisdiction over credible fear determinations under § 208.30 and reasonable fear determinations under § 208.31... reasonable fear determinations referred to the Immigration Court under § 208.31, and credible fear... longer than authorized; (ii) An alien stowaway who has been found to have a credible fear of persecution...

8 CFR 1208.6 - Disclosure to third parties.

Code of Federal Regulations, 2010 CFR

2010-01-01

... application, records pertaining to any credible fear determination conducted pursuant to § 1208.30, and records pertaining to any reasonable fear determination conducted pursuant to § 1208.31, shall not be... a credible fear or reasonable fear interview, or received a credible fear or reasonable fear review...

Communicating Evidence-Based Information on Cancer Prevention to State-Level Policy Makers

PubMed Central

Dodson, Elizabeth A.; Stamatakis, Katherine A.; Casey, Christopher M.; Elliott, Michael B.; Luke, Douglas A.; Wintrode, Christopher G.; Kreuter, Matthew W.

2011-01-01

Background Opportunities exist to disseminate evidence-based cancer control strategies to state-level policy makers in both the legislative and executive branches. We explored factors that influence the likelihood that state-level policy makers will find a policy brief understandable, credible, and useful. Methods A systematic approach was used to develop four types of policy briefs on the topic of mammography screening to reduce breast cancer mortality: data-focused brief with state-level data, data-focused brief with local-level data, story-focused brief with state-level data, and story-focused brief with local-level data. Participants were recruited from three groups of state-level policy makers—legislative staff, legislators, and executive branch administrators— in six states that were randomly chosen after stratifying all 50 states by population size and dominant political party in state legislature. Participants from each of the three policy groups were randomly assigned to receive one of the four types of policy briefs and completed a questionnaire that included a series of Likert scale items. Primary outcomes—whether the brief was understandable, credible, likely to be used, and likely to be shared—were measured by a 5-point Likert scale according to the degree of agreement (1 = strongly disagree, 5 = strongly agree). Data were analyzed with analysis of variance and with classification trees. All statistical tests were two-sided. Results Data on response to the policy briefs (n = 291) were collected from February through December 2009 (overall response rate = 35%). All three policy groups found the briefs to be understandable and credible, with mean ratings that ranged from 4.3 to 4.5. The likelihood of using the brief (the dependent variable) differed statistically significantly by study condition for staffers (P = .041) and for legislators (P = .018). Staffers found the story-focused brief containing state-level data most useful, whereas legislators found the data-focused brief containing state-level data most useful. Exploratory classification trees showed distinctive patterns for brief usefulness across the three policy groups. Conclusion Our results suggest that taking a “one-size-fits-all” approach when delivering information to policy makers may be less effective than communicating information based on the type of policy maker. PMID:21212381

Carryover aquatic effects on survival of metamorphic frogs during pond emigration

USGS Publications Warehouse

Chelgren, N.D.; Rosenberg, D.K.; Heppell, S.S.; Gitelman, A.I.

2006-01-01

In organisms with complex life cycles, physiological stressors during early life stages may have fitness-level impacts that are delayed into later stages or habitats. We tested the hypothesis that body size and date of metamorphosis, which are highly responsive to aquatic stressors, influence post-metamorphic survival and movement patterns in the terrestrial phase of an ephemeral pond-breeding frog by examining these traits in two populations of northern red-legged frogs (Rana aurora aurora). To increase variation of body size at metamorphosis, we manipulated food availability for 314 of 1045 uniquely marked tadpoles and estimated the probability that frogs survived and emigrated using concentric rings of drift fencing surrounding ponds and Bayesian capture-recapture modeling. The odds of surviving and emigrating from the ponds to the innermost drift fences, ???12 m, increased by factors of 2.20 (95% credibility intervals 1.39-4.23) and 2.54 (0.94-4.91) with each millimeter increase in snout-vent length and decreased by factors of 0.91 (0.85-0.96) and 0.89 (0.80-1.00) with each day's delay in metamorphosis for the two ponds. The odds of surviving and moving to the next ring of fencing, 12 m to ???40 m from the ponds, increased by a factor of 1.20 (0.45-4.06) with each millimeter increase in size. Our results demonstrated that body size and timing of metamorphosis relate strongly to the performance of newly metamorphosed frogs during their initial transition into terrestrial habitat. Carryover effects of aquatic stressors that reduce size and delay metamorphosis may have population-level impacts that are not expressed until terrestrial stages. Since changes in both aquatic and terrestrial systems are implicated in many amphibian declines, quantifying both immediate and delayed effects of stressors on demographic rates is critical to sound management. ?? 2006 by the Ecological Society of America.

Relating off-premises alcohol outlet density to intentional and unintentional injuries.

PubMed

Morrison, Christopher; Smith, Karen; Gruenewald, Paul J; Ponicki, William R; Lee, Juliet P; Cameron, Peter

2016-01-01

This study investigated the hypotheses that (i) intentional and unintentional injuries occur more frequently in areas with greater density of off-premises alcohol outlets; and (ii) larger and chain outlets selling cheaper alcohol contribute more substantially to injury risk than smaller and independent outlets. Ecological cross-sectional. From the 256 Statistical Area level 2 (SA2) census units in Melbourne, Australia, we selected a random sample of 62 units. There were 2119 Statistical Area level 1 (SA1) units nested within the selected SA2 units. The selected units contained 295 off-premises outlets. Two independent observers conducted premises assessments in all off-premises outlets, assessing the volume of alcohol available for sale (paces of shelf space), price (least wine price) and other operating characteristics (chain versus independent, drive-through). Outlet counts, assessed outlet characteristics and other area characteristics (population density, median age, median income, retail zoning) were aggregated within SA1 units. Dependent variables were counts of ambulance attended intentional injuries (assaults, stabbings, shootings) and unintentional injuries (falls, crush injuries and object strikes). In univariable analyses, chain outlets were larger (r = 0.383; P < 0.001) and sold cheaper alcohol (r = -0.484; P < 0.001) compared with independent outlets. In Bayesian spatial Poisson models, off-premises outlet density was positively related to both intentional [incidence rate ratio (IRR) = 1.38; 95% credible interval (CI) = 1.19, 1.60] and unintentional injuries (IRR = 1.18; 95% CI = 1.06, 1.30). After disaggregation by outlet characteristics, chain outlet density was also related to both intentional (IRR = 1.35; 95% CI = 1.11, 1.64) and unintentional injuries (IRR = 1.20; 95% CI = 1.08, 1.38). Greater off-premises outlet density is related to greater incidence of traumatic injury, and chain outlets appear to contribute most substantially to traumatic injury risk. © 2015 Society for the Study of Addiction.

Relating Off-Premises Alcohol Outlet Density to Intentional and Unintentional Injuries

PubMed Central

Morrison, Christopher; Smith, Karen; Gruenewald, Paul J.; Ponicki, William R.; Lee, Juliet P.; Cameron, Peter

2015-01-01

Aims This study investigated the hypotheses that (i) intentional and unintentional injuries occur more frequently in areas with greater density of off-premises alcohol outlets; and (ii) larger and chain outlets selling cheaper alcohol contribute more substantially to injury risk than smaller and independent outlets. Design Ecological cross-sectional. Setting From the 256 Statistical Area level 2 (SA2) Census units in Melbourne, Australia, we selected a random sample of 62 units. There were 2,119 Statistical Area level 1 (SA1) units nested within the selected SA2 units. Participants The selected units contained 295 off-premises outlets. Measurements Two independent observers conducted premises assessments in all off-premises outlets, assessing the volume of alcohol available for sale (paces of shelf space), price (least wine price), and other operating characteristics (chain vs. independent, drive-through). Outlet counts, assessed outlet characteristics, and other area characteristics (population density, median age, median income, retail zoning) were aggregated within SA1 units. Dependent variables were counts of ambulance attended intentional injuries (assaults, stabbings, shootings) and unintentional injuries (falls, crush injuries, and object strikes). Findings In univariable analyses, chain outlets were larger (r = 0.383; p < 0.001) and sold cheaper alcohol (r = −0.484; p < 0.001) compared with independent outlets. In Bayesian spatial Poisson models, off-premises outlet density was positively related to both intentional (Incidence Rate Ratio = 1.38; 95% Credible Interval: 1.19, 1.60) and unintentional injuries (IRR = 1.18; 95% CI: 1.06, 1.30). After disaggregation by outlet characteristics, chain outlet density was also related to both intentional (IRR = 1.35; 95% CI: 1.11, 1.64) and unintentional injuries (IRR = 1.20; 95% CI: 1.08, 1.38). Conclusions Greater off-premises outlet density is related to greater incidence of traumatic injury, and chain outlets appear to contribute most substantially to traumatic injury risk. PMID:26283189

A mixed methods evaluation of televised health promotion advertisements targeted at older adults

PubMed Central

Berry, Tanya R.; Spence, John C.; Plotnikoff, Ronald C.; Bauman, Adrian; McCargar, Linda; Witcher, Chad; Clark, Marianne; Stolp, Sean

2016-01-01

The purpose of this research was to evaluate television advertisements targeted at 55–70-year olds that promoted physical activity and fruit and vegetable consumption. Awareness of the campaign, perceived credibility of the source, intentions to visit a promoted website, and intentions to perform the healthy behaviors were evaluated using mixed methods research. Results from a population level survey (n = 1600) showed low unprompted and prompted awareness of the campaign and no differences in intentions or behaviors among those who were aware of the campaign. Unprompted recall resulted in a very wide range of responses including the citation of many commercial advertisers. Qualitative themes that emerged from the focus groups included neutral, positive, and negative comments about the advertisements, source credibility, website considerations specific to seniors, and suggestions about appropriate advertising for older adults. This research showed that the increased attention paid to the advertisements was due in a large part to negative reactions to the character used in the advertisements. Another important finding was the government was not considered to be a credible source of health information. Finally, health promoters should be cautious about websites as the primary source of information, particularly for older adults. PMID:19493572

2νββ decay of 76Ge into excited states with GERDA phase I

NASA Astrophysics Data System (ADS)

GERDA Collaboration; Agostini, M.; Allardt, M.; Bakalyarov, A. M.; Balata, M.; Barabanov, I.; Barros, N.; Baudis, L.; Bauer, C.; Becerici-Schmidt, N.; Bellotti, E.; Belogurov, S.; Belyaev, S. T.; Benato, G.; Bettini, A.; Bezrukov, L.; Bode, T.; Borowicz, D.; Brudanin, V.; Brugnera, R.; Budjáš, D.; Caldwell, A.; Cattadori, C.; Chernogorov, A.; D'Andrea, V.; Demidova, E. V.; di Vacri, A.; Domula, A.; Doroshkevich, E.; Egorov, V.; Falkenstein, R.; Fedorova, O.; Freund, K.; Frodyma, N.; Gangapshev, A.; Garfagnini, A.; Gooch, C.; Grabmayr, P.; Gurentsov, V.; Gusev, K.; Hegai, A.; Heisel, M.; Hemmer, S.; Heusser, G.; Hofmann, W.; Hult, M.; Inzhechik, L. V.; Janicskó Csáthy, J.; Jochum, J.; Junker, M.; Kazalov, V.; Kihm, T.; Kirpichnikov, I. V.; Kirsch, A.; Klimenko, A.; Knöpfle, K. T.; Kochetov, O.; Kornoukhov, V. N.; Kuzminov, V. V.; Laubenstein, M.; Lazzaro, A.; Lebedev, V. I.; Lehnert, B.; Liao, H. Y.; Lindner, M.; Lippi, I.; Lubashevskiy, A.; Lubsandorzhiev, B.; Lutter, G.; Macolino, C.; Majorovits, B.; Maneschg, W.; Medinaceli, E.; Mi, Y.; Misiaszek, M.; Moseev, P.; Nemchenok, I.; Palioselitis, D.; Panas, K.; Pandola, L.; Pelczar, K.; Pullia, A.; Riboldi, S.; Rumyantseva, N.; Sada, C.; Salathe, M.; Schmitt, C.; Schneider, B.; Schreiner, J.; Schulz, O.; Schwingenheuer, B.; Schönert, S.; Schütz, A.-K.; Selivanenko, O.; Shirchenko, M.; Simgen, H.; Smolnikov, A.; Stanco, L.; Stepaniuk, M.; Ur, C. A.; Vanhoefer, L.; Vasenko, A. A.; Veresnikova, A.; von Sturm, K.; Wagner, V.; Walter, M.; Wegmann, A.; Wester, T.; Wilsenach, H.; Wojcik, M.; Yanovich, E.; Zavarise, P.; Zhitnikov, I.; Zhukov, S. V.; Zinatulina, D.; Zuber, K.; Zuzel, G.

2015-11-01

Two neutrino double beta decay of {}76{Ge} to excited states of {}76{Se} has been studied using data from Phase I of the GERDA experiment. An array composed of up to 14 germanium detectors including detectors that have been isotopically enriched in {}76{Ge} was deployed in liquid argon. The analysis of various possible transitions to excited final states is based on coincidence events between pairs of detectors where a de-excitation γ ray is detected in one detector and the two electrons in the other. No signal has been observed and an event counting profile likelihood analysis has been used to determine Frequentist 90% C.L. bounds for three transitions: {0}{{g}.{{s}}.}+-{2}1+: {T}1/22ν \\gt 1.6× {10}23 yr, {0}{{g}.{{s}}.}+-{0}1+: {T}1/22ν \\gt 3.7× {10}23 yr and {0}{{g}.{{s}}.}+-{2}2+: {T}1/22ν \\gt 2.3× {10}23 yr. These bounds are more than two orders of magnitude larger than those reported previously. Bayesian 90% credibility bounds were extracted and used to exclude several models for the {0}{{g}.{{s}}.}+-{0}1+ transition.

Residential Racial Isolation and Spatial Patterning of Type 2 Diabetes Mellitus in Durham, North Carolina.

PubMed

Bravo, Mercedes A; Anthopolos, Rebecca; Kimbro, Rachel T; Miranda, Marie Lynn

2018-05-14

Neighborhood characteristics such as racial segregation may be associated with type 2 diabetes mellitus, but studies have not examined these relationships using spatial models appropriate for geographically patterned health outcomes. We construct a local, spatial index of racial isolation (RI) for blacks, which measures the extent to which blacks are exposed to only one another, to estimate associations of diabetes with RI and examine how RI relates to spatial patterning in diabetes. We obtained 2007-2011 electronic health records from the Duke Medicine Enterprise Data Warehouse. Patient data were linked to RI based on census block of residence. We use aspatial and spatial Bayesian models to assess spatial variation in diabetes and relationships with RI. Compared to spatial models with patient age and sex, residual geographic heterogeneity in diabetes in spatial models that also included RI was 29% and 24% lower for non-Hispanic whites and blacks, respectively. A 0.20 unit increase in RI was associated with 1.24 (95% credible interval: 1.17, 1.31) and 1.07 (1.05, 1.10) increased risk of diabetes for whites and blacks, respectively. Improved understanding of neighborhood characteristics associated with diabetes can inform development of policy interventions.

The Discrepancy between Einstein Mass and Dynamical Mass for SIS and Power-law Mass Models

NASA Astrophysics Data System (ADS)

Li, Rui; Wang, Jiancheng; Shu, Yiping; Xu, Zhaoyi

2018-03-01

We investigate the discrepancy between the two-dimensional projected lensing mass and the dynamical mass for an ensemble of 97 strong gravitational lensing systems discovered by the Sloan Lens ACS Survey, the BOSS Emission-Line Lens Survey (BELLS), and the BELLS for GALaxy-Lyα EmitteR sYstems Survey. We fit the lensing data to obtain the Einstein mass and use the velocity dispersion of the lensing galaxies provided by the Sloan Digital Sky Survey to get the projected dynamical mass within the Einstein radius by assuming the power-law mass approximation. The discrepancy is found to be obvious and quantified by Bayesian analysis. For the singular isothermal sphere mass model, we obtain that the Einstein mass is 20.7% more than the dynamical mass, and the discrepancy increases with the redshift of the lensing galaxies. For the more general power-law mass model, the discrepancy still exists within a 1σ credible region. We suspect the main reason for this discrepancy is mass contamination, including all invisible masses along the line of sight. In addition, the measurement errors and the approximation of the mass models could also contribute to the discrepancy.

Assessing evidence for behaviour change affecting the course of HIV epidemics: a new mathematical modelling approach and application to data from Zimbabwe.

PubMed

Hallett, Timothy B; Gregson, Simon; Mugurungi, Owen; Gonese, Elizabeth; Garnett, Geoff P

2009-06-01

Determining whether interventions to reduce HIV transmission have worked is essential, but complicated by the potential for generalised epidemics to evolve over time without individuals changing risk behaviour. We aimed to develop a method to evaluate evidence for changes in risk behaviour altering the course of an HIV epidemic. We developed a mathematical model of HIV transmission, incorporating the potential for natural changes in the epidemic as it matures and the introduction of antiretroviral treatment, and applied a Bayesian Melding framework, in which the model and observed trends in prevalence can be compared. We applied the model to Zimbabwe, using HIV prevalence estimates from antenatal clinic surveillance and house-hold based surveys, and basing model parameters on data from sexual behaviour surveys. There was strong evidence for reductions in risk behaviour stemming HIV transmission. We estimate these changes occurred between 1999 and 2004 and averted 660,000 (95% credible interval: 460,000-860,000) infections by 2008. The model and associated analysis framework provide a robust way to evaluate the evidence for changes in risk behaviour affecting the course of HIV epidemics, avoiding confounding by the natural evolution of HIV epidemics.

Bayesian evidence for the prevalence of waterworlds

NASA Astrophysics Data System (ADS)

Simpson, Fergus

2017-07-01

Should we expect most habitable planets to share the Earth's marbled appearance? For a planetary surface to boast extensive areas of both land and water, a delicate balance must be struck between the volume of water it retains and the capacity of its perturbations. These two quantities may show substantial variability across the full spectrum of water-bearing worlds. This would suggest that, barring strong feedback effects, most surfaces are heavily dominated by either water or land. Why is the Earth so finely poised? To address this question, we construct a simple model for the selection bias that would arise within an ensemble of surface conditions. Based on the Earth's ocean coverage of 71 per cent, we find substantial evidence (Bayes factor K ≃ 6) supporting the hypothesis that anthropic selection effects are at work. Furthermore, due to the Earth's proximity to the waterworld limit, this model predicts that most habitable planets are dominated by oceans spanning over 90 per cent of their surface area (95 per cent credible interval). This scenario, in which the Earth has a much greater land area than most habitable planets, is consistent with results from numerical simulations and could help explain the apparently low-mass transition in the mass-radius relation.

Joint time/frequency-domain inversion of reflection data for seabed geoacoustic profiles and uncertainties.

PubMed

Dettmer, Jan; Dosso, Stan E; Holland, Charles W

2008-03-01

This paper develops a joint time/frequency-domain inversion for high-resolution single-bounce reflection data, with the potential to resolve fine-scale profiles of sediment velocity, density, and attenuation over small seafloor footprints (approximately 100 m). The approach utilizes sequential Bayesian inversion of time- and frequency-domain reflection data, employing ray-tracing inversion for reflection travel times and a layer-packet stripping method for spherical-wave reflection-coefficient inversion. Posterior credibility intervals from the travel-time inversion are passed on as prior information to the reflection-coefficient inversion. Within the reflection-coefficient inversion, parameter information is passed from one layer packet inversion to the next in terms of marginal probability distributions rotated into principal components, providing an efficient approach to (partially) account for multi-dimensional parameter correlations with one-dimensional, numerical distributions. Quantitative geoacoustic parameter uncertainties are provided by a nonlinear Gibbs sampling approach employing full data error covariance estimation (including nonstationary effects) and accounting for possible biases in travel-time picks. Posterior examination of data residuals shows the importance of including data covariance estimates in the inversion. The joint inversion is applied to data collected on the Malta Plateau during the SCARAB98 experiment.

Estimation of divergence times in cnidarian evolution based on mitochondrial protein-coding genes and the fossil record.

PubMed

Park, Eunji; Hwang, Dae-Sik; Lee, Jae-Seong; Song, Jun-Im; Seo, Tae-Kun; Won, Yong-Jin

2012-01-01

The phylum Cnidaria is comprised of remarkably diverse and ecologically significant taxa, such as the reef-forming corals, and occupies a basal position in metazoan evolution. The origin of this phylum and the most recent common ancestors (MRCAs) of its modern classes remain mostly unknown, although scattered fossil evidence provides some insights on this topic. Here, we investigate the molecular divergence times of the major taxonomic groups of Cnidaria (27 Hexacorallia, 16 Octocorallia, and 5 Medusozoa) on the basis of mitochondrial DNA sequences of 13 protein-coding genes. For this analysis, the complete mitochondrial genomes of seven octocoral and two scyphozoan species were newly sequenced and combined with all available mitogenomic data from GenBank. Five reliable fossil dates were used to calibrate the Bayesian estimates of divergence times. The molecular evidence suggests that cnidarians originated 741 million years ago (Ma) (95% credible region of 686-819), and the major taxa diversified prior to the Cambrian (543 Ma). The Octocorallia and Scleractinia may have originated from radiations of survivors of the Permian-Triassic mass extinction, which matches their fossil record well. Copyright © 2011 Elsevier Inc. All rights reserved.

Implementation of Instrumental Variable Bounds for Data Missing Not at Random.

PubMed

Marden, Jessica R; Wang, Linbo; Tchetgen, Eric J Tchetgen; Walter, Stefan; Glymour, M Maria; Wirth, Kathleen E

2018-05-01

Instrumental variables are routinely used to recover a consistent estimator of an exposure causal effect in the presence of unmeasured confounding. Instrumental variable approaches to account for nonignorable missing data also exist but are less familiar to epidemiologists. Like instrumental variables for exposure causal effects, instrumental variables for missing data rely on exclusion restriction and instrumental variable relevance assumptions. Yet these two conditions alone are insufficient for point identification. For estimation, researchers have invoked a third assumption, typically involving fairly restrictive parametric constraints. Inferences can be sensitive to these parametric assumptions, which are typically not empirically testable. The purpose of our article is to discuss another approach for leveraging a valid instrumental variable. Although the approach is insufficient for nonparametric identification, it can nonetheless provide informative inferences about the presence, direction, and magnitude of selection bias, without invoking a third untestable parametric assumption. An important contribution of this article is an Excel spreadsheet tool that can be used to obtain empirical evidence of selection bias and calculate bounds and corresponding Bayesian 95% credible intervals for a nonidentifiable population proportion. For illustrative purposes, we used the spreadsheet tool to analyze HIV prevalence data collected by the 2007 Zambia Demographic and Health Survey (DHS).

Evaluation of the procedure 1A component of the 1980 US/Canada wheat and barley exploratory experiment

NASA Technical Reports Server (NTRS)

Chapman, G. M. (Principal Investigator); Carnes, J. G.

1981-01-01

Several techniques which use clusters generated by a new clustering algorithm, CLASSY, are proposed as alternatives to random sampling to obtain greater precision in crop proportion estimation: (1) Proportional Allocation/relative count estimator (PA/RCE) uses proportional allocation of dots to clusters on the basis of cluster size and a relative count cluster level estimate; (2) Proportional Allocation/Bayes Estimator (PA/BE) uses proportional allocation of dots to clusters and a Bayesian cluster-level estimate; and (3) Bayes Sequential Allocation/Bayesian Estimator (BSA/BE) uses sequential allocation of dots to clusters and a Bayesian cluster level estimate. Clustering in an effective method in making proportion estimates. It is estimated that, to obtain the same precision with random sampling as obtained by the proportional sampling of 50 dots with an unbiased estimator, samples of 85 or 166 would need to be taken if dot sets with AI labels (integrated procedure) or ground truth labels, respectively were input. Dot reallocation provides dot sets that are unbiased. It is recommended that these proportion estimation techniques are maintained, particularly the PA/BE because it provides the greatest precision.

A conceptual model for site-level ecology of the giant gartersnake (Thamnophis gigas) in the Sacramento Valley, California

USGS Publications Warehouse

Halstead, Brian J.; Wylie, Glenn D.; Casazza, Michael L.; Hansen, Eric C.; Scherer, Rick D.; Patterson, Laura C.

2015-08-14

Bayesian networks further provide a clear visual display of the model that facilitates understanding among various stakeholders (Marcot and others, 2001; Uusitalo , 2007). Empirical data and expert judgment can be combined, as continuous or categorical variables, to update knowledge about the system (Marcot and others, 2001; Uusitalo , 2007). Importantly, Bayesian network models allow inference from causes to consequences, but also from consequences to causes, so that data can inform the states of nodes (values of different random variables) in either direction (Marcot and others, 2001; Uusitalo , 2007). Because they can incorporate both decision nodes that represent management actions and utility nodes that quantify the costs and benefits of outcomes, Bayesian networks are ideally suited to risk analysis and adaptive management (Nyberg and others, 2006; Howes and others, 2010). Thus, Bayesian network models are useful in situations where empirical data are not available, such as questions concerning the responses of giant gartersnakes to management.

Bayesian hierarchical model of ceftriaxone resistance proportions among Salmonella serotype Heidelberg infections.

PubMed

Gu, Weidong; Medalla, Felicita; Hoekstra, Robert M

2018-02-01

The National Antimicrobial Resistance Monitoring System (NARMS) at the Centers for Disease Control and Prevention tracks resistance among Salmonella infections. The annual number of Salmonella isolates of a particular serotype from states may be small, making direct estimation of resistance proportions unreliable. We developed a Bayesian hierarchical model to improve estimation by borrowing strength from relevant sampling units. We illustrate the models with different specifications of spatio-temporal interaction using 2004-2013 NARMS data for ceftriaxone-resistant Salmonella serotype Heidelberg. Our results show that Bayesian estimates of resistance proportions were smoother than observed values, and the difference between predicted and observed proportions was inversely related to the number of submitted isolates. The model with interaction allowed for tracking of annual changes in resistance proportions at the state level. We demonstrated that Bayesian hierarchical models provide a useful tool to examine spatio-temporal patterns of small sample size such as those found in NARMS. Published by Elsevier Ltd.

The Importance of Being…Social? Instructor Credibility and the Millennials

ERIC Educational Resources Information Center

Gerhardt, Megan W.

2016-01-01

Using the framework of generational identity, the current study explores how a range of characteristics impact Millennial perceptions of instructor credibility. Millennial Generation student ratings of the impact of competence, character, and sociability on instructor credibility were compared to faculty ratings of the same characteristics.…

Marginality, Credibility, and Impression Management: The Asian Sociologist in America.

ERIC Educational Resources Information Center

Unnithan, N. Prabha

1988-01-01

Relates personal experiences of a sociologist of Asian origin in an effort to illustrate problems inherent in the process of becoming accepted as an academic sociologist. Identifies important themes of marginality, credibility, and impression management. Points out ways in which the Asian sociologists can go about achieving credibility. (KO)

8 CFR 208.6 - Disclosure to third parties.

Code of Federal Regulations, 2010 CFR

2010-01-01

... credible fear determination conducted pursuant to § 208.30, and records pertaining to any reasonable fear... that a specific alien has applied for asylum, received a credible fear or reasonable fear interview, or received a credible fear or reasonable fear review shall also be protected from disclosure. The Service...

Scientific independence: A key to credibility

Treesearch

Leonard F. Ruggiero

2007-01-01

Independence and objectivity are key ingredients of scientific credibility, especially in research organizations that are part of a natural resource management agency like the Forest Service. Credibility, in turn, is essential to the utility of scientific information in socio-political processes. In order to develop this thesis further, a basic understanding of Forest...

Sexual Preference Similarity, Attitude Similarity, and Perceived Counselor Credibility and Attractiveness.

ERIC Educational Resources Information Center

Atkinson, Donald R.; And Others

1981-01-01

Examined the effect of membership group and attitudinal similarity on perceived counselor credibility and attractiveness. Homosexual men (N=84) rated the counselor's credibility and attractiveness after listening to a recorded counseling interview. The counselor was rated more expert, trustworthy, and attractive when he stated a sexual preference…

Data Credibility: A Perspective from Systematic Reviews in Environmental Management

ERIC Educational Resources Information Center

Pullin, Andrew S.; Knight, Teri M.

2009-01-01

To use environmental program evaluation to increase effectiveness, predictive power, and resource allocation efficiency, evaluators need good data. Data require sufficient credibility in terms of fitness for purpose and quality to develop the necessary evidence base. The authors examine elements of data credibility using experience from critical…

The Effects of Source Credibility in the Presence or Absence of Prior Attitudes: Implications for the Design of Persuasive Communication Campaigns.

PubMed

Kumkale, G Tarcan; Albarracín, Dolores; Seignourel, Paul J

2010-06-01

Most theories of persuasion predict that limited ability and motivation to think about communications should increase the impact of source credibility on persuasion. Furthermore, this effect is assumed to occur, regardless of whether or not the recipients have prior attitudes. In this study, the effects of source credibility, ability, and motivation (knowledge, message repetition, relevance) on persuasion were examined meta-analytically across both attitude formation and change conditions. Findings revealed that the Source Credibility × Ability/Motivation interaction emerged only when participants lacked prior attitudes and were unable to form a new attitude based on the message content. In such settings, the effects of source credibility decayed rapidly. The implications of these findings for applied communication campaigns are discussed.

The Effects of Source Credibility in the Presence or Absence of Prior Attitudes: Implications for the Design of Persuasive Communication Campaigns1

PubMed Central

Kumkale, G. Tarcan; AlbarracÍn, Dolores; Seignourel, Paul J.

2011-01-01

Most theories of persuasion predict that limited ability and motivation to think about communications should increase the impact of source credibility on persuasion. Furthermore, this effect is assumed to occur, regardless of whether or not the recipients have prior attitudes. In this study, the effects of source credibility, ability, and motivation (knowledge, message repetition, relevance) on persuasion were examined meta-analytically across both attitude formation and change conditions. Findings revealed that the Source Credibility × Ability/Motivation interaction emerged only when participants lacked prior attitudes and were unable to form a new attitude based on the message content. In such settings, the effects of source credibility decayed rapidly. The implications of these findings for applied communication campaigns are discussed. PMID:21625405

The effect of source credibility on consumers' perceptions of the quality of health information on the Internet.

PubMed

Bates, Benjamin R; Romina, Sharon; Ahmed, Rukhsana; Hopson, Danielle

2006-03-01

Recent use of the Internet as a source of health information has raised concerns about consumers' ability to tell 'good' information from 'bad' information. Although consumers report that they use source credibility to judge information quality, several observational studies suggest that consumers make little use of source credibility. This study examines consumer evaluations of web pages attributed to a credible source as compared to generic web pages on measures of message quality. In spring 2005, a community-wide convenience survey was distributed in a regional hub city in Ohio, USA. 519 participants were randomly assigned one of six messages discussing lung cancer prevention: three messages each attributed to a highly credible national organization and three identical messages each attributed to a generic web page. Independent sample t-tests were conducted to compare each attributed message to its counterpart attributed to a generic web page on measures of trustworthiness, truthfulness, readability, and completeness. The results demonstrated that differences in attribution to a source did not have a significant effect on consumers' evaluations of the quality of the information.Conclusions. The authors offer suggestions for national organizations to promote credibility to consumers as a heuristic for choosing better online health information through the use of media co-channels to emphasize credibility.

The credibility of exposure therapy: Does the theoretical rationale matter?

PubMed

Arch, Joanna J; Twohig, Michael P; Deacon, Brett J; Landy, Lauren N; Bluett, Ellen J

2015-09-01

Little is understood about how the public perceives exposure-based therapy (ET) for treating anxiety and trauma-related disorders or how ET rationales affect treatment credibility. Distinct approaches to framing ET are practiced, including those emphasized in traditional cognitive behavioral therapy, acceptance and commitment therapy, and the more recent inhibitory learning model. However, their relative effect on ET's credibility remains unknown. A final sample of 964 U.S. adults provided baseline views of ET. Participants rated ET treatment credibility following a simple ET definition (pre-rationale) and following randomization to rationale modules addressing ET goals, fear, and cognitive strategies from distinct theoretical perspectives (post-rationale). Baseline ET views, symptoms, and sociodemographic characteristics were examined as putative moderators and predictors. At baseline, the majority had never heard of ET. From pre- to post-rationale, ET treatment credibility significantly increased but the rationales' theoretical perspective had little impact. More negative baseline ET views, specific ethnic/racial minority group status, and lower education moderated or predicted greater increases in treatment credibility following the rationale. ET remains relatively unknown as a treatment for anxiety or trauma, supporting the need for direct-to-consumer marketing. Diverse theory-driven rationales similarly increased ET credibility, particularly among those less likely to use ET. Copyright © 2015 Elsevier Ltd. All rights reserved.

A test of faith in God and treatment: the relationship of belief in God to psychiatric treatment outcomes.

PubMed

Rosmarin, David H; Bigda-Peyton, Joseph S; Kertz, Sarah J; Smith, Nasya; Rauch, Scott L; Björgvinsson, Thröstur

2013-04-25

Belief in God is very common and tied to mental health/illness in the general population, yet its relevance to psychiatric patients has not been adequately studied. We examined relationships between belief in God and treatment outcomes, and identified mediating mechanisms. We conducted a prospective study with n=159 patients in a day-treatment program at an academic psychiatric hospital. Belief in God, treatment credibility/expectancy, emotion regulation and congregational support were assessed prior to treatment. Primary outcomes were treatment response as well as degree of reduction in depression over treatment. Secondary outcomes were improvements in psychological well-being and reduction in self-harm. Belief in God was significantly higher among treatment responders than non-responders F(1,114)=4.81, p<.05. Higher levels of belief were also associated with greater reductions in depression (r=.21, p<.05) and self-harm (r=.24, p<.01), and greater improvements in psychological well-being (r=.19, p<.05) over course of treatment. Belief remained correlated with changes in depression and self-harm after controlling for age and gender. Perceived treatment credibility/expectancy, but not emotional regulation or community support, mediated relationships between belief in God and reductions in depression. No variables mediated relationships to other outcomes. Religious affiliation was also associated with treatment credibility/expectancy but not treatment outcomes. Belief in God, but not religious affiliation, was associated with better treatment outcomes. With respect to depression, this relationship was mediated by belief in the credibility of treatment and expectations for treatment gains. Copyright © 2012 Elsevier B.V. All rights reserved.

End User Acceptance - Requirements or Specifications, Certification, Testing

NASA Technical Reports Server (NTRS)

Jeevarajan, Judith

2013-01-01

NASA follows top level safety requirement of two-failure tolerance (t hree levels of controls or design for minimum risk) to all catastroph ic hazards in the design of safe li-ion batteries for space use. ? R igorous development testing at appropriate levels to credible offnominal conditions and review of test data. ? Implement robust design con trols based on test results and test again to confirm safety at the a ppropriate levels. ? Stringent testing of all (100%) flight batteries (from button cells to large batteries).

An Excel sheet for inferring children's number-knower levels from give-N data.

PubMed

Negen, James; Sarnecka, Barbara W; Lee, Michael D

2012-03-01

Number-knower levels are a series of stages of number concept development in early childhood. A child's number-knower level is typically assessed using the give-N task. Although the task procedure has been highly refined, the standard ways of analyzing give-N data remain somewhat crude. Lee and Sarnecka (Cogn Sci 34:51-67, 2010, in press) have developed a Bayesian model of children's performance on the give-N task that allows knower level to be inferred in a more principled way. However, this model requires considerable expertise and computational effort to implement and apply to data. Here, we present an approximation to the model's inference that can be computed with Microsoft Excel. We demonstrate the accuracy of the approximation and provide instructions for its use. This makes the powerful inferential capabilities of the Bayesian model accessible to developmental researchers interested in estimating knower levels from give-N data.