Reinforcement sensitivity theory and alcohol outcome expectancies in early adolescence.

PubMed

Lopez-Vergara, Hector I; Colder, Craig R; Hawk, Larry W; Wieczorek, William F; Eiden, Rina D; Lengua, Liliana J; Read, Jennifer P

2012-03-01

Little research has examined the development of alcohol expectancies in childhood, a notable omission as expectancies are viable targets for prevention programs. Moreover, limited alcohol expectancies research has been conducted from the perspective of psychobiological models of motivation despite the strong conceptual links between such models and cognitive models of alcohol use. To examine if the associations between individual differences from the revised reinforcement sensitivity theory (Gray JA, McNaughton N. The Neuropsychology of Anxiety: An Enquiry into the Functions of the Septo-hippocampal System (2nd ed.). Oxford, UK: Oxford University Press, 2000) and alcohol use is mediated by alcohol expectancies in a large community sample of early adolescents using a prospective design. 378 families (1 caregiver; 1 child) were recruited via random digit phone call using a prospective design. Our findings suggest that both a strong behavioral approach system and fight-flight or freeze system were associated with high levels of positive outcome expectancies, which subsequently predicted an increase in likelihood of alcohol use. There was also some evidence that drive (an aspect of behavioral approach system) was also positively associated with negative expectancies, which subsequently predicted a low probability of alcohol use. Individual differences in reinforcement sensitivity may influence the acquisition of positive and negative outcome expectancies, thereby potentially influencing the likelihood of alcohol use in early adolescence. Thus, reinforcement sensitivity theory is a promising theory to account for the link between neural models of addiction and early acquisition of alcohol use in humans.

The Simple Rules of Social Contagion

PubMed Central

Hodas, Nathan O.; Lerman, Kristina

2014-01-01

It is commonly believed that information spreads between individuals like a pathogen, with each exposure by an informed friend potentially resulting in a naive individual becoming infected. However, empirical studies of social media suggest that individual response to repeated exposure to information is far more complex. As a proxy for intervention experiments, we compare user responses to multiple exposures on two different social media sites, Twitter and Digg. We show that the position of exposing messages on the user-interface strongly affects social contagion. Accounting for this visibility significantly simplifies the dynamics of social contagion. The likelihood an individual will spread information increases monotonically with exposure, while explicit feedback about how many friends have previously spread it increases the likelihood of a response. We provide a framework for unifying information visibility, divided attention, and explicit social feedback to predict the temporal dynamics of user behavior. PMID:24614301

Predicting the likelihood of altered streamflows at ungauged rivers across the conterminous United States

USGS Publications Warehouse

Eng, Kenny; Carlisle, Daren M.; Wolock, David M.; Falcone, James A.

2013-01-01

An approach is presented in this study to aid water-resource managers in characterizing streamflow alteration at ungauged rivers. Such approaches can be used to take advantage of the substantial amounts of biological data collected at ungauged rivers to evaluate the potential ecological consequences of altered streamflows. National-scale random forest statistical models are developed to predict the likelihood that ungauged rivers have altered streamflows (relative to expected natural condition) for five hydrologic metrics (HMs) representing different aspects of the streamflow regime. The models use human disturbance variables, such as number of dams and road density, to predict the likelihood of streamflow alteration. For each HM, separate models are derived to predict the likelihood that the observed metric is greater than (‘inflated’) or less than (‘diminished’) natural conditions. The utility of these models is demonstrated by applying them to all river segments in the South Platte River in Colorado, USA, and for all 10-digit hydrologic units in the conterminous United States. In general, the models successfully predicted the likelihood of alteration to the five HMs at the national scale as well as in the South Platte River basin. However, the models predicting the likelihood of diminished HMs consistently outperformed models predicting inflated HMs, possibly because of fewer sites across the conterminous United States where HMs are inflated. The results of these analyses suggest that the primary predictors of altered streamflow regimes across the Nation are (i) the residence time of annual runoff held in storage in reservoirs, (ii) the degree of urbanization measured by road density and (iii) the extent of agricultural land cover in the river basin.

The comparative accuracy of rapid diagnostic test with microscopy to diagnose malaria in subdistrict lima puluh batubara regency North Sumatera province

NASA Astrophysics Data System (ADS)

Rezeki, S.; Pasaribu, A. P.

2018-03-01

Indonesia is the country where malaria is still the most common population problem. The high rate of mortality and morbidity occurred due to delays in diagnosis whichis strongly influenced by the availability of diagnostic tools and personnel with required laboratory skill. This diagnostic study aims to compare the accuracy of a Rapid Diagnostic Test (RDT) without skill requirement, to agold standard microscopic method for malaria diagnosis. The study was conducted in Subdistrict Lima Puluh North Sumatera Province from December 2015 to January 2016. The subject was taken cross-sectionally from a population with characteristics typically found in malaria patients in Subdistrict Lima Puluh. The result showed a sensitivity of 100% and a specificity of 72.4% with a positive predictive value of 89.9% and a negative predictive value of 100%; the negative likelihood ratio is 0 and the positive likelihood ratio of 27.6 for Parascreen. This research indicates that Parascreen had a high sensitivity and specificity and may be consideredas an alternative for the diagnosis of malaria in Subdistrict Lima Puluh North Sumatera Province especially in areas where no skilled microscopist is available.

Three methods to construct predictive models using logistic regression and likelihood ratios to facilitate adjustment for pretest probability give similar results.

PubMed

Chan, Siew Foong; Deeks, Jonathan J; Macaskill, Petra; Irwig, Les

2008-01-01

To compare three predictive models based on logistic regression to estimate adjusted likelihood ratios allowing for interdependency between diagnostic variables (tests). This study was a review of the theoretical basis, assumptions, and limitations of published models; and a statistical extension of methods and application to a case study of the diagnosis of obstructive airways disease based on history and clinical examination. Albert's method includes an offset term to estimate an adjusted likelihood ratio for combinations of tests. Spiegelhalter and Knill-Jones method uses the unadjusted likelihood ratio for each test as a predictor and computes shrinkage factors to allow for interdependence. Knottnerus' method differs from the other methods because it requires sequencing of tests, which limits its application to situations where there are few tests and substantial data. Although parameter estimates differed between the models, predicted "posttest" probabilities were generally similar. Construction of predictive models using logistic regression is preferred to the independence Bayes' approach when it is important to adjust for dependency of tests errors. Methods to estimate adjusted likelihood ratios from predictive models should be considered in preference to a standard logistic regression model to facilitate ease of interpretation and application. Albert's method provides the most straightforward approach.

Competition between learned reward and error outcome predictions in anterior cingulate cortex.

PubMed

Alexander, William H; Brown, Joshua W

2010-02-15

The anterior cingulate cortex (ACC) is implicated in performance monitoring and cognitive control. Non-human primate studies of ACC show prominent reward signals, but these are elusive in human studies, which instead show mainly conflict and error effects. Here we demonstrate distinct appetitive and aversive activity in human ACC. The error likelihood hypothesis suggests that ACC activity increases in proportion to the likelihood of an error, and ACC is also sensitive to the consequence magnitude of the predicted error. Previous work further showed that error likelihood effects reach a ceiling as the potential consequences of an error increase, possibly due to reductions in the average reward. We explored this issue by independently manipulating reward magnitude of task responses and error likelihood while controlling for potential error consequences in an Incentive Change Signal Task. The fMRI results ruled out a modulatory effect of expected reward on error likelihood effects in favor of a competition effect between expected reward and error likelihood. Dynamic causal modeling showed that error likelihood and expected reward signals are intrinsic to the ACC rather than received from elsewhere. These findings agree with interpretations of ACC activity as signaling both perceptions of risk and predicted reward. Copyright 2009 Elsevier Inc. All rights reserved.

First Results of the Regional Earthquake Likelihood Models Experiment

USGS Publications Warehouse

Schorlemmer, D.; Zechar, J.D.; Werner, M.J.; Field, E.H.; Jackson, D.D.; Jordan, T.H.

2010-01-01

The ability to successfully predict the future behavior of a system is a strong indication that the system is well understood. Certainly many details of the earthquake system remain obscure, but several hypotheses related to earthquake occurrence and seismic hazard have been proffered, and predicting earthquake behavior is a worthy goal and demanded by society. Along these lines, one of the primary objectives of the Regional Earthquake Likelihood Models (RELM) working group was to formalize earthquake occurrence hypotheses in the form of prospective earthquake rate forecasts in California. RELM members, working in small research groups, developed more than a dozen 5-year forecasts; they also outlined a performance evaluation method and provided a conceptual description of a Testing Center in which to perform predictability experiments. Subsequently, researchers working within the Collaboratory for the Study of Earthquake Predictability (CSEP) have begun implementing Testing Centers in different locations worldwide, and the RELM predictability experiment-a truly prospective earthquake prediction effort-is underway within the U. S. branch of CSEP. The experiment, designed to compare time-invariant 5-year earthquake rate forecasts, is now approximately halfway to its completion. In this paper, we describe the models under evaluation and present, for the first time, preliminary results of this unique experiment. While these results are preliminary-the forecasts were meant for an application of 5 years-we find interesting results: most of the models are consistent with the observation and one model forecasts the distribution of earthquakes best. We discuss the observed sample of target earthquakes in the context of historical seismicity within the testing region, highlight potential pitfalls of the current tests, and suggest plans for future revisions to experiments such as this one. ?? 2010 The Author(s).

First Results of the Regional Earthquake Likelihood Models Experiment

NASA Astrophysics Data System (ADS)

Schorlemmer, Danijel; Zechar, J. Douglas; Werner, Maximilian J.; Field, Edward H.; Jackson, David D.; Jordan, Thomas H.

2010-08-01

The ability to successfully predict the future behavior of a system is a strong indication that the system is well understood. Certainly many details of the earthquake system remain obscure, but several hypotheses related to earthquake occurrence and seismic hazard have been proffered, and predicting earthquake behavior is a worthy goal and demanded by society. Along these lines, one of the primary objectives of the Regional Earthquake Likelihood Models (RELM) working group was to formalize earthquake occurrence hypotheses in the form of prospective earthquake rate forecasts in California. RELM members, working in small research groups, developed more than a dozen 5-year forecasts; they also outlined a performance evaluation method and provided a conceptual description of a Testing Center in which to perform predictability experiments. Subsequently, researchers working within the Collaboratory for the Study of Earthquake Predictability (CSEP) have begun implementing Testing Centers in different locations worldwide, and the RELM predictability experiment—a truly prospective earthquake prediction effort—is underway within the U.S. branch of CSEP. The experiment, designed to compare time-invariant 5-year earthquake rate forecasts, is now approximately halfway to its completion. In this paper, we describe the models under evaluation and present, for the first time, preliminary results of this unique experiment. While these results are preliminary—the forecasts were meant for an application of 5 years—we find interesting results: most of the models are consistent with the observation and one model forecasts the distribution of earthquakes best. We discuss the observed sample of target earthquakes in the context of historical seismicity within the testing region, highlight potential pitfalls of the current tests, and suggest plans for future revisions to experiments such as this one.

Moral Identity Predicts Doping Likelihood via Moral Disengagement and Anticipated Guilt.

PubMed

Kavussanu, Maria; Ring, Christopher

2017-08-01

In this study, we integrated elements of social cognitive theory of moral thought and action and the social cognitive model of moral identity to better understand doping likelihood in athletes. Participants (N = 398) recruited from a variety of team sports completed measures of moral identity, moral disengagement, anticipated guilt, and doping likelihood. Moral identity predicted doping likelihood indirectly via moral disengagement and anticipated guilt. Anticipated guilt about potential doping mediated the relationship between moral disengagement and doping likelihood. Our findings provide novel evidence to suggest that athletes, who feel that being a moral person is central to their self-concept, are less likely to use banned substances due to their lower tendency to morally disengage and the more intense feelings of guilt they expect to experience for using banned substances.

Within-person Changes in Individual Symptoms of Depression Predict Subsequent Depressive Episodes in Adolescents: A Prospective Study

PubMed Central

Kouros, Chrystyna D.; Morris, Matthew C.; Garber, Judy

2015-01-01

The current longitudinal study examined which individual symptoms of depression uniquely predicted a subsequent Major Depressive Episode (MDE) in adolescents, and whether these relations differed by sex. Adolescents (N=240) were first interviewed in grade 6 (M=11.86 years old; SD = 0.56; 54% female; 81.5% Caucasian) and then annually through grade 12 regarding their individual symptoms of depression as well as the occurrence of MDEs. Individual symptoms of depression were assessed with the Children’s Depression Rating Scale-Revised (CDRS-R) and depressive episodes were assessed with the Longitudinal Interval Follow-up Evaluation (LIFE). Results showed that within-person changes in sleep problems and low self-esteem/excessive guilt positively predicted an increased likelihood of an MDE for both boys and girls. Significant sex differences also were found. Within-person changes in anhedonia predicted an increased likelihood of a subsequent MDE among boys, whereas irritability predicted a decreased likelihood of a future MDE among boys, and concentration difficulties predicted a decreased likelihood of an MDE in girls. These results identified individual depressive symptoms that predicted subsequent depressive episodes in male and female adolescents, and may be used to guide the early detection, treatment, and prevention of depressive disorders in youth. PMID:26105209

Things Are Not as Bad as They Seem: Physicians' Ability to Predict Their Clinical Practice When a New Vaccine Becomes Available

PubMed Central

Hurley, Laura; Crane, Lori A.; Dong, Fran; Stokley, Shannon; Daley, Matthew F.; Barrow, Jennifer; Babbel, Christine; Dickinson, L. Miriam; Kempe, Allison

2013-01-01

Survey results regarding primary care physicians' likelihood of recommending a new vaccine were compared before and after the vaccine was licensed by the Food and Drug Administration for three new vaccines: herpes zoster (HZ), human papillomavirus (HPV) and rotavirus (RV), using physician networks representative of United States physicians. The main purpose of this study was to determine (a) how accurately physicians predict their eventual vaccine recommendations and the barriers they will experience in delivering the new vaccine and (b) whether physicians shift towards more or less strongly recommending a new vaccine from pre- to post-licensure. Responses from 284, 152 and 184 physicians were analyzed for the three vaccines, respectively. For all vaccines, there was a significant association between physicians' pre- and post-licensure recommendations (p<0.05). When responses changed from pre- to post-licensure, physicians tended to recommend a given vaccine more strongly than they had anticipated pre-licensure. Before vaccine availability, physicians tended to predict greater barriers to vaccine delivery than they eventually experienced. Surveys are useful for predicting physician practices, but may provide a slightly pessimistic view of physician adoption of new vaccines. Such data can be helpful in devising strategies to encourage vaccine delivery by physicians. PMID:23968639

Assessment of parametric uncertainty for groundwater reactive transport modeling,

USGS Publications Warehouse

Shi, Xiaoqing; Ye, Ming; Curtis, Gary P.; Miller, Geoffery L.; Meyer, Philip D.; Kohler, Matthias; Yabusaki, Steve; Wu, Jichun

2014-01-01

The validity of using Gaussian assumptions for model residuals in uncertainty quantification of a groundwater reactive transport model was evaluated in this study. Least squares regression methods explicitly assume Gaussian residuals, and the assumption leads to Gaussian likelihood functions, model parameters, and model predictions. While the Bayesian methods do not explicitly require the Gaussian assumption, Gaussian residuals are widely used. This paper shows that the residuals of the reactive transport model are non-Gaussian, heteroscedastic, and correlated in time; characterizing them requires using a generalized likelihood function such as the formal generalized likelihood function developed by Schoups and Vrugt (2010). For the surface complexation model considered in this study for simulating uranium reactive transport in groundwater, parametric uncertainty is quantified using the least squares regression methods and Bayesian methods with both Gaussian and formal generalized likelihood functions. While the least squares methods and Bayesian methods with Gaussian likelihood function produce similar Gaussian parameter distributions, the parameter distributions of Bayesian uncertainty quantification using the formal generalized likelihood function are non-Gaussian. In addition, predictive performance of formal generalized likelihood function is superior to that of least squares regression and Bayesian methods with Gaussian likelihood function. The Bayesian uncertainty quantification is conducted using the differential evolution adaptive metropolis (DREAM(zs)) algorithm; as a Markov chain Monte Carlo (MCMC) method, it is a robust tool for quantifying uncertainty in groundwater reactive transport models. For the surface complexation model, the regression-based local sensitivity analysis and Morris- and DREAM(ZS)-based global sensitivity analysis yield almost identical ranking of parameter importance. The uncertainty analysis may help select appropriate likelihood functions, improve model calibration, and reduce predictive uncertainty in other groundwater reactive transport and environmental modeling.

On the existence of maximum likelihood estimates for presence-only data

USGS Publications Warehouse

Hefley, Trevor J.; Hooten, Mevin B.

2015-01-01

It is important to identify conditions for which maximum likelihood estimates are unlikely to be identifiable from presence-only data. In data sets where the maximum likelihood estimates do not exist, penalized likelihood and Bayesian methods will produce coefficient estimates, but these are sensitive to the choice of estimation procedure and prior or penalty term. When sample size is small or it is thought that habitat preferences are strong, we propose a suite of estimation procedures researchers can consider using.

The Effect and Relative Importance of Neutral Genetic Diversity for Predicting Parasitism Varies across Parasite Taxa

PubMed Central

Ruiz-López, María José; Monello, Ryan J.; Gompper, Matthew E.; Eggert, Lori S.

2012-01-01

Understanding factors that determine heterogeneity in levels of parasitism across individuals is a major challenge in disease ecology. It is known that genetic makeup plays an important role in infection likelihood, but the mechanism remains unclear as does its relative importance when compared to other factors. We analyzed relationships between genetic diversity and macroparasites in outbred, free-ranging populations of raccoons (Procyon lotor). We measured heterozygosity at 14 microsatellite loci and modeled the effects of both multi-locus and single-locus heterozygosity on parasitism using an information theoretic approach and including non-genetic factors that are known to influence the likelihood of parasitism. The association of genetic diversity and parasitism, as well as the relative importance of genetic diversity, differed by parasitic group. Endoparasite species richness was better predicted by a model that included genetic diversity, with the more heterozygous hosts harboring fewer endoparasite species. Genetic diversity was also important in predicting abundance of replete ticks (Dermacentor variabilis). This association fit a curvilinear trend, with hosts that had either high or low levels of heterozygosity harboring fewer parasites than those with intermediate levels. In contrast, genetic diversity was not important in predicting abundance of non-replete ticks and lice (Trichodectes octomaculatus). No strong single-locus effects were observed for either endoparasites or replete ticks. Our results suggest that in outbred populations multi-locus diversity might be important for coping with parasitism. The differences in the relationships between heterozygosity and parasitism for the different parasites suggest that the role of genetic diversity varies with parasite-mediated selective pressures. PMID:23049796

Discriminant analysis for predictor of falls in stroke patients by using the Berg Balance Scale.

PubMed

Maeda, Noriaki; Urabe, Yukio; Murakami, Masahito; Itotani, Keisuke; Kato, Junichi

2015-05-01

An observational study was carried out to estimate the strength of the relationships among balance, mobility and falls in hemiplegic stroke inpatients. The objective was to examine factors that may aid in the prediction of the likelihood of falls in stroke patients. A total of 53 stroke patients (30 male, 23 female) aged 67.0 ± 11.1 years were interviewed regarding their fall history. Physical performance was assessed using the Berg Balance Scale (BBS) and the Functional Independence Measure (FIM) scale. Variables that differed between fallers and non-fallers were identified, and a discriminant function analysis was carried out to determine the combination of variables that effectively predicted fall status. Of the 53 stroke patients, 19 were fallers. Compared with the non-fallers, the fallers scored low on the FIM, and differed with respect to age, time from stroke onset, length of hospital stay, Brunnstrom recovery stage and admission BBS score. Discriminant analysis for predicting falls in stroke patients showed that admission BBS score was significantly related to the likelihood of falls. Moreover, discriminant analysis showed that the use of a significant BBS score to classify fallers and non-fallers had an accuracy of 81.1%. The discriminating criterion between the two groups was a score of 31 points on the BBS. The results of this study suggest that BBS score is a strong predictor of falls in stroke patients. As balance is closely related to the risk of falls in hospitalised stroke patients, BBS might be useful in the prediction of falls.

Predicting Persistent Back Symptoms by Psychosocial Risk Factors: Validity Criteria for the ÖMPSQ and the HKF-R 10 in Germany.

PubMed

Riewe, E; Neubauer, E; Pfeifer, A C; Schiltenwolf, M

2016-01-01

10% of all individuals in Germany develop persistent symptoms due to nonspecific back pain (NSBP) causing up to 90% of direct and indirect expenses for health care systems. Evidence indicates a strong relationship between chronic nonspecific back pain and psychosocial risk factors. The Örebro Musculoskeletal Pain Screening Questionnaire (ÖMPSQ) and the German Heidelberger Kurzfragebogen Rückenschmerz (HKF-R 10) are deemed valid in prediction of persistent pain, functional loss or amount of sick leave. This study provides and discusses validity criteria for these questionnaires using ROC-curve analyses. Quality measurements included sensitivity and specificity, likelihood-ratio related test-efficiencies and clinical utility in regard to predictive values. 265 patients recruited from primary and secondary care units completed both questionnaires during the same timeframe. From the total, 133 patients returned a 6-month follow-up questionnaire to assess the validity criteria for outcomes of pain, function and sick leave. Based on heterogeneous cut-offs for the ÖMPSQ, sensitivity and specificity were moderate for outcome of pain (72%/75%). Very high sensitivity was observed for function (97%/57%) and high specificity for sick leave (63%/85%). The latter also applied to the HKF-R 10 (pain 50%/84%). Proportions between sensitivity and specificity were unbalanced except for the ÖMPSQ outcome of pain. Likelihood-ratios and positive predictive values ranged from low to moderate. Although the ÖMPSQ may be considered useful in identification of long-term functional loss or pain, over- and underestimation of patients at risk of chronic noncspecific back pain led to limited test-efficiencies and clinical utility for both questionnaires. Further studies are required to quantify the predictive validity of both questionnaires in Germany.

Improving and Evaluating Nested Sampling Algorithm for Marginal Likelihood Estimation

NASA Astrophysics Data System (ADS)

Ye, M.; Zeng, X.; Wu, J.; Wang, D.; Liu, J.

2016-12-01

With the growing impacts of climate change and human activities on the cycle of water resources, an increasing number of researches focus on the quantification of modeling uncertainty. Bayesian model averaging (BMA) provides a popular framework for quantifying conceptual model and parameter uncertainty. The ensemble prediction is generated by combining each plausible model's prediction, and each model is attached with a model weight which is determined by model's prior weight and marginal likelihood. Thus, the estimation of model's marginal likelihood is crucial for reliable and accurate BMA prediction. Nested sampling estimator (NSE) is a new proposed method for marginal likelihood estimation. The process of NSE is accomplished by searching the parameters' space from low likelihood area to high likelihood area gradually, and this evolution is finished iteratively via local sampling procedure. Thus, the efficiency of NSE is dominated by the strength of local sampling procedure. Currently, Metropolis-Hasting (M-H) algorithm is often used for local sampling. However, M-H is not an efficient sampling algorithm for high-dimensional or complicated parameter space. For improving the efficiency of NSE, it could be ideal to incorporate the robust and efficient sampling algorithm - DREAMzs into the local sampling of NSE. The comparison results demonstrated that the improved NSE could improve the efficiency of marginal likelihood estimation significantly. However, both improved and original NSEs suffer from heavy instability. In addition, the heavy computation cost of huge number of model executions is overcome by using an adaptive sparse grid surrogates.

Computationally derived rules for persistence of C60 nanowires on recumbent pentacene bilayers.

PubMed

Cantrell, Rebecca A; James, Christine; Clancy, Paulette

2011-08-16

The tendency for C(60) nanowires to persist on two monolayers of recumbent pentacene is studied using molecular dynamics (MD) simulations. A review of existing experimental literature for the tilt angle adopted by pentacene on noble metal surfaces shows that studies cover a limited range from 55° to 90°, motivating simulation studies of essentially the entire range of tilt angles (10°-90°) to predict the optimum surface tilt angle for C(60) nanowire formation. The persistence of a 1D nanowire depends sensitively on this tilt angle, the amount of initial tensile strain, and the presence of surface step edges. At room temperature, C(60) nanowires oriented along the pentacene short axes persist for several nanoseconds and are more likely to occur if they reside between, or within, pentacene rows for ϕ ≤ ∼60°. The likelihood of this persistence increases the smaller the tilt angle. Nanowires oriented along the long axes of pentacene molecules are unlikely to form. The limit of stability of nanowires was tested by raising the temperature to 400 K. Nanowires located between pentacene rows survived this temperature rise, but those located initially within pentacene rows are only stable in the range ϕ(1) = 30°-50°. Flatter pentacene surfaces, that is, tilt angles above about 60°, are subject to disorder caused by C(60) molecules "burrowing" into the pentacene surface. An initial strain of 5% applied to the C(60) nanowires significantly decreases the likelihood of nanowire persistence. In contrast, any appreciable surface roughness, even by half a monolayer in height of a third pentacene monolayer, strongly enhances the likelihood of nanowire formation due to the strong binding energy of C(60) molecules to step edges.

Predicting sun protection behaviors using protection motivation variables.

PubMed

Ch'ng, Joanne W M; Glendon, A Ian

2014-04-01

Protection motivation theory components were used to predict sun protection behaviors (SPBs) using four outcome measures: typical reported behaviors, previous reported behaviors, current sunscreen use as determined by interview, and current observed behaviors (clothing worn) to control for common method bias. Sampled from two SE Queensland public beaches during summer, 199 participants aged 18-29 years completed a questionnaire measuring perceived severity, perceived vulnerability, response efficacy, response costs, and protection motivation (PM). Personal perceived risk (similar to threat appraisal) and response likelihood (similar to coping appraisal) were derived from their respective PM components. Protection motivation predicted all four SPB criterion variables. Personal perceived risk and response likelihood predicted protection motivation. Protection motivation completely mediated the effect of response likelihood on all four criterion variables. Alternative models are considered. Strengths and limitations of the study are outlined and suggestions made for future research.

Does health insurance mitigate inequities in non-communicable disease treatment? Evidence from 48 low- and middle-income countries.

PubMed

El-Sayed, Abdulrahman M; Palma, Anton; Freedman, Lynn P; Kruk, Margaret E

2015-09-01

Non-communicable diseases (NCDs) are the greatest contributor to morbidity and mortality in low- and middle-income countries (LMICs). However, NCD care is limited in LMICs, particularly among the disadvantaged and rural. We explored the role of insurance in mitigating socioeconomic and urban-rural disparities in NCD treatment across 48 LMICs included in the 2002-2004 World Health Survey (WHS). We analyzed data about ever having received treatment for diagnosed high-burden NCDs (any diagnosis, angina, asthma, depression, arthritis, schizophrenia, or diabetes) or having sold or borrowed to pay for healthcare. We fit multivariable regression models of each outcome by the interaction between insurance coverage and household wealth (richest 20% vs. poorest 50%) and urbanicity, respectively. We found that insurance was associated with higher treatment likelihood for NCDs in LMICs, and helped mitigate socioeconomic and regional disparities in treatment likelihood. These influences were particularly strong among women. Insurance also predicted lower likelihood of borrowing or selling to pay for health services among the poorest women. Taken together, insurance coverage may serve as an important policy tool in promoting NCD treatment and in reducing inequities in NCD treatment by household wealth, urbanicity, and sex in LMICs. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Identifying habitats at risk: simple models can reveal complex ecosystem dynamics.

PubMed

Maxwell, Paul S; Pitt, Kylie A; Olds, Andrew D; Rissik, David; Connolly, Rod M

2015-03-01

The relationship between ecological impact and ecosystem structure is often strongly nonlinear, so that small increases in impact levels can cause a disproportionately large response in ecosystem structure. Nonlinear ecosystem responses can be difficult to predict because locally relevant data sets can be difficult or impossible to obtain. Bayesian networks (BN) are an emerging tool that can help managers to define ecosystem relationships using a range of data types from comprehensive quantitative data sets to expert opinion. We show how a simple BN can reveal nonlinear dynamics in seagrass ecosystems using ecological relationships sourced from the literature. We first developed a conceptual diagram by cataloguing the ecological responses of seagrasses to a range of drivers and impacts. We used the conceptual diagram to develop a BN populated with values sourced from published studies. We then applied the BN to show that the amount of initial seagrass biomass has a mitigating effect on the level of impact a meadow can withstand without loss, and that meadow recovery can often require disproportionately large improvements in impact levels. This mitigating effect resulted in the middle ranges of impact levels having a wide likelihood of seagrass presence, a situation known as bistability. Finally, we applied the model in a case study to identify the risk of loss and the likelihood of recovery for the conservation and management of seagrass meadows in Moreton Bay, Queensland, Australia. We used the model to predict the likelihood of bistability in 23 locations in the Bay. The model predicted bistability in seven locations, most of which have experienced seagrass loss at some stage in the past 25 years providing essential information for potential future restoration efforts. Our results demonstrate the capacity of simple, flexible modeling tools to facilitate collation and synthesis of disparate information. This approach can be adopted in the initial stages of conservation programs as a low-cost and relatively straightforward way to provide preliminary assessments of.nonlinear dynamics in ecosystems.

IS TREATMENT ADHERENCE CONSISTENT ACROSS TIME, ACROSS DIFFERENT TREATMENTS, AND ACROSS DIAGNOSES?

PubMed Central

Simon, Gregory E; Peterson, Do; Hubbard, Rebecca

2012-01-01

Objective Examine consistency of adherence across depression treatments and consistency of adherence between depression treatments and treatments for chronic medical illness. Methods For 25,456 health plan members beginning psychotherapy for depression between 2003 and 2008, health plan records were used to examine adherence to all episodes of psychotherapy, antidepressant medication, antihypertensive medication, and lipid-lowering medication. Results Within treatments, adherence to psychotherapy in one episode predicted approximately 20% greater likelihood of subsequent psychotherapy adherence (OR 2.20, 95% CI 1.83 to 2.64). Similarly, adherence to antidepressant medication in one episode predicted approximately 20% greater likelihood of subsequent antidepressant adherence (OR 1.99, 95% CI 1.74 to 2.28). Across treatments, adherence to antidepressant medication predicted approximately 10% greater likelihood of concurrent or subsequent adherence to psychotherapy (OR 1.52, 95% CI 1.42 to 1.63), a 4% greater likelihood of adherence to antihypertensive medication (OR 1.24, 95% CI 1.14 to 1.37) and a 3% greater likelihood of adherence to lipid-lowering medication (OR 1.16, 95% CI 1.03 to 1.32). Adherence to psychotherapy predicted a 2% greater likelihood of concurrent or subsequent adherence to antihypertensive medication (OR 1.11, 95% CI 1.04 to 1.19) and was not a significant predictor of adherence to lipid-lowering medication (OR 0.99, 95% CI 0.90 to 1.18). Conclusions Adherence is moderately consistent across episodes of depression treatment. Depression treatment adherence is a statistically significant, but relatively weak, predictor of adherence to antihypertensive or lipid-lowering medication. PMID:23141589

Rational selection of experimental readout and intervention sites for reducing uncertainties in computational model predictions.

PubMed

Flassig, Robert J; Migal, Iryna; der Zalm, Esther van; Rihko-Struckmann, Liisa; Sundmacher, Kai

2015-01-16

Understanding the dynamics of biological processes can substantially be supported by computational models in the form of nonlinear ordinary differential equations (ODE). Typically, this model class contains many unknown parameters, which are estimated from inadequate and noisy data. Depending on the ODE structure, predictions based on unmeasured states and associated parameters are highly uncertain, even undetermined. For given data, profile likelihood analysis has been proven to be one of the most practically relevant approaches for analyzing the identifiability of an ODE structure, and thus model predictions. In case of highly uncertain or non-identifiable parameters, rational experimental design based on various approaches has shown to significantly reduce parameter uncertainties with minimal amount of effort. In this work we illustrate how to use profile likelihood samples for quantifying the individual contribution of parameter uncertainty to prediction uncertainty. For the uncertainty quantification we introduce the profile likelihood sensitivity (PLS) index. Additionally, for the case of several uncertain parameters, we introduce the PLS entropy to quantify individual contributions to the overall prediction uncertainty. We show how to use these two criteria as an experimental design objective for selecting new, informative readouts in combination with intervention site identification. The characteristics of the proposed multi-criterion objective are illustrated with an in silico example. We further illustrate how an existing practically non-identifiable model for the chlorophyll fluorescence induction in a photosynthetic organism, D. salina, can be rendered identifiable by additional experiments with new readouts. Having data and profile likelihood samples at hand, the here proposed uncertainty quantification based on prediction samples from the profile likelihood provides a simple way for determining individual contributions of parameter uncertainties to uncertainties in model predictions. The uncertainty quantification of specific model predictions allows identifying regions, where model predictions have to be considered with care. Such uncertain regions can be used for a rational experimental design to render initially highly uncertain model predictions into certainty. Finally, our uncertainty quantification directly accounts for parameter interdependencies and parameter sensitivities of the specific prediction.

A Game Theoretical Approach to Hacktivism: Is Attack Likelihood a Product of Risks and Payoffs?

PubMed

Bodford, Jessica E; Kwan, Virginia S Y

2018-02-01

The current study examines hacktivism (i.e., hacking to convey a moral, ethical, or social justice message) through a general game theoretic framework-that is, as a product of costs and benefits. Given the inherent risk of carrying out a hacktivist attack (e.g., legal action, imprisonment), it would be rational for the user to weigh these risks against perceived benefits of carrying out the attack. As such, we examined computer science students' estimations of risks, payoffs, and attack likelihood through a game theoretic design. Furthermore, this study aims at constructing a descriptive profile of potential hacktivists, exploring two predicted covariates of attack decision making, namely, peer prevalence of hacking and sex differences. Contrary to expectations, results suggest that participants' estimations of attack likelihood stemmed solely from expected payoffs, rather than subjective risks. Peer prevalence significantly predicted increased payoffs and attack likelihood, suggesting an underlying descriptive norm in social networks. Notably, we observed no sex differences in the decision to attack, nor in the factors predicting attack likelihood. Implications for policymakers and the understanding and prevention of hacktivism are discussed, as are the possible ramifications of widely communicated payoffs over potential risks in hacking communities.

Conflict effects without conflict in anterior cingulate cortex: multiple response effects and context specific representations

PubMed Central

Brown, Joshua W.

2009-01-01

The error likelihood computational model of anterior cingulate cortex (ACC) (Brown & Braver, 2005) has successfully predicted error likelihood effects, risk prediction effects, and how individual differences in conflict and error likelihood effects vary with trait differences in risk aversion. The same computational model now makes a further prediction that apparent conflict effects in ACC may result in part from an increasing number of simultaneously active responses, regardless of whether or not the cued responses are mutually incompatible. In Experiment 1, the model prediction was tested with a modification of the Eriksen flanker task, in which some task conditions require two otherwise mutually incompatible responses to be generated simultaneously. In that case, the two response processes are no longer in conflict with each other. The results showed small but significant medial PFC effects in the incongruent vs. congruent contrast, despite the absence of response conflict, consistent with model predictions. This is the multiple response effect. Nonetheless, actual response conflict led to greater ACC activation, suggesting that conflict effects are specific to particular task contexts. In Experiment 2, results from a change signal task suggested that the context dependence of conflict signals does not depend on error likelihood effects. Instead, inputs to ACC may reflect complex and task specific representations of motor acts, such as bimanual responses. Overall, the results suggest the existence of a richer set of motor signals monitored by medial PFC and are consistent with distinct effects of multiple responses, conflict, and error likelihood in medial PFC. PMID:19375509

Likelihood-based gene annotations for gap filling and quality assessment in genome-scale metabolic models

DOE PAGES

Benedict, Matthew N.; Mundy, Michael B.; Henry, Christopher S.; ...

2014-10-16

Genome-scale metabolic models provide a powerful means to harness information from genomes to deepen biological insights. With exponentially increasing sequencing capacity, there is an enormous need for automated reconstruction techniques that can provide more accurate models in a short time frame. Current methods for automated metabolic network reconstruction rely on gene and reaction annotations to build draft metabolic networks and algorithms to fill gaps in these networks. However, automated reconstruction is hampered by database inconsistencies, incorrect annotations, and gap filling largely without considering genomic information. Here we develop an approach for applying genomic information to predict alternative functions for genesmore » and estimate their likelihoods from sequence homology. We show that computed likelihood values were significantly higher for annotations found in manually curated metabolic networks than those that were not. We then apply these alternative functional predictions to estimate reaction likelihoods, which are used in a new gap filling approach called likelihood-based gap filling to predict more genomically consistent solutions. To validate the likelihood-based gap filling approach, we applied it to models where essential pathways were removed, finding that likelihood-based gap filling identified more biologically relevant solutions than parsimony-based gap filling approaches. We also demonstrate that models gap filled using likelihood-based gap filling provide greater coverage and genomic consistency with metabolic gene functions compared to parsimony-based approaches. Interestingly, despite these findings, we found that likelihoods did not significantly affect consistency of gap filled models with Biolog and knockout lethality data. This indicates that the phenotype data alone cannot necessarily be used to discriminate between alternative solutions for gap filling and therefore, that the use of other information is necessary to obtain a more accurate network. All described workflows are implemented as part of the DOE Systems Biology Knowledgebase (KBase) and are publicly available via API or command-line web interface.« less

Likelihood-Based Gene Annotations for Gap Filling and Quality Assessment in Genome-Scale Metabolic Models

PubMed Central

Benedict, Matthew N.; Mundy, Michael B.; Henry, Christopher S.; Chia, Nicholas; Price, Nathan D.

2014-01-01

Genome-scale metabolic models provide a powerful means to harness information from genomes to deepen biological insights. With exponentially increasing sequencing capacity, there is an enormous need for automated reconstruction techniques that can provide more accurate models in a short time frame. Current methods for automated metabolic network reconstruction rely on gene and reaction annotations to build draft metabolic networks and algorithms to fill gaps in these networks. However, automated reconstruction is hampered by database inconsistencies, incorrect annotations, and gap filling largely without considering genomic information. Here we develop an approach for applying genomic information to predict alternative functions for genes and estimate their likelihoods from sequence homology. We show that computed likelihood values were significantly higher for annotations found in manually curated metabolic networks than those that were not. We then apply these alternative functional predictions to estimate reaction likelihoods, which are used in a new gap filling approach called likelihood-based gap filling to predict more genomically consistent solutions. To validate the likelihood-based gap filling approach, we applied it to models where essential pathways were removed, finding that likelihood-based gap filling identified more biologically relevant solutions than parsimony-based gap filling approaches. We also demonstrate that models gap filled using likelihood-based gap filling provide greater coverage and genomic consistency with metabolic gene functions compared to parsimony-based approaches. Interestingly, despite these findings, we found that likelihoods did not significantly affect consistency of gap filled models with Biolog and knockout lethality data. This indicates that the phenotype data alone cannot necessarily be used to discriminate between alternative solutions for gap filling and therefore, that the use of other information is necessary to obtain a more accurate network. All described workflows are implemented as part of the DOE Systems Biology Knowledgebase (KBase) and are publicly available via API or command-line web interface. PMID:25329157

How much to trust the senses: Likelihood learning

PubMed Central

Sato, Yoshiyuki; Kording, Konrad P.

2014-01-01

Our brain often needs to estimate unknown variables from imperfect information. Our knowledge about the statistical distributions of quantities in our environment (called priors) and currently available information from sensory inputs (called likelihood) are the basis of all Bayesian models of perception and action. While we know that priors are learned, most studies of prior-likelihood integration simply assume that subjects know about the likelihood. However, as the quality of sensory inputs change over time, we also need to learn about new likelihoods. Here, we show that human subjects readily learn the distribution of visual cues (likelihood function) in a way that can be predicted by models of statistically optimal learning. Using a likelihood that depended on color context, we found that a learned likelihood generalized to new priors. Thus, we conclude that subjects learn about likelihood. PMID:25398975

Infertility Evaluation and Treatment among Women in the United States

PubMed Central

Kessler, Lawrence M.; Craig, Benjamin M.; Plosker, Shayne M.; Reed, Damon R.; Quinn, Gwendolyn P.

2013-01-01

Objective To examine the characteristics of women seeking infertility evaluation and treatment. Design Cross-sectional survey based on in-person interviews, followed by two-step hurdle analysis. Participants 4,558 married or cohabitating women ages 25–44 Setting U.S. household population of women based on the 2006–2010 National Survey of Family Growth Intervention None Main Outcome Measure(s) Likelihood of seeking preliminary infertility evaluation. Likelihood of seeking infertility treatment once evaluated. Treatment type provided. Results 623 women (13.7%) reported seeking infertility evaluation, of which 328 reported undergoing subsequent infertility treatment. Age at marriage, marital status, education, health insurance status, race/ethnicity, and religion were associated with the likelihood of seeking infertility evaluation. For example, the predicted probability that a non-White woman who married at 25 will seek evaluation was 12%. This probability increased to 34% for White women with a graduate degree who married at age 30. Among women who are evaluated, income, employment status, and ethnicity correlated strongly with the likelihood of seeking infertility treatment. Infertility drug therapy was the most frequent treatment used. Reproductive surgery and in vitro fertilization (IVF) were used the least. Conclusions The use of infertility services is not random and understanding the socio-demographic factors correlated with use may assist new couples with family planning. Roughly 50% of the women evaluated for infertility progressed to treatment, and only a small proportion were treated with more advanced assisted reproductive technologies (ARTs) such as IVF therapy. Future research aimed at improving access to effective healthcare treatments within the boundaries of affordability is warranted. PMID:23849845

The risk of developing cardiovascular disease in Bangladesh: does diabetes mellitus matter? Which socioeconomic status does it impact? A cross sectional study.

PubMed

Islam, G M Rabiul

2017-01-01

The elevation of blood pressure levels has been recognized as a determinant of the risk for several common cardiovascular diseases. This work explores the evidence of disparities in the form of association between hypertension and diabetes mellitus in different socioeconomic statuses (SESs) at household level. A population sample of 7561 individuals aged ≥35 years from the 2011 Bangladesh Demographic Health Survey (BDHS) was used for this study. Concentration indexes are used to measure the disparities of myocardial infarction and diabetes mellitus with SES. A two-level hierarchical logit model was used to examine the effects of participants and household SES accompanied by other explanatory variables on having hypertension. Then, the analysis is stratified by SES groups to examine how the overall effect of diabetes mellitus on hypertension may vary with SES. Finally, predictive margins are determined to understand the predictive probability of diabetes and SES of having hypertension as a risk factor of developing cardiovascular disease. The descriptive summary measures of SES inequality indicate that prevalence of hypertension and diabetes was higher among high SES. The multivariate analysis covering all samples reveals that there is a strong association between diabetes and hypertension (P < .01). Likewise, after stratifying, it is evident that in high SES, there is a strong association between individuals with diabetes mellitus and hypertension development; they have around four-fold higher chance of being affected by hypertension in comparison to individuals with normal fasting plasma glucose (P < .01). Moreover, there are strong associations between individuals in low and medium SESs having diabetes and having hypertension (P < .01); the likelihood of having hypertension is almost double compared to individuals who have no diabetes. The result of this study also shed light on the chance of an increase in prevalence of hypertension in prediabetes individuals and in medium and high SES groups, although the association is statistically insignificant (P > .05). Finally, the predictive analysis reveals that the predictive margin of having hypertension is high among individuals belonging to the high SES (23%; CI, 20-23) and diabetic patients with high SES (37%; CI, 33-47). Contrary to other developed countries, hypertension in Bangladesh is prevalent among all SES, and the likelihood is high among diabetic patients in the medium and high SES. Hence, urgent preventive measures are needed to control the impending comorbidity of diabetes and developing cardiovascular disease risk. Copyright © 2016 American Society of Hypertension. Published by Elsevier Inc. All rights reserved.

CT Texture Analysis of Ex Vivo Renal Stones Predicts Ease of Fragmentation with Shockwave Lithotripsy.

PubMed

Cui, Helen W; Devlies, Wout; Ravenscroft, Samuel; Heers, Hendrik; Freidin, Andrew J; Cleveland, Robin O; Ganeshan, Balaji; Turney, Benjamin W

2017-07-01

Understanding the factors affecting success of extracorporeal shockwave lithotripsy (SWL) would improve informed decision-making on the most appropriate treatment modality for an individual patient. Although stone size and skin-to-stone distance do correlate with fragmentation efficacy, it has been shown that stone composition and architecture, as reflected by structural heterogeneity on CT, are also important factors. This study aims to determine if CT texture analysis (CTTA), a novel, nondestructive, and objective tool that generates statistical metrics reflecting stone heterogeneity, could have utility in predicting likelihood of SWL success. Seven spontaneously passed, intact renal tract stones, were scanned ex vivo using standard CT KUB and micro-CT. The stones were then fragmented in vitro using a clinical lithotripter, after which, chemical composition analysis was performed. CTTA was used to generate a number of metrics that were correlated to the number of shocks needed to fragment the stone. CTTA metrics reflected stone characteristics and composition, and predicted ease of SWL fragmentation. The strongest correlation with number of shocks required to fragment the stone was mean Hounsfield unit (HU) density (r = 0.806, p = 0.028) and a CTTA metric measuring the entropy of the pixel distribution of the stone image (r = 0.804, p = 0.039). Using multiple linear regression analysis, the best model showed that CTTA metrics of entropy and kurtosis could predict 92% of the outcome of number of shocks needed to fragment the stone. This was superior to using stone volume or density. CTTA metrics entropy and kurtosis have been shown in this experimental ex vivo setting to strongly predict fragmentation by SWL. This warrants further investigation in a larger clinical study for the contribution of CT textural metrics as a measure of stone heterogeneity, along with other known clinical factors, to predict likelihood of SWL success.

Updated logistic regression equations for the calculation of post-fire debris-flow likelihood in the western United States

USGS Publications Warehouse

Staley, Dennis M.; Negri, Jacquelyn A.; Kean, Jason W.; Laber, Jayme L.; Tillery, Anne C.; Youberg, Ann M.

2016-06-30

Wildfire can significantly alter the hydrologic response of a watershed to the extent that even modest rainstorms can generate dangerous flash floods and debris flows. To reduce public exposure to hazard, the U.S. Geological Survey produces post-fire debris-flow hazard assessments for select fires in the western United States. We use publicly available geospatial data describing basin morphology, burn severity, soil properties, and rainfall characteristics to estimate the statistical likelihood that debris flows will occur in response to a storm of a given rainfall intensity. Using an empirical database and refined geospatial analysis methods, we defined new equations for the prediction of debris-flow likelihood using logistic regression methods. We showed that the new logistic regression model outperformed previous models used to predict debris-flow likelihood.

I Do…Do You? Dependence and Biological Sex Moderate Daters’ Cortisol Responses When Accommodating a Partner’s Thoughts about Marriage

PubMed Central

Schoenfeld, Elizabeth A.; Loving, Timothy J.

2012-01-01

We examined how daters’ levels of relationship dependence interact with men’s and women’s degree of accommodation during a likelihood of marriage discussion to predict cortisol levels at the conclusion of the discussion. Upon arriving at the laboratory, couple members were separated and asked to graph their perceived likelihood of one day marrying each other. Couples were reunited and instructed to create a joint graph depicting their agreed-upon chance of marriage. For the majority of couples, negotiating their likelihood of marriage required one or both partners to accommodate each other’s presumed likelihood of marriage. Multilevel analyses revealed a significant Dependence x Accommodation x Sex interaction. For women who increased their likelihood of marriage, feelings of dependence predicted heightened levels of cortisol relative to baseline; we suggest such a response is indicative of eustress. Among men, those who accommodated by decreasing their likelihood of marriage experienced significantly lower levels of cortisol to the extent they were less dependent on their partners. Discussion focuses on why men and women show different physiological reactions in response to seemingly favorable outcomes from a relationship discussion. PMID:22801249

I do…do you? Dependence and biological sex moderate daters' cortisol responses when accommodating a partner's thoughts about marriage.

PubMed

Schoenfeld, Elizabeth A; Loving, Timothy J

2013-06-01

We examined how daters' levels of relationship dependence interact with men's and women's degree of accommodation during a likelihood of marriage discussion to predict cortisol levels at the conclusion of the discussion. Upon arriving at the laboratory, couple members were separated and asked to graph their perceived likelihood of one day marrying each other. Couples were reunited and instructed to create a joint graph depicting their agreed-upon chance of marriage. For the majority of couples, negotiating their likelihood of marriage required one or both partners to accommodate each other's presumed likelihood of marriage. Multilevel analyses revealed a significant Dependence×Accommodation×Sex interaction. For women who increased their likelihood of marriage, feelings of dependence predicted heightened levels of cortisol relative to baseline; we suggest such a response is indicative of eustress. Among men, those who accommodated by decreasing their likelihood of marriage experienced significantly lower levels of cortisol to the extent that they were less dependent on their partners. Discussion focuses on why men and women show different physiological reactions in response to seemingly favorable outcomes from a relationship discussion. Copyright © 2012 Elsevier B.V. All rights reserved.

Imposing constraints on parameter values of a conceptual hydrological model using baseflow response

NASA Astrophysics Data System (ADS)

Dunn, S. M.

Calibration of conceptual hydrological models is frequently limited by a lack of data about the area that is being studied. The result is that a broad range of parameter values can be identified that will give an equally good calibration to the available observations, usually of stream flow. The use of total stream flow can bias analyses towards interpretation of rapid runoff, whereas water quality issues are more frequently associated with low flow condition. This paper demonstrates how model distinctions between surface an sub-surface runoff can be used to define a likelihood measure based on the sub-surface (or baseflow) response. This helps to provide more information about the model behaviour, constrain the acceptable parameter sets and reduce uncertainty in streamflow prediction. A conceptual model, DIY, is applied to two contrasting catchments in Scotland, the Ythan and the Carron Valley. Parameter ranges and envelopes of prediction are identified using criteria based on total flow efficiency, baseflow efficiency and combined efficiencies. The individual parameter ranges derived using the combined efficiency measures still cover relatively wide bands, but are better constrained for the Carron than the Ythan. This reflects the fact that hydrological behaviour in the Carron is dominated by a much flashier surface response than in the Ythan. Hence, the total flow efficiency is more strongly controlled by surface runoff in the Carron and there is a greater contrast with the baseflow efficiency. Comparisons of the predictions using different efficiency measures for the Ythan also suggest that there is a danger of confusing parameter uncertainties with data and model error, if inadequate likelihood measures are defined.

Separation in Logistic Regression: Causes, Consequences, and Control.

PubMed

Mansournia, Mohammad Ali; Geroldinger, Angelika; Greenland, Sander; Heinze, Georg

2018-04-01

Separation is encountered in regression models with a discrete outcome (such as logistic regression) where the covariates perfectly predict the outcome. It is most frequent under the same conditions that lead to small-sample and sparse-data bias, such as presence of a rare outcome, rare exposures, highly correlated covariates, or covariates with strong effects. In theory, separation will produce infinite estimates for some coefficients. In practice, however, separation may be unnoticed or mishandled because of software limits in recognizing and handling the problem and in notifying the user. We discuss causes of separation in logistic regression and describe how common software packages deal with it. We then describe methods that remove separation, focusing on the same penalized-likelihood techniques used to address more general sparse-data problems. These methods improve accuracy, avoid software problems, and allow interpretation as Bayesian analyses with weakly informative priors. We discuss likelihood penalties, including some that can be implemented easily with any software package, and their relative advantages and disadvantages. We provide an illustration of ideas and methods using data from a case-control study of contraceptive practices and urinary tract infection.

A maximum likelihood convolutional decoder model vs experimental data comparison

NASA Technical Reports Server (NTRS)

Chen, R. Y.

1979-01-01

This article describes the comparison of a maximum likelihood convolutional decoder (MCD) prediction model and the actual performance of the MCD at the Madrid Deep Space Station. The MCD prediction model is used to develop a subroutine that has been utilized by the Telemetry Analysis Program (TAP) to compute the MCD bit error rate for a given signal-to-noise ratio. The results indicate that that the TAP can predict quite well compared to the experimental measurements. An optimal modulation index also can be found through TAP.

Wald Sequential Probability Ratio Test for Analysis of Orbital Conjunction Data

NASA Technical Reports Server (NTRS)

Carpenter, J. Russell; Markley, F. Landis; Gold, Dara

2013-01-01

We propose a Wald Sequential Probability Ratio Test for analysis of commonly available predictions associated with spacecraft conjunctions. Such predictions generally consist of a relative state and relative state error covariance at the time of closest approach, under the assumption that prediction errors are Gaussian. We show that under these circumstances, the likelihood ratio of the Wald test reduces to an especially simple form, involving the current best estimate of collision probability, and a similar estimate of collision probability that is based on prior assumptions about the likelihood of collision.

Lack of racial and sex stereotypes in the prediction of completed suicide.

PubMed

Redd, Charlitta S; Lester, David

2013-12-01

A sample of 252 college students was presented with vignettes and asked to predict the likelihood that the protagonist in each vignette would complete suicide. The crisis confronting the protagonist significantly affected judgments of the likelihood of completed suicide, but neither the race nor the sex of the protagonist affected this judgment, suggesting that sex and racial stereotypes about who completes suicide may no longer exist.

Can 3-dimensional power Doppler indices improve the prenatal diagnosis of a potentially morbidly adherent placenta in patients with placenta previa?

PubMed

Haidar, Ziad A; Papanna, Ramesha; Sibai, Baha M; Tatevian, Nina; Viteri, Oscar A; Vowels, Patricia C; Blackwell, Sean C; Moise, Kenneth J

2017-08-01

Traditionally, 2-dimensional ultrasound parameters have been used for the diagnosis of a suspected morbidly adherent placenta previa. More objective techniques have not been well studied yet. The objective of the study was to determine the ability of prenatal 3-dimensional power Doppler analysis of flow and vascular indices to predict the morbidly adherent placenta objectively. A prospective cohort study was performed in women between 28 and 32 gestational weeks with known placenta previa. Patients underwent a two-dimensional gray-scale ultrasound that determined management decisions. 3-Dimensional power Doppler volumes were obtained during the same examination and vascular, flow, and vascular flow indices were calculated after manual tracing of the viewed placenta in the sweep; data were blinded to obstetricians. Morbidly adherent placenta was confirmed by histology. Severe morbidly adherent placenta was defined as increta/percreta on histology, blood loss >2000 mL, and >2 units of PRBC transfused. Sensitivities, specificities, predictive values, and likelihood ratios were calculated. Student t and χ 2 tests, logistic regression, receiver-operating characteristic curves, and intra- and interrater agreements using Kappa statistics were performed. The following results were found: (1) 50 women were studied: 23 had morbidly adherent placenta, of which 12 (52.2%) were severe morbidly adherent placenta; (2) 2-dimensional parameters diagnosed morbidly adherent placenta with a sensitivity of 82.6% (95% confidence interval, 60.4-94.2), a specificity of 88.9% (95% confidence interval, 69.7-97.1), a positive predictive value of 86.3% (95% confidence interval, 64.0-96.4), a negative predictive value of 85.7% (95% confidence interval, 66.4-95.3), a positive likelihood ratio of 7.4 (95% confidence interval, 2.5-21.9), and a negative likelihood ratio of 0.2 (95% confidence interval, 0.08-0.48); (3) mean values of the vascular index (32.8 ± 7.4) and the vascular flow index (14.2 ± 3.8) were higher in morbidly adherent placenta (P < .001); (4) area under the receiver-operating characteristic curve for the vascular and vascular flow indices were 0.99 and 0.97, respectively; (5) the vascular index ≥21 predicted morbidly adherent placenta with a sensitivity and a specificity of 95% (95% confidence interval, 88.2-96.9) and 91%, respectively (95% confidence interval, 87.5-92.4), 92% positive predictive value (95% confidence interval, 85.5-94.3), 90% negative predictive value (95% confidence interval, 79.9-95.3), positive likelihood ratio of 10.55 (95% confidence interval, 7.06-12.75), and negative likelihood ratio of 0.05 (95% confidence interval, 0.03-0.13); and (6) for the severe morbidly adherent placenta, 2-dimensional ultrasound had a sensitivity of 33.3% (95% confidence interval, 11.3-64.6), a specificity of 81.8% (95% confidence interval, 47.8-96.8), a positive predictive value of 66.7% (95% confidence interval, 24.1-94.1), a negative predictive value of 52.9% (95% confidence interval, 28.5-76.1), a positive likelihood ratio of 1.83 (95% confidence interval, 0.41-8.11), and a negative likelihood ratio of 0.81 (95% confidence interval, 0.52-1.26). A vascular index ≥31 predicted the diagnosis of a severe morbidly adherent placenta with a 100% sensitivity (95% confidence interval, 72-100), a 90% specificity (95% confidence interval, 81.7-93.8), an 88% positive predictive value (95% confidence interval, 55.0-91.3), a 100% negative predictive value (95% confidence interval, 90.9-100), a positive likelihood ratio of 10.0 (95% confidence interval, 3.93-16.13), and a negative likelihood ratio of 0 (95% confidence interval, 0-0.34). Intrarater and interrater agreements were 94% (P < .001) and 93% (P < .001), respectively. The vascular index accurately predicts the morbidly adherent placenta in patients with placenta previa. In addition, 3-dimensional power Doppler vascular and vascular flow indices were more predictive of severe cases of morbidly adherent placenta compared with 2-dimensional ultrasound. This objective technique may limit the variations in diagnosing morbidly adherent placenta because of the subjectivity of 2-dimensional ultrasound interpretations. Copyright © 2017 Elsevier Inc. All rights reserved.

Gaussian copula as a likelihood function for environmental models

NASA Astrophysics Data System (ADS)

Wani, O.; Espadas, G.; Cecinati, F.; Rieckermann, J.

2017-12-01

Parameter estimation of environmental models always comes with uncertainty. To formally quantify this parametric uncertainty, a likelihood function needs to be formulated, which is defined as the probability of observations given fixed values of the parameter set. A likelihood function allows us to infer parameter values from observations using Bayes' theorem. The challenge is to formulate a likelihood function that reliably describes the error generating processes which lead to the observed monitoring data, such as rainfall and runoff. If the likelihood function is not representative of the error statistics, the parameter inference will give biased parameter values. Several uncertainty estimation methods that are currently being used employ Gaussian processes as a likelihood function, because of their favourable analytical properties. Box-Cox transformation is suggested to deal with non-symmetric and heteroscedastic errors e.g. for flow data which are typically more uncertain in high flows than in periods with low flows. Problem with transformations is that the results are conditional on hyper-parameters, for which it is difficult to formulate the analyst's belief a priori. In an attempt to address this problem, in this research work we suggest learning the nature of the error distribution from the errors made by the model in the "past" forecasts. We use a Gaussian copula to generate semiparametric error distributions . 1) We show that this copula can be then used as a likelihood function to infer parameters, breaking away from the practice of using multivariate normal distributions. Based on the results from a didactical example of predicting rainfall runoff, 2) we demonstrate that the copula captures the predictive uncertainty of the model. 3) Finally, we find that the properties of autocorrelation and heteroscedasticity of errors are captured well by the copula, eliminating the need to use transforms. In summary, our findings suggest that copulas are an interesting departure from the usage of fully parametric distributions as likelihood functions - and they could help us to better capture the statistical properties of errors and make more reliable predictions.

Assessing performance and validating finite element simulations using probabilistic knowledge

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

Dolin, Ronald M.; Rodriguez, E. A.

Two probabilistic approaches for assessing performance are presented. The first approach assesses probability of failure by simultaneously modeling all likely events. The probability each event causes failure along with the event's likelihood of occurrence contribute to the overall probability of failure. The second assessment method is based on stochastic sampling using an influence diagram. Latin-hypercube sampling is used to stochastically assess events. The overall probability of failure is taken as the maximum probability of failure of all the events. The Likelihood of Occurrence simulation suggests failure does not occur while the Stochastic Sampling approach predicts failure. The Likelihood of Occurrencemore » results are used to validate finite element predictions.« less

Predicting Rotator Cuff Tears Using Data Mining and Bayesian Likelihood Ratios

PubMed Central

Lu, Hsueh-Yi; Huang, Chen-Yuan; Su, Chwen-Tzeng; Lin, Chen-Chiang

2014-01-01

Objectives Rotator cuff tear is a common cause of shoulder diseases. Correct diagnosis of rotator cuff tears can save patients from further invasive, costly and painful tests. This study used predictive data mining and Bayesian theory to improve the accuracy of diagnosing rotator cuff tears by clinical examination alone. Methods In this retrospective study, 169 patients who had a preliminary diagnosis of rotator cuff tear on the basis of clinical evaluation followed by confirmatory MRI between 2007 and 2011 were identified. MRI was used as a reference standard to classify rotator cuff tears. The predictor variable was the clinical assessment results, which consisted of 16 attributes. This study employed 2 data mining methods (ANN and the decision tree) and a statistical method (logistic regression) to classify the rotator cuff diagnosis into “tear” and “no tear” groups. Likelihood ratio and Bayesian theory were applied to estimate the probability of rotator cuff tears based on the results of the prediction models. Results Our proposed data mining procedures outperformed the classic statistical method. The correction rate, sensitivity, specificity and area under the ROC curve of predicting a rotator cuff tear were statistical better in the ANN and decision tree models compared to logistic regression. Based on likelihood ratios derived from our prediction models, Fagan's nomogram could be constructed to assess the probability of a patient who has a rotator cuff tear using a pretest probability and a prediction result (tear or no tear). Conclusions Our predictive data mining models, combined with likelihood ratios and Bayesian theory, appear to be good tools to classify rotator cuff tears as well as determine the probability of the presence of the disease to enhance diagnostic decision making for rotator cuff tears. PMID:24733553

Macaques can predict social outcomes from facial expressions.

PubMed

Waller, Bridget M; Whitehouse, Jamie; Micheletta, Jérôme

2016-09-01

There is widespread acceptance that facial expressions are useful in social interactions, but empirical demonstration of their adaptive function has remained elusive. Here, we investigated whether macaques can use the facial expressions of others to predict the future outcomes of social interaction. Crested macaques (Macaca nigra) were shown an approach between two unknown individuals on a touchscreen and were required to choose between one of two potential social outcomes. The facial expressions of the actors were manipulated in the last frame of the video. One subject reached the experimental stage and accurately predicted different social outcomes depending on which facial expressions the actors displayed. The bared-teeth display (homologue of the human smile) was most strongly associated with predicted friendly outcomes. Contrary to our predictions, screams and threat faces were not associated more with conflict outcomes. Overall, therefore, the presence of any facial expression (compared to neutral) caused the subject to choose friendly outcomes more than negative outcomes. Facial expression in general, therefore, indicated a reduced likelihood of social conflict. The findings dispute traditional theories that view expressions only as indicators of present emotion and instead suggest that expressions form part of complex social interactions where individuals think beyond the present.

Factors influencing healthy eating habits among college students: an application of the health belief model.

PubMed

Deshpande, Sameer; Basil, Michael D; Basil, Debra Z

2009-01-01

Poor eating habits are an important public health issue that has large health and economic implications. Many food preferences are established early, but because people make more and more independent eating decisions as they move through adolescence, the transition to independent living during the university days is an important event. To study the phenomenon of food selection, the heath belief model was applied to predict the likelihood of healthy eating among university students. Structural equation modeling was used to investigate the validity of the health belief model (HBM) among 194 students, followed by gender-based analyses. The data strongly supported the HBM. Social change campaign implications are discussed.

MR Enterography of the Ileoanal Pouch: Descriptive Radiologic Analysis With Endoscopic and Pathologic Correlation.

PubMed

Sahi, Kamaldeep Singh; Lee, Karen S; Moss, Alan; Yee, Eric; Allard, Felicia; Brook, Alexander; Mortele, Koenraad J

2015-11-01

The purpose of this study was to describe the MR enterography (MRE) appearance of inflammation of the ileoanal pouch after ileal pouch-anal anastomosis (IPAA) surgery and to correlate it with pouch endoscopic and histopathologic findings. All MRE studies performed between October 1, 2007, and September 30, 2013, for patients who had previously undergone IPAA (n = 54) were retrieved. After review of medical records, the patients who underwent MRE, pouch endoscopy, and biopsy within 90 days (14 men, 14 women; mean age, 42.2 years; range, 24-67 years) were selected for inclusion in the study. Two blinded MRI radiologists in consensus retrospectively evaluated MRE studies for multiple MRI features. Two MRI scores were then calculated: an active and a composite inflammation score. A gastroenterologist retrospectively reviewed the pouch endoscopic images, and a pathologist reviewed the slides; both of these investigators were blinded. Both MRI scores were correlated with the pouch endoscopic and histopathologic findings. The composite MRI score had strong positive correlation with the endoscopic score (r = 0.61; p = 0.0005) but weak positive correlation with the histopathologic score (r = 0.31; p = 0.10, not statistically significant). The active inflammation MRI score had moderate positive correlation with the endoscopic score (r = 0.57; p = 0.0017) and weak positive correlation with the histopathologic score (r = 0.20; p = 0.31, not statistically significant). An MRI score ≥ 4 indicated the best results, with sensitivity of 86%, specificity of 79%, positive predictive value of 80%, negative predictive value of 85%, and accuracy of 82% for pouch inflammation. A positive likelihood ratio of 4.00 and negative likelihood ratio of 0.18 were obtained. In patients who have undergone IPAA surgery, the MRE findings strongly correlate with the pouch endoscopic findings with high sensitivity and positive predictive value for pouch inflammation. Therefore, MRE is a useful noninvasive test performed without ionizing radiation that can be used to evaluate patients with clinical symptoms and possibly alleviate the need for endoscopy in a select patient population.

The numerical evaluation of maximum-likelihood estimates of the parameters for a mixture of normal distributions from partially identified samples

NASA Technical Reports Server (NTRS)

Walker, H. F.

1976-01-01

Likelihood equations determined by the two types of samples which are necessary conditions for a maximum-likelihood estimate are considered. These equations, suggest certain successive-approximations iterative procedures for obtaining maximum-likelihood estimates. These are generalized steepest ascent (deflected gradient) procedures. It is shown that, with probability 1 as N sub 0 approaches infinity (regardless of the relative sizes of N sub 0 and N sub 1, i=1,...,m), these procedures converge locally to the strongly consistent maximum-likelihood estimates whenever the step size is between 0 and 2. Furthermore, the value of the step size which yields optimal local convergence rates is bounded from below by a number which always lies between 1 and 2.

Physician Bayesian updating from personal beliefs about the base rate and likelihood ratio.

PubMed

Rottman, Benjamin Margolin

2017-02-01

Whether humans can accurately make decisions in line with Bayes' rule has been one of the most important yet contentious topics in cognitive psychology. Though a number of paradigms have been used for studying Bayesian updating, rarely have subjects been allowed to use their own preexisting beliefs about the prior and the likelihood. A study is reported in which physicians judged the posttest probability of a diagnosis for a patient vignette after receiving a test result, and the physicians' posttest judgments were compared to the normative posttest calculated from their own beliefs in the sensitivity and false positive rate of the test (likelihood ratio) and prior probability of the diagnosis. On the one hand, the posttest judgments were strongly related to the physicians' beliefs about both the prior probability as well as the likelihood ratio, and the priors were used considerably more strongly than in previous research. On the other hand, both the prior and the likelihoods were still not used quite as much as they should have been, and there was evidence of other nonnormative aspects to the updating, such as updating independent of the likelihood beliefs. By focusing on how physicians use their own prior beliefs for Bayesian updating, this study provides insight into how well experts perform probabilistic inference in settings in which they rely upon their own prior beliefs rather than experimenter-provided cues. It suggests that there is reason to be optimistic about experts' abilities, but that there is still considerable need for improvement.

Multitasking With Television Among Adolescents

PubMed Central

Christensen, Claire G.; Bickham, David; Ross, Craig S.; Rich, Michael

2015-01-01

Using Ecological Momentary Assessment, we explored predictors of adolescents’ television (TV) multitasking behaviors. We investigated whether demographic characteristics (age, gender, race/ethnicity, and maternal education) predict adolescents’ likelihood of multitasking with TV. We also explored whether characteristics of the TV-multitasking moment (affect, TV genre, attention to people, and media multitasking) predict adolescents’ likelihood of paying primary versus secondary attention to TV. Demographic characteristics do not predict TV multitasking. In TV-multitasking moments, primary attention to TV was more likely if adolescents experienced negative affect, watched a drama, or attended to people; it was less likely if they used computers or video games. PMID:26549930

Multitasking With Television Among Adolescents.

PubMed

Christensen, Claire G; Bickham, David; Ross, Craig S; Rich, Michael

Using Ecological Momentary Assessment, we explored predictors of adolescents' television (TV) multitasking behaviors. We investigated whether demographic characteristics (age, gender, race/ethnicity, and maternal education) predict adolescents' likelihood of multitasking with TV. We also explored whether characteristics of the TV-multitasking moment (affect, TV genre, attention to people, and media multitasking) predict adolescents' likelihood of paying primary versus secondary attention to TV. Demographic characteristics do not predict TV multitasking. In TV-multitasking moments, primary attention to TV was more likely if adolescents experienced negative affect, watched a drama, or attended to people; it was less likely if they used computers or video games.

A systematic review of the diagnostic performance of orthopedic physical examination tests of the hip

PubMed Central

2013-01-01

Background Previous reviews of the diagnostic performances of physical tests of the hip in orthopedics have drawn limited conclusions because of the low to moderate quality of primary studies published in the literature. This systematic review aims to build on these reviews by assessing a broad range of hip pathologies, and employing a more selective approach to the inclusion of studies in order to accurately gauge diagnostic performance for the purposes of making recommendations for clinical practice and future research. It specifically identifies tests which demonstrate strong and moderate diagnostic performance. Methods A systematic search of Medline, Embase, Embase Classic and CINAHL was conducted to identify studies of hip tests. Our selection criteria included an analysis of internal and external validity. We reported diagnostic performance in terms of sensitivity, specificity, predictive values and likelihood ratios. Likelihood ratios were used to identify tests with strong and moderate diagnostic utility. Results Only a small proportion of tests reported in the literature have been assessed in methodologically valid primary studies. 16 studies were included in our review, producing 56 independent test-pathology combinations. Two tests demonstrated strong clinical utility, the patellar-pubic percussion test for excluding radiologically occult hip fractures (negative LR 0.05, 95% Confidence Interval [CI] 0.03-0.08) and the hip abduction sign for diagnosing sarcoglycanopathies in patients with known muscular dystrophies (positive LR 34.29, 95% CI 10.97-122.30). Fifteen tests demonstrated moderate diagnostic utility for diagnosing and/or excluding hip fractures, symptomatic osteoarthritis and loosening of components post-total hip arthroplasty. Conclusions We have identified a number of tests demonstrating strong and moderate diagnostic performance. These findings must be viewed with caution as there are concerns over the methodological quality of the primary studies from which we have extracted our data. Future studies should recruit larger, representative populations and allow for the construction of complete 2×2 contingency tables. PMID:23987589

A systematic review of the diagnostic performance of orthopedic physical examination tests of the hip.

PubMed

Rahman, Labib Ataur; Adie, Sam; Naylor, Justine Maree; Mittal, Rajat; So, Sarah; Harris, Ian Andrew

2013-08-30

Previous reviews of the diagnostic performances of physical tests of the hip in orthopedics have drawn limited conclusions because of the low to moderate quality of primary studies published in the literature. This systematic review aims to build on these reviews by assessing a broad range of hip pathologies, and employing a more selective approach to the inclusion of studies in order to accurately gauge diagnostic performance for the purposes of making recommendations for clinical practice and future research. It specifically identifies tests which demonstrate strong and moderate diagnostic performance. A systematic search of Medline, Embase, Embase Classic and CINAHL was conducted to identify studies of hip tests. Our selection criteria included an analysis of internal and external validity. We reported diagnostic performance in terms of sensitivity, specificity, predictive values and likelihood ratios. Likelihood ratios were used to identify tests with strong and moderate diagnostic utility. Only a small proportion of tests reported in the literature have been assessed in methodologically valid primary studies. 16 studies were included in our review, producing 56 independent test-pathology combinations. Two tests demonstrated strong clinical utility, the patellar-pubic percussion test for excluding radiologically occult hip fractures (negative LR 0.05, 95% Confidence Interval [CI] 0.03-0.08) and the hip abduction sign for diagnosing sarcoglycanopathies in patients with known muscular dystrophies (positive LR 34.29, 95% CI 10.97-122.30). Fifteen tests demonstrated moderate diagnostic utility for diagnosing and/or excluding hip fractures, symptomatic osteoarthritis and loosening of components post-total hip arthroplasty. We have identified a number of tests demonstrating strong and moderate diagnostic performance. These findings must be viewed with caution as there are concerns over the methodological quality of the primary studies from which we have extracted our data. Future studies should recruit larger, representative populations and allow for the construction of complete 2×2 contingency tables.

The Association between Preservice Elementary Teacher Animal Attitude and Likelihood of Animal Incorporation in Future Science Curriculum

ERIC Educational Resources Information Center

Wagler, Ron

2010-01-01

The purpose of this study was to assess the association between United States K-4 preservice teacher's attitudes toward specific animals and the likelihood that the preservice elementary teachers would incorporate these specific animals in their future science curriculum. A strong statistically significant association was found between the…

Modeling drought impact occurrence based on climatological drought indices for four European countries

NASA Astrophysics Data System (ADS)

Stagge, James H.; Kohn, Irene; Tallaksen, Lena M.; Stahl, Kerstin

2014-05-01

The relationship between atmospheric conditions and the likelihood of a significant drought impact has, in the past, been difficult to quantify, particularly in Europe where political boundaries and language have made acquiring comprehensive drought impact information difficult. As such, the majority of studies linking meteorological drought with the occurrence or severity of drought impacts have previously focused on specific regions, very detailed impact types, or both. This study describes a new methodology to link the likelihood of drought impact occurrence with climatological drought indices across different European climatic regions and impact sectors using the newly developed European Drought Impact report Inventory (EDII), a collaborative database of drought impact information (www.geo.uio.no/edc/droughtdb/). The Standardized Precipitation Index (SPI) and Standardized Precipitation-Evapotranspiration Index (SPEI) are used as predictor variables to quantify meteorological drought severity over prior time periods (here 1, 2, 3, 6, 9, 12, and 24 months are used). The indices are derived using the gridded WATCH Forcing Datasets, covering the period 1958-2012. Analysis was performed using logistic regression to identify the climatological drought index and accumulation period, or linear combination of drought indices, that best predicts the likelihood of a documented drought impact, defined by monthly presence/absence. The analysis was carried out for a subset of four European countries (Germany, UK, Norway, Slovenia) and four of the best documented impact sectors: Public Water Supply, Agriculture and Livestock Farming, Energy and Industry, and Environmental Quality. Preliminary results show that drought impacts in these countries occur most frequently due to a combination of short-term (2-6 month) precipitation deficits and long-term (12-24 month) potential evapotranspiration anomaly, likely associated with increased temperatures. Agricultural drought impacts were explained best by shorter, seasonal indices (2-6 months), while impacts to the Energy sector were best explained by long-duration (12-24 month) anomalies, related to hydropower reservoir storage. Notably, drought impacts in the UK were not affected by short (< 6 month) anomalies, which may point to successful management strategies or underlying geoclimatic differences. By identifying the climatological drought indices most strongly linked to drought impact occurrence and generating regression equations that can predict the likelihood of a drought event, this research is a valuable step towards measuring and predicting drought risk. This work provides a methodological example using only a subset of European countries and impact types, but the accuracy and scope of these results will improve as the EDII grows with further contributions and collaboration.

The influence of non-clinical patient factors on medical oncologists' decisions to recommend breast cancer adjuvant chemotherapy.

PubMed

Pini, T May; Hawley, Sarah T; Li, Yun; Katz, Steven J; Griggs, Jennifer J

2012-07-01

The extent to which medical oncologists consider non-clinical patient factors when deciding to recommend adjuvant chemotherapy is unknown. Medical oncologists who treated a population-based sample of early stage breast cancer patients reported to the Los Angeles and Detroit Surveillance, Epidemiology, and End Results registries 2005-2007 were asked how strongly they consider a patient's ability to follow instructions, level of social support, and level of work support/flexibility in decisions to recommend adjuvant chemotherapy. Responses of 4 (Quite strongly) or 5 (Very strongly) on a five-point Likert scale defined strong consideration. Associations between oncologist/practice characteristics and strong consideration of each non-clinical factor were examined. 134 oncologists (66 %) reported strong consideration of one or more factor. Ability to follow instructions was strongly considered by 120 oncologists (59 %), social support by 78 (38 %), and work support/flexibility by 73 (36 %). Larger percent of practice devoted to breast cancer was associated with lower likelihood of strongly considering ability to follow instructions [odds ratio (OR) 0.98, 95 % confidence interval (CI) 0.97-0.99; P = 0.04]. Increased years in practice was associated with lower likelihood of strongly considering social support (OR 0.96, CI 0.93-0.99; P = 0.011), while non-white race (OR 2.1, CI 1.03-4.26; P = 0.041) and tumor board access (OR 2.04, CI 1.01-4.12; P = 0.048) were associated with higher likelihood. Non-white race was associated with strongly considering work support/flexibility (OR 2.44, CI 1.21-4.92; P = 0.013). Tumor board access (OR 2, CI 1.00-4.02; P = 0.051) was borderline significant. Non-clinical patient factors play a role in medical oncologist decision-making for breast cancer adjuvant chemotherapy recommendations.

Preoperative Serum Thyrotropin to Thyroglobulin Ratio Is Effective for Thyroid Nodule Evaluation in Euthyroid Patients.

PubMed

Wang, Lina; Li, Hao; Yang, Zhongyuan; Guo, Zhuming; Zhang, Quan

2015-07-01

This study was designed to assess the efficiency of the serum thyrotropin to thyroglobulin ratio for thyroid nodule evaluation in euthyroid patients. Cross-sectional study. Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China. Retrospective analysis was performed for 400 previously untreated cases presenting with thyroid nodules. Thyroid function was tested with commercially available radioimmunoassays. The receiver operating characteristic curves were constructed to determine cutoff values. The efficacy of the thyrotropin:thyroglobulin ratio and thyroid-stimulating hormone for thyroid nodule evaluation was evaluated in terms of sensitivity, specificity, positive predictive value, positive likelihood ratio, negative likelihood ratio, and odds ratio. In receiver operating characteristic curve analysis, the area under the curve was 0.746 for the thyrotropin:thyroglobulin ratio and 0.659 for thyroid-stimulating hormone. With a cutoff point value of 24.97 IU/g for the thyrotropin:thyroglobulin ratio, the sensitivity, specificity, positive predictive value, positive likelihood ratio, and negative likelihood ratio were 78.9%, 60.8%, 75.5%, 2.01, and 0.35, respectively. The odds ratio for the thyrotropin:thyroglobulin ratio indicating malignancy was 5.80. With a cutoff point value of 1.525 µIU/mL for thyroid-stimulating hormone, the sensitivity, specificity, positive predictive value, positive likelihood ratio, and negative likelihood ratio were 74.0%, 53.2%, 70.8%, 1.58, and 0.49, respectively. The odds ratio indicating malignancy for thyroid-stimulating hormone was 3.23. Increasing preoperative serum thyrotropin:thyroglobulin ratio is a risk factor for thyroid carcinoma, and the correlation of the thyrotropin:thyroglobulin ratio to malignancy is higher than that for serum thyroid-stimulating hormone. © American Academy of Otolaryngology—Head and Neck Surgery Foundation 2015.

Quantifying uncertainties in streamflow predictions through signature based inference of hydrological model parameters

NASA Astrophysics Data System (ADS)

Fenicia, Fabrizio; Reichert, Peter; Kavetski, Dmitri; Albert, Calro

2016-04-01

The calibration of hydrological models based on signatures (e.g. Flow Duration Curves - FDCs) is often advocated as an alternative to model calibration based on the full time series of system responses (e.g. hydrographs). Signature based calibration is motivated by various arguments. From a conceptual perspective, calibration on signatures is a way to filter out errors that are difficult to represent when calibrating on the full time series. Such errors may for example occur when observed and simulated hydrographs are shifted, either on the "time" axis (i.e. left or right), or on the "streamflow" axis (i.e. above or below). These shifts may be due to errors in the precipitation input (time or amount), and if not properly accounted in the likelihood function, may cause biased parameter estimates (e.g. estimated model parameters that do not reproduce the recession characteristics of a hydrograph). From a practical perspective, signature based calibration is seen as a possible solution for making predictions in ungauged basins. Where streamflow data are not available, it may in fact be possible to reliably estimate streamflow signatures. Previous research has for example shown how FDCs can be reliably estimated at ungauged locations based on climatic and physiographic influence factors. Typically, the goal of signature based calibration is not the prediction of the signatures themselves, but the prediction of the system responses. Ideally, the prediction of system responses should be accompanied by a reliable quantification of the associated uncertainties. Previous approaches for signature based calibration, however, do not allow reliable estimates of streamflow predictive distributions. Here, we illustrate how the Bayesian approach can be employed to obtain reliable streamflow predictive distributions based on signatures. A case study is presented, where a hydrological model is calibrated on FDCs and additional signatures. We propose an approach where the likelihood function for the signatures is derived from the likelihood for streamflow (rather than using an "ad-hoc" likelihood for the signatures as done in previous approaches). This likelihood is not easily tractable analytically and we therefore cannot apply "simple" MCMC methods. This numerical problem is solved using Approximate Bayesian Computation (ABC). Our result indicate that the proposed approach is suitable for producing reliable streamflow predictive distributions based on calibration to signature data. Moreover, our results provide indications on which signatures are more appropriate to represent the information content of the hydrograph.

Gene expression profiles in paraffin-embedded core biopsy tissue predict response to chemotherapy in women with locally advanced breast cancer.

PubMed

Gianni, Luca; Zambetti, Milvia; Clark, Kim; Baker, Joffre; Cronin, Maureen; Wu, Jenny; Mariani, Gabriella; Rodriguez, Jaime; Carcangiu, Marialuisa; Watson, Drew; Valagussa, Pinuccia; Rouzier, Roman; Symmans, W Fraser; Ross, Jeffrey S; Hortobagyi, Gabriel N; Pusztai, Lajos; Shak, Steven

2005-10-10

We sought to identify gene expression markers that predict the likelihood of chemotherapy response. We also tested whether chemotherapy response is correlated with the 21-gene Recurrence Score assay that quantifies recurrence risk. Patients with locally advanced breast cancer received neoadjuvant paclitaxel and doxorubicin. RNA was extracted from the pretreatment formalin-fixed paraffin-embedded core biopsies. The expression of 384 genes was quantified using reverse transcriptase polymerase chain reaction and correlated with pathologic complete response (pCR). The performance of genes predicting for pCR was tested in patients from an independent neoadjuvant study where gene expression was obtained using DNA microarrays. Of 89 assessable patients (mean age, 49.9 years; mean tumor size, 6.4 cm), 11 (12%) had a pCR. Eighty-six genes correlated with pCR (unadjusted P < .05); pCR was more likely with higher expression of proliferation-related genes and immune-related genes, and with lower expression of estrogen receptor (ER) -related genes. In 82 independent patients treated with neoadjuvant paclitaxel and doxorubicin, DNA microarray data were available for 79 of the 86 genes. In univariate analysis, 24 genes correlated with pCR with P < .05 (false discovery, four genes) and 32 genes showed correlation with P < .1 (false discovery, eight genes). The Recurrence Score was positively associated with the likelihood of pCR (P = .005), suggesting that the patients who are at greatest recurrence risk are more likely to have chemotherapy benefit. Quantitative expression of ER-related genes, proliferation genes, and immune-related genes are strong predictors of pCR in women with locally advanced breast cancer receiving neoadjuvant anthracyclines and paclitaxel.

Dietary restraint in college women: fear of an imperfect fat self is stronger than hope of a perfect thin self.

PubMed

Dalley, Simon E; Toffanin, Paolo; Pollet, Thomas V

2012-09-01

We predicted that the perceived likelihood of acquiring a hoped-for thin self would mediate perfectionistic strivings on dietary restraint, and that the perceived likelihood of acquiring a feared fat self would mediate perfectionistic concerns on dietary restraint. We also predicted that the mediation pathway from perfectionistic concerns to dietary restraint would have a greater impact than that from perfectionistic strivings. Participants were 222 female college students who reported their height and weight and completed measures of perfectionism, the likelihood of acquiring the feared fat and hoped-for thin selves, and dietary restraint. Statistical analyses revealed that the perceived likelihood of acquiring the feared fat self mediated both perfectionistic concerns and perfectionistic strivings on dietary restraint, and that the mediating pathway from perfectionistic concerns to dietary restraint was greater than that from perfectionistic strivings. Implications for future research and eating pathology interventions are discussed. Copyright © 2012 Elsevier Ltd. All rights reserved.

Adaptively Reevaluated Bayesian Localization (ARBL). A Novel Technique for Radiological Source Localization

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

Miller, Erin A.; Robinson, Sean M.; Anderson, Kevin K.

2015-01-19

Here we present a novel technique for the localization of radiological sources in urban or rural environments from an aerial platform. The technique is based on a Bayesian approach to localization, in which measured count rates in a time series are compared with predicted count rates from a series of pre-calculated test sources to define likelihood. Furthermore, this technique is expanded by using a localized treatment with a limited field of view (FOV), coupled with a likelihood ratio reevaluation, allowing for real-time computation on commodity hardware for arbitrarily complex detector models and terrain. In particular, detectors with inherent asymmetry ofmore » response (such as those employing internal collimation or self-shielding for enhanced directional awareness) are leveraged by this approach to provide improved localization. Our results from the localization technique are shown for simulated flight data using monolithic as well as directionally-aware detector models, and the capability of the methodology to locate radioisotopes is estimated for several test cases. This localization technique is shown to facilitate urban search by allowing quick and adaptive estimates of source location, in many cases from a single flyover near a source. In particular, this method represents a significant advancement from earlier methods like full-field Bayesian likelihood, which is not generally fast enough to allow for broad-field search in real time, and highest-net-counts estimation, which has a localization error that depends strongly on flight path and cannot generally operate without exhaustive search« less

The Effects of Alcohol Problems, PTSD, and Combat Exposure on Nonphysical and Physical Aggression Among Iraq and Afghanistan War Veterans

PubMed Central

Stappenbeck, Cynthia A.; Hellmuth, Julianne C.; Simpson, Tracy; Jakupcak, Matthew

2014-01-01

Aggression among combat veterans is of great concern. Although some studies have found an association between combat exposure and aggressive behavior following deployment, others conclude that aggression is more strongly associated with symptoms of posttraumatic stress disorder (PTSD), and that alcohol misuse may influence this association. Many of these studies have assessed aggression as a single construct, whereas the current study explored both nonphysical aggression only and physical aggression in a sample of Iraq and Afghanistan war veterans (N = 337; 91% male). We found that alcohol problems interacted with PTSD symptom severity to predict nonphysical aggression only. At low levels of PTSD symptoms, veterans with alcohol problems were more likely to perpetrate nonphysical aggression only, as compared with no aggression, than veterans without an alcohol problem. There was no difference in the likelihood of nonphysical aggression only between those with and without alcohol problems at high levels of PTSD symptoms. The likelihood of nonphysical aggression only, as compared with no aggression, was also greater among younger veterans. Greater combat exposure and PTSD symptom severity were associated with an increased likelihood of perpetrating physical aggression, as compared with no aggression. Ethnic minority status and younger age were also associated with physical aggression, as compared with no aggression. Findings suggest that a more detailed assessment of veterans’ aggressive behavior, as well as their alcohol problems and PTSD symptoms, by researchers and clinicians is needed in order to determine how best to intervene. PMID:25225593

Likelihood analysis of spatial capture-recapture models for stratified or class structured populations

USGS Publications Warehouse

Royle, J. Andrew; Sutherland, Christopher S.; Fuller, Angela K.; Sun, Catherine C.

2015-01-01

We develop a likelihood analysis framework for fitting spatial capture-recapture (SCR) models to data collected on class structured or stratified populations. Our interest is motivated by the necessity of accommodating the problem of missing observations of individual class membership. This is particularly problematic in SCR data arising from DNA analysis of scat, hair or other material, which frequently yields individual identity but fails to identify the sex. Moreover, this can represent a large fraction of the data and, given the typically small sample sizes of many capture-recapture studies based on DNA information, utilization of the data with missing sex information is necessary. We develop the class structured likelihood for the case of missing covariate values, and then we address the scaling of the likelihood so that models with and without class structured parameters can be formally compared regardless of missing values. We apply our class structured model to black bear data collected in New York in which sex could be determined for only 62 of 169 uniquely identified individuals. The models containing sex-specificity of both the intercept of the SCR encounter probability model and the distance coefficient, and including a behavioral response are strongly favored by log-likelihood. Estimated population sex ratio is strongly influenced by sex structure in model parameters illustrating the importance of rigorous modeling of sex differences in capture-recapture models.

Radiographic predictors of symptomatic screw removal after retrograde femoral nail insertion.

PubMed

Hamaker, Max; O'Hara, Nathan N; Eglseder, W Andrew; Sciadini, Marcus F; Nascone, Jason W; O'Toole, Robert V

2017-03-01

Removal of symptomatic implants is a common procedure performed by orthopaedic trauma surgeons. No guidance is available regarding which factors contribute to the likelihood of an implant becoming symptomatic. Our objective was to determine whether radiographic parameters associated with distal interlocks in retrograde femoral nails are associated with the rate of symptomatic screw removal. We conducted a retrospective review at a Level I trauma center. Study patients (n=442) had femoral fractures treated with retrograde intramedullary nails from 2007 to 2014 and at least 1year of follow-up. The main outcome measurement was symptomatic distal screw removal as predicted by radiographic parameters. Symptomatic screw removal occurred in 12% of the patients. Increased distance between the most distal screw and the articular surface of the femur significantly reduced likelihood of symptomatic screw removal. A cutoff of 40mm from the articular block was predictive of removal (≥40mm, 0% removal; <40mm, 18% removal, p<0.0001). In patients with distal screws placed within 40mm of the articular surface of the femur, a ratio of screw length to distance between medial and lateral femoral cortices that was ≥1 was a strong predictor of symptomatic screw removal (area under Receiver Operating Characteristic curve, 0.75; p<0.0001). More distal screws and screws that radiographically extend to or beyond the medial cortex are more likely to cause pain and require removal in femoral fractures treated with retrograde intramedullary nails. We identified a specific distance from the joint (<40mm) and a ratio of screw length to bone width (≥1) that significantly increased the likelihood of symptomatic screw removal. Clinicians can use these data to inform patients of the likely risk of implant removal and perhaps to better guide placement and length of screws when the clinical scenario allows some flexibility in location and length of screws. Copyright © 2017 Elsevier Ltd. All rights reserved.

Parents’ and students’ perceptions of college alcohol risk: The role of parental risk perception in intentions to communicate about alcohol

PubMed Central

Napper, Lucy E.; Grimaldi, Elizabeth M.; LaBrie, Joseph W.

2017-01-01

The current study aims to examine discrepancies in parents’ and college students’ perceptions of alcohol risk and the role of perceived risk in predicting parents’ intentions to discuss alcohol with their child. In total, 246 college student-parent dyads (56.1% female students, 77.2% mothers) were recruited from a mid-size university. Participants completed measures of absolute likelihood, comparative likelihood, and severity of alcohol consequences. In comparison to students, parents perceived the risks of alcohol poisoning (p < .001), academic impairment (p < .05), and problems with others (p < .05) to be more likely. In addition, parents rated the majority alcohol consequences (e.g., passing out, regrettable sexual situation, throwing up) as more severe than students (all ps < .001). However, parents tended to be more optimistic than their child about the comparative likelihood of alcohol consequences. After controlling for demographics and past alcohol communication, greater absolute likelihood (β = .20, p = .016) and less confidence in knowledge of student behavior (β = .20, p = .013) predicted greater intentions to discuss alcohol. Providing parents of college students with information about college drinking norms and the likelihood of alcohol consequences may help prompt alcohol-related communication. PMID:25437267

Analysis of Propagation Plans in NSF-Funded Education Development Projects

NASA Astrophysics Data System (ADS)

Stanford, Courtney; Cole, Renee; Froyd, Jeff; Henderson, Charles; Friedrichsen, Debra; Khatri, Raina

2017-08-01

Increasing adoption and adaptation of promising instructional strategies and materials has been identified as a critical component needed to improve science, technology, engineering, and mathematics (STEM) education. This paper examines typical propagation practices and resulting outcomes of proposals written by developers of educational innovations. These proposals were analyzed using the Designing for Sustained Adoption Assessment Instrument (DSAAI), an instrument developed to evaluate propagation plans, and the results used to predict the likelihood that a successful project would result in adoption by others. We found that few education developers propose strong propagation plans. Afterwards, a follow-up analysis was conducted to see which propagation strategies developers actually used to help develop, disseminate, and support their innovations. A web search and interviews with principal investigators were used to determine the degree to which propagation plans were actually implemented and to estimate adoption of the innovations. In this study, we analyzed 71 education development proposals funded by the National Science Foundation and predicted that 80% would be unsuccessful in propagating their innovations. Follow-up data collection with a subset of these suggests that the predictions were reasonably accurate.

Predictive Capacity of Cloninger's temperament and character inventory (TCI-R) in alcohol use disorder outcomes.

PubMed

Ávila Escribano, José Juan; Sánchez Barba, Mercedes; Álvarez Pedrero, Aida; López Villarreal, Ana; Recio Pérez, Joaquina; Rodríguez Rodilla, Manuela; Fraile García, Eulalia

2016-06-14

to investigate the ability to predict the outcome of alcohol use disorders through Cloninger's temperament and character inventory (TCI-R). this is a prospective study consisting of 237 outpatients with alcohol use disorders who underwent follow-up treatment for 6 months and whose personality traits were studied using TCI-R. At the end of that period, the scores of each TCI-R trait were analyzed in terms of those who remained in treatment and those who dropped out. The whole group scored highly in novelty seeking (NS) and harm avoidance (HA) and produced low scores in self-directedness (SD), these last traits are considered prominent. The drop-out group scored significantly (p=.004) higher in novelty seeking (NS) than the follow-up group. Also, when the score was higher than the 67 percentile the likelihood of abandoning the treatment was 1.07 times higher. Cloninger's temperament and character inventory is a good instrument to predict the outcome of treatment of patients with alcohol use disorders and the novelty seeking (NS) dimension is strongly related to therapeutic drop-out.

Likelihood testing of seismicity-based rate forecasts of induced earthquakes in Oklahoma and Kansas

USGS Publications Warehouse

Moschetti, Morgan P.; Hoover, Susan M.; Mueller, Charles

2016-01-01

Likelihood testing of induced earthquakes in Oklahoma and Kansas has identified the parameters that optimize the forecasting ability of smoothed seismicity models and quantified the recent temporal stability of the spatial seismicity patterns. Use of the most recent 1-year period of earthquake data and use of 10–20-km smoothing distances produced the greatest likelihood. The likelihood that the locations of January–June 2015 earthquakes were consistent with optimized forecasts decayed with increasing elapsed time between the catalogs used for model development and testing. Likelihood tests with two additional sets of earthquakes from 2014 exhibit a strong sensitivity of the rate of decay to the smoothing distance. Marked reductions in likelihood are caused by the nonstationarity of the induced earthquake locations. Our results indicate a multiple-fold benefit from smoothed seismicity models in developing short-term earthquake rate forecasts for induced earthquakes in Oklahoma and Kansas, relative to the use of seismic source zones.

Two simple clinical tests for predicting onset of medial tibial stress syndrome: shin palpation test and shin oedema test.

PubMed

Newman, Phil; Adams, Roger; Waddington, Gordon

2012-09-01

To examine the relationship between two clinical test results and future diagnosis of (Medial Tibial Stress Syndrome) MTSS in personnel at a military trainee establishment. Data from a preparticipation musculoskeletal screening test performed on 384 Australian Defence Force Academy Officer Cadets were compared against 693 injuries reported by 326 of the Officer Cadets in the following 16 months. Data were held in an Injury Surveillance database and analysed using χ² and Fisher's Exact tests, and Receiver Operating Characteristic Curve analysis. Diagnosis of MTSS, confirmed by an independent blinded health practitioner. Both the palpation and oedema clinical tests were each found to be significant predictors for later onset of MTSS. Specifically: Shin palpation test OR 4.63, 95% CI 2.5 to 8.5, Positive Likelihood Ratio 3.38, Negative Likelihood Ratio 0.732, Pearson χ² p<0.001; Shin oedema test OR 76.1 95% CI 9.6 to 602.7, Positive Likelihood Ratio 7.26, Negative Likelihood Ratio 0.095, Fisher's Exact p<0.001; Combined Shin Palpation Test and Shin Oedema Test Positive Likelihood Ratio 7.94, Negative Likelihood Ratio <0.001, Fisher's Exact p<0.001. Female gender was found to be an independent risk factor (OR 2.97, 95% CI 1.66 to 5.31, Positive Likelihood Ratio 2.09, Negative Likelihood Ratio 0.703, Pearson χ² p<0.001) for developing MTSS. The tests for MTSS employed here are components of a normal clinical examination used to diagnose MTSS. This paper confirms that these tests and female gender can also be confidently applied in predicting those in an asymptomatic population who are at greater risk of developing MTSS symptoms with activity at some point in the future.

Usefulness of Two Aspergillus PCR Assays and Aspergillus Galactomannan and β-d-Glucan Testing of Bronchoalveolar Lavage Fluid for Diagnosis of Chronic Pulmonary Aspergillosis

PubMed Central

Urabe, Naohisa; Sano, Go; Suzuki, Junko; Hebisawa, Akira; Nakamura, Yasuhiko; Koyama, Kazuya; Ishii, Yoshikazu; Tateda, Kazuhiro; Homma, Sakae

2017-01-01

ABSTRACT We evaluated the usefulness of an Aspergillus galactomannan (GM) test, a β-d-glucan (βDG) test, and two different Aspergillus PCR assays of bronchoalveolar lavage fluid (BALF) samples for the diagnosis of chronic pulmonary aspergillosis (CPA). BALF samples from 30 patients with and 120 patients without CPA were collected. We calculated the sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio for each test individually and in combination with other tests. The optical density index values, as determined by receiver operating characteristic analysis, for the diagnosis of CPA were 0.5 and 100 for GM and βDG testing of BALF, respectively. The sensitivity and specificity of the GM test, βDG test, and PCR assays 1 and 2 were 77.8% and 90.0%, 77.8% and 72.5%, 86.7% and 84.2%, and 66.7% and 94.2%, respectively. A comparison of the PCR assays showed that PCR assay 1 had a better sensitivity, a better negative predictive value, and a better negative likelihood ratio and PCR assay 2 had a better specificity, a better positive predictive value, and a better positive likelihood ratio. The combination of the GM and βDG tests had the highest diagnostic odds ratio. The combination of the GM and βDG tests on BALF was more useful than any single test for diagnosing CPA. PMID:28330887

Parameter Estimation and Model Selection for Indoor Environments Based on Sparse Observations

NASA Astrophysics Data System (ADS)

Dehbi, Y.; Loch-Dehbi, S.; Plümer, L.

2017-09-01

This paper presents a novel method for the parameter estimation and model selection for the reconstruction of indoor environments based on sparse observations. While most approaches for the reconstruction of indoor models rely on dense observations, we predict scenes of the interior with high accuracy in the absence of indoor measurements. We use a model-based top-down approach and incorporate strong but profound prior knowledge. The latter includes probability density functions for model parameters and sparse observations such as room areas and the building footprint. The floorplan model is characterized by linear and bi-linear relations with discrete and continuous parameters. We focus on the stochastic estimation of model parameters based on a topological model derived by combinatorial reasoning in a first step. A Gauss-Markov model is applied for estimation and simulation of the model parameters. Symmetries are represented and exploited during the estimation process. Background knowledge as well as observations are incorporated in a maximum likelihood estimation and model selection is performed with AIC/BIC. The likelihood is also used for the detection and correction of potential errors in the topological model. Estimation results are presented and discussed.

Parent figure transitions and delinquency and drug use among early adolescent children of substance abusers.

PubMed

Keller, Thomas E; Catalano, Richard F; Haggerty, Kevin P; Fleming, Charles B

2002-01-01

Children of substance abusing parents have an elevated risk for experiencing disruptions in household composition and for engaging in problem behaviors. This study investigated whether multiple parent figure transitions predicted the likelihood of delinquency and drug use among a sample of early adolescents with parents receiving methadone treatment for opiate addiction. Controlling for baseline delinquency, child characteristics, family conflict, parental depression, and parent criminal history, a greater number of parenting disruptions during the longitudinal study period was associated with a higher probability of delinquent behavior. Gender moderated the effect of parent figure transitions in a parallel analysis for drug use. After accounting for baseline drug use and potentially confounding factors, only adolescent females had a higher likelihood of drug use as the number of family disruptions increased. In contrast, age was strongly associated with drug use for males. A subgroup of youths who experienced tremendous family instability and had no single consistent parent figure during the study period were at extreme risk for delinquent behavior. The findings are interpreted in terms of cumulative stress resulting from multiple parenting disruptions over time and differential influences on the expression of problem behaviors depending on gender.

The effects of co-morbidity in defining major depression subtypes associated with long-term course and severity.

PubMed

Wardenaar, K J; van Loo, H M; Cai, T; Fava, M; Gruber, M J; Li, J; de Jonge, P; Nierenberg, A A; Petukhova, M V; Rose, S; Sampson, N A; Schoevers, R A; Wilcox, M A; Alonso, J; Bromet, E J; Bunting, B; Florescu, S E; Fukao, A; Gureje, O; Hu, C; Huang, Y Q; Karam, A N; Levinson, D; Medina Mora, M E; Posada-Villa, J; Scott, K M; Taib, N I; Viana, M C; Xavier, M; Zarkov, Z; Kessler, R C

2014-11-01

Although variation in the long-term course of major depressive disorder (MDD) is not strongly predicted by existing symptom subtype distinctions, recent research suggests that prediction can be improved by using machine learning methods. However, it is not known whether these distinctions can be refined by added information about co-morbid conditions. The current report presents results on this question. Data came from 8261 respondents with lifetime DSM-IV MDD in the World Health Organization (WHO) World Mental Health (WMH) Surveys. Outcomes included four retrospectively reported measures of persistence/severity of course (years in episode; years in chronic episodes; hospitalization for MDD; disability due to MDD). Machine learning methods (regression tree analysis; lasso, ridge and elastic net penalized regression) followed by k-means cluster analysis were used to augment previously detected subtypes with information about prior co-morbidity to predict these outcomes. Predicted values were strongly correlated across outcomes. Cluster analysis of predicted values found three clusters with consistently high, intermediate or low values. The high-risk cluster (32.4% of cases) accounted for 56.6-72.9% of high persistence, high chronicity, hospitalization and disability. This high-risk cluster had both higher sensitivity and likelihood ratio positive (LR+; relative proportions of cases in the high-risk cluster versus other clusters having the adverse outcomes) than in a parallel analysis that excluded measures of co-morbidity as predictors. Although the results using the retrospective data reported here suggest that useful MDD subtyping distinctions can be made with machine learning and clustering across multiple indicators of illness persistence/severity, replication with prospective data is needed to confirm this preliminary conclusion.

Influencers and preference predictors of HPV vaccine uptake among US male and female young adult college students.

PubMed

LaJoie, A Scott; Kerr, Jelani C; Clover, Richard D; Harper, Diane M

2018-06-01

The purpose of the study was to assess the knowledge, attitudes and beliefs of male and female college students in Kentucky about HPV associated diseases and vaccines, and to determine which parameters predicted self-reported uptake of HPV vaccination. A self-selected cross-sectional sample of college students completed an evidence-based online survey. Of approximately 1200 potential respondents, 585 completed the survey. The average age was 20.6 (SD 3.15) and 78% were female; 84% of the population had had one or more sexual partners. Concern for HPV vaccine safety and potential need for boosters did not significantly deter vaccine uptake. Likewise, knowledge about HPV associated cancers was not predictive of vaccine uptake. On the other hand, parental influence for vaccination was a strong predictor for vaccine uptake (aOR = 5.32, 2.71-13.03), and free vaccine nearly doubled the likelihood of being vaccinated (aOR 1.90, 1.05-3.41). In addition, the strong preference for the respondent's partner to be HPV vaccinated predicted vaccine uptake (aOR = 4.04, 95% CI: 2.31-7.05), but the lack of preference for partner vaccination predicted an unvaccinated self (aOR = 0.50, 0.27-0.93). HPV vaccination has been successful in young adult college students in Kentucky. Young adults prefer their partners to be HPV vaccinated regardless of whether they themselves are vaccinated. Parental influence and free vaccine were positive predictors for vaccine uptake in this population. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

How much is a word? Predicting ease of articulation planning from apraxic speech error patterns.

PubMed

Ziegler, Wolfram; Aichert, Ingrid

2015-08-01

According to intuitive concepts, 'ease of articulation' is influenced by factors like word length or the presence of consonant clusters in an utterance. Imaging studies of speech motor control use these factors to systematically tax the speech motor system. Evidence from apraxia of speech, a disorder supposed to result from speech motor planning impairment after lesions to speech motor centers in the left hemisphere, supports the relevance of these and other factors in disordered speech planning and the genesis of apraxic speech errors. Yet, there is no unified account of the structural properties rendering a word easy or difficult to pronounce. To model the motor planning demands of word articulation by a nonlinear regression model trained to predict the likelihood of accurate word production in apraxia of speech. We used a tree-structure model in which vocal tract gestures are embedded in hierarchically nested prosodic domains to derive a recursive set of terms for the computation of the likelihood of accurate word production. The model was trained with accuracy data from a set of 136 words averaged over 66 samples from apraxic speakers. In a second step, the model coefficients were used to predict a test dataset of accuracy values for 96 new words, averaged over 120 samples produced by a different group of apraxic speakers. Accurate modeling of the first dataset was achieved in the training study (R(2)adj = .71). In the cross-validation, the test dataset was predicted with a high accuracy as well (R(2)adj = .67). The model shape, as reflected by the coefficient estimates, was consistent with current phonetic theories and with clinical evidence. In accordance with phonetic and psycholinguistic work, a strong influence of word stress on articulation errors was found. The proposed model provides a unified and transparent account of the motor planning requirements of word articulation. Copyright © 2015 Elsevier Ltd. All rights reserved.

A reinforcement sensitivity model of affective and behavioral dysregulation in marijuana use and associated problems.

PubMed

Emery, Noah N; Simons, Jeffrey S

2017-08-01

This study tested a model linking sensitivity to punishment (SP) and reward (SR) to marijuana use and problems via affect lability and poor control. A 6-month prospective design was used in a sample of 2,270 young-adults (64% female). The hypothesized SP × SR interaction did not predict affect lability or poor control, but did predict use likelihood at baseline. At low levels of SR, SP was associated with an increased likelihood of abstaining, which was attenuated as SR increased. SP and SR displayed positive main effects on both affect lability and poor control. Affect lability and poor control, in turn, mediated effects on the marijuana outcomes. Poor control predicted both increased marijuana use and, controlling for use level, greater intensity of problems. Affect lability predicted greater intensity of problems, but was not associated with use level. There were few prospective effects. SR consistently predicted greater marijuana use and problems. SP however, exhibited both risk and protective pathways. Results indicate that SP is associated with a decreased likelihood of marijuana use. However, once use is initiated SP is associated with increased risk of problems, in part, due to its effects on both affect and behavioral dysregulation. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Lung nodule malignancy prediction using multi-task convolutional neural network

NASA Astrophysics Data System (ADS)

Li, Xiuli; Kao, Yueying; Shen, Wei; Li, Xiang; Xie, Guotong

2017-03-01

In this paper, we investigated the problem of diagnostic lung nodule malignancy prediction using thoracic Computed Tomography (CT) screening. Unlike most existing studies classify the nodules into two types benign and malignancy, we interpreted the nodule malignancy prediction as a regression problem to predict continuous malignancy level. We proposed a joint multi-task learning algorithm using Convolutional Neural Network (CNN) to capture nodule heterogeneity by extracting discriminative features from alternatingly stacked layers. We trained a CNN regression model to predict the nodule malignancy, and designed a multi-task learning mechanism to simultaneously share knowledge among 9 different nodule characteristics (Subtlety, Calcification, Sphericity, Margin, Lobulation, Spiculation, Texture, Diameter and Malignancy), and improved the final prediction result. Each CNN would generate characteristic-specific feature representations, and then we applied multi-task learning on the features to predict the corresponding likelihood for that characteristic. We evaluated the proposed method on 2620 nodules CT scans from LIDC-IDRI dataset with the 5-fold cross validation strategy. The multitask CNN regression result for regression RMSE and mapped classification ACC were 0.830 and 83.03%, while the results for single task regression RMSE 0.894 and mapped classification ACC 74.9%. Experiments show that the proposed method could predict the lung nodule malignancy likelihood effectively and outperforms the state-of-the-art methods. The learning framework could easily be applied in other anomaly likelihood prediction problem, such as skin cancer and breast cancer. It demonstrated the possibility of our method facilitating the radiologists for nodule staging assessment and individual therapeutic planning.

Fatty liver index and hepatic steatosis index for prediction of non-alcoholic fatty liver disease in type 1 diabetes.

PubMed

Sviklāne, Laura; Olmane, Evija; Dzērve, Zane; Kupčs, Kārlis; Pīrāgs, Valdis; Sokolovska, Jeļizaveta

2018-01-01

Little is known about the diagnostic value of hepatic steatosis index (HSI) and fatty liver index (FLI), as well as their link to metabolic syndrome in type 1 diabetes mellitus. We have screened the effectiveness of FLI and HSI in an observational pilot study of 40 patients with type 1 diabetes. FLI and HSI were calculated for 201 patients with type 1 diabetes. Forty patients with FLI/HSI values corresponding to different risk of liver steatosis were invited for liver magnetic resonance study. In-phase/opposed-phase technique of magnetic resonance was used. Accuracy of indices was assessed from the area under the receiver operating characteristic curve. Twelve (30.0%) patients had liver steatosis. For FLI, sensitivity was 90%; specificity, 74%; positive likelihood ratio, 3.46; negative likelihood ratio, 0.14; positive predictive value, 0.64; and negative predictive value, 0.93. For HSI, sensitivity was 86%; specificity, 66%; positive likelihood ratio, 1.95; negative likelihood ratio, 0.21; positive predictive value, 0.50; and negative predictive value, 0.92. Area under the receiver operating characteristic curve for FLI was 0.86 (95% confidence interval [0.72; 0.99]); for HSI 0.75 [0.58; 0.91]. Liver fat correlated with liver enzymes, waist circumference, triglycerides, and C-reactive protein. FLI correlated with C-reactive protein, liver enzymes, and blood pressure. HSI correlated with waist circumference and C-reactive protein. FLI ≥ 60 and HSI ≥ 36 were significantly associated with metabolic syndrome and nephropathy. The tested indices, especially FLI, can serve as surrogate markers for liver fat content and metabolic syndrome in type 1 diabetes. © 2017 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

A Scoring Tool to Identify East African HIV-1 Serodiscordant Partnerships with a High Likelihood of Pregnancy.

PubMed

Heffron, Renee; Cohen, Craig R; Ngure, Kenneth; Bukusi, Elizabeth; Were, Edwin; Kiarie, James; Mugo, Nelly; Celum, Connie; Baeten, Jared M

2015-01-01

HIV-1 prevention programs targeting HIV-1 serodiscordant couples need to identify couples that are likely to become pregnant to facilitate discussions about methods to minimize HIV-1 risk during pregnancy attempts (i.e. safer conception) or effective contraception when pregnancy is unintended. A clinical prediction tool could be used to identify HIV-1 serodiscordant couples with a high likelihood of pregnancy within one year. Using standardized clinical prediction methods, we developed and validated a tool to identify heterosexual East African HIV-1 serodiscordant couples with an increased likelihood of becoming pregnant in the next year. Datasets were from three prospectively followed cohorts, including nearly 7,000 couples from Kenya and Uganda participating in HIV-1 prevention trials and delivery projects. The final score encompassed the age of the woman, woman's number of children living, partnership duration, having had condomless sex in the past month, and non-use of an effective contraceptive. The area under the curve (AUC) for the probability of the score to correctly predict pregnancy was 0.74 (95% CI 0.72-0.76). Scores ≥ 7 predicted a pregnancy incidence of >17% per year and captured 78% of the pregnancies. Internal and external validation confirmed the predictive ability of the score. A pregnancy likelihood score encompassing basic demographic, clinical and behavioral factors defined African HIV-1 serodiscordant couples with high one-year pregnancy incidence rates. This tool could be used to engage African HIV-1 serodiscordant couples in counseling discussions about fertility intentions in order to offer services for safer conception or contraception that align with their reproductive goals.

Validation of an Algorithm to Predict the Likelihood of an 8/8 HLA-Matched Unrelated Donor at Search Initiation.

PubMed

Davis, Eric; Devlin, Sean; Cooper, Candice; Nhaissi, Melissa; Paulson, Jennifer; Wells, Deborah; Scaradavou, Andromachi; Giralt, Sergio; Papadopoulos, Esperanza; Kernan, Nancy A; Byam, Courtney; Barker, Juliet N

2018-05-01

A strategy to rapidly determine if a matched unrelated donor (URD) can be secured for allograft recipients is needed. We sought to validate the accuracy of (1) HapLogic match predictions and (2) a resultant novel Search Prognosis (SP) patient categorization that could predict 8/8 HLA-matched URD(s) likelihood at search initiation. Patient prognosis categories at search initiation were correlated with URD confirmatory typing results. HapLogic-based SP categorizations accurately predicted the likelihood of an 8/8 HLA-match in 830 patients (1530 donors tested). Sixty percent of patients had 8/8 URD(s) identified. Patient SP categories (217 very good, 104 good, 178 fair, 33 poor, 153 very poor, 145 futile) were associated with a marked progressive decrease in 8/8 URD identification and transplantation. Very good to good categories were highly predictive of identifying and receiving an 8/8 URD regardless of ancestry. Europeans in fair/poor categories were more likely to identify and receive an 8/8 URD compared with non-Europeans. In all ancestries very poor and futile categories predicted no 8/8 URDs. HapLogic permits URD search results to be predicted once patient HLA typing and ancestry is obtained, dramatically improving search efficiency. Poor, very poor, andfutile searches can be immediately recognized, thereby facilitating prompt pursuit of alternative donors. Copyright © 2017 The American Society for Blood and Marrow Transplantation. Published by Elsevier Inc. All rights reserved.

Explaining radical group behavior: Developing emotion and efficacy routes to normative and nonnormative collective action.

PubMed

Tausch, Nicole; Becker, Julia C; Spears, Russell; Christ, Oliver; Saab, Rim; Singh, Purnima; Siddiqui, Roomana N

2011-07-01

A recent model of collective action distinguishes 2 distinct pathways: an emotional pathway whereby anger in response to injustice motivates action and an efficacy pathway where the belief that issues can be solved collectively increases the likelihood that group members take action (van Zomeren, Spears, Fischer, & Leach, 2004). Research supporting this model has, however, focused entirely on relatively normative actions such as participating in demonstrations. We argue that the relations between emotions, efficacy, and action differ for more extreme, nonnormative actions and propose (a) that nonnormative actions are often driven by a sense of low efficacy and (b) that contempt, which, unlike anger, entails psychological distancing and a lack of reconciliatory intentions, predicts nonnormative action. These ideas were tested in 3 survey studies examining student protests against tuition fees in Germany (N = 332), Indian Muslims' action support in relation to ingroup disadvantage (N = 156), and British Muslims' responses to British foreign policy (N = 466). Results were generally supportive of predictions and indicated that (a) anger was strongly related to normative action but overall unrelated or less strongly related to nonnormative action, (b) contempt was either unrelated or negatively related to normative action but significantly positively predicted nonnormative action, and (c) efficacy was positively related to normative action and negatively related to nonnormative action. The implications of these findings for understanding and dealing with extreme intergroup phenomena such as terrorism are discussed. PsycINFO Database Record (c) 2011 APA, all rights reserved

A controlled evaluation of an eating disorders primary prevention videotape using the Elaboration Likelihood Model of Persuasion.

PubMed

Withers, Giselle F; Twigg, Kylie; Wertheim, Eleanor H; Paxton, Susan J

2002-11-01

The aim was to extend findings related to a previously reported eating disorders prevention program by comparing treatment and control groups, adding a follow-up, and examining whether receiver characteristics, personal relevance and need for cognition (NFC), could predict attitude change in early adolescent girls. Grade 7 girls were either shown a brief prevention videotape on dieting and body image (n = 104) or given no intervention (n = 114). All girls completed pre-, post- and 1-month follow-up questionnaires. The intervention group resulted in significantly more positive changes in attitude and knowledge at post-intervention, but only in knowledge at follow-up. There was no strong evidence that pre-intervention characteristics of recipients predicted responses to the videotape intervention when changes were compared to the control group. This prevention videotape appeared to have positive immediate effects, but additional intervention (e.g., booster sessions) may be required for longer-term change. Copyright 2002 Elsevier Science Inc.

A Bayesian Alternative for Multi-objective Ecohydrological Model Specification

NASA Astrophysics Data System (ADS)

Tang, Y.; Marshall, L. A.; Sharma, A.; Ajami, H.

2015-12-01

Process-based ecohydrological models combine the study of hydrological, physical, biogeochemical and ecological processes of the catchments, which are usually more complex and parametric than conceptual hydrological models. Thus, appropriate calibration objectives and model uncertainty analysis are essential for ecohydrological modeling. In recent years, Bayesian inference has become one of the most popular tools for quantifying the uncertainties in hydrological modeling with the development of Markov Chain Monte Carlo (MCMC) techniques. Our study aims to develop appropriate prior distributions and likelihood functions that minimize the model uncertainties and bias within a Bayesian ecohydrological framework. In our study, a formal Bayesian approach is implemented in an ecohydrological model which combines a hydrological model (HyMOD) and a dynamic vegetation model (DVM). Simulations focused on one objective likelihood (Streamflow/LAI) and multi-objective likelihoods (Streamflow and LAI) with different weights are compared. Uniform, weakly informative and strongly informative prior distributions are used in different simulations. The Kullback-leibler divergence (KLD) is used to measure the dis(similarity) between different priors and corresponding posterior distributions to examine the parameter sensitivity. Results show that different prior distributions can strongly influence posterior distributions for parameters, especially when the available data is limited or parameters are insensitive to the available data. We demonstrate differences in optimized parameters and uncertainty limits in different cases based on multi-objective likelihoods vs. single objective likelihoods. We also demonstrate the importance of appropriately defining the weights of objectives in multi-objective calibration according to different data types.

Parents' and students' perceptions of college alcohol risk: the role of parental risk perception in intentions to communicate about alcohol.

PubMed

Napper, Lucy E; Grimaldi, Elizabeth M; LaBrie, Joseph W

2015-03-01

The current study aims to examine discrepancies in parents' and college students' perceptions of alcohol risk and the role of perceived risk in predicting parents' intentions to discuss alcohol with their child. In total, 246 college student-parent dyads (56.1% female students, 77.2% mothers) were recruited from a mid-size university. Participants completed measures of absolute likelihood, comparative likelihood, and severity of alcohol consequences. In comparison to students, parents perceived the risks of alcohol poisoning (p<.001), academic impairment (p<.05), and problems with others (p<.05) to be more likely. In addition, parents rated the majority of alcohol consequences (e.g., passing out, regrettable sexual situation, throwing up) as more severe than students (all ps<.001). However, parents tended to be more optimistic than their child about the comparative likelihood of alcohol consequences. After controlling for demographics and past alcohol communication, greater absolute likelihood (β=.20, p=.016) and less confidence in knowledge of student behavior (β=.20, p=.013) predicted greater intentions to discuss alcohol. Providing parents of college students with information about college drinking norms and the likelihood of alcohol consequences may help prompt alcohol-related communication. Copyright © 2014 Elsevier Ltd. All rights reserved.

GASP: Gapped Ancestral Sequence Prediction for proteins

PubMed Central

Edwards, Richard J; Shields, Denis C

2004-01-01

Background The prediction of ancestral protein sequences from multiple sequence alignments is useful for many bioinformatics analyses. Predicting ancestral sequences is not a simple procedure and relies on accurate alignments and phylogenies. Several algorithms exist based on Maximum Parsimony or Maximum Likelihood methods but many current implementations are unable to process residues with gaps, which may represent insertion/deletion (indel) events or sequence fragments. Results Here we present a new algorithm, GASP (Gapped Ancestral Sequence Prediction), for predicting ancestral sequences from phylogenetic trees and the corresponding multiple sequence alignments. Alignments may be of any size and contain gaps. GASP first assigns the positions of gaps in the phylogeny before using a likelihood-based approach centred on amino acid substitution matrices to assign ancestral amino acids. Important outgroup information is used by first working down from the tips of the tree to the root, using descendant data only to assign probabilities, and then working back up from the root to the tips using descendant and outgroup data to make predictions. GASP was tested on a number of simulated datasets based on real phylogenies. Prediction accuracy for ungapped data was similar to three alternative algorithms tested, with GASP performing better in some cases and worse in others. Adding simple insertions and deletions to the simulated data did not have a detrimental effect on GASP accuracy. Conclusions GASP (Gapped Ancestral Sequence Prediction) will predict ancestral sequences from multiple protein alignments of any size. Although not as accurate in all cases as some of the more sophisticated maximum likelihood approaches, it can process a wide range of input phylogenies and will predict ancestral sequences for gapped and ungapped residues alike. PMID:15350199

Understanding the properties of diagnostic tests - Part 2: Likelihood ratios.

PubMed

Ranganathan, Priya; Aggarwal, Rakesh

2018-01-01

Diagnostic tests are used to identify subjects with and without disease. In a previous article in this series, we examined some attributes of diagnostic tests - sensitivity, specificity, and predictive values. In this second article, we look at likelihood ratios, which are useful for the interpretation of diagnostic test results in everyday clinical practice.

Thinking versus feeling: differentiating between cognitive and affective components of perceived cancer risk.

PubMed

Janssen, Eva; van Osch, Liesbeth; Lechner, Lilian; Candel, Math; de Vries, Hein

2012-01-01

Despite the increased recognition of affect in guiding probability estimates, perceived risk has been mainly operationalised in a cognitive way and the differentiation between rational and intuitive judgements is largely unexplored. This study investigated the validity of a measurement instrument differentiating cognitive and affective probability beliefs and examined whether behavioural decision making is mainly guided by cognition or affect. Data were obtained from four surveys focusing on smoking (N=268), fruit consumption (N=989), sunbed use (N=251) and sun protection (N=858). Correlational analyses showed that affective likelihood was more strongly correlated with worry compared to cognitive likelihood and confirmatory factor analysis provided support for a two-factor model of perceived likelihood instead of a one-factor model (i.e. cognition and affect combined). Furthermore, affective likelihood was significantly associated with the various outcome variables, whereas the association for cognitive likelihood was absent in three studies. The findings provide support for the construct validity of the measures used to assess cognitive and affective likelihood. Since affective likelihood might be a better predictor of health behaviour than the commonly used cognitive operationalisation, both dimensions should be considered in future research.

Age and the experience of strong self-conscious emotion.

PubMed

Henry, Julie D; von Hippel, William; Nangle, Matthew R; Waters, Michele

2018-04-01

It remains unclear whether there are age-related changes in the experience of strong self-conscious emotion, such as shame, guilt, pride and embarrassment. Because shame and guilt figure prominently in the aetiology of depressive symptoms and other mental health problems, a better understanding of how age affects the strong experience of these two negative self-conscious emotions is of particular importance. Thirty younger, 30 middle-aged and 30 older adults were compared on standardised cognitive assessments, in addition to an interview-based measure that assessed whether there are age differences in the likelihood of strongly experiencing four different types of self-conscious emotion within the past five years (shame, guilt, embarrassment and pride). The three groups did not differ in their likelihood of reporting an event that strongly elicited the positive self-conscious emotion of pride. However, older adults were more likely to report sources of pride that were other (as opposed to self) focused. Older adults were also less likely to report experiencing events that elicited all three negative self-conscious emotions, in particular, shame. Strong negative self-conscious emotion, and in particular shame, appears to be experienced less by older than younger adults.

Usefulness of Two Aspergillus PCR Assays and Aspergillus Galactomannan and β-d-Glucan Testing of Bronchoalveolar Lavage Fluid for Diagnosis of Chronic Pulmonary Aspergillosis.

PubMed

Urabe, Naohisa; Sakamoto, Susumu; Sano, Go; Suzuki, Junko; Hebisawa, Akira; Nakamura, Yasuhiko; Koyama, Kazuya; Ishii, Yoshikazu; Tateda, Kazuhiro; Homma, Sakae

2017-06-01

We evaluated the usefulness of an Aspergillus galactomannan (GM) test, a β-d-glucan (βDG) test, and two different Aspergillus PCR assays of bronchoalveolar lavage fluid (BALF) samples for the diagnosis of chronic pulmonary aspergillosis (CPA). BALF samples from 30 patients with and 120 patients without CPA were collected. We calculated the sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio for each test individually and in combination with other tests. The optical density index values, as determined by receiver operating characteristic analysis, for the diagnosis of CPA were 0.5 and 100 for GM and βDG testing of BALF, respectively. The sensitivity and specificity of the GM test, βDG test, and PCR assays 1 and 2 were 77.8% and 90.0%, 77.8% and 72.5%, 86.7% and 84.2%, and 66.7% and 94.2%, respectively. A comparison of the PCR assays showed that PCR assay 1 had a better sensitivity, a better negative predictive value, and a better negative likelihood ratio and PCR assay 2 had a better specificity, a better positive predictive value, and a better positive likelihood ratio. The combination of the GM and βDG tests had the highest diagnostic odds ratio. The combination of the GM and βDG tests on BALF was more useful than any single test for diagnosing CPA. Copyright © 2017 American Society for Microbiology.

Provider perceptions concerning use of chest x-ray studies in adult blunt trauma assessments.

PubMed

Calderon, Georgina; Perez, Daniel; Fortman, Jonathan; Kea, Bory; Rodriguez, Robert M

2012-10-01

Although they infrequently lead to management changing diagnoses, chest x-rays (CXRs) are the most commonly ordered imaging study in blunt trauma evaluation. To determine: 1) the reasons physicians order chest X-ray studies (CXRs) in blunt trauma assessments; 2) what injuries they expect CXRs to reveal; and 3) whether physicians can accurately predict low likelihood of injury on CXR. At a Level I Trauma Center, we asked resident and attending physicians treating adult blunt trauma patients: 1) the primary reason(s) for getting CXRs; 2) what, if any, significant intrathoracic injuries (SITI) they expected CXRs to reveal; and 3) the likelihood of these injuries. An expert panel defined SITI as two or more rib fractures, sternal fracture, pulmonary contusion, pneumothorax, hemothorax, or aortic injury on official CXR readings. There were 484 patient encounters analyzed--65% of participating physicians were residents and 35% were attendings; 16 (3.3%) patients had SITI. The most common reasons for ordering CXRs were: "enough concern for significant injury" (62.9%) and belief that CXR is a "standard part of trauma work-up" (24.8%). Residents were more likely than attendings to cite "standard trauma work-up" (mean difference = 13.5%, p = 0.003). When physicians estimated a < 10% likelihood of SITI on CXR, 2.1% (95% confidence interval [CI] 1.0-4.1%) of patients had SITI; when they predicted a 10-25% likelihood, 5.7% (95% CI 1.2-15.7%) had SITI; and when they predicted a > 25% likelihood, 9.1% (95% CI 3.0-20.0%) had SITI. Physicians order CXRs in blunt trauma patients because they expect to find injuries and believe that CXRs are part of a "standard" work-up. Providers commonly do not expect CXRs to reveal SITI. When providers estimated low likelihood of SITI, the rate of SITI was very low. Published by Elsevier Inc.

Fecal immunochemical test for predicting mucosal healing in ulcerative colitis patients: A systematic review and meta-analysis.

PubMed

Dai, Cong; Jiang, Min; Sun, Ming-Jun; Cao, Qin

2018-05-01

Fecal immunochemical test (FIT) is a promising marker for assessment of inflammatory bowel disease activity. However, the utility of FIT for predicting mucosal healing (MH) of ulcerative colitis (UC) patients has yet to be clearly demonstrated. The objective of our study was to perform a diagnostic test accuracy test meta-analysis evaluating the diagnostic accuracy of FIT in predicting MH of UC patients. We systematically searched the databases from inception to November 2017 that evaluated MH in UC. The methodological quality of each study was assessed according to the Quality Assessment of Diagnostic Accuracy Studies checklist. The extracted data were pooled using a summary receiver operating characteristic curve model. Random-effects model was used to summarize the diagnostic odds ratio, sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio. Six studies comprising 625 UC patients were included in the meta-analysis. The pooled sensitivity and specificity values for predicting MH in UC were 0.77 (95% confidence interval [CI], 0.72-0.81) and 0.81 (95% CI, 0.76-0.85), respectively. The FIT level had a high rule-in value (positive likelihood ratio, 3.79; 95% CI, 2.85-5.03) and a moderate rule-out value (negative likelihood ratio, 0.26; 95% CI, 0.16-0.43) for predicting MH in UC. The results of the receiver operating characteristic curve analysis (area under the curve, 0.88; standard error of the mean, 0.02) and diagnostic odds ratio (18.08; 95% CI, 9.57-34.13) also revealed improved discrimination for identifying MH in UC with FIT concentration. Our meta-analysis has found that FIT is a simple, reliable non-invasive marker for predicting MH in UC patients. © 2018 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

Perceived Sexual Control, Sex-Related Alcohol Expectancies and Behavior Predict Substance-Related Sexual Revictimization

PubMed Central

Walsh, Kate; Messman-Moore, Terri; Zerubavel, Noga; Chandley, Rachel B.; DeNardi, Kathleen A.; Walker, Dave P.

2013-01-01

Objectives Although numerous studies have documented linkages between childhood sexual abuse (CSA) and later sexual revictimization, mechanisms underlying revictimization, particularly assaults occurring in the context of substance use, are not well-understood. Consistent with Traumagenic Dynamics theory, the present study tested a path model positing that lowered perceptions of sexual control resulting from CSA may be associated with increased sex-related alcohol expectancies and heightened likelihood of risky sexual behavior, which in turn, may predict adult substance-related rape. Methods Participants were 546 female college students who completed anonymous surveys regarding CSA and adult rape, perceptions of sexual control, sex-related alcohol expectancies, and likelihood of engaging in risky sexual behavior. Results The data fit the hypothesized model well and all hypothesized path coefficients were significant and in the expected directions. As expected, sex-related alcohol expectancies and likelihood of risky sexual behavior only predicted substance-related rape, not forcible rape. Conclusions Findings suggested that low perceived sexual control stemming from CSA is associated with increased sex-related alcohol expectancies and a higher likelihood of engaging in sexual behavior in the context of alcohol use. In turn these proximal risk factors heighten vulnerability to substance-related rape. Programs which aim to reduce risk for substance-related rape could be improved by addressing expectancies and motivations for risky sexual behavior in the context of substance use. Implications and future directions are discussed. PMID:23312991

SeqAPASS: Predicting chemical susceptibility to threatened/endangered species

EPA Science Inventory

Conservation of a molecular target across species can be used as a line-of-evidence to predict the likelihood of chemical susceptibility. The web-based Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS; https://seqapass.epa.gov/seqapass/) application was devel...

Evaluating the use of verbal probability expressions to communicate likelihood information in IPCC reports

NASA Astrophysics Data System (ADS)

Harris, Adam

2014-05-01

The Intergovernmental Panel on Climate Change (IPCC) prescribes that the communication of risk and uncertainty information pertaining to scientific reports, model predictions etc. be communicated with a set of 7 likelihood expressions. These range from "Extremely likely" (intended to communicate a likelihood of greater than 99%) through "As likely as not" (33-66%) to "Extremely unlikely" (less than 1%). Psychological research has investigated the degree to which these expressions are interpreted as intended by the IPCC, both within and across cultures. I will present a selection of this research and demonstrate some problems associated with communicating likelihoods in this way, as well as suggesting some potential improvements.

R-rated movies, bedroom televisions, and initiation of smoking by white and black adolescents.

PubMed

Jackson, Christine; Brown, Jane D; L'Engle, Kelly L

2007-03-01

To test movie exposure and television use as predictors of smoking initiation among white and black adolescents who had never smoked cigarettes. Survey research using audio computer-assisted self-interviews at baseline and at 2-year follow-up (2002-2004). Participants' homes located in central North Carolina. A sample of 735 12- to 14-year-old adolescents drawn from 14 public middle schools. Frequency of exposure to movies rated R, PG-13, PG, or G; frequency, location, and parental oversight of television viewing. Initiation of smoking, indicated by the first occasion of puffing on a cigarette. Among white adolescents, high relative exposure to R-rated movies predicted a significantly greater likelihood of smoking initiation at follow-up, and private access to television during early adolescence, indicated by having a bedroom television, was also a significant independent predictor of smoking initiation at follow-up. No significant associations were observed between any movie-exposure or television-use variables and likelihood of smoking among black adolescents. Indicators of risky media use were associated with a significantly greater likelihood of smoking for white but not for black adolescents. These results diverge strongly from past results, which have indicated that all adolescents, regardless of race or place of residence, have a higher risk of smoking initiation as their exposure to movie smoking increases. Research is needed to identify the antecedents of risky media use and to understand how audience attributes, including race and other factors, moderate the effects of risky media use on health-related behaviors.

Personality and adolescent pregnancy outcomes

PubMed Central

Harville, Emily W.; Madkour, Aubrey Spriggs; Xie, Yiqiong

2014-01-01

Aims To examine the relationship between personality, pregnancy and birth outcomes in adolescents Background Personality has been shown to be a strong predictor of many health outcomes. Adolescents who become pregnant have worse birth outcomes than adults. Design Cross-sectional study using data from the National Longitudinal Study of Adolescent Health (baseline, 1994-1995; follow-up, 2007-2008). Methods The study sample was 6529 girls, 820 of whom reported on pregnancy outcomes for a teenage birth. Personality data was taken from the Mini International Personality Item Pool personality tool, which measures the five-factor personality traits of neuroticism, conscientiousness, intellect/imagination, extraversion and agreeableness. Logistic regression was used to predict teen pregnancy and linear regression was used to predict birth weight and gestational age with adjustment for confounders and stratification by race. Results Agreeableness and intellect/imagination were associated with a reduced likelihood of becoming pregnant as an adolescent, while neuroticism, conscientiousness and extraversion were all associated with an increased likelihood of becoming pregnant. Higher neuroticism was associated with lower birth weight and gestational age among Black girls, but not non-Black. Conscientiousness was associated with lower gestational age among non-Black girls. No relationships were found with extraversion or agreeableness and birth outcomes. Receiving late or no prenatal care was associated with higher intellect/imagination. Conclusions Personality is understudied with respect to pregnancy and birth outcomes compared with other health outcomes. Such research could help professionals and clinicians design and target programs that best fit the characteristics of the population most likely to need them, such as those with high neuroticism. PMID:25040691

Crossing the Threshold From Porn Use to Porn Problem: Frequency and Modality of Porn Use as Predictors of Sexually Coercive Behaviors.

PubMed

Marshall, Ethan A; Miller, Holly A; Bouffard, Jeff A

2017-11-01

According to recent statistics, as many as one in five female college students are victims of sexual assault during their college career. To combat what has been called the "Campus Rape Crisis," researchers have attempted to understand what variables are associated with sexually coercive behaviors in college males. Although investigators have found support for the relationship between pornography consumption and sexually coercive behavior, researchers typically operationalize pornography use in terms of frequency of use. Furthermore, frequency of use has been assessed vaguely and inconsistently. The current study offered a more concrete assessment of frequency of use and an additional variable not yet included for pornography use: number of modalities. Beyond examining the relationship between pornography use and sexual coercion likelihood, the current study was the first to use pornography variables in a threshold analysis to test whether there is a cut point that is predictive of sexual coercion likelihood. Analyses were conducted with a sample of 463 college males. Results indicated that both pornography use variables were significantly related to a higher likelihood of sexually coercive behaviors. When both frequency of use and number of modalities were included in the model, modalities were significant and frequency was not. In addition, significant thresholds for both pornography variables that predicted sexual coercion likelihood were identified. These results imply that factors other than frequency of use, such as number of modalities, may be more important for the prediction of sexual coercive behaviors. Furthermore, threshold analyses revealed the most significant increase in risk occurred between one modality and two, indicating that it is not pornography use in general that is related to sexual coercion likelihood, but rather, specific aspects of pornography use.

Self-Concealment, Avoidance of Psychological Services, and Perceived Likelihood of Seeking Professional Help.

ERIC Educational Resources Information Center

Cepeda-Benito, Antonio; Short, Paul

1998-01-01

New information about the role of self-concealment in the decision to seek psychological services is investigated. Different types of distress selectively predict students' perceived likelihood of seeking help according to the problems for which help would be sought (N=732). Results are discussed in contrast to previous researchers' findings. (EMK)

Source and Message Factors in Persuasion: A Reply to Stiff's Critique of the Elaboration Likelihood Model.

ERIC Educational Resources Information Center

Petty, Richard E.; And Others

1987-01-01

Answers James Stiff's criticism of the Elaboration Likelihood Model (ELM) of persuasion. Corrects certain misperceptions of the ELM and criticizes Stiff's meta-analysis that compares ELM predictions with those derived from Kahneman's elastic capacity model. Argues that Stiff's presentation of the ELM and the conclusions he draws based on the data…

Likelihood Methods for Adaptive Filtering and Smoothing. Technical Report #455.

ERIC Educational Resources Information Center

Butler, Ronald W.

The dynamic linear model or Kalman filtering model provides a useful methodology for predicting the past, present, and future states of a dynamic system, such as an object in motion or an economic or social indicator that is changing systematically with time. Recursive likelihood methods for adaptive Kalman filtering and smoothing are developed.…

Indirect Bullying: Predictors of Teacher Intervention, and Outcome of a Pilot Educational Presentation about Impact on Adolescent Mental Health

ERIC Educational Resources Information Center

Dedousis-Wallace, Anna; Shute, Rosalyn H.

2009-01-01

We examined teacher characteristics predicting likelihood of intervening in indirect bullying (N=55) and piloted a 45-minute educational presentation about its mental health impact. Teachers' global empathy and perceived seriousness of indirect bullying vignettes were predictors of their likelihood of intervening, but knowledge of mental health…

Predicting the Likelihood of Going to Graduate School: The Importance of Locus of Control

ERIC Educational Resources Information Center

Nordstrom, Cynthia R.; Segrist, Dan J.

2009-01-01

Although many undergraduates apply to graduate school, only a fraction will be admitted. A question arises as to what factors relate to the likelihood of pursuing graduate studies. The current research examined this question by surveying students in a Careers in Psychology course. We hypothesized that GPA, a more internal locus of control…

An iterative procedure for obtaining maximum-likelihood estimates of the parameters for a mixture of normal distributions

NASA Technical Reports Server (NTRS)

Peters, B. C., Jr.; Walker, H. F.

1978-01-01

This paper addresses the problem of obtaining numerically maximum-likelihood estimates of the parameters for a mixture of normal distributions. In recent literature, a certain successive-approximations procedure, based on the likelihood equations, was shown empirically to be effective in numerically approximating such maximum-likelihood estimates; however, the reliability of this procedure was not established theoretically. Here, we introduce a general iterative procedure, of the generalized steepest-ascent (deflected-gradient) type, which is just the procedure known in the literature when the step-size is taken to be 1. We show that, with probability 1 as the sample size grows large, this procedure converges locally to the strongly consistent maximum-likelihood estimate whenever the step-size lies between 0 and 2. We also show that the step-size which yields optimal local convergence rates for large samples is determined in a sense by the 'separation' of the component normal densities and is bounded below by a number between 1 and 2.

An iterative procedure for obtaining maximum-likelihood estimates of the parameters for a mixture of normal distributions, 2

NASA Technical Reports Server (NTRS)

Peters, B. C., Jr.; Walker, H. F.

1976-01-01

The problem of obtaining numerically maximum likelihood estimates of the parameters for a mixture of normal distributions is addressed. In recent literature, a certain successive approximations procedure, based on the likelihood equations, is shown empirically to be effective in numerically approximating such maximum-likelihood estimates; however, the reliability of this procedure was not established theoretically. Here, a general iterative procedure is introduced, of the generalized steepest-ascent (deflected-gradient) type, which is just the procedure known in the literature when the step-size is taken to be 1. With probability 1 as the sample size grows large, it is shown that this procedure converges locally to the strongly consistent maximum-likelihood estimate whenever the step-size lies between 0 and 2. The step-size which yields optimal local convergence rates for large samples is determined in a sense by the separation of the component normal densities and is bounded below by a number between 1 and 2.

The skewed weak lensing likelihood: why biases arise, despite data and theory being sound

NASA Astrophysics Data System (ADS)

Sellentin, Elena; Heymans, Catherine; Harnois-Déraps, Joachim

2018-07-01

We derive the essentials of the skewed weak lensing likelihood via a simple hierarchical forward model. Our likelihood passes four objective and cosmology-independent tests which a standard Gaussian likelihood fails. We demonstrate that sound weak lensing data are naturally biased low, since they are drawn from a skewed distribution. This occurs already in the framework of Lambda cold dark matter. Mathematically, the biases arise because noisy two-point functions follow skewed distributions. This form of bias is already known from cosmic microwave background analyses, where the low multipoles have asymmetric error bars. Weak lensing is more strongly affected by this asymmetry as galaxies form a discrete set of shear tracer particles, in contrast to a smooth shear field. We demonstrate that the biases can be up to 30 per cent of the standard deviation per data point, dependent on the properties of the weak lensing survey and the employed filter function. Our likelihood provides a versatile framework with which to address this bias in future weak lensing analyses.

The skewed weak lensing likelihood: why biases arise, despite data and theory being sound.

NASA Astrophysics Data System (ADS)

Sellentin, Elena; Heymans, Catherine; Harnois-Déraps, Joachim

2018-04-01

We derive the essentials of the skewed weak lensing likelihood via a simple Hierarchical Forward Model. Our likelihood passes four objective and cosmology-independent tests which a standard Gaussian likelihood fails. We demonstrate that sound weak lensing data are naturally biased low, since they are drawn from a skewed distribution. This occurs already in the framework of ΛCDM. Mathematically, the biases arise because noisy two-point functions follow skewed distributions. This form of bias is already known from CMB analyses, where the low multipoles have asymmetric error bars. Weak lensing is more strongly affected by this asymmetry as galaxies form a discrete set of shear tracer particles, in contrast to a smooth shear field. We demonstrate that the biases can be up to 30% of the standard deviation per data point, dependent on the properties of the weak lensing survey and the employed filter function. Our likelihood provides a versatile framework with which to address this bias in future weak lensing analyses.

Pseudomonas aeruginosa dose response and bathing water infection.

PubMed

Roser, D J; van den Akker, B; Boase, S; Haas, C N; Ashbolt, N J; Rice, S A

2014-03-01

Pseudomonas aeruginosa is the opportunistic pathogen mostly implicated in folliculitis and acute otitis externa in pools and hot tubs. Nevertheless, infection risks remain poorly quantified. This paper reviews disease aetiologies and bacterial skin colonization science to advance dose-response theory development. Three model forms are identified for predicting disease likelihood from pathogen density. Two are based on Furumoto & Mickey's exponential 'single-hit' model and predict infection likelihood and severity (lesions/m2), respectively. 'Third-generation', mechanistic, dose-response algorithm development is additionally scoped. The proposed formulation integrates dispersion, epidermal interaction, and follicle invasion. The review also details uncertainties needing consideration which pertain to water quality, outbreaks, exposure time, infection sites, biofilms, cerumen, environmental factors (e.g. skin saturation, hydrodynamics), and whether P. aeruginosa is endogenous or exogenous. The review's findings are used to propose a conceptual infection model and identify research priorities including pool dose-response modelling, epidermis ecology and infection likelihood-based hygiene management.

Posterior Predictive Bayesian Phylogenetic Model Selection

PubMed Central

Lewis, Paul O.; Xie, Wangang; Chen, Ming-Hui; Fan, Yu; Kuo, Lynn

2014-01-01

We present two distinctly different posterior predictive approaches to Bayesian phylogenetic model selection and illustrate these methods using examples from green algal protein-coding cpDNA sequences and flowering plant rDNA sequences. The Gelfand–Ghosh (GG) approach allows dissection of an overall measure of model fit into components due to posterior predictive variance (GGp) and goodness-of-fit (GGg), which distinguishes this method from the posterior predictive P-value approach. The conditional predictive ordinate (CPO) method provides a site-specific measure of model fit useful for exploratory analyses and can be combined over sites yielding the log pseudomarginal likelihood (LPML) which is useful as an overall measure of model fit. CPO provides a useful cross-validation approach that is computationally efficient, requiring only a sample from the posterior distribution (no additional simulation is required). Both GG and CPO add new perspectives to Bayesian phylogenetic model selection based on the predictive abilities of models and complement the perspective provided by the marginal likelihood (including Bayes Factor comparisons) based solely on the fit of competing models to observed data. [Bayesian; conditional predictive ordinate; CPO; L-measure; LPML; model selection; phylogenetics; posterior predictive.] PMID:24193892

Measures of accuracy and performance of diagnostic tests.

PubMed

Drobatz, Kenneth J

2009-05-01

Diagnostic tests are integral to the practice of veterinary cardiology, any other specialty, and general veterinary medicine. Developing and understanding diagnostic tests is one of the cornerstones of clinical research. This manuscript describes the diagnostic test properties including sensitivity, specificity, predictive value, likelihood ratio, receiver operating characteristic curve. Review of practical book chapters and standard statistics manuscripts. Diagnostics such as sensitivity, specificity, predictive value, likelihood ratio, and receiver operating characteristic curve are described and illustrated. Basic understanding of how diagnostic tests are developed and interpreted is essential in reviewing clinical scientific papers and understanding evidence based medicine.

Bias correction in the hierarchical likelihood approach to the analysis of multivariate survival data.

PubMed

Jeon, Jihyoun; Hsu, Li; Gorfine, Malka

2012-07-01

Frailty models are useful for measuring unobserved heterogeneity in risk of failures across clusters, providing cluster-specific risk prediction. In a frailty model, the latent frailties shared by members within a cluster are assumed to act multiplicatively on the hazard function. In order to obtain parameter and frailty variate estimates, we consider the hierarchical likelihood (H-likelihood) approach (Ha, Lee and Song, 2001. Hierarchical-likelihood approach for frailty models. Biometrika 88, 233-243) in which the latent frailties are treated as "parameters" and estimated jointly with other parameters of interest. We find that the H-likelihood estimators perform well when the censoring rate is low, however, they are substantially biased when the censoring rate is moderate to high. In this paper, we propose a simple and easy-to-implement bias correction method for the H-likelihood estimators under a shared frailty model. We also extend the method to a multivariate frailty model, which incorporates complex dependence structure within clusters. We conduct an extensive simulation study and show that the proposed approach performs very well for censoring rates as high as 80%. We also illustrate the method with a breast cancer data set. Since the H-likelihood is the same as the penalized likelihood function, the proposed bias correction method is also applicable to the penalized likelihood estimators.

Is it possible to predict office hysteroscopy failure?

PubMed

Cobellis, Luigi; Castaldi, Maria Antonietta; Giordano, Valentino; De Franciscis, Pasquale; Signoriello, Giuseppe; Colacurci, Nicola

2014-10-01

The purpose of this study was to develop a clinical tool, the HFI (Hysteroscopy Failure Index), which gives criteria to predict hysteroscopic examination failure. This was a retrospective diagnostic test study, aimed to validate the HFI, set at the Department of Gynaecology, Obstetric and Reproductive Science of the Second University of Naples, Italy. The HFI was applied to our database of 995 consecutive women, who underwent office based to assess abnormal uterine bleeding (AUB), infertility, cervical polyps, and abnormal sonographic patterns (postmenopausal endometrial thickness of more than 5mm, endometrial hyperechogenic spots, irregular endometrial line, suspect of uterine septa). Demographic characteristics, previous surgery, recurrent infections, sonographic data, Estro-Progestins, IUD and menopausal status were collected. Receiver operating characteristic (ROC) curve analysis was used to assess the ability of the model to identify patients who were correctly identified (true positives) divided by the total number of failed hysteroscopies (true positives+false negatives). Positive and Negative Likelihood Ratios with 95%CI were calculated. The HFI score is able to predict office hysteroscopy failure in 76% of cases. Moreover, the Positive likelihood ratio was 11.37 (95% CI: 8.49-15.21), and the Negative likelihood ratio was 0.33 (95% CI: 0.27-0.41). Hysteroscopy failure index was able to retrospectively predict office hysteroscopy failure. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Likelihood of achieving air quality targets under model uncertainties.

PubMed

Digar, Antara; Cohan, Daniel S; Cox, Dennis D; Kim, Byeong-Uk; Boylan, James W

2011-01-01

Regulatory attainment demonstrations in the United States typically apply a bright-line test to predict whether a control strategy is sufficient to attain an air quality standard. Photochemical models are the best tools available to project future pollutant levels and are a critical part of regulatory attainment demonstrations. However, because photochemical models are uncertain and future meteorology is unknowable, future pollutant levels cannot be predicted perfectly and attainment cannot be guaranteed. This paper introduces a computationally efficient methodology for estimating the likelihood that an emission control strategy will achieve an air quality objective in light of uncertainties in photochemical model input parameters (e.g., uncertain emission and reaction rates, deposition velocities, and boundary conditions). The method incorporates Monte Carlo simulations of a reduced form model representing pollutant-precursor response under parametric uncertainty to probabilistically predict the improvement in air quality due to emission control. The method is applied to recent 8-h ozone attainment modeling for Atlanta, Georgia, to assess the likelihood that additional controls would achieve fixed (well-defined) or flexible (due to meteorological variability and uncertain emission trends) targets of air pollution reduction. The results show that in certain instances ranking of the predicted effectiveness of control strategies may differ between probabilistic and deterministic analyses.

A Large-scale Cross-sectional Study of ALK Rearrangements and EGFR Mutations in Non-small-cell Lung Cancer in Chinese Han Population

PubMed Central

Hong, Shaodong; Fang, Wenfeng; Hu, Zhihuang; Zhou, Ting; Yan, Yue; Qin, Tao; Tang, Yanna; Ma, Yuxiang; Zhao, Yuanyuan; Xue, Cong; Huang, Yan; Zhao, Hongyun; Zhang, Li

2014-01-01

The predictive power of age at diagnosis and smoking history for ALK rearrangements and EGFR mutations in non-small-cell lung cancer (NSCLC) remains not fully understood. In this cross-sectional study, 1160 NSCLC patients were prospectively enrolled and genotyped for EML4-ALK rearrangements and EGFR mutations. Multivariate logistic regression analysis was performed to explore the association between clinicopathological features and these two genetic aberrations. Receiver operating characteristic (ROC) curves methodology was applied to evaluate the predictive value. We showed that younger age at diagnosis was the only independent variable associated with EML4-ALK rearrangements (odds ratio (OR) per 5 years' increment, 0.68; p < 0.001), while lower tobacco exposure (OR per 5 pack-years' increment, 0.88; p < 0.001), adenocarcinoma (OR, 6.61; p < 0.001), and moderate to high differentiation (OR, 2.05; p < 0.001) were independently associated with EGFR mutations. Age at diagnosis was a very strong predictor of ALK rearrangements but poorly predicted EGFR mutations, while smoking pack-years may predict the presence of EGFR mutations and ALK rearrangements but with rather limited power. These findings should assist clinicians in assessing the likelihood of EML4-ALK rearrangements and EGFR mutations and understanding their biological implications in NSCLC. PMID:25434695

Phase distribution of spliceosomal introns: implications for intron origin

PubMed Central

Nguyen, Hung D; Yoshihama, Maki; Kenmochi, Naoya

2006-01-01

Background The origin of spliceosomal introns is the central subject of the introns-early versus introns-late debate. The distribution of intron phases is non-uniform, with an excess of phase-0 introns. Introns-early explains this by speculating that a fraction of present-day introns were present between minigenes in the progenote and therefore must lie in phase-0. In contrast, introns-late predicts that the nonuniformity of intron phase distribution reflects the nonrandomness of intron insertions. Results In this paper, we tested the two theories using analyses of intron phase distribution. We inferred the evolution of intron phase distribution from a dataset of 684 gene orthologs from seven eukaryotes using a maximum likelihood method. We also tested whether the observed intron phase distributions from 10 eukaryotes can be explained by intron insertions on a genome-wide scale. In contrast to the prediction of introns-early, the inferred evolution of intron phase distribution showed that the proportion of phase-0 introns increased over evolution. Consistent with introns-late, the observed intron phase distributions matched those predicted by an intron insertion model quite well. Conclusion Our results strongly support the introns-late hypothesis of the origin of spliceosomal introns. PMID:16959043

Associated Information Increases Subjective Perception of Duration.

PubMed

Schweitzer, Richard; Trapp, Sabrina; Bar, Moshe

2017-08-01

Our sense of time is prone to various biases. For instance, one factor that can dilate an event's perceived duration is the violation of predictions; when a series of repeated stimuli is interrupted by an unpredictable oddball. On the other hand, when the probability of a repetition itself is manipulated, predictable conditions can also increase estimated duration. This suggests that manipulations of expectations have different or even opposing effects on time perception. In previous studies, expectations were generated because stimuli were repeated or because the likelihood of a sequence or a repetition was varied. In the natural environment, however, expectations are often built via associative processes, for example, the context of a kitchen promotes the expectation of plates, appliances, and other associated objects. Here, we manipulated such association-based expectations by using oddballs that were either contextually associated or nonassociated with the standard items. We find that duration was more strongly overestimated for contextually associated oddballs. We reason that top-down attention is biased toward associated information, and thereby dilates subjective duration for associated oddballs. Based on this finding, we propose an interplay between top-down attention and predictive processing in the perception of time.

Thought-action fusion and its relationship to schizotypy and OCD symptoms.

PubMed

Lee, Han-Joo; Cougle, Jesse R; Telch, Michael J

2005-01-01

Thought-action fusion (TAF) is a cognitive bias that has been linked to obsessive-compulsive disorder (OCD). Preliminary evidence suggests schizotypal traits may be associated with some types of OCD obsessions but not others. We examined the relationship between each of the two major types of TAF (i.e., likelihood and moral), schizotypal traits, and OCD symptoms in 969 nonclinical undergraduate students. We hypothesized that likelihood TAF would be associated with schizotypal traits; whereas moral TAF would not. Consistent with prediction, schizotypal-magical thinking was significantly associated with likelihood TAF even after controlling for the effects of OCD symptoms, general anxiety, and depression. Moreover, the relationship between likelihood TAF and OCD symptoms was significantly attenuated after controlling for schizotypal traits. In contrast, moral TAF demonstrated negligible association with OCD symptoms, depression, or schizotypal traits. These findings provide preliminary support for the linkage between likelihood TAF and schizotypal traits.

Investigating the role of executive attentional control to self-harm in a non-clinical cohort with borderline personality features

PubMed Central

Drabble, Jennifer; Bowles, David P.; Barker, Lynne Ann

2014-01-01

Self-injurious behavior (or self-harm) is a frequently reported maladaptive behavior in the general population and a key feature of borderline personality disorder (BPD). Poor affect regulation is strongly linked to a propensity to self-harm, is a core component of BPD, and is linked with reduced attentional control abilities. The idea that attentional control difficulties may provide a link between BPD, negative affect and self-harm has yet to be established, however. The present study explored the putative relationship between levels of BPD features, three aspects of attentional/executive control, affect, and self-harm history in a sample of 340 non-clinical participants recruited online from self-harm forums and social networking sites. Analyses showed that self-reported levels of BPD features and attentional focusing predicted self-harm incidence, and high attentional focusing increased the likelihood of a prior self-harm history in those with high BPD features. Ability to shift attention was associated with a reduced likelihood of self-harm, suggesting that good attentional switching ability may provide a protective buffer against self-harm behavior for some individuals. These attentional control differences mediated the association between negative affect and self-harm, but the relationship between BPD and self-harm appears independent. PMID:25191235

How Broad Liberal Arts Training Produces Phd Economists: Carleton's Story

ERIC Educational Resources Information Center

Bourne, Jenny; Grawe, Nathan D.

2015-01-01

Several recent studies point to strong performance in economics PhD programs of graduates from liberal arts colleges. While every undergraduate program is unique and the likelihood of selection bias combines with small sample sizes to caution against drawing strong conclusions, the authors reflect on their experience at Carleton College to…

Perceived sexual control, sex-related alcohol expectancies and behavior predict substance-related sexual revictimization.

PubMed

Walsh, Kate; Messman-Moore, Terri; Zerubavel, Noga; Chandley, Rachel B; Denardi, Kathleen A; Walker, Dave P

2013-05-01

Although numerous studies have documented linkages between childhood sexual abuse (CSA) and later sexual revictimization, mechanisms underlying revictimization, particularly assaults occurring in the context of substance use, are not well-understood. Consistent with Traumagenic Dynamics theory, the present study tested a path model positing that lowered perceptions of sexual control resulting from CSA may be associated with increased sex-related alcohol expectancies and heightened likelihood of risky sexual behavior, which in turn, may predict adult substance-related rape. Participants were 546 female college students who completed anonymous surveys regarding CSA and adult rape, perceptions of sexual control, sex-related alcohol expectancies, and likelihood of engaging in risky sexual behavior. The data fit the hypothesized model well and all hypothesized path coefficients were significant and in the expected directions. As expected, sex-related alcohol expectancies and likelihood of risky sexual behavior only predicted substance-related rape, not forcible rape. Findings suggested that low perceived sexual control stemming from CSA is associated with increased sex-related alcohol expectancies and a higher likelihood of engaging in sexual behavior in the context of alcohol use. In turn these proximal risk factors heighten vulnerability to substance-related rape. Programs which aim to reduce risk for substance-related rape could be improved by addressing expectancies and motivations for risky sexual behavior in the context of substance use. Implications and future directions are discussed. Copyright © 2012 Elsevier Ltd. All rights reserved.

[Waist-to-height ratio is an indicator of metabolic risk in children].

PubMed

Valle-Leal, Jaime; Abundis-Castro, Leticia; Hernández-Escareño, Juan; Flores-Rubio, Salvador

2016-01-01

Abdominal fat, particularly visceral, is associated with a high risk of metabolic complications. The waist-height ratio (WHtR) is used to assess abdominal fat in individuals of all ages. To determine the ability of the waist-to-height ratio to detect metabolic risk in mexican schoolchildren. A study was conducted on children between 6 and 12 years. Obesity was diagnosed as a body mass index (BMI) ≥ 85th percentile, and an ICE ≥0.5 was considered abdominal obesity. Blood levels of glucose, cholesterol and triglycerides were measured. The sensitivity, specificity, positive predictive and negative value, area under curve, the positive likelihood ratio and negative likelihood ratio of the WHtR and BMI were calculated in order to identify metabolic alterations. WHtR and BMI were compared to determine which had the best diagnostic efficiency. Of the 223 children included in the study, 51 had hypertriglyceridaemia, 27 with hypercholesterolaemia, and 9 with hyperglycaemia. On comparing the diagnostic efficiency of WHtR with that of BMI, there was a sensitivity of 100% vs. 56% for hyperglycaemia, 93 vs. 70% for cholesterol, and 76 vs. 59% for hypertriglyceridaemia. The specificity, negative predictive value, positive predictive value, positive likelihood ratio, negative likelihood ratio, and area under curve were also higher for WHtR. The WHtR is a more efficient indicator than BMI in identifying metabolic risk in mexican school-age. Copyright © 2015 Sociedad Chilena de Pediatría. Publicado por Elsevier España, S.L.U. All rights reserved.

Social Capital and International Migration from Latin America

PubMed Central

Massey, Douglas S.; Aysa-Lastra, María

2011-01-01

We combine data from the Latin American Migration Project and the Mexican Migration Project to estimate models predicting the likelihood of taking of first and later trips to the United States from five nations: Mexico, the Dominican Republic, Costa Rica, Nicaragua, and Peru. The models test specific hypotheses about the effects of social capital on international migration and how these effects vary with respect to contextual factors. Our findings confirm the ubiquity of migrant networks and the universality of social capital effects throughout Latin America. They also reveal how the sizes of these effects are not uniform across settings. Social capital operates more powerfully on first as opposed to later trips and interacts with the cost of migration. In addition, effects are somewhat different when considering individual social capital (measuring strong ties) and community social capital (measuring weak ties). On first trips, the effect of strong ties in promoting migration increases with distance whereas the effect of weak ties decreases with distance. On later trips, the direction of effects for both individual and community social capital is negative for long distances but positive for short distances. PMID:21915379

Why Do Drivers Use Mobile Phones While Driving? The Contribution of Compensatory Beliefs.

PubMed

Zhou, Ronggang; Yu, Mengli; Wang, Xinyi

2016-01-01

The current study is the first to investigate the contribution of compensatory beliefs (i.e., the belief that the negative effects of an unsafe behavior can be "neutralized" by engaging in another safe behavior; e.g., "I can use a mobile phone now because I will slow down ") on drivers' mobile phone use while driving. The effects of drivers' personal characteristics on compensatory beliefs, mobile phone use and self-regulatory behaviors were also examined. A series of questions were administered to drivers, which included (1) personal measures, (2) scales that measured compensatory beliefs generally in substance use and with regard to driving safety, and (3) questions to measure drivers' previous primary mobile phone usage and corresponding self-regulatory actions. Overall, drivers reported a low likelihood of compensatory beliefs, prior mobile phone use, and a strong frequency of self-regulatory behaviors. Respondents who had a higher tendency toward compensatory beliefs reported more incidents or crash involvement caused by making or answering calls and sending or reading messages. The findings provide strong support for the contribution of compensatory beliefs in predicting mobile phone usage in the context of driving. Compensatory beliefs can explain 41% and 43% of the variance in the active activities of making calls and texting/sending messages compared with 18% and 31% of the variance in the passive activities of answering calls and reading messages. Among the regression models for predicting self-regulatory behaviors at the tactical or operational level, compensatory beliefs emerge as significant predictors only in predicting shorter conversations while on a call. The findings and limitations of the current study are discussed.

The use of early summer mosquito surveillance to predict late summer West Nile virus activity

USGS Publications Warehouse

Ginsberg, Howard S.; Rochlin, Ilia; Campbell, Scott R.

2010-01-01

Utility of early-season mosquito surveillance to predict West Nile virus activity in late summer was assessed in Suffolk County, NY. Dry ice-baited CDC miniature light traps paired with gravid traps were set weekly. Maximum-likelihood estimates of WNV positivity, minimum infection rates, and % positive pools were generally well correlated. However, positivity in gravid traps was not correlated with positivity in CDC light traps. The best early-season predictors of WNV activity in late summer (estimated using maximum-likelihood estimates of Culex positivity in August and September) were early date of first positive pool, low numbers of mosquitoes in July, and low numbers of mosquito species in July. These results suggest that early-season entomological samples can be used to predict WNV activity later in the summer, when most human cases are acquired. Additional research is needed to establish which surveillance variables are most predictive and to characterize the reliability of the predictions.

Individualized relapse prediction: Personality measures and striatal and insular activity during reward-processing robustly predict relapse.

PubMed

Gowin, Joshua L; Ball, Tali M; Wittmann, Marc; Tapert, Susan F; Paulus, Martin P

2015-07-01

Nearly half of individuals with substance use disorders relapse in the year after treatment. A diagnostic tool to help clinicians make decisions regarding treatment does not exist for psychiatric conditions. Identifying individuals with high risk for relapse to substance use following abstinence has profound clinical consequences. This study aimed to develop neuroimaging as a robust tool to predict relapse. 68 methamphetamine-dependent adults (15 female) were recruited from 28-day inpatient treatment. During treatment, participants completed a functional MRI scan that examined brain activation during reward processing. Patients were followed 1 year later to assess abstinence. We examined brain activation during reward processing between relapsing and abstaining individuals and employed three random forest prediction models (clinical and personality measures, neuroimaging measures, a combined model) to generate predictions for each participant regarding their relapse likelihood. 18 individuals relapsed. There were significant group by reward-size interactions for neural activation in the left insula and right striatum for rewards. Abstaining individuals showed increased activation for large, risky relative to small, safe rewards, whereas relapsing individuals failed to show differential activation between reward types. All three random forest models yielded good test characteristics such that a positive test for relapse yielded a likelihood ratio 2.63, whereas a negative test had a likelihood ratio of 0.48. These findings suggest that neuroimaging can be developed in combination with other measures as an instrument to predict relapse, advancing tools providers can use to make decisions about individualized treatment of substance use disorders. Published by Elsevier Ireland Ltd.

Emotional predictors of bowel screening: the avoidance-promoting role of fear, embarrassment, and disgust.

PubMed

Reynolds, Lisa M; Bissett, Ian P; Consedine, Nathan S

2018-05-03

Despite considerable efforts to address practical barriers, colorectal cancer screening numbers are often low. People do not always act rationally, and investigating emotions may offer insight into the avoidance of screening. The current work assessed whether fear, embarrassment, and disgust predicted colorectal cancer screening avoidance. A community sample (N = 306) aged 45+ completed a questionnaire assessing colorectal cancer screening history and the extent that perceptions of cancer risk, colorectal cancer knowledge, doctor discussions, and a specifically developed scale, the Emotional Barriers to Bowel Screening (EBBS), were associated with previous screening behaviours and anticipated bowel health decision-making. Step-wise logistic regression models revealed that a decision to delay seeking healthcare in the hypothetical presence of bowel symptoms was less likely in people who had discussed risk with their doctor, whereas greater colorectal cancer knowledge and greater fear of a negative outcome predicted greater likelihood of delay. Having previously provided a faecal sample was predicted by discussions about risk with a doctor, older age, and greater embarrassment, whereas perceptions of lower risk predicted a lower likelihood. Likewise, greater insertion disgust predicted a lower likelihood of having had an invasive bowel screening test in the previous 5 years. Alongside medical and demographic factors, fear, embarrassment and disgust are worthy of consideration in colorectal cancer screening. Understanding how specific emotions impact screening decisions and behaviour is an important direction for future work and has potential to inform screening development and communications in bowel health.

Development and validation of a cancer-specific swallowing assessment tool: MASA-C.

PubMed

Carnaby, Giselle D; Crary, Michael A

2014-03-01

We present data from a sample of patients receiving radiotherapy for head/neck cancer to define and measure the validity of a new clinical assessment measure for swallowing. Fifty-eight patients undergoing radiotherapy (±chemotherapy) for head/neck cancer (HNC) supported the development of a physiology-based assessment tool of swallowing (Mann Assessment of Swallowing Ability--Cancer: MASA-C) administered at two time points (baseline and following radiotherapy treatment). The new exam was evaluated for internal consistency of items using Cronbach's alpha. Reliability of measurement was evaluated with intraclass correlation (ICC) and the Kappa statistic between two independent raters. Concurrent validity was established through comparison with the original MASA examination and against the referent standard videofluoroscopic swallowing examination (VFE). Sensitivity, specificity, and likelihood ratios along with 95 % confidence intervals (CIs) were derived for comparison of the two evaluation forms (MASA vs. MASA-C). Accuracy of diagnostic precision was displayed using receiver operator characteristic curves. The new MASA-C tool demonstrated superior validity to the original MASA examination applied to a HNC population. In comparison to the VFE referent exam, the MASA-C revealed strong sensitivity and specificity (Se 83, Sp 96), predictive values (positive predictive value (PPV) 0.95, negative predictive value (NPV) 0.86), and likelihood ratios (21.6). In addition, it demonstrated good reliability (ICC = 0.96) between speech-language pathology raters. The MASA-C is a reliable and valid scale that is sensitive to differences in swallowing performance in HNC patients with and without dysphagia. Future longitudinal evaluation of this tool in larger samples is suggested. The development and refinement of this swallowing assessment tool for use in multidisciplinary HNC teams will facilitate earlier identification of patients with swallowing difficulties and enable more efficient allocation of resources to the management of dysphagia in this population. The MASA-C may also prove useful in future clinical HNC rehabilitation trials with this population.

A Complex Story: Universal Preference vs. Individual Differences Shaping Aesthetic Response to Fractals Patterns.

PubMed

Street, Nichola; Forsythe, Alexandra M; Reilly, Ronan; Taylor, Richard; Helmy, Mai S

2016-01-01

Fractal patterns offer one way to represent the rough complexity of the natural world. Whilst they dominate many of our visual experiences in nature, little large-scale perceptual research has been done to explore how we respond aesthetically to these patterns. Previous research (Taylor et al., 2011) suggests that the fractal patterns with mid-range fractal dimensions (FDs) have universal aesthetic appeal. Perceptual and aesthetic responses to visual complexity have been more varied with findings suggesting both linear (Forsythe et al., 2011) and curvilinear (Berlyne, 1970) relationships. Individual differences have been found to account for many of the differences we see in aesthetic responses but some, such as culture, have received little attention within the fractal and complexity research fields. This two-study article aims to test preference responses to FD and visual complexity, using a large cohort (N = 443) of participants from around the world to allow universality claims to be tested. It explores the extent to which age, culture and gender can predict our preferences for fractally complex patterns. Following exploratory analysis that found strong correlations between FD and visual complexity, a series of linear mixed-effect models were implemented to explore if each of the individual variables could predict preference. The first tested a linear complexity model (likelihood of selecting the more complex image from the pair of images) and the second a mid-range FD model (likelihood of selecting an image within mid-range). Results show that individual differences can reliably predict preferences for complexity across culture, gender and age. However, in fitting with current findings the mid-range models show greater consistency in preference not mediated by gender, age or culture. This article supports the established theory that the mid-range fractal patterns appear to be a universal construct underlying preference but also highlights the fragility of universal claims by demonstrating individual differences in preference for the interrelated concept of visual complexity. This highlights a current stalemate in the field of empirical aesthetics.

Validation of a Previously Developed Geospatial Model That Predicts the Prevalence of Listeria monocytogenes in New York State Produce Fields

PubMed Central

Weller, Daniel; Shiwakoti, Suvash; Bergholz, Peter; Grohn, Yrjo; Wiedmann, Martin

2015-01-01

Technological advancements, particularly in the field of geographic information systems (GIS), have made it possible to predict the likelihood of foodborne pathogen contamination in produce production environments using geospatial models. Yet, few studies have examined the validity and robustness of such models. This study was performed to test and refine the rules associated with a previously developed geospatial model that predicts the prevalence of Listeria monocytogenes in produce farms in New York State (NYS). Produce fields for each of four enrolled produce farms were categorized into areas of high or low predicted L. monocytogenes prevalence using rules based on a field's available water storage (AWS) and its proximity to water, impervious cover, and pastures. Drag swabs (n = 1,056) were collected from plots assigned to each risk category. Logistic regression, which tested the ability of each rule to accurately predict the prevalence of L. monocytogenes, validated the rules based on water and pasture. Samples collected near water (odds ratio [OR], 3.0) and pasture (OR, 2.9) showed a significantly increased likelihood of L. monocytogenes isolation compared to that for samples collected far from water and pasture. Generalized linear mixed models identified additional land cover factors associated with an increased likelihood of L. monocytogenes isolation, such as proximity to wetlands. These findings validated a subset of previously developed rules that predict L. monocytogenes prevalence in produce production environments. This suggests that GIS and geospatial models can be used to accurately predict L. monocytogenes prevalence on farms and can be used prospectively to minimize the risk of preharvest contamination of produce. PMID:26590280

Predicting damage in concrete due to expansive aggregates : modeling to enable sustainable material design.

DOT National Transportation Integrated Search

2012-04-01

A poroelastic model is developed that can predict stress and strain distributions and, thus, ostensibly : damage likelihood in concrete under freezing conditions caused by aggregates with undesirable : combinations of geometry and constitutive proper...

Testing the Predictive Power of Coulomb Stress on Aftershock Sequences

NASA Astrophysics Data System (ADS)

Woessner, J.; Lombardi, A.; Werner, M. J.; Marzocchi, W.

2009-12-01

Empirical and statistical models of clustered seismicity are usually strongly stochastic and perceived to be uninformative in their forecasts, since only marginal distributions are used, such as the Omori-Utsu and Gutenberg-Richter laws. In contrast, so-called physics-based aftershock models, based on seismic rate changes calculated from Coulomb stress changes and rate-and-state friction, make more specific predictions: anisotropic stress shadows and multiplicative rate changes. We test the predictive power of models based on Coulomb stress changes against statistical models, including the popular Short Term Earthquake Probabilities and Epidemic-Type Aftershock Sequences models: We score and compare retrospective forecasts on the aftershock sequences of the 1992 Landers, USA, the 1997 Colfiorito, Italy, and the 2008 Selfoss, Iceland, earthquakes. To quantify predictability, we use likelihood-based metrics that test the consistency of the forecasts with the data, including modified and existing tests used in prospective forecast experiments within the Collaboratory for the Study of Earthquake Predictability (CSEP). Our results indicate that a statistical model performs best. Moreover, two Coulomb model classes seem unable to compete: Models based on deterministic Coulomb stress changes calculated from a given fault-slip model, and those based on fixed receiver faults. One model of Coulomb stress changes does perform well and sometimes outperforms the statistical models, but its predictive information is diluted, because of uncertainties included in the fault-slip model. Our results suggest that models based on Coulomb stress changes need to incorporate stochastic features that represent model and data uncertainty.

The predictive consequences of parameterization

NASA Astrophysics Data System (ADS)

White, J.; Hughes, J. D.; Doherty, J. E.

2013-12-01

In numerical groundwater modeling, parameterization is the process of selecting the aspects of a computer model that will be allowed to vary during history matching. This selection process is dependent on professional judgment and is, therefore, inherently subjective. Ideally, a robust parameterization should be commensurate with the spatial and temporal resolution of the model and should include all uncertain aspects of the model. Limited computing resources typically require reducing the number of adjustable parameters so that only a subset of the uncertain model aspects are treated as estimable parameters; the remaining aspects are treated as fixed parameters during history matching. We use linear subspace theory to develop expressions for the predictive error incurred by fixing parameters. The predictive error is comprised of two terms. The first term arises directly from the sensitivity of a prediction to fixed parameters. The second term arises from prediction-sensitive adjustable parameters that are forced to compensate for fixed parameters during history matching. The compensation is accompanied by inappropriate adjustment of otherwise uninformed, null-space parameter components. Unwarranted adjustment of null-space components away from prior maximum likelihood values may produce bias if a prediction is sensitive to those components. The potential for subjective parameterization choices to corrupt predictions is examined using a synthetic model. Several strategies are evaluated, including use of piecewise constant zones, use of pilot points with Tikhonov regularization and use of the Karhunen-Loeve transformation. The best choice of parameterization (as defined by minimum error variance) is strongly dependent on the types of predictions to be made by the model.

Reorganization of interaction networks modulates the persistence of species in late successional stages.

PubMed

Saavedra, Serguei; Cenci, Simone; Del-Val, Ek; Boege, Karina; Rohr, Rudolf P

2017-09-01

Ecological interaction networks constantly reorganize as interspecific interactions change across successional stages and environmental gradients. This reorganization can also be associated with the extent to which species change their preference for types of niches available in their local sites. Despite the pervasiveness of these interaction changes, previous studies have revealed that network reorganizations have a minimal or insignificant effect on global descriptors of network architecture, such as connectance, modularity and nestedness. However, little is known about whether these reorganizations may have an effect on community dynamics and composition. To answer the question above, we study the multi-year dynamics and reorganization of plant-herbivore interaction networks across secondary successional stages of a tropical dry forest. We develop new quantitative tools based on a structural stability approach to estimate the potential impact of network reorganization on species persistence. Then, we investigate whether this impact can explain the likelihood of persistence of herbivore species in the observed communities. We find that resident (early-arriving) herbivore species increase their likelihood of persistence across time and successional stages. Importantly, we demonstrate that, in late successional stages, the reorganization of interactions among resident species has a strong inhibitory effect on the likelihood of persistence of colonizing (late-arriving) herbivores. These findings support earlier predictions suggesting that, in mature communities, changes of species interactions can act as community-control mechanisms (also known as priority effects). Furthermore, our results illustrate that the dynamics and composition of ecological communities cannot be fully understood without attention to their reorganization processes, despite the invariability of global network properties. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

Effects of Contextual Predictability and Transitional Probability on Eye Movements During Reading

ERIC Educational Resources Information Center

Frisson, Steven; Rayner, Keith; Pickering, Martin J.

2005-01-01

In 2 eye-movement experiments, the authors tested whether transitional probability (the statistical likelihood that a word precedes or follows another word) affects reading times and whether this occurs independently from contextual predictability effects. Experiment 1 showed early effects of predictability, replicating S. A. McDonald and R. C.…

Undernutrition among adults in India: the significance of individual-level and contextual factors impacting on the likelihood of underweight across sub-populations.

PubMed

Siddiqui, Md Zakaria; Donato, Ronald

2017-01-01

To investigate the extent to which individual-level as well as macro-level contextual factors influence the likelihood of underweight across adult sub-populations in India. Population-based cross-sectional survey included in India's National Health Family Survey conducted in 2005-06. We disaggregated into eight sub-populations. Multistage nationally representative household survey covering 99 % of India's population. The survey covered 124 385 females aged 15-49 years and 74 369 males aged 15-54 years. A social gradient in underweight exists in India. Even after allowing for wealth status, differences in the predicted probability of underweight persisted based upon rurality, age/maturity and gender. We found individual-level education lowered the likelihood of underweight for males, but no statistical association for females. Paradoxically, rural young (15-24 years) females from more educated villages had a higher likelihood of underweight relative to those in less educated villages; but for rural mature (>24 years) females the opposite was the case. Christians had a significantly lower likelihood of underweight relative to other socio-religious groups (OR=0·53-0·80). Higher state-level inequality increased the likelihood of underweight across most population groups, while neighbourhood inequality exhibited a similar relationship for the rural young population subgroups only. Individual states/neighbourhoods accounted for 5-9 % of the variation in the prediction of underweight. We found that rural young females represent a particularly highly vulnerable sub-population. Economic growth alone is unlikely to reduce the burden of malnutrition in India; accordingly, policy makers need to address the broader social determinants that contribute to higher underweight prevalence in specific demographic subgroups.

Defining thresholds of specific IgE levels to grass pollen and birch pollen allergens improves clinical interpretation.

PubMed

Van Hoeyveld, Erna; Nickmans, Silvie; Ceuppens, Jan L; Bossuyt, Xavier

2015-10-23

Cut-off values and predictive values are used for the clinical interpretation of specific IgE antibody results. However, cut-off levels are not well defined, and predictive values are dependent on the prevalence of disease. The objective of this study was to document clinically relevant diagnostic accuracy of specific IgE for inhalant allergens (grass pollen and birch pollen) based on test result interval-specific likelihood ratios. Likelihood ratios are independent of the prevalence and allow to provide diagnostic accuracy information for test result intervals. In a prospective study we included consecutive adult patients presenting at an allergy clinic with complaints of rhinitis or rhinoconjunctivitis. The standard for diagnosis was a suggestive clinical history of grass or birch pollen allergy and a positive skin test. Specific IgE was determined with the ImmunoCAP Fluorescence Enzyme Immuno-Assay. We established specific IgE test result interval related likelihood ratios for clinical allergy to inhalant allergens (grass pollen, rPhl p 1,5, birch pollen, rBet v 1). The likelihood ratios for allergy increased with increasing specific IgE antibody levels. The likelihood ratio was <0.03 for specific IgE <0.1 kU/L, between 0.1 and 1.4 for specific IgE between 0.1 kU/L and 0.35 kU/L, between 1.4 and 4.2 for specific IgE between 0.35 kU/L and 3.5 kU/L, >6.3 for specific IgE>0.7, and very high (∞) for specific IgE >3.5 kU/L. Test result interval specific likelihood ratios provide a useful tool for the interpretation of specific IgE test results for inhalant allergens. Copyright © 2015 Elsevier B.V. All rights reserved.

Prediction of Safety Margin and Optimization of Dosing Protocol for a Novel Antibiotic using Quantitative Systems Pharmacology Modeling.

PubMed

Woodhead, Jeffrey L; Paech, Franziska; Maurer, Martina; Engelhardt, Marc; Schmitt-Hoffmann, Anne H; Spickermann, Jochen; Messner, Simon; Wind, Mathias; Witschi, Anne-Therese; Krähenbühl, Stephan; Siler, Scott Q; Watkins, Paul B; Howell, Brett A

2018-06-07

Elevations of liver enzymes have been observed in clinical trials with BAL30072, a novel antibiotic. In vitro assays have identified potential mechanisms for the observed hepatotoxicity, including electron transport chain (ETC) inhibition and reactive oxygen species (ROS) generation. DILIsym, a quantitative systems pharmacology (QSP) model of drug-induced liver injury, has been used to predict the likelihood that each mechanism explains the observed toxicity. DILIsym was also used to predict the safety margin for a novel BAL30072 dosing scheme; it was predicted to be low. DILIsym was then used to recommend potential modifications to this dosing scheme; weight-adjusted dosing and a requirement to assay plasma alanine aminotransferase (ALT) daily and stop dosing as soon as ALT increases were observed improved the predicted safety margin of BAL30072 and decreased the predicted likelihood of severe injury. This research demonstrates a potential application for QSP modeling in improving the safety profile of candidate drugs. © 2018 The Authors. Clinical and Translational Science published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Hypothesis testing and earthquake prediction.

PubMed

Jackson, D D

1996-04-30

Requirements for testing include advance specification of the conditional rate density (probability per unit time, area, and magnitude) or, alternatively, probabilities for specified intervals of time, space, and magnitude. Here I consider testing fully specified hypotheses, with no parameter adjustments or arbitrary decisions allowed during the test period. Because it may take decades to validate prediction methods, it is worthwhile to formulate testable hypotheses carefully in advance. Earthquake prediction generally implies that the probability will be temporarily higher than normal. Such a statement requires knowledge of "normal behavior"--that is, it requires a null hypothesis. Hypotheses can be tested in three ways: (i) by comparing the number of actual earth-quakes to the number predicted, (ii) by comparing the likelihood score of actual earthquakes to the predicted distribution, and (iii) by comparing the likelihood ratio to that of a null hypothesis. The first two tests are purely self-consistency tests, while the third is a direct comparison of two hypotheses. Predictions made without a statement of probability are very difficult to test, and any test must be based on the ratio of earthquakes in and out of the forecast regions.

Hypothesis testing and earthquake prediction.

PubMed Central

Jackson, D D

1996-01-01

Requirements for testing include advance specification of the conditional rate density (probability per unit time, area, and magnitude) or, alternatively, probabilities for specified intervals of time, space, and magnitude. Here I consider testing fully specified hypotheses, with no parameter adjustments or arbitrary decisions allowed during the test period. Because it may take decades to validate prediction methods, it is worthwhile to formulate testable hypotheses carefully in advance. Earthquake prediction generally implies that the probability will be temporarily higher than normal. Such a statement requires knowledge of "normal behavior"--that is, it requires a null hypothesis. Hypotheses can be tested in three ways: (i) by comparing the number of actual earth-quakes to the number predicted, (ii) by comparing the likelihood score of actual earthquakes to the predicted distribution, and (iii) by comparing the likelihood ratio to that of a null hypothesis. The first two tests are purely self-consistency tests, while the third is a direct comparison of two hypotheses. Predictions made without a statement of probability are very difficult to test, and any test must be based on the ratio of earthquakes in and out of the forecast regions. PMID:11607663

Sensitivity, predictive values, pretest-posttest probabilities, and likelihood ratios of presurgery clinical diagnosis of nonmelanoma skin cancers.

PubMed

Ermertcan, Aylin Türel; Oztürk, Ferdi; Gençoğlan, Gülsüm; Eskiizmir, Görkem; Temiz, Peyker; Horasan, Gönül Dinç

2011-03-01

The precision of clinical diagnosis of skin tumors is not commonly measured and, therefore, very little is known about the diagnostic ability of clinicians. This study aimed to compare clinical and histopathologic diagnoses of nonmelanoma skin cancers with regard to sensitivity, predictive values, pretest-posttest probabilities, and likelihood ratios. Two hundred nineteen patients with 241 nonmelanoma skin cancers were enrolled in this study. Of these patients, 49.4% were female and 50.6% were male. The mean age ± standard deviation (SD) was 63.66 ± 16.44 years for the female patients and 64.77 ± 14.88 years for the male patients. The mean duration of the lesions was 20.90 ± 32.95 months. One hundred forty-eight (61.5%) of the lesions were diagnosed as basal cell carcinoma (BCC) and 93 (38.5%) were diagnosed as squamous cell carcinoma (SCC) histopathologically. Sensitivity, positive predictive value, and posttest probability were calculated as 75.96%, 87.77%, and 87.78% for BCC and 70.37%, 37.25%, and 37.20% for SCC, respectively. The correlation between clinical and histopathologic diagnoses was found to be higher in BCC. Knowledge of sensitivity, predictive values, likelihood ratios, and posttest probabilities may have implications for the management of skin cancers. To prevent unnecessary surgeries and achieve high diagnostic accuracies, multidisciplinary approaches are recommended.

A strategy for improved computational efficiency of the method of anchored distributions

NASA Astrophysics Data System (ADS)

Over, Matthew William; Yang, Yarong; Chen, Xingyuan; Rubin, Yoram

2013-06-01

This paper proposes a strategy for improving the computational efficiency of model inversion using the method of anchored distributions (MAD) by "bundling" similar model parametrizations in the likelihood function. Inferring the likelihood function typically requires a large number of forward model (FM) simulations for each possible model parametrization; as a result, the process is quite expensive. To ease this prohibitive cost, we present an approximation for the likelihood function called bundling that relaxes the requirement for high quantities of FM simulations. This approximation redefines the conditional statement of the likelihood function as the probability of a set of similar model parametrizations "bundle" replicating field measurements, which we show is neither a model reduction nor a sampling approach to improving the computational efficiency of model inversion. To evaluate the effectiveness of these modifications, we compare the quality of predictions and computational cost of bundling relative to a baseline MAD inversion of 3-D flow and transport model parameters. Additionally, to aid understanding of the implementation we provide a tutorial for bundling in the form of a sample data set and script for the R statistical computing language. For our synthetic experiment, bundling achieved a 35% reduction in overall computational cost and had a limited negative impact on predicted probability distributions of the model parameters. Strategies for minimizing error in the bundling approximation, for enforcing similarity among the sets of model parametrizations, and for identifying convergence of the likelihood function are also presented.

[An evaluation of some of the relationships between thought-action fusion, attributional styles, and depressive and obsessive-compulsive symptoms].

PubMed

Piri, Serap; Kabakçi, Elif

2007-01-01

Thought-action fusion (TAF) is a cognitive bias presumed to underlie the development of obsessional problems. Two domains of TAF have been identified. The first, TAF-moral, is characterized by the belief that having morally unacceptable thoughts is as bad as actually carrying them out. The second, TAF-likelihood, refers to the belief that certain thoughts cause particular events. The event can be related to one's self (likelihood-self) or to someone else (likelihood-others). The other cognitive variable of the study is attributional style. The theory of attributional styles, in terms of the causes of good and bad events, is taken into account especially in the context of depression and has four dimensions: internality-externality, stability-instability, globality-specifity, and importance-unimportance. The first objective of the present study was to investigate the relationships between TAF, and attributional style, and depressive and obsessive-compulsive symptoms. The second objective was to determine the predictors of TAF when the effects of depressive and obsessive-compulsive symptoms are statistically controlled. The sample consisted of 312 students randomly selected from different departments at Hacettepe University. The Thought-Action Fusion Scale (TAFS), Attributional Style Questionnaire (ASQ), Maudsley Obsessive-Compulsive Inventory (MOCI), and Beck Depression Inventory (BDI) were administered to these students. The correlations among all the subtypes of TAF (TAF-moral, likelihood-self, and likelihood-others), and the global attributions for bad events, BDI, and MOCI were significant. In addition, the correlation between TAF-moral and the importance of the attribution for bad events was significant. TAF-likelihood-others and TAF-likelihood-self were predicted by global attributions for bad events and TAF-moral was predicted by the importance of the attributions for bad events. TAF, and attributional styles, and depressive and obsessive-compulsive symptoms may be related to each other. The results also suggest a possible effect of other variables not controlled in this study, both on TAF and the dimensions of attributional styles.

Smoking and Cardiac Rehabilitation Participation: Associations with Referral, Attendance and Adherence

PubMed Central

Gaalema, Diann E.; Cutler, Alexander Y.; Higgins, Stephen T.; Ades, Philip A.

2015-01-01

Objective Continued smoking after a cardiac event greatly increases mortality risk. Smoking cessation and participation in cardiac rehabilitation (CR) are effective in reducing morbidity and mortality. However, these two behaviors may interact; those who smoke may be less likely to access or complete CR. This review explores the association between smoking status and CR referral, attendance, and adherence. Methods A systematic literature search was conducted examining associations between smoking status and CR referral, attendance and completion in peer-reviewed studies published through July 1st, 2014. For inclusion, studies had to report data on outpatient CR referral, attendance or completion rates and smoking status had to be considered as a variable associated with these outcomes. Results Fifty-six studies met inclusion criteria. In summary, a history of smoking was associated with an increased likelihood of referral to CR. However, smoking status also predicted not attending CR and was a strong predictor of CR dropout. Conclusion Continued smoking after a cardiac event predicts lack of attendance in, and completion of CR. The issue of smoking following a coronary event deserves renewed attention. PMID:25900804

Defining physicians' readiness to screen and manage intimate partner violence in Greek primary care settings.

PubMed

Papadakaki, Maria; Prokopiadou, Dimitra; Petridou, Eleni; Kogevinas, Manolis; Lionis, Christos

2012-06-01

The current article aims to translate the PREMIS (Physician Readiness to Manage Intimate Partner Violence) survey into the Greek language and test its validity and reliability in a sample of primary care physicians. The validation study was conducted in 2010 and involved all the general practitioners serving two adjacent prefectures of Greece (n = 80). Maximum-likelihood factor analysis (MLF) was used to extract key survey factors. The instrument was further assessed for the following psychometric properties: (a) scale reliability, (b) item-specific reliability, (c) test-retest reliability, (d) scale construct validity, and (e) internal predictive validity. The MLF analysis of 23 opinion items revealed a seven-factor solution (preparation, constraint, workplace issues, screening, self-efficacy, alcohol/drugs, victim understanding), which was statistically sound (p = .293). Most of the newly derived scales displayed satisfactory internal consistency (α ≥ .60), high item-specific reliability, strong construct, and internal predictive validity (F = 2.82; p = .004), and high repeatability when retested with 20 individuals (intraclass correlation coefficient [ICC] > .70). The tool was found appropriate to facilitate the identification of competence deficits and the evaluation of training initiatives.

Contextual control over task-set retrieval.

PubMed

Crump, Matthew J C; Logan, Gordon D

2010-11-01

Contextual cues signaling task likelihood or the likelihood of task repetition are known to modulate the size of switch costs. We follow up on the finding by Leboe, Wong, Crump, and Stobbe (2008) that location cues predictive of the proportion of switch or repeat trials modulate switch costs. Their design employed one cue per task, whereas our experiment employed two cues per task, which allowed separate assessment of modulations to the cue-repetition benefit, a measure of lower level cue-encoding processes, and to the task-alternation cost, a measure of higher level processes representing task-set information. We demonstrate that location information predictive of switch proportion modulates performance at the level of task-set representations. Furthermore, we demonstrate that contextual control occurs even when subjects are unaware of the associations between context and switch likelihood. We discuss the notion that contextual information provides rapid, unconscious control over the extent to which prior task-set representations are retrieved in the service of guiding online performance.

Evaluation of Dynamic Coastal Response to Sea-level Rise Modifies Inundation Likelihood

NASA Technical Reports Server (NTRS)

Lentz, Erika E.; Thieler, E. Robert; Plant, Nathaniel G.; Stippa, Sawyer R.; Horton, Radley M.; Gesch, Dean B.

2016-01-01

Sea-level rise (SLR) poses a range of threats to natural and built environments, making assessments of SLR-induced hazards essential for informed decision making. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30x30m resolution predictions for more than 38,000 sq km of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.

The dorsal medial frontal cortex is sensitive to time on task, not response conflict or error likelihood.

PubMed

Grinband, Jack; Savitskaya, Judith; Wager, Tor D; Teichert, Tobias; Ferrera, Vincent P; Hirsch, Joy

2011-07-15

The dorsal medial frontal cortex (dMFC) is highly active during choice behavior. Though many models have been proposed to explain dMFC function, the conflict monitoring model is the most influential. It posits that dMFC is primarily involved in detecting interference between competing responses thus signaling the need for control. It accurately predicts increased neural activity and response time (RT) for incompatible (high-interference) vs. compatible (low-interference) decisions. However, it has been shown that neural activity can increase with time on task, even when no decisions are made. Thus, the greater dMFC activity on incompatible trials may stem from longer RTs rather than response conflict. This study shows that (1) the conflict monitoring model fails to predict the relationship between error likelihood and RT, and (2) the dMFC activity is not sensitive to congruency, error likelihood, or response conflict, but is monotonically related to time on task. Copyright © 2010 Elsevier Inc. All rights reserved.

Sialylated Fetuin-A as a candidate predictive biomarker for successful grass pollen allergen immunotherapy.

PubMed

Caillot, Noémie; Bouley, Julien; Jain, Karine; Mariano, Sandrine; Luce, Sonia; Horiot, Stéphane; Airouche, Sabi; Beuraud, Chloé; Beauvallet, Christian; Devillier, Philippe; Chollet-Martin, Sylvie; Kellenberger, Christine; Mascarell, Laurent; Chabre, Henri; Batard, Thierry; Nony, Emmanuel; Lombardi, Vincent; Baron-Bodo, Véronique; Moingeon, Philippe

2017-09-01

Eligibility to immunotherapy is based on the determination of IgE reactivity to a specific allergen by means of skin prick or in vitro testing. Biomarkers predicting the likelihood of clinical improvement during immunotherapy would significantly improve patient selection. Proteins were differentially assessed by using 2-dimensional differential gel electrophoresis and label-free mass spectrometry in pretreatment sera obtained from clinical responders and nonresponders within a cohort of 82 patients with grass pollen allergy receiving sublingual immunotherapy or placebo. Functional studies of Fetuin-A (FetA) were conducted by using gene silencing in a mouse asthma model, human dendritic cell in vitro stimulation assays, and surface plasmon resonance. Analysis by using quantitative proteomics of pretreatment sera from patients with grass pollen allergy reveals that high levels of O-glycosylated sialylated FetA isoforms are found in patients exhibiting a strong decrease in rhinoconjunctivitis symptoms after sublingual immunotherapy. Although FetA is involved in numerous inflammatory conditions, its potential role in allergy is unknown. In vivo silencing of the FETUA gene in BALB/c mice results in a dramatic upregulation of airway hyperresponsiveness, lung resistance, and T H 2 responses after allergic sensitization to ovalbumin. Both sialylated and nonsialytated FetA bind to LPS, but only the former synergizes with LPS and grass pollen or mite allergens to enhance the Toll-like receptor 4-mediated proallergic properties of human dendritic cells. As a reflection of the patient's inflammatory status, pretreatment levels of sialylated FetA in the blood are indicative of the likelihood of clinical responses during grass pollen immunotherapy. Copyright © 2016 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Predictive Uncertainty And Parameter Sensitivity Of A Sediment-Flux Model: Nitrogen Flux and Sediment Oxygen Demand

EPA Science Inventory

Estimating model predictive uncertainty is imperative to informed environmental decision making and management of water resources. This paper applies the Generalized Sensitivity Analysis (GSA) to examine parameter sensitivity and the Generalized Likelihood Uncertainty Estimation...

Self-stigma of seeking treatment and being male predict an increased likelihood of having an undiagnosed eating disorder.

PubMed

Griffiths, Scott; Mond, Jonathan M; Li, Zhicheng; Gunatilake, Sanduni; Murray, Stuart B; Sheffield, Jeanie; Touyz, Stephen

2015-09-01

To examine whether self-stigma of seeking psychological help and being male would be associated with an increased likelihood of having an undiagnosed eating disorder. A multi-national sample of 360 individuals with diagnosed eating disorders and 125 individuals with undiagnosed eating disorders were recruited. Logistic regression was used to identify variables affecting the likelihood of having an undiagnosed eating disorder, including sex, self-stigma of seeking psychological help, and perceived stigma of having a mental illness, controlling for a broad range of covariates. Being male and reporting greater self-stigma of seeking psychological help was independently associated with an increased likelihood of being undiagnosed. Further, the association between self-stigma of seeking psychological help and increased likelihood of being undiagnosed was significantly stronger for males than for females. Perceived stigma associated with help-seeking may be a salient barrier to treatment for eating disorders-particularly among male sufferers. © 2015 Wiley Periodicals, Inc.

Comparison of two weighted integration models for the cueing task: linear and likelihood

NASA Technical Reports Server (NTRS)

Shimozaki, Steven S.; Eckstein, Miguel P.; Abbey, Craig K.

2003-01-01

In a task in which the observer must detect a signal at two locations, presenting a precue that predicts the location of a signal leads to improved performance with a valid cue (signal location matches the cue), compared to an invalid cue (signal location does not match the cue). The cue validity effect has often been explained with a limited capacity attentional mechanism improving the perceptual quality at the cued location. Alternatively, the cueing effect can also be explained by unlimited capacity models that assume a weighted combination of noisy responses across the two locations. We compare two weighted integration models, a linear model and a sum of weighted likelihoods model based on a Bayesian observer. While qualitatively these models are similar, quantitatively they predict different cue validity effects as the signal-to-noise ratios (SNR) increase. To test these models, 3 observers performed in a cued discrimination task of Gaussian targets with an 80% valid precue across a broad range of SNR's. Analysis of a limited capacity attentional switching model was also included and rejected. The sum of weighted likelihoods model best described the psychophysical results, suggesting that human observers approximate a weighted combination of likelihoods, and not a weighted linear combination.

Predicting the evolution of complex networks via similarity dynamics

NASA Astrophysics Data System (ADS)

Wu, Tao; Chen, Leiting; Zhong, Linfeng; Xian, Xingping

2017-01-01

Almost all real-world networks are subject to constant evolution, and plenty of them have been investigated empirically to uncover the underlying evolution mechanism. However, the evolution prediction of dynamic networks still remains a challenging problem. The crux of this matter is to estimate the future network links of dynamic networks. This paper studies the evolution prediction of dynamic networks with link prediction paradigm. To estimate the likelihood of the existence of links more accurate, an effective and robust similarity index is presented by exploiting network structure adaptively. Moreover, most of the existing link prediction methods do not make a clear distinction between future links and missing links. In order to predict the future links, the networks are regarded as dynamic systems in this paper, and a similarity updating method, spatial-temporal position drift model, is developed to simulate the evolutionary dynamics of node similarity. Then the updated similarities are used as input information for the future links' likelihood estimation. Extensive experiments on real-world networks suggest that the proposed similarity index performs better than baseline methods and the position drift model performs well for evolution prediction in real-world evolving networks.

Combining Mean and Standard Deviation of Hounsfield Unit Measurements from Preoperative CT Allows More Accurate Prediction of Urinary Stone Composition Than Mean Hounsfield Units Alone.

PubMed

Tailly, Thomas; Larish, Yaniv; Nadeau, Brandon; Violette, Philippe; Glickman, Leonard; Olvera-Posada, Daniel; Alenezi, Husain; Amann, Justin; Denstedt, John; Razvi, Hassan

2016-04-01

The mineral composition of a urinary stone may influence its surgical and medical treatment. Previous attempts at identifying stone composition based on mean Hounsfield Units (HUm) have had varied success. We aimed to evaluate the additional use of standard deviation of HU (HUsd) to more accurately predict stone composition. We identified patients from two centers who had undergone urinary stone treatment between 2006 and 2013 and had mineral stone analysis and a computed tomography (CT) available. HUm and HUsd of the stones were compared with ANOVA. Receiver operative characteristic analysis with area under the curve (AUC), Youden index, and likelihood ratio calculations were performed. Data were available for 466 patients. The major components were calcium oxalate monohydrate (COM), uric acid, hydroxyapatite, struvite, brushite, cystine, and CO dihydrate (COD) in 41.4%, 19.3%, 12.4%, 7.5%, 5.8%, 5.4%, and 4.7% of patients, respectively. The HUm of UA and Br was significantly lower and higher than the HUm of any other stone type, respectively. HUm and HUsd were most accurate in predicting uric acid with an AUC of 0.969 and 0.851, respectively. The combined use of HUm and HUsd resulted in increased positive predictive value and higher likelihood ratios for identifying a stone's mineral composition for all stone types but COM. To the best of our knowledge, this is the first report of CT data aiding in the prediction of brushite stone composition. Both HUm and HUsd can help predict stone composition and their combined use results in higher likelihood ratios influencing probability.

Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS): A web-based tool for addressing the challenges of cross-species extrapolation of chemical toxicity

EPA Science Inventory

Conservation of a molecular target across species can be used as a line-of-evidence to predict the likelihood of chemical susceptibility. The web-based Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was developed to simplify, streamline, and quantitat...

Weapon carrying and psychopathic-like features in a population-based sample of Finnish adolescents.

PubMed

Saukkonen, Suvi; Laajasalo, Taina; Jokela, Markus; Kivivuori, Janne; Salmi, Venla; Aronen, Eeva T

2016-02-01

We investigated the prevalence of juvenile weapon carrying and psychosocial and personality-related risk factors for carrying different types of weapons in a nationally representative, population-based sample of Finnish adolescents. Specifically, we aimed to investigate psychopathic-like personality features as a risk factor for weapon carrying. The participants were 15-16-year-old adolescents from the Finnish self-report delinquency study (n = 4855). Four different groups were formed based on self-reported weapon carrying: no weapon carrying, carrying knife, gun or other weapon. The associations between psychosocial factors, psychopathic-like features and weapon carrying were examined with multinomial logistic regression analysis. 9% of the participants had carried a weapon in the past 12 months. Adolescents with a history of delinquency, victimization and antisocial friends were more likely to carry weapons in general; however, delinquency and victimization were most strongly related to gun carrying, while perceived peer delinquency (antisocial friends) was most strongly related to carrying a knife. Better academic performance was associated with a reduced likelihood of carrying a gun and knife, while feeling secure correlated with a reduced likelihood of gun carrying only. Psychopathic-like features were related to a higher likelihood of weapon carrying, even after adjusting for other risk factors. The findings of the study suggest that adolescents carrying a weapon have a large cluster of problems in their lives, which may vary based on the type of weapon carried. Furthermore, psychopathic-like features strongly relate to a higher risk of carrying a weapon.

Fast automated analysis of strong gravitational lenses with convolutional neural networks.

PubMed

Hezaveh, Yashar D; Levasseur, Laurence Perreault; Marshall, Philip J

2017-08-30

Quantifying image distortions caused by strong gravitational lensing-the formation of multiple images of distant sources due to the deflection of their light by the gravity of intervening structures-and estimating the corresponding matter distribution of these structures (the 'gravitational lens') has primarily been performed using maximum likelihood modelling of observations. This procedure is typically time- and resource-consuming, requiring sophisticated lensing codes, several data preparation steps, and finding the maximum likelihood model parameters in a computationally expensive process with downhill optimizers. Accurate analysis of a single gravitational lens can take up to a few weeks and requires expert knowledge of the physical processes and methods involved. Tens of thousands of new lenses are expected to be discovered with the upcoming generation of ground and space surveys. Here we report the use of deep convolutional neural networks to estimate lensing parameters in an extremely fast and automated way, circumventing the difficulties that are faced by maximum likelihood methods. We also show that the removal of lens light can be made fast and automated using independent component analysis of multi-filter imaging data. Our networks can recover the parameters of the 'singular isothermal ellipsoid' density profile, which is commonly used to model strong lensing systems, with an accuracy comparable to the uncertainties of sophisticated models but about ten million times faster: 100 systems in approximately one second on a single graphics processing unit. These networks can provide a way for non-experts to obtain estimates of lensing parameters for large samples of data.

Do psychopathic traits assessed in mid-adolescence predict mental health, psychosocial, and antisocial, including criminal outcomes, over the subsequent 5 years?

PubMed

Hemphälä, Malin; Hodgins, Sheilagh

2014-01-01

To determine whether psychopathic traits assessed in mid-adolescence predicted mental health, psychosocial, and antisocial (including criminal) outcomes 5 years later and would thereby provide advantages over diagnosing conduct disorder (CD). Eighty-six women and 61 men were assessed in mid-adolescence when they first contacted a clinic for substance misuse and were reassessed 5 years later. Assessments in adolescence include the Psychopathy Checklist-Youth Version (PCL-YV), and depending on their age, either the Kiddie-Schedule for Affective Disorders and Schizophrenia for School-Aged Children or the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (SCID). Assessments in early adulthood included the SCID, self-reports of psychosocial functioning, aggressive behaviour, and criminality and official criminal records. The antisocial facet score positively predicted the number of anxiety symptoms and likelihood of receiving treatment for substance use disorders (SUDs). Lifestyle and antisocial facet scores negatively predicted Global Assessment of Functioning scores. By contrast, the interpersonal score and male sex independently and positively predicted the number of months worked or studied, as did the interaction of Lifestyle × Sex indicating that among men, but not women, an increase in lifestyle facet score was associated with less time worked or studied. Interpersonal and antisocial scores positively predicted school drop-out. Antisocial facet scores predicted the number of symptoms of antisocial personality disorder, alcohol and SUDs, and violent and nonviolent criminality but much more strongly among males than females. Predictions from numbers of CD symptoms were similar. Psychopathic traits among adolescents who misuse substances predict an array of outcomes over the subsequent 5 years. Information on the levels of these traits may be useful for planning treatment.

[Differences between experts and novices in estimations of cue predictive power in crime].

PubMed

García-Retamero, Rocío; Dhami, Mandeep K

2009-08-01

In this study, we compared experts' and novices' estimates of the power of several cues to predict residential burglary. Participants were experienced police officers and burglars, and graduates with no experience in this domain. They all estimated the weight of each cue in predicting the likelihood of a property being burgled. In addition, they ranked the cues according to how useful they would be in predicting the likelihood of burglary. Results showed that the two expert groups differed substantially in their cue weights and rankings, and the police officers were actually more similar to novices in this regard. Beyond this, the two expert groups were more consistent in their responses than novices, that is, they showed less variability in their estimates when using different response method and were more consistent with other participants from their own group. Our results extend the literature on expert-novice differences, and have implications for criminal justice policy and decision making.

The incremental value of self-reported mental health measures in predicting functional outcomes of veterans.

PubMed

Eisen, Susan V; Bottonari, Kathryn A; Glickman, Mark E; Spiro, Avron; Schultz, Mark R; Herz, Lawrence; Rosenheck, Robert; Rofman, Ethan S

2011-04-01

Research on patient-centered care supports use of patient/consumer self-report measures in monitoring health outcomes. This study examined the incremental value of self-report mental health measures relative to a clinician-rated measure in predicting functional outcomes among mental health service recipients. Participants (n = 446) completed the Behavior and Symptom Identification Scale, the Brief Symptom Inventory, and the Veterans/Rand Short Form-36 at enrollment in the study (T1) and 3 months later (T2). Global Assessment of Functioning (GAF) ratings, mental health service utilization, and psychiatric diagnoses were obtained from administrative data files. Controlling for demographic and clinical variables, results indicated that improvement based on the self-report measures significantly predicted one or more functional outcomes (i.e., decreased likelihood of post-enrollment psychiatric hospitalization and increased likelihood of paid employment), above and beyond the predictive value of the GAF. Inclusion of self-report measures may be a useful addition to performance measurement efforts.

Evidence-Based Occupational Hearing Screening I: Modeling the Effects of Real-World Noise Environments on the Likelihood of Effective Speech Communication.

PubMed

Soli, Sigfrid D; Giguère, Christian; Laroche, Chantal; Vaillancourt, Véronique; Dreschler, Wouter A; Rhebergen, Koenraad S; Harkins, Kevin; Ruckstuhl, Mark; Ramulu, Pradeep; Meyers, Lawrence S

The objectives of this study were to (1) identify essential hearing-critical job tasks for public safety and law enforcement personnel; (2) determine the locations and real-world noise environments where these tasks are performed; (3) characterize each noise environment in terms of its impact on the likelihood of effective speech communication, considering the effects of different levels of vocal effort, communication distances, and repetition; and (4) use this characterization to define an objective normative reference for evaluating the ability of individuals to perform essential hearing-critical job tasks in noisy real-world environments. Data from five occupational hearing studies performed over a 17-year period for various public safety agencies were analyzed. In each study, job task analyses by job content experts identified essential hearing-critical tasks and the real-world noise environments where these tasks are performed. These environments were visited, and calibrated recordings of each noise environment were made. The extended speech intelligibility index (ESII) was calculated for each 4-sec interval in each recording. These data, together with the estimated ESII value required for effective speech communication by individuals with normal hearing, allowed the likelihood of effective speech communication in each noise environment for different levels of vocal effort and communication distances to be determined. These likelihoods provide an objective norm-referenced and standardized means of characterizing the predicted impact of real-world noise on the ability to perform essential hearing-critical tasks. A total of 16 noise environments for law enforcement personnel and eight noise environments for corrections personnel were analyzed. Effective speech communication was essential to hearing-critical tasks performed in these environments. Average noise levels, ranged from approximately 70 to 87 dBA in law enforcement environments and 64 to 80 dBA in corrections environments. The likelihood of effective speech communication at communication distances of 0.5 and 1 m was often less than 0.50 for normal vocal effort. Likelihood values often increased to 0.80 or more when raised or loud vocal effort was used. Effective speech communication at and beyond 5 m was often unlikely, regardless of vocal effort. ESII modeling of nonstationary real-world noise environments may prove an objective means of characterizing their impact on the likelihood of effective speech communication. The normative reference provided by these measures predicts the extent to which hearing impairments that increase the ESII value required for effective speech communication also decrease the likelihood of effective speech communication. These predictions may provide an objective evidence-based link between the essential hearing-critical job task requirements of public safety and law enforcement personnel and ESII-based hearing assessment of individuals who seek to perform these jobs.

Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion.

PubMed

Zafar, Raheel; Dass, Sarat C; Malik, Aamir Saeed

2017-01-01

Electroencephalogram (EEG)-based decoding human brain activity is challenging, owing to the low spatial resolution of EEG. However, EEG is an important technique, especially for brain-computer interface applications. In this study, a novel algorithm is proposed to decode brain activity associated with different types of images. In this hybrid algorithm, convolutional neural network is modified for the extraction of features, a t-test is used for the selection of significant features and likelihood ratio-based score fusion is used for the prediction of brain activity. The proposed algorithm takes input data from multichannel EEG time-series, which is also known as multivariate pattern analysis. Comprehensive analysis was conducted using data from 30 participants. The results from the proposed method are compared with current recognized feature extraction and classification/prediction techniques. The wavelet transform-support vector machine method is the most popular currently used feature extraction and prediction method. This method showed an accuracy of 65.7%. However, the proposed method predicts the novel data with improved accuracy of 79.9%. In conclusion, the proposed algorithm outperformed the current feature extraction and prediction method.

Link Prediction in Evolving Networks Based on Popularity of Nodes.

PubMed

Wang, Tong; He, Xing-Sheng; Zhou, Ming-Yang; Fu, Zhong-Qian

2017-08-02

Link prediction aims to uncover the underlying relationship behind networks, which could be utilized to predict missing edges or identify the spurious edges. The key issue of link prediction is to estimate the likelihood of potential links in networks. Most classical static-structure based methods ignore the temporal aspects of networks, limited by the time-varying features, such approaches perform poorly in evolving networks. In this paper, we propose a hypothesis that the ability of each node to attract links depends not only on its structural importance, but also on its current popularity (activeness), since active nodes have much more probability to attract future links. Then a novel approach named popularity based structural perturbation method (PBSPM) and its fast algorithm are proposed to characterize the likelihood of an edge from both existing connectivity structure and current popularity of its two endpoints. Experiments on six evolving networks show that the proposed methods outperform state-of-the-art methods in accuracy and robustness. Besides, visual results and statistical analysis reveal that the proposed methods are inclined to predict future edges between active nodes, rather than edges between inactive nodes.

Anxious and Hostile: Consequences of Anxious Adult Attachment in Predicting Male-Perpetrated Sexual Assault.

PubMed

Barbaro, Nicole; Parkhill, Michele R; Nguyen, David

2018-07-01

Attachment theory has increasingly been utilized to understand the etiology of sexual violence, and anxious attachment appears to be especially informative in this domain. We investigate the influence of general anxious attachment and specific anxious attachment on hostile masculine attitudes to predict male-perpetrated sexual assault. We hypothesize that hostile masculinity will mediate the relationship between general anxious attachment style and sexual assault perpetration (Hypothesis 1) and the relationship between specific anxious attachment to the assaulted woman and sexual assault perpetration (Hypothesis 2). Men ( N = 193) completed the Sexual Experiences Survey (SES) to determine sexual assault history and completed measures of general attachment style, specific attachment to the woman involved in the sexual activity, and measures of hostile masculine attitudes. Results support the hypothesized mediation models, such that general anxious attachment and specific anxious attachment are significantly associated with hostile masculinity, which in turn, predicts the likelihood of male-perpetrated sexual assault. The findings suggest that the unique characteristics of anxious attachment may escalate into hostile masculinity, which then increases the likelihood of sexual assault perpetration. This research is the first to investigate attachment bonds to the woman involved in the sexual activity and likelihood of sexual assault perpetration against the same woman.

Transperineal ultrasound compared to evacuation proctography for diagnosing enteroceles and intussusceptions.

PubMed

Weemhoff, M; Kluivers, K B; Govaert, B; Evers, J L H; Kessels, A G H; Baeten, C G

2013-03-01

This study concerns the level of agreement between transperineal ultrasound and evacuation proctography for diagnosing enteroceles and intussusceptions. In a prospective observational study, 50 consecutive women who were planned to have an evacuation proctography underwent transperineal ultrasound too. Sensitivity, specificity, positive (PPV) and negative predictive value, as well as the positive and negative likelihood ratio of transperineal ultrasound were assessed in comparison to evacuation proctography. To determine the interobserver agreement of transperineal ultrasound, the quadratic weighted kappa was calculated. Furthermore, receiver operating characteristic curves were generated to show the diagnostic capability of transperineal ultrasound. For diagnosing intussusceptions (PPV 1.00), a positive finding on transperineal ultrasound was predictive of an abnormal evacuation proctography. Sensitivity of transperineal ultrasound was poor for intussusceptions (0.25). For diagnosing enteroceles, the positive likelihood ratio was 2.10 and the negative likelihood ratio, 0.85. There are many false-positive findings of enteroceles on ultrasonography (PPV 0.29). The interobserver agreement of the two ultrasonographers assessed as the quadratic weighted kappa of diagnosing enteroceles was 0.44 and that of diagnosing intussusceptions was 0.23. An intussusception on ultrasound is predictive of an abnormal evacuation proctography. For diagnosing enteroceles, the diagnostic quality of transperineal ultrasound was limited compared to evacuation proctography.

Cumulative risk and AIDS-orphanhood: interactions of stigma, bullying and poverty on child mental health in South Africa.

PubMed

Cluver, Lucie; Orkin, Mark

2009-10-01

Research shows that AIDS-orphaned children are more likely to experience clinical-range psychological problems. Little is known about possible interactions between factors mediating these high distress levels. We assessed how food insecurity, bullying, and AIDS-related stigma interacted with each other and with likelihood of experiencing clinical-range disorder. In South Africa, 1025 adolescents completed standardised measures of depression, anxiety and post-traumatic stress. 52 potential mediators were measured, including AIDS-orphanhood status. Logistic regressions and hierarchical log-linear modelling were used to identify interactions among significant risk factors. Food insecurity, stigma and bullying all independently increased likelihood of disorder. Poverty and stigma were found to interact strongly, and with both present, likelihood of disorder rose from 19% to 83%. Similarly, bullying interacted with AIDS-orphanhood status, and with both present, likelihood of disorder rose from 12% to 76%. Approaches to alleviating psychological distress amongst AIDS-affected children must address cumulative risk effects.

Postincident Support for Healthcare Workers Experiencing Occupational Violence and Aggression.

PubMed

Shea, Tracey; Cooper, Brian; De Cieri, Helen; Sheehan, Cathy; Donohue, Ross; Lindsay, Sarah

2018-05-10

To investigate the relative contributions of workplace type, occupational violence and aggression (OVA) strategies and interventions along with perceptions of the occupational health and safety (OHS) environment on the likelihood of receiving postincident support following the experience of OVA. We used a cross-sectional study design with an online survey to collect data from employees in nursing and midwifery in Victoria, Australia. Survey data collected from 3,072 members of the Australian Nursing and Midwifery Federation (Victorian branch) were analyzed using logistic regression. Of the 3,072 respondents who had experienced OVA in the preceding 12 months, 1,287 (42%) reported that they had received postincident support. Hierarchical logistic regression revealed that the OHS environment was the dominant factor that predicted the likelihood of workers receiving postincident support. Working in a positive OHS environment characterized by higher levels of leading indicators of OHS, prioritization of OHS, supervisor support for safety, and team psychological safety was the stronger predictor of postincident support. Being employed in a workplace that offered training in the management and prevention of OVA also increased the likelihood of receiving postincident support. While training in the management and prevention of OVA contributed to the likelihood of receiving postincident support, a greater emphasis on the OHS environment was more important in predicting the likelihood that workers received support. This study identifies workplace practices that facilitate the provision of postincident support for healthcare workers. Facilitating effective postincident support could improve outcomes for workers, their patients and workplaces, and society in general. © 2018 Sigma Theta Tau International.

Why Do Drivers Use Mobile Phones While Driving? The Contribution of Compensatory Beliefs

PubMed Central

Zhou, Ronggang; Yu, Mengli; Wang, Xinyi

2016-01-01

The current study is the first to investigate the contribution of compensatory beliefs (i.e., the belief that the negative effects of an unsafe behavior can be "neutralized" by engaging in another safe behavior; e.g., "I can use a mobile phone now because I will slow down ") on drivers’ mobile phone use while driving. The effects of drivers’ personal characteristics on compensatory beliefs, mobile phone use and self-regulatory behaviors were also examined. A series of questions were administered to drivers, which included (1) personal measures, (2) scales that measured compensatory beliefs generally in substance use and with regard to driving safety, and (3) questions to measure drivers’ previous primary mobile phone usage and corresponding self-regulatory actions. Overall, drivers reported a low likelihood of compensatory beliefs, prior mobile phone use, and a strong frequency of self-regulatory behaviors. Respondents who had a higher tendency toward compensatory beliefs reported more incidents or crash involvement caused by making or answering calls and sending or reading messages. The findings provide strong support for the contribution of compensatory beliefs in predicting mobile phone usage in the context of driving. Compensatory beliefs can explain 41% and 43% of the variance in the active activities of making calls and texting/sending messages compared with 18% and 31% of the variance in the passive activities of answering calls and reading messages. Among the regression models for predicting self-regulatory behaviors at the tactical or operational level, compensatory beliefs emerge as significant predictors only in predicting shorter conversations while on a call. The findings and limitations of the current study are discussed. PMID:27494524

Network-based analysis of genotype-phenotype correlations between different inheritance modes.

PubMed

Hao, Dapeng; Li, Chuanxing; Zhang, Shaojun; Lu, Jianping; Jiang, Yongshuai; Wang, Shiyuan; Zhou, Meng

2014-11-15

Recent studies on human disease have revealed that aberrant interaction between proteins probably underlies a substantial number of human genetic diseases. This suggests a need to investigate disease inheritance mode using interaction, and based on which to refresh our conceptual understanding of a series of properties regarding inheritance mode of human disease. We observed a strong correlation between the number of protein interactions and the likelihood of a gene causing any dominant diseases or multiple dominant diseases, whereas no correlation was observed between protein interaction and the likelihood of a gene causing recessive diseases. We found that dominant diseases are more likely to be associated with disruption of important interactions. These suggest inheritance mode should be understood using protein interaction. We therefore reviewed the previous studies and refined an interaction model of inheritance mode, and then confirmed that this model is largely reasonable using new evidences. With these findings, we found that the inheritance mode of human genetic diseases can be predicted using protein interaction. By integrating the systems biology perspectives with the classical disease genetics paradigm, our study provides some new insights into genotype-phenotype correlations. haodapeng@ems.hrbmu.edu.cn or biofomeng@hotmail.com Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Low load for disruptive mutations in autism genes and their biased transmission

PubMed Central

Iossifov, Ivan; Levy, Dan; Allen, Jeremy; Ye, Kenny; Ronemus, Michael; Lee, Yoon-ha; Yamrom, Boris; Wigler, Michael

2015-01-01

We previously computed that genes with de novo (DN) likely gene-disruptive (LGD) mutations in children with autism spectrum disorders (ASD) have high vulnerability: disruptive mutations in many of these genes, the vulnerable autism genes, will have a high likelihood of resulting in ASD. Because individuals with ASD have lower fecundity, such mutations in autism genes would be under strong negative selection pressure. An immediate prediction is that these genes will have a lower LGD load than typical genes in the human gene pool. We confirm this hypothesis in an explicit test by measuring the load of disruptive mutations in whole-exome sequence databases from two cohorts. We use information about mutational load to show that lower and higher intelligence quotients (IQ) affected individuals can be distinguished by the mutational load in their respective gene targets, as well as to help prioritize gene targets by their likelihood of being autism genes. Moreover, we demonstrate that transmission of rare disruptions in genes with a lower LGD load occurs more often to affected offspring; we show transmission originates most often from the mother, and transmission of such variants is seen more often in offspring with lower IQ. A surprising proportion of transmission of these rare events comes from genes expressed in the embryonic brain that show sharply reduced expression shortly after birth. PMID:26401017

Enrollment Management in Medical School Admissions: A Novel Evidence-Based Approach at One Institution.

PubMed

Burkhardt, John C; DesJardins, Stephen L; Teener, Carol A; Gay, Steven E; Santen, Sally A

2016-11-01

In higher education, enrollment management has been developed to accurately predict the likelihood of enrollment of admitted students. This allows evidence to dictate numbers of interviews scheduled, offers of admission, and financial aid package distribution. The applicability of enrollment management techniques for use in medical education was tested through creation of a predictive enrollment model at the University of Michigan Medical School (U-M). U-M and American Medical College Application Service data (2006-2014) were combined to create a database including applicant demographics, academic application scores, institutional financial aid offer, and choice of school attended. Binomial logistic regression and multinomial logistic regression models were estimated in order to study factors related to enrollment at the local institution versus elsewhere and to groupings of competing peer institutions. A predictive analytic "dashboard" was created for practical use. Both models were significant at P < .001 and had similar predictive performance. In the binomial model female, underrepresented minority students, grade point average, Medical College Admission Test score, admissions committee desirability score, and most individual financial aid offers were significant (P < .05). The significant covariates were similar in the multinomial model (excluding female) and provided separate likelihoods of students enrolling at different institutional types. An enrollment-management-based approach would allow medical schools to better manage the number of students they admit and target recruitment efforts to improve their likelihood of success. It also performs a key institutional research function for understanding failed recruitment of highly desirable candidates.

Ready or not: does household preparedness prevent absenteeism among emergency department staff during a disaster?

PubMed

Mercer, Mary P; Ancock, Benedict; Levis, Joel T; Reyes, Vivian

2014-01-01

During major disasters, hospitals experience varied levels of absenteeism among healthcare workers (HCWs) in the immediate response period. Loss of critical hospital personnel, including Emergency Department (ED) staff, during this time can negatively impact a facility's ability to effectively treat large numbers of ill and injured patients. Prior studies have examined factors contributing to HCW ability and willingness to report for duty during a disaster. The purpose of this study was to determine if the degree of readiness of ED personnel, as measured by household preparedness, is associated with predicted likelihood of reporting for duty. Additionally, the authors sought to elucidate other factors associated with absenteeism among ED staff during a disaster. ED staff of five hospitals participated in this survey-based study, answering questions regarding demographic information, past disaster experience, household disaster preparedness (using a novel,15-point scale), and likelihood of reporting to work during various categories of disaster. The primary outcome was personal predicted likelihood of reporting for duty following a disaster. A total of 399 subjects participated in the study. ED staffs were most likely to report for duty in the setting of an earthquake (95 percent) or other natural disaster, followed by an epidemic (90 percent) and were less likely to report for work during a biological, chemical, or a nuclear event (63 percent). Degree of household preparedness was determined to have no association with an ED HCW's predicted likelihood of reporting for duty. Factors associated with predicted absenteeism varied based on type of disaster and included having dependents in the home, female gender, past disaster relief experience, having a spouse or domestic partner, and not owning pets. Having dependents in the home was associated with predicted absenteeism for all disaster types (OR 0.30-0.66). However, when stratified by gender, the presence of dependents at home was only a significantly associated with predicted absenteeism among women as opposed to men (OR 0.07-0.59 versus OR 0.41-1.02). Personal household preparedness, while an admirable goal, appears to have no effect on predicted absenteeism among ED staff following a disaster. Having responsibilities for dependents is the most consistent factor associated with predicted absenteeism among female staff. Hospital and ED disaster planners should consider focusing preparedness efforts less toward household preparedness for staff and instead concentrate on addressing dependent care needs in addition to professional preparedness.

Geographic variation in cesarean delivery in the United States by payer.

PubMed

Henke, Rachel Mosher; Wier, Lauren M; Marder, William D; Friedman, Bernard S; Wong, Herbert S

2014-11-19

The rate of cesarean delivery in the United States is variable across geographic areas. The aims of this study are two-fold: (1) to determine whether the geographic variation in cesarean delivery rate is consistent for private insurance and Medicaid (2) to identify the patient, population, and market factors associated with cesarean rate and determine if these factors vary by payer. We used the Healthcare Cost and Utilization Project (HCUP) State Inpatient Databases (SID) to measure the cesarean rate at the Core-Based Statistical Area (CBSA) level. We linked the hospitalization data to data from other national sources to measure population and market characteristics. We calculated unadjusted and risk-adjusted CBSA cesarean rates by payer. For the second aim, we estimated a hierarchical logistical model with the hospitalization as the unit of analysis to determine the factors associated with cesarean delivery. The average CBSA cesarean rate for women with private insurance was higher (18.9 percent) than for women with Medicaid (16.4 percent). The factors predicting cesarean rate were largely consistent across payers, with the following exceptions: women under age 18 had a greater likelihood of cesarean section if they had Medicaid but had a greater likelihood of vaginal birth if they had private insurance; Asian and Native American women with private insurance had a greater likelihood of cesarean section but Asian and Native American women with Medicaid had a greater likelihood of vaginal birth. The percent African American in the population predicted increased cesarean rates for private insurance only; the number of acute care beds per capita predicted increased cesarean rate for women with Medicaid but not women with private insurance. Further we found the number of obstetricians/gynecologists per capita predicted increased cesarean rate for women with private insurance only, and the number of midwives per capita predicted increased vaginal birth rate for women with private insurance only. Factors associated with geographic variation in cesarean delivery, a frequent and high-resource inpatient procedure, vary somewhat by payer. Using this information to identify areas for intervention is key to improving quality of care and reducing healthcare costs.

Factors that predict the use or non-use of virtual dissection by high school biology teachers

NASA Astrophysics Data System (ADS)

Cockerham, William

2001-07-01

With the advent of computers into scholastic classrooms, virtual dissection has become a potential educational tool in high school biology lab settings. Utilizing non-experimental survey research methodology, this study attempted to identify factors that may influence high school biology teachers to use or not to use a virtual dissection. A 75-item research survey instrument consisting of both demographic background and Likert style questions was completed by 215 high school members of the National Association of Biology Teachers. The survey responses provided data to answer the research questions concerning the relationship between the likelihood of a high school biology teacher using a virtual dissection and a number of independent variables from the following three categories: (a) demographics, (b) attitude and experience, and (c) resources and support. These data also allowed for the determination of a demographic profile of the sample population. The demographic profile showed the sample population of high school biology teachers to be two-thirds female, mature, highly educated and very experienced. Analysis of variance and Pearson product moment correlational statistics were used to determine if there was a relationship between high school biology teachers' likelihood to use a virtual dissection and the independent variables. None of the demographic or resource and support independent variables demonstrated a strong relationship to the dependent variable of teachers' likelihood to use a virtual dissection. Three of the attitude and experience independent variables showed a statistically significant (p < .05) relationship to teachers' likelihood to use a virtual dissection: attitude toward virtual dissection, previous use of a virtual dissection and intention to use a real animal dissection. These findings may indicate that teachers are using virtual dissection as a supplement rather than a substitute. It appears that those concerned with promoting virtual dissection in high school biology classrooms will have to develop simulations that are more compelling to the teachers. Additionally, if science teacher organizations want to reduce the controversy surrounding dissection, they may need to re-visit their positions on the importance of real animal dissection.

Extrapolating Weak Selection in Evolutionary Games

PubMed Central

Wu, Bin; García, Julián; Hauert, Christoph; Traulsen, Arne

2013-01-01

In evolutionary games, reproductive success is determined by payoffs. Weak selection means that even large differences in game outcomes translate into small fitness differences. Many results have been derived using weak selection approximations, in which perturbation analysis facilitates the derivation of analytical results. Here, we ask whether results derived under weak selection are also qualitatively valid for intermediate and strong selection. By “qualitatively valid” we mean that the ranking of strategies induced by an evolutionary process does not change when the intensity of selection increases. For two-strategy games, we show that the ranking obtained under weak selection cannot be carried over to higher selection intensity if the number of players exceeds two. For games with three (or more) strategies, previous examples for multiplayer games have shown that the ranking of strategies can change with the intensity of selection. In particular, rank changes imply that the most abundant strategy at one intensity of selection can become the least abundant for another. We show that this applies already to pairwise interactions for a broad class of evolutionary processes. Even when both weak and strong selection limits lead to consistent predictions, rank changes can occur for intermediate intensities of selection. To analyze how common such games are, we show numerically that for randomly drawn two-player games with three or more strategies, rank changes frequently occur and their likelihood increases rapidly with the number of strategies . In particular, rank changes are almost certain for , which jeopardizes the predictive power of results derived for weak selection. PMID:24339769

Regional cost and experience, not size or hospital inclusion, helps predict ACO success.

PubMed

Schulz, John; DeCamp, Matthew; Berkowitz, Scott A

2017-06-01

The Medicare Shared Savings Program (MSSP) continues to expand and now includes 434 accountable care organizations (ACOs) serving more than 7 million beneficiaries. During 2014, 86 of these ACOs earned over $300 million in shared savings payments by promoting higher-quality patient care at a lower cost.Whether organizational characteristics, regional cost of care, or experience in the MSSP are associated with the ability to achieve shared savings remains uncertain.Using financial results from 2013 and 2014, we examined all 339 MSSP ACOs with a 2012, 2013, or 2014 start-date. We used a cross-sectional analysis to examine all ACOs and used a multivariate logistic model to predict probability of achieving shared savings.Experience, as measured by years in the MSSP program, was associated with success and the ability to earn shared savings varied regionally. This variation was strongly associated with differences in regional Medicare fee-for-service per capita costs: ACOs in high cost regions were more likely to earn savings. In the multivariate model, the number of ACO beneficiaries, inclusion of a hospital or involvement of an academic medical center, was not associated with likelihood of earning shared savings, after accounting for regional baseline cost variation.These results suggest ACOs are learning and improving from their experience. Additionally, the results highlight regional differences in ACO success and the strong association with variation in regional per capita costs, which can inform CMS policy to help promote ACO success nationwide.

Attenuation relation for strong motion in Eastern Java based on appropriate database and method

NASA Astrophysics Data System (ADS)

Mahendra, Rian; Rohadi, Supriyanto; Rudyanto, Ariska

2017-07-01

The selection and determination of attenuation relation has become important for seismic hazard assessment in active seismic region. This research initially constructs the appropriate strong motion database, including site condition and type of the earthquake. The data set consisted of large number earthquakes of 5 ≤ Mw ≤ 9 and distance less than 500 km that occurred around Java from 2009 until 2016. The location and depth of earthquake are being relocated using double difference method to improve the quality of database. Strong motion data from twelve BMKG's accelerographs which are located in east Java is used. The site condition is known by using dominant period and Vs30. The type of earthquake is classified into crustal earthquake, interface, and intraslab based on slab geometry analysis. A total of 10 Ground Motion Prediction Equations (GMPEs) are tested using Likelihood (Scherbaum et al., 2004) and Euclidean Distance Ranking method (Kale and Akkar, 2012) with the associated database. The evaluation of these methods lead to a set of GMPEs that can be applied for seismic hazard in East Java where the strong motion data is collected. The result of these methods found that there is still high deviation of GMPEs, so the writer modified some GMPEs using inversion method. Validation was performed by analysing the attenuation curve of the selected GMPE and observation data in period 2015 up to 2016. The results show that the selected GMPE is suitable for estimated PGA value in East Java.

Migration, Business Formation, and the Informal Economy in Urban Mexico

PubMed Central

Riosmena, Fernando

2013-01-01

Although the informal economy has grown rapidly in several developing nations, and migration and informality may be related to similar types of credit constraints and market failures, previous research has not systematically attempted to identify if migrant households are more likely to start informal and formal businesses alike and if this association varies across local contexts. We examine the relationship between prior U.S. migration and the creation of both formal and informal businesses in urban Mexico using several criteria to indirectly assess sector location. We use data from 56 communities from the Mexican Migration Project to estimate multilevel survival and nonmultilevel competing risk models predicting the likelihood of informal, formal, and no business formation. The recent return migration of the household head is strongly associated with informal business creation, particularly in economically dynamic areas. On the other hand, migrants are only marginally more likely to start formal businesses in highly economically dynamic sending areas. PMID:23721676

Ecological and morphological traits predict depth-generalist fishes on coral reefs

PubMed Central

Bridge, Tom C. L.; Luiz, Osmar J.; Coleman, Richard R.; Kane, Corinne N.; Kosaki, Randall K.

2016-01-01

Ecological communities that occupy similar habitats may exhibit functional convergence despite significant geographical distances and taxonomic dissimilarity. On coral reefs, steep gradients in key environmental variables (e.g. light and wave energy) restrict some species to shallow depths. We show that depth-generalist reef fishes are correlated with two species-level traits: caudal fin aspect ratio and diet. Fishes with high aspect ratio (lunate) caudal fins produce weaker vortices in the water column while swimming, and we propose that ‘silent swimming’ reduces the likelihood of detection and provides an advantage on deeper reefs with lower light irradiance and water motion. Significant differences in depth preference among trophic guilds reflect variations in the availability of different food sources along a depth gradient. The significance of these two traits across three geographically and taxonomically distinct assemblages suggests that deep-water habitats exert a strong environmental filter on coral reef-fish assemblages. PMID:26791616

Data Mining and Knowledge Management in Higher Education -Potential Applications.

ERIC Educational Resources Information Center

Luan, Jing

This paper introduces a new decision support tool, data mining, in the context of knowledge management. The most striking features of data mining techniques are clustering and prediction. The clustering aspect of data mining offers comprehensive characteristics analysis of students, while the predicting function estimates the likelihood for a…

Do Judgments of Learning Predict Automatic Influences of Memory?

ERIC Educational Resources Information Center

Undorf, Monika; Böhm, Simon; Cüpper, Lutz

2016-01-01

Current memory theories generally assume that memory performance reflects both recollection and automatic influences of memory. Research on people's predictions about the likelihood of remembering recently studied information on a memory test, that is, on judgments of learning (JOLs), suggests that both magnitude and resolution of JOLs are linked…

Evaluation of dynamic coastal response to sea-level rise modifies inundation likelihood

USGS Publications Warehouse

Lentz, Erika E.; Thieler, E. Robert; Plant, Nathaniel G.; Stippa, Sawyer R.; Horton, Radley M.; Gesch, Dean B.

2016-01-01

Sea-level rise (SLR) poses a range of threats to natural and built environments1, 2, making assessments of SLR-induced hazards essential for informed decision making3. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30 × 30 m resolution predictions for more than 38,000 km2 of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.

Literature review on vehicle travel speeds and pedestrian injuries

DOT National Transportation Integrated Search

1999-10-01

The relationship between vehicle travel speeds and resulting pedestrian injury was reviewed in the literature and in existing data sets. Results indicated that higher vehicle speeds are strongly associated with both a greater likelihood of pedestrian...

Designing environmental campaigns by using agent-based simulations: strategies for changing environmental attitudes.

PubMed

Mosler, Hans-Joachim; Martens, Thomas

2008-09-01

Agent-based computer simulation was used to create artificial communities in which each individual was constructed according to the principles of the elaboration likelihood model of Petty and Cacioppo [1986. The elaboration likelihood model of persuasion. In: Berkowitz, L. (Ed.), Advances in Experimental Social Psychology. Academic Press, New York, NY, pp. 123-205]. Campaigning strategies and community characteristics were varied systematically to understand and test their impact on attitudes towards environmental protection. The results show that strong arguments influence a green (environmentally concerned) population with many contacts most effectively, while peripheral cues have the greatest impact on a non-green population with fewer contacts. Overall, deeper information scrutiny increases the impact of strong arguments but is especially important for convincing green populations. Campaigns involving person-to-person communication are superior to mass-media campaigns because they can be adapted to recipients' characteristics.

Education and black-white interracial marriage.

PubMed

Gullickson, Aaron

2006-11-01

This article examines competing theoretical claims regarding how an individual's education will affect his or her likelihood of interracial marriage. I demonstrate that prior models of interracial marriage have failed to adequately distinguish the joint and marginal effects of education on interracial marriage and present a model capable of distinguishing these effects. I test this model on black-white interracial marriages using 1980, 1990, and 2000 U.S. census data. The results reveal partial support for status exchange theory within black male-white female unions and strong isolation of lower-class blacks from the interracial marriage market. Structural assimilation theory is not supported because the educational attainment of whites is not related in any consistent fashion to the likelihood of interracial marriage. The strong isolation of lower-class blacks from the interracial marriage market has gone unnoticed in prior research because of the failure of prior methods to distinguish joint and marginal effects.

Maximum likelihood convolutional decoding (MCD) performance due to system losses

NASA Technical Reports Server (NTRS)

Webster, L.

1976-01-01

A model for predicting the computational performance of a maximum likelihood convolutional decoder (MCD) operating in a noisy carrier reference environment is described. This model is used to develop a subroutine that will be utilized by the Telemetry Analysis Program to compute the MCD bit error rate. When this computational model is averaged over noisy reference phase errors using a high-rate interpolation scheme, the results are found to agree quite favorably with experimental measurements.

Multifactorial Likelihood Assessment of BRCA1 and BRCA2 Missense Variants Confirms That BRCA1:c.122A>G(p.His41Arg) Is a Pathogenic Mutation

PubMed Central

Whiley, Phillip J.; Parsons, Michael T.; Leary, Jennifer; Tucker, Kathy; Warwick, Linda; Dopita, Belinda; Thorne, Heather; Lakhani, Sunil R.; Goldgar, David E.; Brown, Melissa A.; Spurdle, Amanda B.

2014-01-01

Rare exonic, non-truncating variants in known cancer susceptibility genes such as BRCA1 and BRCA2 are problematic for genetic counseling and clinical management of relevant families. This study used multifactorial likelihood analysis and/or bioinformatically-directed mRNA assays to assess pathogenicity of 19 BRCA1 or BRCA2 variants identified following patient referral to clinical genetic services. Two variants were considered to be pathogenic (Class 5). BRCA1:c.4484G> C(p.Arg1495Thr) was shown to result in aberrant mRNA transcripts predicted to encode truncated proteins. The BRCA1:c.122A>G(p.His41Arg) RING-domain variant was found from multifactorial likelihood analysis to have a posterior probability of pathogenicity of 0.995, a result consistent with existing protein functional assay data indicating lost BARD1 binding and ubiquitin ligase activity. Of the remaining variants, seven were determined to be not clinically significant (Class 1), nine were likely not pathogenic (Class 2), and one was uncertain (Class 3).These results have implications for genetic counseling and medical management of families carrying these specific variants. They also provide additional multifactorial likelihood variant classifications as reference to evaluate the sensitivity and specificity of bioinformatic prediction tools and/or functional assay data in future studies. PMID:24489791

Epidemiology of Suicide Attempts among Youth Transitioning to Adulthood.

PubMed

Thompson, Martie P; Swartout, Kevin

2018-04-01

Suicide is the second leading cause of death for older adolescents and young adults. Although empirical literature has identified important risk factors of suicidal behavior, it is less understood if changes in risk factors correspond with changes in suicide risk. To address this knowledge gap, we assessed if there were different trajectories of suicidal behavior as youth transition into young adulthood and determined what time-varying risk factors predicted these trajectories. This study used four waves of data spanning approximately 13 years from the National Longitudinal Study of Adolescent Health. The sample included 9027 respondents who were 12-18 years old (M = 15.26; SD = 1.76) at Wave 1, 50% male, 17% Hispanic, and 58% White. The results indicated that 93.6% of the sample had a low likelihood for suicide attempts across time, 5.1% had an elevated likelihood of attempting suicide in adolescence but not young adulthood, and 1.3% had an elevated likelihood of attempting suicide during adolescence and adulthood. The likelihood of a suicide attempt corresponded with changes on depression, impulsivity, delinquency, alcohol problems, family and friend suicide history, and experience with partner violence. Determining how suicide risk changes as youth transition into young adulthood and what factors predict these changes can help prevent suicide. Interventions targeting these risk factors could lead to reductions in suicide attempts.

Stochastic capture zone analysis of an arsenic-contaminated well using the generalized likelihood uncertainty estimator (GLUE) methodology

NASA Astrophysics Data System (ADS)

Morse, Brad S.; Pohll, Greg; Huntington, Justin; Rodriguez Castillo, Ramiro

2003-06-01

In 1992, Mexican researchers discovered concentrations of arsenic in excess of World Heath Organization (WHO) standards in several municipal wells in the Zimapan Valley of Mexico. This study describes a method to delineate a capture zone for one of the most highly contaminated wells to aid in future well siting. A stochastic approach was used to model the capture zone because of the high level of uncertainty in several input parameters. Two stochastic techniques were performed and compared: "standard" Monte Carlo analysis and the generalized likelihood uncertainty estimator (GLUE) methodology. The GLUE procedure differs from standard Monte Carlo analysis in that it incorporates a goodness of fit (termed a likelihood measure) in evaluating the model. This allows for more information (in this case, head data) to be used in the uncertainty analysis, resulting in smaller prediction uncertainty. Two likelihood measures are tested in this study to determine which are in better agreement with the observed heads. While the standard Monte Carlo approach does not aid in parameter estimation, the GLUE methodology indicates best fit models when hydraulic conductivity is approximately 10-6.5 m/s, with vertically isotropic conditions and large quantities of interbasin flow entering the basin. Probabilistic isochrones (capture zone boundaries) are then presented, and as predicted, the GLUE-derived capture zones are significantly smaller in area than those from the standard Monte Carlo approach.

Indeterminate lung nodules in cancer patients: pretest probability of malignancy and the role of 18F-FDG PET/CT.

PubMed

Evangelista, Laura; Panunzio, Annalori; Polverosi, Roberta; Pomerri, Fabio; Rubello, Domenico

2014-03-01

The purpose of this study was to determine likelihood of malignancy for indeterminate lung nodules identified on CT comparing two standardized models with (18)F-FDG PET/CT. Fifty-nine cancer patients with indeterminate lung nodules (solid tumors; diameter, ≥5 mm) on CT had FDG PET/CT for lesion characterization. Mayo Clinic and Veterans Affairs Cooperative Study models of likelihood of malignancy were applied to solitary pulmonary nodules. High probability of malignancy was assigned a priori for multiple nodules. Low (<5%), intermediate (5-60%), and high (>60%) pretest malignancy probabilities were analyzed separately. Patients were reclassified with PET/CT. Histopathology or 2-year imaging follow-up established diagnosis. Outcome-based reclassification differences were defined as net reclassification improvement. A null hypothesis of asymptotic test was applied. Thirty-one patients had histology-proven malignancy. PET/CT was true-positive in 24 and true-negative in 25 cases. Negative predictive value was 78% and positive predictive value was 89%. On the basis of the Mayo Clinic model (n=31), 18 patients had low, 12 had intermediate, and one had high pretest likelihood; on the basis of the Veterans Affairs model (n=26), 5 patients had low, 20 had intermediate, and one had high pretest likelihood. Because of multiple lung nodules, 28 patients were classified as having high malignancy risk. PET/CT showed 32 negative and 27 positive scans. Net reclassification improvements respectively were 0.95 and 1.6 for Mayo Clinic and Veterans Affairs models (both p<0.0001). Fourteen of 31 (45.2%) and 12 of 26 (46.2%) patients with low and intermediate pretest likelihood, respectively, had positive findings on PET/CT for the Mayo Clinic and Veterans Affairs models, respectively. Of 15 patients with high pretest likelihood and negative findings on PET/CT, 13 (86.7%) did not have lung malignancy. PET/CT improves stratification of cancer patients with indeterminate pulmonary nodules. A substantial number of patients considered at low and intermediate pretest likelihood of malignancy with histology-proven lung malignancy showed abnormal PET/CT findings.

Transvaginal ultrasonographic cervical measurement in predicting failed labor induction and cesarean delivery for failure to progress in nulliparous women.

PubMed

Park, Kyo Hoon

2007-08-01

The aim of this study was to evaluate the value of transvaginal sonographic cervical measurement in predicting failed labor induction and cesarean delivery for failure to progress in nulliparous women. One hundred and sixty-one women scheduled for labor induction underwent transvaginal ultrasonography and digital cervical examinations. Logistic regression demonstrated that cervical length and gestational age at induction, but not the Bishop score, significantly and independently predicted failed labor induction. According to the receiver operating characteristic curves analysis, the best cut-off value of cervical length for predicting failed labor induction was 28 mm, with a sensitivity of 62% and a specificity of 60%. In terms of the likelihood of a cesarean delivery for failure to progress as the outcome variable, logistic regression indicated that maternal height and birth weight, but not cervical length or Bishop score, were significantly and independently associated with an increased risk of cesarean delivery for failure to progress. Transvaginal sonographic measurements of cervical length thus independently predicted failed labor induction in nulliparous women. However, the relatively poor predictive performance of this test undermines its clinical usefulness as a predictor of failed labor induction. Moreover, cervical length appears to have a poor predictive value for the likelihood of a cesarean delivery for failure to progress.

Urine cytokine and chemokine levels predict urinary tract infection severity independent of uropathogen, urine bacterial burden, host genetics, and host age.

PubMed

Armbruster, Chelsie E; Smith, Sara N; Mody, Lona; Mobley, Harry L T

2018-06-11

Urinary tract infections (UTIs) are among the most common infections worldwide. Diagnosing UTIs in older adults poses a significant challenge as asymptomatic colonization is common. Identification of a non-invasive profile that predicts likelihood of progressing from urine colonization to severe disease would provide a significant advantage in clinical practice. We monitored colonization susceptibility, disease severity, and immune response to two uropathogens in two mouse strains across three age groups to identify predictors of infection outcome. Proteus mirabilis caused more severe disease than Escherichia coli, regardless of mouse strain or age, and was associated with differences in IL-1β, IFN-β, CXCL5 (LIX), CCL5 (RANTES), and CCL2 (MCP-1). In comparing the response to infection across age groups, mature adult mice were better able to control colonization and prevent progression to kidney colonization and bacteremia than young or aged mice, regardless of mouse strain or bacterial species, and this was associated with differences in IL-23, CXCL1, and CCL5. A bimodal distribution was noted for urine colonization, which was strongly associated with bladder CFUs and the magnitude of the immune response but independent of age or disease severity. To determine the value of urine cytokine and chemokine levels for predicting severe disease, all infection datasets were combined and subjected to a series of logistic regressions. A multivariate model incorporating IL-1β, CXCL1, and CCL2 had strong predictive value for identifying mice that did not develop kidney colonization or bacteremia, regardless of mouse genetic background, age, infecting bacterial species, or urine bacterial burden. In conclusion, urine cytokine profiles could potentially serve as a non-invasive decision-support tool in clinical practice and contribute to antimicrobial stewardship. Copyright © 2018 American Society for Microbiology.

Predicting Likelihood of Surgery Prior to First Visit in Patients with Back and Lower Extremity Symptoms: A simple mathematical model based on over 8000 patients.

PubMed

Boden, Lauren M; Boden, Stephanie A; Premkumar, Ajay; Gottschalk, Michael B; Boden, Scott D

2018-02-09

Retrospective analysis of prospectively collected data. To create a data-driven triage system stratifying patients by likelihood of undergoing spinal surgery within one year of presentation. Low back pain (LBP) and radicular lower extremity (LE) symptoms are common musculoskeletal problems. There is currently no standard data-derived triage process based on information that can be obtained prior to the initial physician-patient encounter to direct patients to the optimal physician type. We analyzed patient-reported data from 8006 patients with a chief complaint of LBP and/or LE radicular symptoms who presented to surgeons at a large multidisciplinary spine center between September 1, 2005 and June 30, 2016. Univariate and multivariate analysis identified independent risk factors for undergoing spinal surgery within one year of initial visit. A model incorporating these risk factors was created using a random sample of 80% of the total patients in our cohort, and validated on the remaining 20%. The baseline one-year surgery rate within our cohort was 39% for all patients and 42% for patients with LE symptoms. Those identified as high likelihood by the center's existing triage process had a surgery rate of 45%. The new triage scoring system proposed in this study was able to identify a high likelihood group in which 58% underwent surgery, which is a 46% higher surgery rate than in non-triaged patients and a 29% improvement from our institution's existing triage system. The data-driven triage model and scoring system derived and validated in this study (Spine Surgery Likelihood model [SSL-11]), significantly improved existing processes in predicting the likelihood of undergoing spinal surgery within one year of initial presentation. This triage system will allow centers to more selectively screen for surgical candidates and more effectively direct patients to surgeons or non-operative spine specialists. 4.

Fast automated analysis of strong gravitational lenses with convolutional neural networks

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

Hezaveh, Yashar D.; Levasseur, Laurence Perreault; Marshall, Philip J.

Quantifying image distortions caused by strong gravitational lensing—the formation of multiple images of distant sources due to the deflection of their light by the gravity of intervening structures—and estimating the corresponding matter distribution of these structures (the ‘gravitational lens’) has primarily been performed using maximum likelihood modelling of observations. Our procedure is typically time- and resource-consuming, requiring sophisticated lensing codes, several data preparation steps, and finding the maximum likelihood model parameters in a computationally expensive process with downhill optimizers. Accurate analysis of a single gravitational lens can take up to a few weeks and requires expert knowledge of the physicalmore » processes and methods involved. Tens of thousands of new lenses are expected to be discovered with the upcoming generation of ground and space surveys. We report the use of deep convolutional neural networks to estimate lensing parameters in an extremely fast and automated way, circumventing the difficulties that are faced by maximum likelihood methods. We also show that the removal of lens light can be made fast and automated using independent component analysis of multi-filter imaging data. Our networks can recover the parameters of the ‘singular isothermal ellipsoid’ density profile, which is commonly used to model strong lensing systems, with an accuracy comparable to the uncertainties of sophisticated models but about ten million times faster: 100 systems in approximately one second on a single graphics processing unit. These networks can provide a way for non-experts to obtain estimates of lensing parameters for large samples of data.« less

Fast automated analysis of strong gravitational lenses with convolutional neural networks

DOE PAGES

Hezaveh, Yashar D.; Levasseur, Laurence Perreault; Marshall, Philip J.

2017-08-30

Quantifying image distortions caused by strong gravitational lensing—the formation of multiple images of distant sources due to the deflection of their light by the gravity of intervening structures—and estimating the corresponding matter distribution of these structures (the ‘gravitational lens’) has primarily been performed using maximum likelihood modelling of observations. Our procedure is typically time- and resource-consuming, requiring sophisticated lensing codes, several data preparation steps, and finding the maximum likelihood model parameters in a computationally expensive process with downhill optimizers. Accurate analysis of a single gravitational lens can take up to a few weeks and requires expert knowledge of the physicalmore » processes and methods involved. Tens of thousands of new lenses are expected to be discovered with the upcoming generation of ground and space surveys. We report the use of deep convolutional neural networks to estimate lensing parameters in an extremely fast and automated way, circumventing the difficulties that are faced by maximum likelihood methods. We also show that the removal of lens light can be made fast and automated using independent component analysis of multi-filter imaging data. Our networks can recover the parameters of the ‘singular isothermal ellipsoid’ density profile, which is commonly used to model strong lensing systems, with an accuracy comparable to the uncertainties of sophisticated models but about ten million times faster: 100 systems in approximately one second on a single graphics processing unit. These networks can provide a way for non-experts to obtain estimates of lensing parameters for large samples of data.« less

Fast automated analysis of strong gravitational lenses with convolutional neural networks

NASA Astrophysics Data System (ADS)

Hezaveh, Yashar D.; Levasseur, Laurence Perreault; Marshall, Philip J.

2017-08-01

Quantifying image distortions caused by strong gravitational lensing—the formation of multiple images of distant sources due to the deflection of their light by the gravity of intervening structures—and estimating the corresponding matter distribution of these structures (the ‘gravitational lens’) has primarily been performed using maximum likelihood modelling of observations. This procedure is typically time- and resource-consuming, requiring sophisticated lensing codes, several data preparation steps, and finding the maximum likelihood model parameters in a computationally expensive process with downhill optimizers. Accurate analysis of a single gravitational lens can take up to a few weeks and requires expert knowledge of the physical processes and methods involved. Tens of thousands of new lenses are expected to be discovered with the upcoming generation of ground and space surveys. Here we report the use of deep convolutional neural networks to estimate lensing parameters in an extremely fast and automated way, circumventing the difficulties that are faced by maximum likelihood methods. We also show that the removal of lens light can be made fast and automated using independent component analysis of multi-filter imaging data. Our networks can recover the parameters of the ‘singular isothermal ellipsoid’ density profile, which is commonly used to model strong lensing systems, with an accuracy comparable to the uncertainties of sophisticated models but about ten million times faster: 100 systems in approximately one second on a single graphics processing unit. These networks can provide a way for non-experts to obtain estimates of lensing parameters for large samples of data.

The role of implementation intention formation in promoting hepatitis B vaccination uptake among men who have sex with men.

PubMed

Vet, Raymond; de Wit, John B F; Das, Enny

2014-02-01

This study assessed the separate and joint effects of having a goal intention and the completeness of implementation intention formation on the likelihood of attending an appointment to obtain vaccination against the hepatitis B virus among men who have sex with men (MSM) in the Netherlands. Extending previous research, it was hypothesized that to be effective in promoting vaccination, implementation intention formation not only requires a strong goal intention, but also complete details specifying when, where and how to make an appointment to obtain hepatitis B virus vaccination among MSM. MSM at risk for hepatitis B virus (N = 616), with strong or weak intentions to obtain hepatitis B virus vaccination, were randomly assigned to form an implementation intention or not. Completeness of implementation intentions was rated and hepatitis B virus uptake was assessed through data linkage with the joint vaccination registry of the collaborating Public Health Services. Having a strong goal intention to obtain hepatitis B virus vaccination and forming an implementation intention, each significantly and independently increased the likelihood of MSM obtaining hepatitis B virus vaccination. In addition, MSM who formed complete implementation intentions were more successful in obtaining vaccination (p < 0.01). The formation of complete implementation intentions was promoted by strong goal intentions (p < 0.01).

Child Maltreatment: An Analysis of Familial and Institutional Predictors.

ERIC Educational Resources Information Center

Ory, Marcia G.; Earp, Jo Anne L.

1980-01-01

Social disorganization in the family was found to be strongly related to the likelihood of child maltreatment. Utilization of social services, on the other hand, had a counterbalancing, negative impact on the occurrence of child maltreatment. (Author/CS)

Effect of Provider Experience on Clinician-Performed Ultrasonography for Hydronephrosis in Patients With Suspected Renal Colic

PubMed Central

Herbst, Meghan K.; Rosenberg, Graeme; Daniels, Brock; Gross, Cary P.; Singh, Dinesh; Molinaro, Annette M.; Luty, Seth; Moore, Christopher L.

2016-01-01

Study objective Hydronephrosis is readily visible on ultrasonography and is a strong predictor of ureteral stones, but ultrasonography is a user-dependent technology and the test characteristics of clinician-performed ultrasonography for hydronephrosis are incompletely characterized, as is the effect of ultrasound fellowship training on predictive accuracy. We seek to determine the test characteristics of ultrasonography for detecting hydronephrosis when performed by clinicians with a wide range of experience under conditions of direct patient care. Methods This was a prospective study of patients presenting to an academic medical center emergency department with suspected renal colic. Before computed tomography (CT) results, an emergency clinician performed bedside ultrasonography, recording the presence and degree of hydronephrosis. CT data were abstracted from the dictated radiology report by an investigator blinded to the bedside ultrasonographic results. Test characteristics of bedside ultrasonography for hydronephrosis were calculated with the CT scan as the reference standard, with test characteristics compared by clinician experience stratified into 4 levels: attending physicians with emergency ultrasound fellowship training, attending physicians without emergency ultrasound fellowship training, ultrasound experienced non–attending physician clinicians (at least 2 weeks of ultrasound training), and ultrasound inexperienced non–attending physician clinicians (physician assistants, nurse practitioners, off-service rotators, and first-year emergency medicine residents with fewer than 2 weeks of ultrasound training). Results There were 670 interpretable bedside ultrasonographic tests performed by 144 unique clinicians, 80.9% of which were performed by clinicians directly involved in the care of the patient. On CT, 47.5% of all subjects had hydronephrosis and 47.0% had a ureteral stone. Among all clinicians, ultrasonography had a sensitivity of 72.6% (95% confidence interval [CI] 65.4% to 78.9%), specificity of 73.3% (95% CI 66.1% to 79.4%), positive likelihood ratio of 2.72 (95% CI 2.25 to 3.27), and negative likelihood ratio of 0.37 (95% CI 0.31 to 0.44) for hydronephrosis, using hydronephrosis on CT as the criterion standard. Among attending physicians with fellowship training, ultrasonography had sensitivity of 92.7% (95% CI 83.8% to 96.9%), positive likelihood ratio of 4.97 (95% CI 2.90 to 8.51), and negative likelihood ratio of 0.08 (95% CI 0.03 to 0.23). Conclusion Overall, ultrasonography performed by emergency clinicians was moderately sensitive and specific for detection of hydronephrosis as seen on CT in patients with suspected renal colic. However, presence or absence of hydronephrosis as determined by emergency physicians with fellowship training in ultrasonography yielded more definitive test results. For clinicians without fellowship training, there was no significant difference between groups in the predictive accuracy of the application according to experience level. PMID:24630203

Effect of provider experience on clinician-performed ultrasonography for hydronephrosis in patients with suspected renal colic.

PubMed

Herbst, Meghan K; Rosenberg, Graeme; Daniels, Brock; Gross, Cary P; Singh, Dinesh; Molinaro, Annette M; Luty, Seth; Moore, Christopher L

2014-09-01

Hydronephrosis is readily visible on ultrasonography and is a strong predictor of ureteral stones, but ultrasonography is a user-dependent technology and the test characteristics of clinician-performed ultrasonography for hydronephrosis are incompletely characterized, as is the effect of ultrasound fellowship training on predictive accuracy. We seek to determine the test characteristics of ultrasonography for detecting hydronephrosis when performed by clinicians with a wide range of experience under conditions of direct patient care. This was a prospective study of patients presenting to an academic medical center emergency department with suspected renal colic. Before computed tomography (CT) results, an emergency clinician performed bedside ultrasonography, recording the presence and degree of hydronephrosis. CT data were abstracted from the dictated radiology report by an investigator blinded to the bedside ultrasonographic results. Test characteristics of bedside ultrasonography for hydronephrosis were calculated with the CT scan as the reference standard, with test characteristics compared by clinician experience stratified into 4 levels: attending physicians with emergency ultrasound fellowship training, attending physicians without emergency ultrasound fellowship training, ultrasound experienced non-attending physician clinicians (at least 2 weeks of ultrasound training), and ultrasound inexperienced non-attending physician clinicians (physician assistants, nurse practitioners, off-service rotators, and first-year emergency medicine residents with fewer than 2 weeks of ultrasound training). There were 670 interpretable bedside ultrasonographic tests performed by 144 unique clinicians, 80.9% of which were performed by clinicians directly involved in the care of the patient. On CT, 47.5% of all subjects had hydronephrosis and 47.0% had a ureteral stone. Among all clinicians, ultrasonography had a sensitivity of 72.6% (95% confidence interval [CI] 65.4% to 78.9%), specificity of 73.3% (95% CI 66.1% to 79.4%), positive likelihood ratio of 2.72 (95% CI 2.25 to 3.27), and negative likelihood ratio of 0.37 (95% CI 0.31 to 0.44) for hydronephrosis, using hydronephrosis on CT as the criterion standard. Among attending physicians with fellowship training, ultrasonography had sensitivity of 92.7% (95% CI 83.8% to 96.9%), positive likelihood ratio of 4.97 (95% CI 2.90 to 8.51), and negative likelihood ratio of 0.08 (95% CI 0.03 to 0.23). Overall, ultrasonography performed by emergency clinicians was moderately sensitive and specific for detection of hydronephrosis as seen on CT in patients with suspected renal colic. However, presence or absence of hydronephrosis as determined by emergency physicians with fellowship training in ultrasonography yielded more definitive test results. For clinicians without fellowship training, there was no significant difference between groups in the predictive accuracy of the application according to experience level. Copyright © 2014 American College of Emergency Physicians. Published by Mosby, Inc. All rights reserved.

A new model to predict weak-lensing peak counts. II. Parameter constraint strategies

NASA Astrophysics Data System (ADS)

Lin, Chieh-An; Kilbinger, Martin

2015-11-01

Context. Peak counts have been shown to be an excellent tool for extracting the non-Gaussian part of the weak lensing signal. Recently, we developed a fast stochastic forward model to predict weak-lensing peak counts. Our model is able to reconstruct the underlying distribution of observables for analysis. Aims: In this work, we explore and compare various strategies for constraining a parameter using our model, focusing on the matter density Ωm and the density fluctuation amplitude σ8. Methods: First, we examine the impact from the cosmological dependency of covariances (CDC). Second, we perform the analysis with the copula likelihood, a technique that makes a weaker assumption than does the Gaussian likelihood. Third, direct, non-analytic parameter estimations are applied using the full information of the distribution. Fourth, we obtain constraints with approximate Bayesian computation (ABC), an efficient, robust, and likelihood-free algorithm based on accept-reject sampling. Results: We find that neglecting the CDC effect enlarges parameter contours by 22% and that the covariance-varying copula likelihood is a very good approximation to the true likelihood. The direct techniques work well in spite of noisier contours. Concerning ABC, the iterative process converges quickly to a posterior distribution that is in excellent agreement with results from our other analyses. The time cost for ABC is reduced by two orders of magnitude. Conclusions: The stochastic nature of our weak-lensing peak count model allows us to use various techniques that approach the true underlying probability distribution of observables, without making simplifying assumptions. Our work can be generalized to other observables where forward simulations provide samples of the underlying distribution.

Analysis of hourly crash likelihood using unbalanced panel data mixed logit model and real-time driving environmental big data.

PubMed

Chen, Feng; Chen, Suren; Ma, Xiaoxiang

2018-06-01

Driving environment, including road surface conditions and traffic states, often changes over time and influences crash probability considerably. It becomes stretched for traditional crash frequency models developed in large temporal scales to capture the time-varying characteristics of these factors, which may cause substantial loss of critical driving environmental information on crash prediction. Crash prediction models with refined temporal data (hourly records) are developed to characterize the time-varying nature of these contributing factors. Unbalanced panel data mixed logit models are developed to analyze hourly crash likelihood of highway segments. The refined temporal driving environmental data, including road surface and traffic condition, obtained from the Road Weather Information System (RWIS), are incorporated into the models. Model estimation results indicate that the traffic speed, traffic volume, curvature and chemically wet road surface indicator are better modeled as random parameters. The estimation results of the mixed logit models based on unbalanced panel data show that there are a number of factors related to crash likelihood on I-25. Specifically, weekend indicator, November indicator, low speed limit and long remaining service life of rutting indicator are found to increase crash likelihood, while 5-am indicator and number of merging ramps per lane per mile are found to decrease crash likelihood. The study underscores and confirms the unique and significant impacts on crash imposed by the real-time weather, road surface, and traffic conditions. With the unbalanced panel data structure, the rich information from real-time driving environmental big data can be well incorporated. Copyright © 2018 National Safety Council and Elsevier Ltd. All rights reserved.

Childhood Sports Participation and Adolescent Sport Profile.

PubMed

Gallant, François; O'Loughlin, Jennifer L; Brunet, Jennifer; Sabiston, Catherine M; Bélanger, Mathieu

2017-12-01

We aimed to increase understanding of the link between sport specialization during childhood and adolescent physical activity (PA). The objectives were as follows: (1) describe the natural course of sport participation over 5 years among children who are early sport samplers or early sport specializers and (2) determine if a sport participation profile in childhood predicts the sport profile in adolescence. Participants ( n = 756, ages 10-11 years at study inception) reported their participation in organized and unorganized PA during in-class questionnaires administered every 4 months over 5 years. They were categorized as early sport samplers, early sport specializers, or nonparticipants in year 1 and as recreational sport participants, performance sport participants, or nonparticipants in years 2 to 5. The likelihood that a childhood sport profile would predict the adolescent profile was computed as relative risks. Polynomial logistic regression was used to identify predictors of an adolescent sport profile. Compared with early sport specialization and nonparticipation, early sport sampling in childhood was associated with a higher likelihood of recreational participation (relative risk, 95% confidence interval: 1.55, 1.18-2.03) and a lower likelihood of nonparticipation (0.69, 0.51-0.93) in adolescence. Early sport specialization was associated with a higher likelihood of performance participation (1.65, 1.19-2.28) but not of nonparticipation (1.01, 0.70-1.47) in adolescence. Nonparticipation in childhood was associated with nearly doubling the likelihood of nonparticipation in adolescence (1.88, 1.36-2.62). Sport sampling should be promoted in childhood because it may be linked to higher PA levels during adolescence. Copyright © 2017 by the American Academy of Pediatrics.

PREDICTING CHRONIC LETHALITY OF CHEMICALS TO FISHES FROM ACUTE TOXICITY TEST DATA: THEORY OF ACCELERATED LIFE TESTING

EPA Science Inventory

A method for modeling aquatic toxicity date based on the theory of accelerated life testing and a procedure for maximum likelihood fitting the proposed model is presented. he procedure is computerized as software, which can predict chronic lethality of chemicals using data from a...

An Evaluation of the Predictive Validity of Confidence Ratings in Identifying Functional Behavioral Assessment Hypothesis Statements

ERIC Educational Resources Information Center

Borgmeier, Chris; Horner, Robert H.

2006-01-01

Faced with limited resources, schools require tools that increase the accuracy and efficiency of functional behavioral assessment. Yarbrough and Carr (2000) provided evidence that informant confidence ratings of the likelihood of problem behavior in specific situations offered a promising tool for predicting the accuracy of function-based…

Curriculum Track and Its Influences on Predicting High School Dropout Likelihood

ERIC Educational Resources Information Center

Mohd Kamalludeen, Rosemaliza

2012-01-01

Dropping out of school is a major concern as high school graduation credentials have been used as an important measurement tool to define post-secondary success. Numerous researchers presented a multitude of factors that predict dropouts at individual and school levels. Curriculum track choice, or high school course-taking sequence, defines…

Psychiatric Diagnoses in Historic and Contemporary Military Cohorts: Combat Deployment and the Healthy Warrior Effect

DTIC Science & Technology

2008-04-23

In general, the positive predictive value of screening questionnaires is quite poor when disease prevalence is modest/rare, as in the ex- ample of...of sensitivity, specificity, likelihood ratios and predictive values with disease prevalence . Stat Med 1997;16:981–91. 26. Wolfe J, Erickson DJ

Relationship between somatization and remission with ECT.

PubMed

Rasmussen, Keith G; Snyder, Karen A; Knapp, Rebecca G; Mueller, Martina; Yim, Eunsil; Husain, Mustafa M; Rummans, Teresa A; Sampson, Shirlene M; O'Connor, M Kevin; Bernstein, Hilary J; Kellner, Charles H

2004-12-30

Patients treated with electroconvulsive therapy (ECT) were divided into those with less severe depression and those with more severe depression. In the less severely depressed group, high somatic anxiety and hypochondriasis predicted a low likelihood of sustained remission with ECT. In the more severely depressed group, these traits were not predictive of ECT outcome.

Validation of a "Spurning Scale" for Teachers: The Chinese Sample.

ERIC Educational Resources Information Center

Cheuk, Wai H.; Wong, Kwok S.; Rosen, Sidney

2002-01-01

Chinese teachers in high-achieving (n=103) and low-achieving (n=77) schools completed measures of job satisfaction, intention to quit, and spurning (student rejection of teacher help). Teachers of lower achievers were spurned more often. For both groups, spurning predicted job satisfaction but not likelihood of quitting and also predicted stress…

Falling Off Track: How Teacher-Student Relationships Predict Early High School Failure Rates.

ERIC Educational Resources Information Center

Miller, Shazia Rafiullah

This paper examines the relationship between the climate of teacher-student relations within a school and individual student's likelihood of freshman year success. Using administrative data from the Chicago Public Schools and survey data, researchers used hierarchical linear modeling to determine whether teacher-student climate predicts students'…

PREDICTING ACADEMIC SUCCESS BEYOND HIGH SCHOOL.

ERIC Educational Resources Information Center

JEX, FRANK B.

THESE TABLES ARE INTENDED TO PREDICT WHICH UTAH COLLEGE CURRICULUM GIVES A STUDENT THE MOST LIKELIHOOD OF SUCCESS. THEY USE HIGH SCHOOL AVERAGE (HSA) AND ACADEMIC ACHIEVEMENT OR APTITUDE TESTS. THE STUDY IS DESIGNED ON CONCLUSIONS FROM EARLIER WORK--(1) THE MAIN HURDLE FOR THE FRESHMAN IS THE REQUIRED GENERAL EDUCATION CORE, (2) GPA'S ARE…

A Social Psychological Model for Predicting Sexual Harassment.

ERIC Educational Resources Information Center

Pryor, John B.; And Others

1995-01-01

Presents a Person X Situation (PXS) model of sexual harassment suggesting that sexually harassing behavior may be predicted from an analysis of social situational and personal factors. Research on sexual harassment proclivities in men is reviewed, and a profile of men who have a high a likelihood to sexually harass is discussed. Possible PXS…

Electroencephalogram-based decoding cognitive states using convolutional neural network and likelihood ratio based score fusion

PubMed Central

2017-01-01

Electroencephalogram (EEG)-based decoding human brain activity is challenging, owing to the low spatial resolution of EEG. However, EEG is an important technique, especially for brain–computer interface applications. In this study, a novel algorithm is proposed to decode brain activity associated with different types of images. In this hybrid algorithm, convolutional neural network is modified for the extraction of features, a t-test is used for the selection of significant features and likelihood ratio-based score fusion is used for the prediction of brain activity. The proposed algorithm takes input data from multichannel EEG time-series, which is also known as multivariate pattern analysis. Comprehensive analysis was conducted using data from 30 participants. The results from the proposed method are compared with current recognized feature extraction and classification/prediction techniques. The wavelet transform-support vector machine method is the most popular currently used feature extraction and prediction method. This method showed an accuracy of 65.7%. However, the proposed method predicts the novel data with improved accuracy of 79.9%. In conclusion, the proposed algorithm outperformed the current feature extraction and prediction method. PMID:28558002

The prospect of predictive testing for personal risk: attitudes and decision making.

PubMed

Wroe, A L; Salkovskis, P M; Rimes, K A

1998-06-01

As predictive tests for medical problems such as genetic disorders become more widely available, it becomes increasingly important to understand the processes involved in the decision whether or not to seek testing. This study investigates the decision to pursue the possibility of testing. Individuals (one group who had already contemplated the possibility of predictive testing and one group who had not) were asked to consider predictive testing for several diseases. They rated the likelihood of opting for testing and specified the reasons which they believed had affected their decision. The ratio of the numbers of reasons stated for testing and the numbers of reasons stated against testing was a good predictor of the stated likelihood of testing, particularly when the reasons were weighted by utility (importance). Those who had previously contemplated testing specified more emotional reasons. It is proposed that the decision process is internally logical although it may seem illogical to others due to there being idiosyncratic premises (or reasons) upon which the decision is based. It is concluded that the Utility Theory is a useful basis for describing how people make decisions related to predictive testing; modifications of the theory are proposed.

Information-theoretic model selection for optimal prediction of stochastic dynamical systems from data

NASA Astrophysics Data System (ADS)

Darmon, David

2018-03-01

In the absence of mechanistic or phenomenological models of real-world systems, data-driven models become necessary. The discovery of various embedding theorems in the 1980s and 1990s motivated a powerful set of tools for analyzing deterministic dynamical systems via delay-coordinate embeddings of observations of their component states. However, in many branches of science, the condition of operational determinism is not satisfied, and stochastic models must be brought to bear. For such stochastic models, the tool set developed for delay-coordinate embedding is no longer appropriate, and a new toolkit must be developed. We present an information-theoretic criterion, the negative log-predictive likelihood, for selecting the embedding dimension for a predictively optimal data-driven model of a stochastic dynamical system. We develop a nonparametric estimator for the negative log-predictive likelihood and compare its performance to a recently proposed criterion based on active information storage. Finally, we show how the output of the model selection procedure can be used to compare candidate predictors for a stochastic system to an information-theoretic lower bound.

Performance Comparison of Systemic Inflammatory Response Syndrome with Logistic Regression Models to Predict Sepsis in Neonates

PubMed Central

Thakur, Jyoti; Pahuja, Sharvan Kumar; Pahuja, Roop

2017-01-01

In 2005, an international pediatric sepsis consensus conference defined systemic inflammatory response syndrome (SIRS) for children <18 years of age, but excluded premature infants. In 2012, Hofer et al. investigated the predictive power of SIRS for term neonates. In this paper, we examined the accuracy of SIRS in predicting sepsis in neonates, irrespective of their gestational age (i.e., pre-term, term, and post-term). We also created two prediction models, named Model A and Model B, using binary logistic regression. Both models performed better than SIRS. We also developed an android application so that physicians can easily use Model A and Model B in real-world scenarios. The sensitivity, specificity, positive likelihood ratio (PLR) and negative likelihood ratio (NLR) in cases of SIRS were 16.15%, 95.53%, 3.61, and 0.88, respectively, whereas they were 29.17%, 97.82%, 13.36, and 0.72, respectively, in the case of Model A, and 31.25%, 97.30%, 11.56, and 0.71, respectively, in the case of Model B. All models were significant with p < 0.001. PMID:29257099

Comparison between presepsin and procalcitonin in early diagnosis of neonatal sepsis.

PubMed

Iskandar, Agustin; Arthamin, Maimun Z; Indriana, Kristin; Anshory, Muhammad; Hur, Mina; Di Somma, Salvatore

2018-05-09

Neonatal sepsis remains worldwide one of the leading causes of morbidity and mortality in both term and preterm infants. Lower mortality rates are related to timely diagnostic evaluation and prompt initiation of empiric antibiotic therapy. Blood culture, as gold standard examination for sepsis, has several limitations for early diagnosis, so that sepsis biomarkers could play an important role in this regard. This study was aimed to compare the value of the two biomarkers presepsin and procalcitonin in early diagnosis of neonatal sepsis. This was a prospective cross-sectional study performed, in Saiful Anwar General Hospital Malang, Indonesia, in 51 neonates that fulfill the criteria of systemic inflammatory response syndrome (SIRS) with blood culture as diagnostic gold standard for sepsis. At reviewer operating characteristic (ROC) curve analyses, using a presepsin cutoff of 706,5 pg/mL, the obtained area under the curve (AUCs) were: sensitivity = 85.7%, specificity = 68.8%, positive predictive value = 85.7%, negative predictive value = 68.8%, positive likelihood ratio = 2.75, negative likelihood ratio = 0.21, and accuracy = 80.4%. On the other hand, with a procalcitonin cutoff value of 161.33 pg/mL the obtained AUCs showed: sensitivity = 68.6%, specificity = 62.5%, positive predictive value = 80%, negative predictive value = 47.6%, positive likelihood ratio = 1.83, the odds ratio negative = 0.5, and accuracy = 66.7%. In early diagnosis of neonatal sepsis, compared with procalcitonin, presepsin seems to provide better early diagnostic value with consequent possible faster therapeutical decision making and possible positive impact on outcome of neonates.

Progression along the Bipolar Spectrum: A Longitudinal Study of Predictors of Conversion from Bipolar Spectrum Conditions to Bipolar I and II Disorders

PubMed Central

Alloy, Lauren B.; Urošević, Snežana; Abramson, Lyn Y.; Jager-Hyman, Shari; Nusslock, Robin; Whitehouse, Wayne G.; Hogan, Michael

2011-01-01

Little longitudinal research has examined progression to more severe bipolar disorders in individuals with “soft” bipolar spectrum conditions. We examine rates and predictors of progression to bipolar I and II diagnoses in a non-patient sample of college-age participants (n = 201) with high General Behavior Inventory scores and childhood or adolescent onset of “soft” bipolar spectrum disorders followed longitudinally for 4.5 years from the Longitudinal Investigation of Bipolar Spectrum (LIBS) project. Of 57 individuals with initial cyclothymia or bipolar disorder not otherwise specified (BiNOS) diagnoses, 42.1% progressed to a bipolar II diagnosis and 10.5% progressed to a bipolar I diagnosis. Of 144 individuals with initial bipolar II diagnoses, 17.4% progressed to a bipolar I diagnosis. Consistent with hypotheses derived from the clinical literature and the Behavioral Approach System (BAS) model of bipolar disorder, and controlling for relevant variables (length of follow-up, initial depressive and hypomanic symptoms, treatment-seeking, and family history), high BAS sensitivity (especially BAS Fun Seeking) predicted a greater likelihood of progression to bipolar II disorder, whereas early age of onset and high impulsivity predicted a greater likelihood of progression to bipolar I (high BAS sensitivity and Fun-Seeking also predicted progression to bipolar I when family history was not controlled). The interaction of high BAS and high Behavioral Inhibition System (BIS) sensitivities also predicted greater likelihood of progression to bipolar I. We discuss implications of the findings for the bipolar spectrum concept, the BAS model of bipolar disorder, and early intervention efforts. PMID:21668080

Recent victimization increases risk for violence in justice-involved persons with mental illness.

PubMed

Sadeh, Naomi; Binder, Renée L; McNiel, Dale E

2014-04-01

A large body of research has examined relationships between distal experiences of victimization and the likelihood of engaging in violence later in life. Less is known about the influence of recent violent victimization on risk for violence perpetration. To our knowledge, this is the first study to examine prospectively whether recent victimization in adulthood increases the risk of future violence. Specifically, the present study assessed the incremental validity of recent violent victimization in the prediction of future violence in a sample of justice-involved adults with serious mental illness. The study examined (a) whether recent experiences of violent victimization (i.e., within 6 months of the baseline assessment) predicted a greater likelihood of perpetrating violence in the next year, and (b) whether inclusion of recent victimization enhanced the predictive validity of a model of violence risk in a sample of justice-involved adults with severe mental illness (N = 167). Hierarchical logistic regression analyses indicated that exposure to recent violent victimization at the baseline assessment predicted a greater likelihood of engaging in violent behavior during the year follow-up period. Additionally, recent exposure to violence at the baseline assessment continued to explain a significant amount of variance in a model of future violence perpetration above the variance accounted for by well-established violence risk factors. Taken together, the findings suggest that recent victimization is important to consider in understanding and evaluating risk of violence by persons with mental disorders who are involved in the criminal justice system. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Risk Estimation and Sexual Behaviour: A Longitudinal Study of 16- 21-year olds.

PubMed

Breakwell, G M; Breakwell, G M

1996-01-01

The relationships among risk estimation, impulsivity and patterns of sexual risk-taking in 16-21-year-olds are examined. A sample of 236 males and 340 females completed a postal questionnaire on three occasions at annual intervals. They reported their assessment of their own risk of HIV infection, the risk of HIV infection associated with six types of sexual activity, their likelihood of engaging in each of these activities, and whether they had participated in these activities between the first and second data collections. Impulsivity was indexed using a standard test. The data support the conclusion that strong social representations of sexual risks exist which do not markedly change during late adolescence. These risk estimates predict behavioural expectations, primarily for the riskiest behaviours, and for females (actual participation in vaginal sex); but for males, risk estimates fail to predict behaviour. Evidence here for a rational model of individual decision- making in relation to sexual risk- taking is sparse. Impulsivity was not a good predictor of expected or actual patterns of sexual behaviour, though higher impulsivity was associated with having more sexual partners and, in females, with starting to have sex younger.

Functional heterogeneity of conflict, error, task-switching, and unexpectedness effects within medial prefrontal cortex.

PubMed

Nee, Derek Evan; Kastner, Sabine; Brown, Joshua W

2011-01-01

The last decade has seen considerable discussion regarding a theoretical account of medial prefrontal cortex (mPFC) function with particular focus on the anterior cingulate cortex. The proposed theories have included conflict detection, error likelihood prediction, volatility monitoring, and several distinct theories of error detection. Arguments for and against particular theories often treat mPFC as functionally homogeneous, or at least nearly so, despite some evidence for distinct functional subregions. Here we used functional magnetic resonance imaging (fMRI) to simultaneously contrast multiple effects of error, conflict, and task-switching that have been individually construed in support of various theories. We found overlapping yet functionally distinct subregions of mPFC, with activations related to dominant error, conflict, and task-switching effects successively found along a rostral-ventral to caudal-dorsal gradient within medial prefrontal cortex. Activations in the rostral cingulate zone (RCZ) were strongly correlated with the unexpectedness of outcomes suggesting a role in outcome prediction and preparing control systems to deal with anticipated outcomes. The results as a whole support a resolution of some ongoing debates in that distinct theories may each pertain to corresponding distinct yet overlapping subregions of mPFC. Copyright © 2010 Elsevier Inc. All rights reserved.

Residential Mobility During Adolescence: Do Even “Upward” Moves Predict Dropout Risk?

PubMed Central

Metzger, Molly W.; Fowler, Patrick J.; Anderson, Courtney Lauren; Lindsay, Constance A.

2015-01-01

This paper uses the National Longitudinal Study of Adolescent Health to investigate the impact of housing instability in adolescence on the likelihood of subsequent graduation from high school. Combining census data, self-reports, and information about respondents’ residential changes, we use the variation in the number of moves and neighborhood quality to predict whether participants obtain a high school diploma. Controlling for major predictors of housing mobility, students experiencing at least one move over a 12-month period have a roughly 50% decreased likelihood of obtaining a high school diploma by the age of 25. These associations are identified regardless of whether students move to a poorer or less-poor neighborhood. Our results carry implications for the development of housing policies and interventions designed for disadvantaged populations. PMID:26188449

A Complex Story: Universal Preference vs. Individual Differences Shaping Aesthetic Response to Fractals Patterns

PubMed Central

Street, Nichola; Forsythe, Alexandra M.; Reilly, Ronan; Taylor, Richard; Helmy, Mai S.

2016-01-01

Fractal patterns offer one way to represent the rough complexity of the natural world. Whilst they dominate many of our visual experiences in nature, little large-scale perceptual research has been done to explore how we respond aesthetically to these patterns. Previous research (Taylor et al., 2011) suggests that the fractal patterns with mid-range fractal dimensions (FDs) have universal aesthetic appeal. Perceptual and aesthetic responses to visual complexity have been more varied with findings suggesting both linear (Forsythe et al., 2011) and curvilinear (Berlyne, 1970) relationships. Individual differences have been found to account for many of the differences we see in aesthetic responses but some, such as culture, have received little attention within the fractal and complexity research fields. This two-study article aims to test preference responses to FD and visual complexity, using a large cohort (N = 443) of participants from around the world to allow universality claims to be tested. It explores the extent to which age, culture and gender can predict our preferences for fractally complex patterns. Following exploratory analysis that found strong correlations between FD and visual complexity, a series of linear mixed-effect models were implemented to explore if each of the individual variables could predict preference. The first tested a linear complexity model (likelihood of selecting the more complex image from the pair of images) and the second a mid-range FD model (likelihood of selecting an image within mid-range). Results show that individual differences can reliably predict preferences for complexity across culture, gender and age. However, in fitting with current findings the mid-range models show greater consistency in preference not mediated by gender, age or culture. This article supports the established theory that the mid-range fractal patterns appear to be a universal construct underlying preference but also highlights the fragility of universal claims by demonstrating individual differences in preference for the interrelated concept of visual complexity. This highlights a current stalemate in the field of empirical aesthetics. PMID:27252634

Performance of blend sign in predicting hematoma expansion in intracerebral hemorrhage: A meta-analysis.

PubMed

Yu, Zhiyuan; Zheng, Jun; Guo, Rui; Ma, Lu; Li, Mou; Wang, Xiaoze; Lin, Sen; Li, Hao; You, Chao

2017-12-01

Hematoma expansion is independently associated with poor outcome in intracerebral hemorrhage (ICH). Blend sign is a simple predictor for hematoma expansion on non-contrast computed tomography. However, its accuracy for predicting hematoma expansion is inconsistent in previous studies. This meta-analysis is aimed to systematically assess the performance of blend sign in predicting hematoma expansion in ICH. A systematic literature search was conducted. Original studies about predictive accuracy of blend sign for hematoma expansion in ICH were included. Pooled sensitivity, specificity, positive and negative likelihood ratios were calculated. Summary receiver operating characteristics curve was constructed. Publication bias was assessed by Deeks' funnel plot asymmetry test. A total of 5 studies with 2248 patients were included in this meta-analysis. The pooled sensitivity, specificity, positive and negative likelihood ratios of blend sign for predicting hematoma expansion were 0.28, 0.92, 3.4 and 0.78, respectively. The area under the curve (AUC) was 0.85. No significant publication bias was found. This meta-analysis demonstrates that blend sign is a useful predictor with high specificity for hematoma expansion in ICH. Further studies with larger sample size are still necessary to verify the accuracy of blend sign for predicting hematoma expansion. Copyright © 2017 Elsevier B.V. All rights reserved.

Diagnostic accuracy of liver fibrosis based on red cell distribution width (RDW) to platelet ratio with fibroscan in chronic hepatitis B

NASA Astrophysics Data System (ADS)

Sembiring, J.; Jones, F.

2018-03-01

Red cell Distribution Width (RDW) and platelet ratio (RPR) can predict liver fibrosis and cirrhosis in chronic hepatitis B with relatively high accuracy. RPR was superior to other non-invasive methods to predict liver fibrosis, such as AST and ALT ratio, AST and platelet ratio Index and FIB-4. The aim of this study was to assess diagnostic accuracy liver fibrosis by using RDW and platelets ratio in chronic hepatitis B patients based on compared with Fibroscan. This cross-sectional study was conducted at Adam Malik Hospital from January-June 2015. We examine 34 patients hepatitis B chronic, screen RDW, platelet, and fibroscan. Data were statistically analyzed. The result RPR with ROC procedure has an accuracy of 72.3% (95% CI: 84.1% - 97%). In this study, the RPR had a moderate ability to predict fibrosis degree (p = 0.029 with AUC> 70%). The cutoff value RPR was 0.0591, sensitivity and spesificity were 71.4% and 60%, Positive Prediction Value (PPV) was 55.6% and Negative Predictions Value (NPV) was 75%, positive likelihood ratio was 1.79 and negative likelihood ratio was 0.48. RPR have the ability to predict the degree of liver fibrosis in chronic hepatitis B patients with moderate accuracy.

Dancing to CHANGA: a self-consistent prediction for close SMBH pair formation time-scales following galaxy mergers

NASA Astrophysics Data System (ADS)

Tremmel, M.; Governato, F.; Volonteri, M.; Quinn, T. R.; Pontzen, A.

2018-04-01

We present the first self-consistent prediction for the distribution of formation time-scales for close supermassive black hole (SMBH) pairs following galaxy mergers. Using ROMULUS25, the first large-scale cosmological simulation to accurately track the orbital evolution of SMBHs within their host galaxies down to sub-kpc scales, we predict an average formation rate density of close SMBH pairs of 0.013 cMpc-3 Gyr-1. We find that it is relatively rare for galaxy mergers to result in the formation of close SMBH pairs with sub-kpc separation and those that do form are often the result of Gyr of orbital evolution following the galaxy merger. The likelihood and time-scale to form a close SMBH pair depends strongly on the mass ratio of the merging galaxies, as well as the presence of dense stellar cores. Low stellar mass ratio mergers with galaxies that lack a dense stellar core are more likely to become tidally disrupted and deposit their SMBH at large radii without any stellar core to aid in their orbital decay, resulting in a population of long-lived `wandering' SMBHs. Conversely, SMBHs in galaxies that remain embedded within a stellar core form close pairs in much shorter time-scales on average. This time-scale is a crucial, though often ignored or very simplified, ingredient to models predicting SMBH mergers rates and the connection between SMBH and star formation activity.

Human amygdala engagement moderated by early life stress exposure is a biobehavioral target for predicting recovery on antidepressants.

PubMed

Goldstein-Piekarski, Andrea N; Korgaonkar, Mayuresh S; Green, Erin; Suppes, Trisha; Schatzberg, Alan F; Hastie, Trevor; Nemeroff, Charles B; Williams, Leanne M

2016-10-18

Amygdala circuitry and early life stress (ELS) are both strongly and independently implicated in the neurobiology of depression. Importantly, animal models have revealed that the contribution of ELS to the development and maintenance of depression is likely a consequence of structural and physiological changes in amygdala circuitry in response to stress hormones. Despite these mechanistic foundations, amygdala engagement and ELS have not been investigated as biobehavioral targets for predicting functional remission in translational human studies of depression. Addressing this question, we integrated human neuroimaging and measurement of ELS within a controlled trial of antidepressant outcomes. Here we demonstrate that the interaction between amygdala activation engaged by emotional stimuli and ELS predicts functional remission on antidepressants with a greater than 80% cross-validated accuracy. Our model suggests that in depressed people with high ELS, the likelihood of remission is highest with greater amygdala reactivity to socially rewarding stimuli, whereas for those with low-ELS exposure, remission is associated with lower amygdala reactivity to both rewarding and threat-related stimuli. This full model predicted functional remission over and above the contribution of demographics, symptom severity, ELS, and amygdala reactivity alone. These findings identify a human target for elucidating the mechanisms of antidepressant functional remission and offer a target for developing novel therapeutics. The results also offer a proof-of-concept for using neuroimaging as a target for guiding neuroscience-informed intervention decisions at the level of the individual person.

Predicting frequent emergency department visits among children with asthma using EHR data.

PubMed

Das, Lala T; Abramson, Erika L; Stone, Anne E; Kondrich, Janienne E; Kern, Lisa M; Grinspan, Zachary M

2017-07-01

For children with asthma, emergency department (ED) visits are common, expensive, and often avoidable. Though several factors are associated with ED use (demographics, comorbidities, insurance, medications), its predictability using electronic health record (EHR) data is understudied. We used a retrospective cohort study design and EHR data from one center to examine the relationship of patient factors in 1 year (2013) and the likelihood of frequent ED use (≥2 visits) in the following year (2014), using bivariate and multivariable statistics. We applied and compared several machine-learning algorithms to predict frequent ED use, then selected a model based on accuracy, parsimony, and interpretability. We identified 2691 children. In bivariate analyses, future frequent ED use was associated with demographics, co-morbidities, insurance status, medication history, and use of healthcare resources. Machine learning algorithms had very good AUC (area under the curve) values [0.66-0.87], though fair PPV (positive predictive value) [48-70%] and poor sensitivity [16-27%]. Our final multivariable logistic regression model contained two variables: insurance status and prior ED use. For publicly insured patients, the odds of frequent ED use were 3.1 [2.2-4.5] times that of privately insured patients. Publicly insured patients with 4+ ED visits and privately insured patients with 6+ ED visits in a year had ≥50% probability of frequent ED use the following year. The model had an AUC of 0.86, PPV of 56%, and sensitivity of 23%. Among children with asthma, prior frequent ED use and insurance status strongly predict future ED use. © 2017 Wiley Periodicals, Inc.

Spliceman2: a computational web server that predicts defects in pre-mRNA splicing.

PubMed

Cygan, Kamil Jan; Sanford, Clayton Hendrick; Fairbrother, William Guy

2017-09-15

Most pre-mRNA transcripts in eukaryotic cells must undergo splicing to remove introns and join exons, and splicing elements present a large mutational target for disease-causing mutations. Splicing elements are strongly position dependent with respect to the transcript annotations. In 2012, we presented Spliceman, an online tool that used positional dependence to predict how likely distant mutations around annotated splice sites were to disrupt splicing. Here, we present an improved version of the previous tool that will be more useful for predicting the likelihood of splicing mutations. We have added industry-standard input options (i.e. Spliceman now accepts variant call format files), which allow much larger inputs than previously available. The tool also can visualize the locations-within exons and introns-of sequence variants to be analyzed and the predicted effects on splicing of the pre-mRNA transcript. In addition, Spliceman2 integrates with RNAcompete motif libraries to provide a prediction of which trans -acting factors binding sites are disrupted/created and links out to the UCSC genome browser. In summary, the new features in Spliceman2 will allow scientists and physicians to better understand the effects of single nucleotide variations on splicing. Freely available on the web at http://fairbrother.biomed.brown.edu/spliceman2 . Website implemented in PHP framework-Laravel 5, PostgreSQL, Apache, and Perl, with all major browsers supported. william_fairbrother@brown.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

In Potential Stroke Patients on Warfarin, the International Normalized Ratio Predicts Ischemia.

PubMed

Cao, Cathy; Martinelli, Ashley; Spoelhof, Brian; Llinas, Rafael H; Marsh, Elisabeth B

2017-01-01

Stroke can occur in patients on warfarin despite anticoagulation. Patients with a low international normalized ratio (INR) should theoretically be at greater risk for ischemia than those who are therapeutic. Therefore, INR may be able to indicate whether new neurological deficits are more likely strokes or stroke mimics in patients on warfarin. This study evaluates the association and predictive value of INR in determining the likelihood of ischemia. Patients were identified using the acute stroke registry at a Primary Stroke Center from January 2013 through December 2014. All adult patients undergoing evaluation for acute stroke with prior documented use of warfarin and an INR level at presentation were included. Data were collected regarding patient demographics, medical comorbidities, stroke severity, reason for anticoagulation, and laboratory studies including INR. Student t tests and χ2 analysis were used to evaluate factors associated with increased likelihood of ischemia (stroke or transient ischemic attack) versus mimic. Significant results were entered into a multivariable regression analysis. Sensitivity and specificity analyses were conducted to determine the predictive value of INR for ischemic risk. 116 patients were included; 46 were diagnosed with ischemia, 70 were diagnosed as mimics. 75% of patients were on warfarin for atrial fibrillation versus 25% for venous thrombosis. A statistically significant difference in mean INR for patients with ischemia (n = 46) versus mimics (n = 70) was observed (1.7 vs. 2.8; p < 0.001). In multivariable analysis, both sub-therapeutic INR (p < 0.001) and atrial fibrillation (p = 0.014) were predictors of ischemia. In patients with an INR ≥2, the predictive value of having a non-ischemic etiology was 79%. No patient with an INR of ≥3.6 was found to have ischemia. Sub-therapeutic INR and atrial fibrillation are strongly associated with ischemia in patients on warfarin presenting with acute neurologic symptoms. Ischemia is far less likely in patients with an INR of ≥2 and rare in those with an INR ≥3.6. This study shows that the INR value of a patient on warfarin can help stratify patients' risk for acute ischemic stroke and guide further neurologic imaging and workup. © 2017 The Author(s). Published by S. Karger AG, Basel.

The Use of Dynamic Stochastic Social Behavior Models to Produce Likelihood Functions for Risk Modeling of Proliferation and Terrorist Attacks

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

Young, Jonathan; Thompson, Sandra E.; Brothers, Alan J.

The ability to estimate the likelihood of future events based on current and historical data is essential to the decision making process of many government agencies. Successful predictions related to terror events and characterizing the risks will support development of options for countering these events. The predictive tasks involve both technical and social component models. The social components have presented a particularly difficult challenge. This paper outlines some technical considerations of this modeling activity. Both data and predictions associated with the technical and social models will likely be known with differing certainties or accuracies – a critical challenge is linkingmore » across these model domains while respecting this fundamental difference in certainty level. This paper will describe the technical approach being taken to develop the social model and identification of the significant interfaces between the technical and social modeling in the context of analysis of diversion of nuclear material.« less

Dissociating response conflict and error likelihood in anterior cingulate cortex.

PubMed

Yeung, Nick; Nieuwenhuis, Sander

2009-11-18

Neuroimaging studies consistently report activity in anterior cingulate cortex (ACC) in conditions of high cognitive demand, leading to the view that ACC plays a crucial role in the control of cognitive processes. According to one prominent theory, the sensitivity of ACC to task difficulty reflects its role in monitoring for the occurrence of competition, or "conflict," between responses to signal the need for increased cognitive control. However, a contrasting theory proposes that ACC is the recipient rather than source of monitoring signals, and that ACC activity observed in relation to task demand reflects the role of this region in learning about the likelihood of errors. Response conflict and error likelihood are typically confounded, making the theories difficult to distinguish empirically. The present research therefore used detailed computational simulations to derive contrasting predictions regarding ACC activity and error rate as a function of response speed. The simulations demonstrated a clear dissociation between conflict and error likelihood: fast response trials are associated with low conflict but high error likelihood, whereas slow response trials show the opposite pattern. Using the N2 component as an index of ACC activity, an EEG study demonstrated that when conflict and error likelihood are dissociated in this way, ACC activity tracks conflict and is negatively correlated with error likelihood. These findings support the conflict-monitoring theory and suggest that, in speeded decision tasks, ACC activity reflects current task demands rather than the retrospective coding of past performance.

Anticipating cognitive effort: roles of perceived error-likelihood and time demands.

PubMed

Dunn, Timothy L; Inzlicht, Michael; Risko, Evan F

2017-11-13

Why are some actions evaluated as effortful? In the present set of experiments we address this question by examining individuals' perception of effort when faced with a trade-off between two putative cognitive costs: how much time a task takes vs. how error-prone it is. Specifically, we were interested in whether individuals anticipate engaging in a small amount of hard work (i.e., low time requirement, but high error-likelihood) vs. a large amount of easy work (i.e., high time requirement, but low error-likelihood) as being more effortful. In between-subject designs, Experiments 1 through 3 demonstrated that individuals anticipate options that are high in perceived error-likelihood (yet less time consuming) as more effortful than options that are perceived to be more time consuming (yet low in error-likelihood). Further, when asked to evaluate which of the two tasks was (a) more effortful, (b) more error-prone, and (c) more time consuming, effort-based and error-based choices closely tracked one another, but this was not the case for time-based choices. Utilizing a within-subject design, Experiment 4 demonstrated overall similar pattern of judgments as Experiments 1 through 3. However, both judgments of error-likelihood and time demand similarly predicted effort judgments. Results are discussed within the context of extant accounts of cognitive control, with considerations of how error-likelihood and time demands may independently and conjunctively factor into judgments of cognitive effort.

Master teachers' responses to twenty literacy and science/mathematics practices in deaf education.

PubMed

Easterbrooks, Susan R; Stephenson, Brenda; Mertens, Donna

2006-01-01

Under a grant to improve outcomes for students who are deaf or hard of hearing awarded to the Association of College Educators--Deaf/Hard of Hearing, a team identified content that all teachers of students who are deaf and hard of hearing must understand and be able to teach. Also identified were 20 practices associated with content standards (10 each, literacy and science/mathematics). Thirty-seven master teachers identified by grant agents rated the practices on a Likert-type scale indicating the maximum benefit of each practice and maximum likelihood that they would use the practice, yielding a likelihood-impact analysis. The teachers showed strong agreement on the benefits and likelihood of use of the rated practices. Concerns about implementation of many of the practices related to time constraints and mixed-ability classrooms were themes of the reviews. Actions for teacher preparation programs were recommended.

Prediction of hamstring injury in professional soccer players by isokinetic measurements

PubMed Central

Dauty, Marc; Menu, Pierre; Fouasson-Chailloux, Alban; Ferréol, Sophie; Dubois, Charles

2016-01-01

Summary Objectives previous studies investigating the ability of isokinetic strength ratios to predict hamstring injuries in soccer players have reported conflicting results. Hypothesis to determine if isokinetic ratios are able to predict hamstring injury occurring during the season in professional soccer players. Study Design case-control study; Level of evidence: 3. Methods from 2001 to 2011, 350 isokinetic tests were performed in 136 professional soccer players at the beginning of the soccer season. Fifty-seven players suffered hamstring injury during the season that followed the isokinetic tests. These players were compared with the 79 uninjured players. The bilateral concentric ratio (hamstring-to-hamstring), ipsilateral concentric ratio (hamstring-to-quadriceps), and mixed ratio (eccentric/concentric hamstring-to-quadriceps) were studied. The predictive ability of each ratio was established based on the likelihood ratio and post-test probability. Results the mixed ratio (30 eccentric/240 concentric hamstring-to-quadriceps) <0.8, ipsilateral ratio (180 concentric hamstring-to-quadriceps) <0.47, and bilateral ratio (60 concentric hamstring-to-hamstring) <0.85 were the most predictive of hamstring injury. The ipsilateral ratio <0.47 allowed prediction of the severity of the hamstring injury, and was also influenced by the length of time since administration of the isokinetic tests. Conclusion isokinetic ratios are useful for predicting the likelihood of hamstring injury in professional soccer players during the competitive season. PMID:27331039

Mental models accurately predict emotion transitions.

PubMed

Thornton, Mark A; Tamir, Diana I

2017-06-06

Successful social interactions depend on people's ability to predict others' future actions and emotions. People possess many mechanisms for perceiving others' current emotional states, but how might they use this information to predict others' future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others' emotional dynamics. People could then use these mental models of emotion transitions to predict others' future emotions from currently observable emotions. To test this hypothesis, studies 1-3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants' ratings of emotion transitions predicted others' experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation-valence, social impact, rationality, and human mind-inform participants' mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants' accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone.

Personality patterns and Smoking behavior among students in Tabriz, Iran

PubMed Central

Fakharri, Ali; Jahani, Ali; Sadeghi-Bazargani, Homayoun; Farahbakhsh, Mostafa; Asl, Asghar Mohammadpour

2017-01-01

Introduction Psychological factors have always been considered for their role on risk taking behavior such as substance abuse, risky driving and smoking. The aim of this study was to determine the association between smoking behavior and potential personality patterns among high school students in Tabriz, Iran. Methods Through a multistage sampling in a cross-sectional study, 1000 students were enrolled to represent the final grade high school student population of Tabriz, Iran in 2013. The personality patterns along with smoking status and some background information were collected through standard questionnaires along with Millon Clinical Multiaxial Inventory-III (MCMI-III). Fourteen personality patterns and ten clinical syndromes. ANOVA and Kruskal Wallis tests were used to compare numeric scales among the study participants, with respect to their smoking status. Stata version 13 statistical software package was used to analyze the data. Multivariate logistic regression was used to predict likelihood of smoking by personality status. Results Two logistic models were developed in both of whom male sex was identified as a determinant of regular smoking (1st model) and ever-smoking (2nd model). Depressive personality increased the likelihood of being a regular smoker by 2.8 times (OR=2.8, 95% CI: 1.3–6.1). The second personality disorder included in the model was sadistic personality with an odds ratio of 7.9 (96% CI: 1.2–53%). Histrionic personality increased the likelihood of experiencing smoking by 2.2 times (OR=2.2, 95% CI: 1.6–3.1) followed by borderline personality (OR=2.8, 95% CI: 0.97–8.1). Conclusion Histrionic and depressive personalities could be considered as strong associates of smoking, followed by borderline and sadistic personalities. A causal relationship couldn’t be assumed unless well controlled longitudinal studies reached the same findings using psychiatric interviews. PMID:28461869

Evaluating Prospective Teachers: Testing the Predictive Validity of the EdTPA

ERIC Educational Resources Information Center

Goldhaber, Dan; Cowan, James; Theobald, Roddy

2017-01-01

We use longitudinal data from Washington State to provide estimates of the extent to which performance on the edTPA, a performance-based, subject-specific assessment of teacher candidates, is predictive of the likelihood of employment in the teacher workforce and value-added measures of teacher effectiveness. While edTPA scores are highly…

Evaluating Prospective Teachers: Testing the Predictive Validity of the edTPA. Working Paper 157

ERIC Educational Resources Information Center

Goldhaber, Dan; Cowan, James; Theobald, Roddy

2016-01-01

We use longitudinal data from Washington State to provide estimates of the extent to which performance on the edTPA, a performance-based, subject-specific assessment of teacher candidates, is predictive of the likelihood of employment in the teacher workforce and value-added measures of teacher effectiveness. While edTPA scores are highly…

Cultural, Human, and Social Capital as Determinants of Corporal Punishment: Toward an Integrated Theoretical Model.

ERIC Educational Resources Information Center

Xu, Xiaohe; Tung, Yuk-Ying; Dunaway, R. Gregory

2000-01-01

This article constructs a model to predict the likelihood of parental use of corporal punishment on children in two-parent families. Reports that corporal punishment is primarily determined by cultural, human, and social capital that are available to, or already acquired by parents. Discusses an integrated, resource-based theory for predicting use…

The High School Experience of Students with Disabilities: Factors That Influence Their Predicted Likelihood of College Graduation

ERIC Educational Resources Information Center

Schechter, Julia F.

2017-01-01

The purpose of this research is to study college planning practices, skills and activities in the secondary school experience of undergraduate students with disabilities that were important to their self-predicted college graduation. This study is limited to exploring factors within the transition programming domains of student-focused planning,…

Estimation Methods for Non-Homogeneous Regression - Minimum CRPS vs Maximum Likelihood

NASA Astrophysics Data System (ADS)

Gebetsberger, Manuel; Messner, Jakob W.; Mayr, Georg J.; Zeileis, Achim

2017-04-01

Non-homogeneous regression models are widely used to statistically post-process numerical weather prediction models. Such regression models correct for errors in mean and variance and are capable to forecast a full probability distribution. In order to estimate the corresponding regression coefficients, CRPS minimization is performed in many meteorological post-processing studies since the last decade. In contrast to maximum likelihood estimation, CRPS minimization is claimed to yield more calibrated forecasts. Theoretically, both scoring rules used as an optimization score should be able to locate a similar and unknown optimum. Discrepancies might result from a wrong distributional assumption of the observed quantity. To address this theoretical concept, this study compares maximum likelihood and minimum CRPS estimation for different distributional assumptions. First, a synthetic case study shows that, for an appropriate distributional assumption, both estimation methods yield to similar regression coefficients. The log-likelihood estimator is slightly more efficient. A real world case study for surface temperature forecasts at different sites in Europe confirms these results but shows that surface temperature does not always follow the classical assumption of a Gaussian distribution. KEYWORDS: ensemble post-processing, maximum likelihood estimation, CRPS minimization, probabilistic temperature forecasting, distributional regression models

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.

Can non‐clinical repolarization assays predict the results of clinical thorough QT studies? Results from a research consortium

PubMed Central

Park, Eunjung; Gintant, Gary A; Bi, Daoqin; Kozeli, Devi; Pettit, Syril D; Skinner, Matthew; Willard, James; Wisialowski, Todd; Koerner, John; Valentin, Jean‐Pierre

2018-01-01

Background and Purpose Translation of non‐clinical markers of delayed ventricular repolarization to clinical prolongation of the QT interval corrected for heart rate (QTc) (a biomarker for torsades de pointes proarrhythmia) remains an issue in drug discovery and regulatory evaluations. We retrospectively analysed 150 drug applications in a US Food and Drug Administration database to determine the utility of established non‐clinical in vitro IKr current human ether‐à‐go‐go‐related gene (hERG), action potential duration (APD) and in vivo (QTc) repolarization assays to detect and predict clinical QTc prolongation. Experimental Approach The predictive performance of three non‐clinical assays was compared with clinical thorough QT study outcomes based on free clinical plasma drug concentrations using sensitivity and specificity, receiver operating characteristic (ROC) curves, positive (PPVs) and negative predictive values (NPVs) and likelihood ratios (LRs). Key Results Non‐clinical assays demonstrated robust specificity (high true negative rate) but poor sensitivity (low true positive rate) for clinical QTc prolongation at low‐intermediate (1×–30×) clinical exposure multiples. The QTc assay provided the most robust PPVs and NPVs (ability to predict clinical QTc prolongation). ROC curves (overall test accuracy) and LRs (ability to influence post‐test probabilities) demonstrated overall marginal performance for hERG and QTc assays (best at 30× exposures), while the APD assay demonstrated minimal value. Conclusions and Implications The predictive value of hERG, APD and QTc assays varies, with drug concentrations strongly affecting translational performance. While useful in guiding preclinical candidates without clinical QT prolongation, hERG and QTc repolarization assays provide greater value compared with the APD assay. PMID:29181850

Predictors of successful smoking cessation following advice from nurses in general practice.

PubMed

Sanders, D; Peveler, R; Mant, D; Fowler, G

1993-12-01

At follow-up of 751 subjects receiving a brief nurse-administered anti-smoking intervention in general practice, 135 subjects (18%) reported stopping smoking, of whom 44 (6%) reported sustained cessation for one year. The demographic, social and attitudinal characteristics of these subjects were compared with 616 subjects who continued to smoke. The most important predictors of cessation were intention to stop (OR 5.1, 95% CI 2.1-12.0), personal rating of likelihood of cessation (OR 4.9, 95% CI 2.8-8.5), nurse rating of likelihood of cessation (OR 4.0, 95% CI 2.2-7.4), and smoking habit of partner (1.9, 95% CI 1.3-2.9). As practice nurses are able to distinguish likely quitters from those who are not motivated and less likely to succeed, it is important to decide whether it is more cost effective to target support at the motivated or to spend more time encouraging less motivated. The most challenging, but possibly the most rewarding, task is to try to reduce the high proportion of new ex-smokers who relapse. Although 41.1% (95% CI 28.1, 58.0) of those expressing a definite intention to stop smoking gave up, only 17.9% (95% CI 8.9, 30.4) achieved sustained cessation. However, as sustained cessation is strongly predicted by social variables, such as marital status and time spent in the company of smokers, preventing relapse may not be easy to achieve through medical intervention alone.

Spatial distribution of Batrachochytrium dendrobatidis in South American caecilians.

PubMed

Lambertini, Carolina; Becker, C Guilherme; Bardier, Cecilia; da Silva Leite, Domingos; Toledo, Luís Felipe

2017-04-20

The amphibian-killing fungus Batrachochytrium dendrobatidis (Bd) is linked to population declines in anurans and salamanders globally. To date, however, few studies have attempted to screen Bd in live caecilians; Bd-positive caecilians have only been reported in Africa and French Guiana. Here, we performed a retrospective survey of museum preserved specimens to (1) describe spatial patterns of Bd infection in Gymnophiona across South America and (2) test whether areas of low climatic suitability for Bd in anurans predict Bd spatial epidemiology in caecilians. We used quantitative PCR to detect Bd in preserved caecilians collected over a 109 yr period, and performed autologistic regressions to test the effect of bioclimatic metrics of temperature and precipitation, vegetation density, and elevation on the likelihood of Bd occurrence. We detected an overall Bd prevalence of 12.4%, with positive samples spanning the Uruguayan savanna, Brazil's Atlantic Forest, and the Amazon basin. Our autologistic models detected a strong effect of macroclimate, a weaker effect of vegetation density, and no effect of elevation on the likelihood of Bd occurrence. Although most of our Bd-positive records overlapped with reported areas of high climatic suitability for the fungus in the Neotropics, many of our new Bd-positive samples extend far into areas of poor suitability for Bd in anurans. Our results highlight an important gap in the study of amphibian chytridiomycosis: the potential negative impact of Bd on Neotropical caecilians and the hypothetical role of caecilians as Bd reservoirs.

Gingivitis and salivary osmolality in children with cerebral palsy.

PubMed

Santos, Maria Teresa Botti Rodrigues; Ferreira, Maria Cristina Duarte; Guaré, Renata Oliveira; Diniz, Michele Baffi; Rösing, Cassiano Kuchenbecker; Rodrigues, Jonas Almeida; Duarte, Danilo Antonio

2016-11-01

To investigate the influence of salivary osmolality on the occurrence of gingivitis in children with cerebral palsy (CP). A total of 82 children with spastic CP were included in this cross-sectional study. Oral motor performance and gingival conditions were evaluated. Unstimulated saliva was collected using cotton swabs, and salivary osmolality was measured using a freezing point depression osmometer. Spearman's coefficient, receiver operating characteristic (ROC), and multiple logistic regression analyses were performed. Strong correlation (r > 0.7) was determined among salivary osmolality, salivary flow rate, visible plaque, dental calculus, and the occurrence of gingivitis. The area under the ROC to predict the influence of salivary osmolality on the occurrence of gingivitis was 0.88 (95% CI 0.81-0.96; P < 0.001). The cutoff value of 84.5 for salivary osmolality presented good sensitivity and specificity, both higher than 77%. The proportion of children presenting salivary osmolality ≤84.5 mOsm/kgH 2 O and gingivitis was 22.5%, whereas for the group presenting osmolality >84.5 mOsm/kgH 2 O, the proportion of children with gingivitis was 77.5%. Salivary osmolality above 84.5 increased the likelihood of gingivitis fivefold, whereas each additional 0.1 mL of salivary flow reduced the likelihood of gingivitis by 97%. Gingivitis occurs more frequently in children with CP showing increased values of salivary osmolality. © 2016 BSPD, IAPD and John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A robust method to forecast volcanic ash clouds

USGS Publications Warehouse

Denlinger, Roger P.; Pavolonis, Mike; Sieglaff, Justin

2012-01-01

Ash clouds emanating from volcanic eruption columns often form trails of ash extending thousands of kilometers through the Earth's atmosphere, disrupting air traffic and posing a significant hazard to air travel. To mitigate such hazards, the community charged with reducing flight risk must accurately assess risk of ash ingestion for any flight path and provide robust forecasts of volcanic ash dispersal. In response to this need, a number of different transport models have been developed for this purpose and applied to recent eruptions, providing a means to assess uncertainty in forecasts. Here we provide a framework for optimal forecasts and their uncertainties given any model and any observational data. This involves random sampling of the probability distributions of input (source) parameters to a transport model and iteratively running the model with different inputs, each time assessing the predictions that the model makes about ash dispersal by direct comparison with satellite data. The results of these comparisons are embodied in a likelihood function whose maximum corresponds to the minimum misfit between model output and observations. Bayes theorem is then used to determine a normalized posterior probability distribution and from that a forecast of future uncertainty in ash dispersal. The nature of ash clouds in heterogeneous wind fields creates a strong maximum likelihood estimate in which most of the probability is localized to narrow ranges of model source parameters. This property is used here to accelerate probability assessment, producing a method to rapidly generate a prediction of future ash concentrations and their distribution based upon assimilation of satellite data as well as model and data uncertainties. Applying this method to the recent eruption of Eyjafjallajökull in Iceland, we show that the 3 and 6 h forecasts of ash cloud location probability encompassed the location of observed satellite-determined ash cloud loads, providing an efficient means to assess all of the hazards associated with these ash clouds.

Prediction of spatially explicit rainfall intensity-duration thresholds for post-fire debris-flow generation in the western United States

NASA Astrophysics Data System (ADS)

Staley, Dennis; Negri, Jacquelyn; Kean, Jason

2016-04-01

Population expansion into fire-prone steeplands has resulted in an increase in post-fire debris-flow risk in the western United States. Logistic regression methods for determining debris-flow likelihood and the calculation of empirical rainfall intensity-duration thresholds for debris-flow initiation represent two common approaches for characterizing hazard and reducing risk. Logistic regression models are currently being used to rapidly assess debris-flow hazard in response to design storms of known intensities (e.g. a 10-year recurrence interval rainstorm). Empirical rainfall intensity-duration thresholds comprise a major component of the United States Geological Survey (USGS) and the National Weather Service (NWS) debris-flow early warning system at a regional scale in southern California. However, these two modeling approaches remain independent, with each approach having limitations that do not allow for synergistic local-scale (e.g. drainage-basin scale) characterization of debris-flow hazard during intense rainfall. The current logistic regression equations consider rainfall a unique independent variable, which prevents the direct calculation of the relation between rainfall intensity and debris-flow likelihood. Regional (e.g. mountain range or physiographic province scale) rainfall intensity-duration thresholds fail to provide insight into the basin-scale variability of post-fire debris-flow hazard and require an extensive database of historical debris-flow occurrence and rainfall characteristics. Here, we present a new approach that combines traditional logistic regression and intensity-duration threshold methodologies. This method allows for local characterization of both the likelihood that a debris-flow will occur at a given rainfall intensity, the direct calculation of the rainfall rates that will result in a given likelihood, and the ability to calculate spatially explicit rainfall intensity-duration thresholds for debris-flow generation in recently burned areas. Our approach synthesizes the two methods by incorporating measured rainfall intensity into each model variable (based on measures of topographic steepness, burn severity and surface properties) within the logistic regression equation. This approach provides a more realistic representation of the relation between rainfall intensity and debris-flow likelihood, as likelihood values asymptotically approach zero when rainfall intensity approaches 0 mm/h, and increase with more intense rainfall. Model performance was evaluated by comparing predictions to several existing regional thresholds. The model, based upon training data collected in southern California, USA, has proven to accurately predict rainfall intensity-duration thresholds for other areas in the western United States not included in the original training dataset. In addition, the improved logistic regression model shows promise for emergency planning purposes and real-time, site-specific early warning. With further validation, this model may permit the prediction of spatially-explicit intensity-duration thresholds for debris-flow generation in areas where empirically derived regional thresholds do not exist. This improvement would permit the expansion of the early-warning system into other regions susceptible to post-fire debris flow.

Preliminary evidence of an interaction between the FOXP2 gene and childhood emotional abuse predicting likelihood of auditory verbal hallucinations in schizophrenia.

PubMed

McCarthy-Jones, Simon; Green, Melissa J; Scott, Rodney J; Tooney, Paul A; Cairns, Murray J; Wu, Jing Qin; Oldmeadow, Christopher; Carr, Vaughan

2014-03-01

The FOXP2 gene is involved in the development of speech and language. As some single nucleotide polymorphisms (SNPs) of FOXP2 have been found to be associated with auditory verbal hallucinations (AVHs) at trend levels, this study set out to undertake the first examination into whether interactions between candidate FOXP2 SNPs and environmental factors (specifically, child abuse) predict the likelihood of AVHs. Data on parental child abuse and FOXP2 SNPs previously linked to AVHs (rs1456031, rs2396753, rs2253478) were obtained from the Australian Schizophrenia Research Bank for people with schizophrenia-spectrum disorders, both with (n = 211) and without (n = 122) a lifetime history of AVHs. Genotypic frequencies did not differ between the two groups; however, logistic regression found that childhood parental emotional abuse (CPEA) interacted with rs1456031 to predict lifetime experience of AVH. CPEA was only associated with significantly higher levels of AVHs in people with CC genotypes (odds ratio = 4.25), yet in the absence of CPEA, people with TT genotypes had significantly higher levels of AVHs than people with CC genotypes (odds ratio = 4.90). This interaction was specific to auditory verbal hallucinations, and did not predict the likelihood of non-verbal auditory hallucinations. Our findings offer tentative evidence that FOXP2 may be a susceptibility gene for AVHs, influencing the probability people experience AVHs in the presence and absence of CPEA. However, these findings are in need of replication in a larger study that addresses the methodological limitations of the present investigation. Copyright © 2013 Elsevier Ltd. All rights reserved.

Anatomic features of enhancing renal masses predict malignant and high-grade pathology: a preoperative nomogram using the RENAL Nephrometry score.

PubMed

Kutikov, Alexander; Smaldone, Marc C; Egleston, Brian L; Manley, Brandon J; Canter, Daniel J; Simhan, Jay; Boorjian, Stephen A; Viterbo, Rosalia; Chen, David Y T; Greenberg, Richard E; Uzzo, Robert G

2011-08-01

Counseling patients with enhancing renal mass currently occurs in the context of significant uncertainty regarding tumor pathology. We evaluated whether radiographic features of renal masses could predict tumor pathology and developed a comprehensive nomogram to quantitate the likelihood of malignancy and high-grade pathology based on these features. We retrospectively queried Fox Chase Cancer Center's prospectively maintained database for consecutive renal masses where a Nephrometry score was available. All patients in the cohort underwent either partial or radical nephrectomy. The individual components of Nephrometry were compared with histology and grade of resected tumors. We used multiple logistic regression to develop nomograms predicting the malignancy of tumors and likelihood of high-grade disease among malignant tumors. Nephrometry score was available for 525 of 1750 renal masses. Nephrometry score correlated with both tumor grade (p < 0.0001) and histology (p < 0.0001), such that small endophytic nonhilar tumors were more likely to represent benign pathology. Conversely, large interpolar and hilar tumors more often represented high-grade cancers. The resulting nomogram from these data offers a useful tool for the preoperative prediction of tumor histology (area under the curve [AUC]: 0.76) and grade (AUC: 0.73). The model was subjected to out-of-sample cross-validation; however, lack of external validation is a limitation of the study. The current study is the first to objectify the relationship between tumor anatomy and pathology. Using the Nephrometry score, we developed a tool to quantitate the preoperative likelihood of malignant and high-grade pathology of an enhancing renal mass. Copyright © 2011 European Association of Urology. Published by Elsevier B.V. All rights reserved.

Prediction of flow-induced failures of braided flexible hoses and bellows

NASA Technical Reports Server (NTRS)

Sack, L. E.; Nelson, R. L.; Mason, D. R.; Cooper, R. A.

1972-01-01

Analytical techniques were developed to evaluate braided hoses and bellows for possibility of flow induced resonance. These techniques determine likelihood of high cycle fatigue failure when such resonance exists.

Transfer Entropy as a Log-Likelihood Ratio

NASA Astrophysics Data System (ADS)

Barnett, Lionel; Bossomaier, Terry

2012-09-01

Transfer entropy, an information-theoretic measure of time-directed information transfer between joint processes, has steadily gained popularity in the analysis of complex stochastic dynamics in diverse fields, including the neurosciences, ecology, climatology, and econometrics. We show that for a broad class of predictive models, the log-likelihood ratio test statistic for the null hypothesis of zero transfer entropy is a consistent estimator for the transfer entropy itself. For finite Markov chains, furthermore, no explicit model is required. In the general case, an asymptotic χ2 distribution is established for the transfer entropy estimator. The result generalizes the equivalence in the Gaussian case of transfer entropy and Granger causality, a statistical notion of causal influence based on prediction via vector autoregression, and establishes a fundamental connection between directed information transfer and causality in the Wiener-Granger sense.

Transfer entropy as a log-likelihood ratio.

PubMed

Barnett, Lionel; Bossomaier, Terry

2012-09-28

Transfer entropy, an information-theoretic measure of time-directed information transfer between joint processes, has steadily gained popularity in the analysis of complex stochastic dynamics in diverse fields, including the neurosciences, ecology, climatology, and econometrics. We show that for a broad class of predictive models, the log-likelihood ratio test statistic for the null hypothesis of zero transfer entropy is a consistent estimator for the transfer entropy itself. For finite Markov chains, furthermore, no explicit model is required. In the general case, an asymptotic χ2 distribution is established for the transfer entropy estimator. The result generalizes the equivalence in the Gaussian case of transfer entropy and Granger causality, a statistical notion of causal influence based on prediction via vector autoregression, and establishes a fundamental connection between directed information transfer and causality in the Wiener-Granger sense.

Kinetics of Water Loss from Cells at Subzero Temperatures and the Likelihood of Intracellular Freezing

PubMed Central

Mazur, Peter

1963-01-01

The survival of various cells subjected to low temperature exposure is higher when they are cooled slowly. This increase is consistent with the view that slow cooling decreases the probability of intracellular freezing by permitting water to leave the cell rapidly enough to keep the protoplasm at its freezing point. The present study derives a quantitative relation between the amount of water in a cell and temperature. The relation is a differential equation involving cooling rate, surface-volume ratio, membrane permeability to water, and the temperature coefficient of the permeability constant. Numerical solutions to this equation give calculated water contents which permit predictions as to the likelihood of intracellular ice formation. Both the calculated water contents and the predictions on internal freezing are consistent with the experimental observations of several investigators. PMID:14085017

Residential mobility during adolescence: Do even "upward" moves predict dropout risk?

PubMed

Metzger, Molly W; Fowler, Patrick J; Anderson, Courtney Lauren; Lindsay, Constance A

2015-09-01

This paper uses the National Longitudinal Study of Adolescent Health to investigate the impact of housing instability in adolescence on the likelihood of subsequent graduation from high school. Combining census data, self-reports, and information about respondents' residential changes, we use the variation in households' number of moves and neighborhood quality to predict whether participants obtain a high school diploma. Controlling for major predictors of housing mobility, students experiencing at least one move over a 12-month period have a roughly 50% decreased likelihood of obtaining a high school diploma by the age of 25. These associations are identified regardless of whether students move to a poorer or less-poor neighborhood. Our results carry implications for the development of housing policies and interventions designed for disadvantaged populations. Copyright © 2015 Elsevier Inc. All rights reserved.

[Accuracy of three methods for the rapid diagnosis of oral candidiasis].

PubMed

Lyu, X; Zhao, C; Yan, Z M; Hua, H

2016-10-09

Objective: To explore a simple, rapid and efficient method for the diagnosis of oral candidiasis in clinical practice. Methods: Totally 124 consecutive patients with suspected oral candidiasis were enrolled from Department of Oral Medicine, Peking University School and Hospital of Stomatology, Beijing, China. Exfoliated cells of oral mucosa and saliva or concentrated oral rinse) obtained from all participants were tested by three rapid smear methods(10% KOH smear, gram-stained smear, Congo red stained smear). The diagnostic efficacy(sensitivity, specificity, Youden's index, likelihood ratio, consistency, predictive value and area under curve(AUC) of each of the above mentioned three methods was assessed by comparing the results with the gold standard(combination of clinical diagnosis, laboratory diagnosis and expert opinion). Results: Gram-stained smear of saliva(or concentrated oral rinse) demonstrated highest sensitivity(82.3%). Test of 10%KOH smear of exfoliated cells showed highest specificity(93.5%). Congo red stained smear of saliva(or concentrated oral rinse) displayed highest diagnostic efficacy(79.0% sensitivity, 80.6% specificity, 0.60 Youden's index, 4.08 positive likelihood ratio, 0.26 negative likelihood ratio, 80% consistency, 80.3% positive predictive value, 79.4% negative predictive value and 0.80 AUC). Conclusions: Test of Congo red stained smear of saliva(or concentrated oral rinse) could be used as a point-of-care tool for the rapid diagnosis of oral candidiasis in clinical practice. Trial registration: Chinese Clinical Trial Registry, ChiCTR-DDD-16008118.

Overcoming Triple Segregation

ERIC Educational Resources Information Center

Gandara, Patricia

2010-01-01

Latinos are, after whites, the most segregated student group in the United States, and their segregation is closely tied to poor academic outcomes. Latinos experience a triple segregation: by race/ethnicity, poverty, and language. Racial segregation perpetuates negative stereotypes, reduces the likelihood of a strong teaching staff, and is often…

Sleep and Hypertension

PubMed Central

Harding, Susan M.

2010-01-01

Ambulatory BP studies indicate that even small increases in BP, particularly nighttime BP levels, are associated with significant increases in cardiovascular morbidity and mortality. Accordingly, sleep-related diseases that induce increases in BP would be anticipated to substantially affect cardiovascular risk. Both sleep deprivation and insomnia have been linked to increases in incidence and prevalence of hypertension. Likewise, sleep disruption attributable to restless legs syndrome increases the likelihood of having hypertension. Observational studies demonstrate a strong correlation between the severity of obstructive sleep apnea (OSA) and the risk and severity of hypertension, whereas prospective studies of patients with OSA demonstrate a positive relationship between OSA and risk of incident hypertension. Intervention trials with continuous positive airway pressure (CPAP) indicate a modest, but inconsistent effect on BP in patients with severe OSA and a greater likelihood of benefit in patients with most CPAP adherence. Additional prospective studies are needed to reconcile observational studies suggesting that OSA is a strong risk factor for hypertension with the modest antihypertensive effects of CPAP observed in intervention studies. PMID:20682533

Multifrequency InSAR height reconstruction through maximum likelihood estimation of local planes parameters.

PubMed

Pascazio, Vito; Schirinzi, Gilda

2002-01-01

In this paper, a technique that is able to reconstruct highly sloped and discontinuous terrain height profiles, starting from multifrequency wrapped phase acquired by interferometric synthetic aperture radar (SAR) systems, is presented. We propose an innovative unwrapping method, based on a maximum likelihood estimation technique, which uses multifrequency independent phase data, obtained by filtering the interferometric SAR raw data pair through nonoverlapping band-pass filters, and approximating the unknown surface by means of local planes. Since the method does not exploit the phase gradient, it assures the uniqueness of the solution, even in the case of highly sloped or piecewise continuous elevation patterns with strong discontinuities.

Interaction strength combinations and the overfishing of a marine food web.

PubMed

Bascompte, Jordi; Melián, Carlos J; Sala, Enric

2005-04-12

The stability of ecological communities largely depends on the strength of interactions between predators and their prey. Here we show that these interaction strengths are structured nonrandomly in a large Caribbean marine food web. Specifically, the cooccurrence of strong interactions on two consecutive levels of food chains occurs less frequently than expected by chance. Even when they occur, these strongly interacting chains are accompanied by strong omnivory more often than expected by chance. By using a food web model, we show that these interaction strength combinations reduce the likelihood of trophic cascades after the overfishing of top predators. However, fishing selectively removes predators that are overrepresented in strongly interacting chains. Hence, the potential for strong community-wide effects remains a threat.

Interaction strength combinations and the overfishing of a marine food web

PubMed Central

Bascompte, Jordi; Melián, Carlos J.; Sala, Enric

2005-01-01

The stability of ecological communities largely depends on the strength of interactions between predators and their prey. Here we show that these interaction strengths are structured nonrandomly in a large Caribbean marine food web. Specifically, the cooccurrence of strong interactions on two consecutive levels of food chains occurs less frequently than expected by chance. Even when they occur, these strongly interacting chains are accompanied by strong omnivory more often than expected by chance. By using a food web model, we show that these interaction strength combinations reduce the likelihood of trophic cascades after the overfishing of top predators. However, fishing selectively removes predators that are overrepresented in strongly interacting chains. Hence, the potential for strong community-wide effects remains a threat. PMID:15802468

Pleural Touch Preparations and Direct Visualization of the Pleura during Medical Thoracoscopy for the Diagnosis of Malignancy.

PubMed

Grosu, Horiana B; Vial-Rodriguez, Macarena; Vakil, Erik; Casal, Roberto F; Eapen, George A; Morice, Rodolfo; Stewart, John; Sarkiss, Mona G; Ost, David E

2017-08-01

During diagnostic thoracoscopy, talc pleurodesis after biopsy is appropriate if the probability of malignancy is sufficiently high. Findings on direct visual assessment of the pleura during thoracoscopy, rapid onsite evaluation (ROSE) of touch preparations (touch preps) of thoracoscopic biopsy specimens, and preoperative imaging may help predict the likelihood of malignancy; however, data on the performance of these methods are limited. To assess the performance of ROSE of touch preps, direct visual assessment of the pleura during thoracoscopy, and preoperative imaging in diagnosing malignancy. Patients who underwent ROSE of touch preps during thoracoscopy for suspected malignancy were retrospectively reviewed. Malignancy was diagnosed on the basis of final pathologic examination of pleural biopsy specimens. ROSE results were categorized as malignant, benign, or atypical cells. Visual assessment results were categorized as tumor studding present or absent. Positron emission tomography (PET) and computed tomography (CT) findings were categorized as abnormal or normal pleura. Likelihood ratios were calculated for each category of test result. The study included 44 patients, 26 (59%) with a final pathologic diagnosis of malignancy. Likelihood ratios were as follows: for ROSE of touch preps: malignant, 1.97 (95% confidence interval [CI], 0.90-4.34); atypical cells, 0.69 (95% CI, 0.21-2.27); benign, 0.11 (95% CI, 0.01-0.93); for direct visual assessment: tumor studding present, 3.63 (95% CI, 1.32-9.99); tumor studding absent, 0.24 (95% CI, 0.09-0.64); for PET: abnormal pleura, 9.39 (95% CI, 1.42-62); normal pleura, 0.24 (95% CI, 0.11-0.52); and for CT: abnormal pleura, 13.15 (95% CI, 1.93-89.63); normal pleura, 0.28 (95% CI, 0.15-0.54). A finding of no malignant cells on ROSE of touch preps during thoracoscopy lowers the likelihood of malignancy significantly, whereas finding of tumor studding on direct visual assessment during thoracoscopy only moderately increases the likelihood of malignancy. A positive finding on PET and/or CT increases the likelihood of malignancy significantly in a moderate-risk patient group and can be used as an adjunct to predict malignancy before pleurodesis.

Technical Note: Approximate Bayesian parameterization of a complex tropical forest model

NASA Astrophysics Data System (ADS)

Hartig, F.; Dislich, C.; Wiegand, T.; Huth, A.

2013-08-01

Inverse parameter estimation of process-based models is a long-standing problem in ecology and evolution. A key problem of inverse parameter estimation is to define a metric that quantifies how well model predictions fit to the data. Such a metric can be expressed by general cost or objective functions, but statistical inversion approaches are based on a particular metric, the probability of observing the data given the model, known as the likelihood. Deriving likelihoods for dynamic models requires making assumptions about the probability for observations to deviate from mean model predictions. For technical reasons, these assumptions are usually derived without explicit consideration of the processes in the simulation. Only in recent years have new methods become available that allow generating likelihoods directly from stochastic simulations. Previous applications of these approximate Bayesian methods have concentrated on relatively simple models. Here, we report on the application of a simulation-based likelihood approximation for FORMIND, a parameter-rich individual-based model of tropical forest dynamics. We show that approximate Bayesian inference, based on a parametric likelihood approximation placed in a conventional MCMC, performs well in retrieving known parameter values from virtual field data generated by the forest model. We analyze the results of the parameter estimation, examine the sensitivity towards the choice and aggregation of model outputs and observed data (summary statistics), and show results from using this method to fit the FORMIND model to field data from an Ecuadorian tropical forest. Finally, we discuss differences of this approach to Approximate Bayesian Computing (ABC), another commonly used method to generate simulation-based likelihood approximations. Our results demonstrate that simulation-based inference, which offers considerable conceptual advantages over more traditional methods for inverse parameter estimation, can successfully be applied to process-based models of high complexity. The methodology is particularly suited to heterogeneous and complex data structures and can easily be adjusted to other model types, including most stochastic population and individual-based models. Our study therefore provides a blueprint for a fairly general approach to parameter estimation of stochastic process-based models in ecology and evolution.

Factors predicting a home death among home palliative care recipients

PubMed Central

Ko, Ming-Chung; Huang, Sheng-Jean; Chen, Chu-Chieh; Chang, Yu-Ping; Lien, Hsin-Yi; Lin, Jia-Yi; Woung, Lin-Chung; Chan, Shang-Yih

2017-01-01

Abstract Awareness of factors affecting the place of death could improve communication between healthcare providers and patients and their families regarding patient preferences and the feasibility of dying in the preferred place. This study aimed to evaluate factors predicting home death among home palliative care recipients. This is a population-based study using a national representative sample retrieved from the National Health Insurance Research Database. Subjects receiving home palliative care, from 2010 to 2012, were analyzed to evaluate the association between a home death and various characteristics related to illness, individual, and health care utilization. A multiple-logistic regression model was used to assess the independent effect of various characteristics on the likelihood of a home death. The overall rate of a home death for home palliative care recipients was 43.6%. Age; gender; urbanization of the area where the patients lived; illness; the total number of home visits by all health care professionals; the number of home visits by nurses; utilization of nasogastric tube, endotracheal tube, or indwelling urinary catheter; the number of emergency department visits; and admission to intensive care unit in previous 1 year were not significantly associated with the risk of a home death. Physician home visits increased the likelihood of a home death. Compared with subjects without physician home visits (31.4%) those with 1 physician home visit (53.0%, adjusted odds ratio [AOR]: 3.23, 95% confidence interval [CI]: 1.93–5.42) and those with ≥2 physician home visits (43.9%, AOR: 2.23, 95% CI: 1.06–4.70) had higher likelihood of a home death. Compared with subjects with hospitalization 0 to 6 times in previous 1 year, those with hospitalization ≥7 times in previous 1 year (AOR: 0.57, 95% CI: 0.34–0.95) had lower likelihood of a home death. Among home palliative care recipients, physician home visits increased the likelihood of a home death. Hospitalizations ≥7 times in previous 1 year decreased the likelihood of a home death. PMID:29019887

Predictive accuracy of changes in transvaginal sonographic cervical length over time for preterm birth: a systematic review and metaanalysis.

PubMed

Conde-Agudelo, Agustin; Romero, Roberto

2015-12-01

To determine the accuracy of changes in transvaginal sonographic cervical length over time in predicting preterm birth in women with singleton and twin gestations. PubMed, Embase, Cinahl, Lilacs, and Medion (all from inception to June 30, 2015), bibliographies, Google scholar, and conference proceedings. Cohort or cross-sectional studies reporting on the predictive accuracy for preterm birth of changes in cervical length over time. Two reviewers independently selected studies, assessed the risk of bias, and extracted the data. Summary receiver-operating characteristic curves, pooled sensitivities and specificities, and summary likelihood ratios were generated. Fourteen studies met the inclusion criteria, of which 7 provided data on singleton gestations (3374 women) and 8 on twin gestations (1024 women). Among women with singleton gestations, the shortening of cervical length over time had a low predictive accuracy for preterm birth at <37 and <35 weeks of gestation with pooled sensitivities and specificities, and summary positive and negative likelihood ratios ranging from 49% to 74%, 44% to 85%, 1.3 to 4.1, and 0.3 to 0.7, respectively. In women with twin gestations, the shortening of cervical length over time had a low to moderate predictive accuracy for preterm birth at <34, <32, <30, and <28 weeks of gestation with pooled sensitivities and specificities, and summary positive and negative likelihood ratios ranging from 47% to 73%, 84% to 89%, 3.8 to 5.3, and 0.3 to 0.6, respectively. There were no statistically significant differences between the predictive accuracies for preterm birth of cervical length shortening over time and the single initial and/or final cervical length measurement in 8 of 11 studies that provided data for making these comparisons. In the largest and highest-quality study, a single measurement of cervical length obtained at 24 or 28 weeks of gestation was significantly more predictive of preterm birth than any decrease in cervical length between these gestational ages. Change in transvaginal sonographic cervical length over time is not a clinically useful test to predict preterm birth in women with singleton or twin gestations. A single cervical length measurement obtained between 18 and 24 weeks of gestation appears to be a better test to predict preterm birth than changes in cervical length over time. Published by Elsevier Inc.

Seasonal species interactions minimize the impact of species turnover on the likelihood of community persistence.

PubMed

Saavedra, Serguei; Rohr, Rudolf P; Fortuna, Miguel A; Selva, Nuria; Bascompte, Jordi

2016-04-01

Many of the observed species interactions embedded in ecological communities are not permanent, but are characterized by temporal changes that are observed along with abiotic and biotic variations. While work has been done describing and quantifying these changes, little is known about their consequences for species coexistence. Here, we investigate the extent to which changes of species composition impact the likelihood of persistence of the predator-prey community in the highly seasonal Białowieza Primeval Forest (northeast Poland), and the extent to which seasonal changes of species interactions (predator diet) modulate the expected impact. This likelihood is estimated extending recent developments on the study of structural stability in ecological communities. We find that the observed species turnover strongly varies the likelihood of community persistence between summer and winter. Importantly, we demonstrate that the observed seasonal interaction changes minimize the variation in the likelihood of persistence associated with species turnover across the year. We find that these community dynamics can be explained as the coupling of individual species to their environment by minimizing both the variation in persistence conditions and the interaction changes between seasons. Our results provide a homeostatic explanation for seasonal species interactions and suggest that monitoring the association of interactions changes with the level of variation in community dynamics can provide a good indicator of the response of species to environmental pressures.

Evaluating Prospective Teachers: Testing the Predictive Validity of the edTPA. CEDR Working Paper. WP #2016-2.2

ERIC Educational Resources Information Center

Goldhaber, Dan; Cowan, James; Theobald, Roddy

2016-01-01

We use longitudinal data from Washington State to provide estimates of the extent to which performance on the edTPA, a performance-based, subject-specific assessment of teacher candidates, is predictive of the likelihood of employment in the teacher workforce and value-added measures of teacher effectiveness. While edTPA scores are highly…

Evaluating Prospective Teachers: Testing the Predictive Validity of the edTPA. CEDR Working Paper. WP #2016-7

ERIC Educational Resources Information Center

Goldhaber, Dan; Cowan, James; Theobald, Roddy

2016-01-01

We use longitudinal data from Washington State to provide estimates of the extent to which performance on the edTPA, a performance-based, subject-specific assessment of teacher candidates, is predictive of the likelihood of employment in the teacher workforce and value-added measures of teacher effectiveness. While edTPA scores are highly…

Does gynecologic malignancy predict likelihood of a tertiary palliative care unit hospital admission? A comparison of local, provincial and national death rates.

PubMed

Pilkey, Jana; Demers, Chantale; Chochinov, Harvey; Venkatesan, Nithya

2012-12-01

The purpose of this study was to determine whether the presence of gynecologic malignancies predicts the likelihood of a tertiary palliative care unit hospital admission. In this study, patients admitted to a specialized tertiary palliative care unit (TPCU) with gynecologic malignancies were compared to national and provincial death rates to determine if gynecologic malignancy predicts admission, and subsequent death, in a TPCU. Eighty-two gynecologic cancer patients were admitted to our TPCU over the 5- year study period. Out of all cancer deaths in the TPCU, death from ovarian cancer was 3.7% compared with 2.4% (p = 0.0068) of all cancer deaths in Manitoba and 2.3% (p = 0.0043) of all cancer deaths in Canada. Cervical cancer accounted for 1.7% of all our patients deaths compared with 0.7% (p = 0.0001) provincially and 0.6% (p = 0.0001) nationally. Uterine cancer deaths were not significantly different from the provincial and national death rates, whereas vulvar and fallopian cancers were too rare to allow for statistical analysis. Gynecologic cancers may be predictive of admission to a palliative care unit.

Climate change, species distribution models, and physiological performance metrics: predicting when biogeographic models are likely to fail.

PubMed

Woodin, Sarah A; Hilbish, Thomas J; Helmuth, Brian; Jones, Sierra J; Wethey, David S

2013-09-01

Modeling the biogeographic consequences of climate change requires confidence in model predictions under novel conditions. However, models often fail when extended to new locales, and such instances have been used as evidence of a change in physiological tolerance, that is, a fundamental niche shift. We explore an alternative explanation and propose a method for predicting the likelihood of failure based on physiological performance curves and environmental variance in the original and new environments. We define the transient event margin (TEM) as the gap between energetic performance failure, defined as CTmax, and the upper lethal limit, defined as LTmax. If TEM is large relative to environmental fluctuations, models will likely fail in new locales. If TEM is small relative to environmental fluctuations, models are likely to be robust for new locales, even when mechanism is unknown. Using temperature, we predict when biogeographic models are likely to fail and illustrate this with a case study. We suggest that failure is predictable from an understanding of how climate drives nonlethal physiological responses, but for many species such data have not been collected. Successful biogeographic forecasting thus depends on understanding when the mechanisms limiting distribution of a species will differ among geographic regions, or at different times, resulting in realized niche shifts. TEM allows prediction of the likelihood of such model failure.

CGBayesNets: Conditional Gaussian Bayesian Network Learning and Inference with Mixed Discrete and Continuous Data

PubMed Central

Weiss, Scott T.

2014-01-01

Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com. PMID:24922310

CGBayesNets: conditional Gaussian Bayesian network learning and inference with mixed discrete and continuous data.

PubMed

McGeachie, Michael J; Chang, Hsun-Hsien; Weiss, Scott T

2014-06-01

Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com.

An improved approximate-Bayesian model-choice method for estimating shared evolutionary history

PubMed Central

2014-01-01

Background To understand biological diversification, it is important to account for large-scale processes that affect the evolutionary history of groups of co-distributed populations of organisms. Such events predict temporally clustered divergences times, a pattern that can be estimated using genetic data from co-distributed species. I introduce a new approximate-Bayesian method for comparative phylogeographical model-choice that estimates the temporal distribution of divergences across taxa from multi-locus DNA sequence data. The model is an extension of that implemented in msBayes. Results By reparameterizing the model, introducing more flexible priors on demographic and divergence-time parameters, and implementing a non-parametric Dirichlet-process prior over divergence models, I improved the robustness, accuracy, and power of the method for estimating shared evolutionary history across taxa. Conclusions The results demonstrate the improved performance of the new method is due to (1) more appropriate priors on divergence-time and demographic parameters that avoid prohibitively small marginal likelihoods for models with more divergence events, and (2) the Dirichlet-process providing a flexible prior on divergence histories that does not strongly disfavor models with intermediate numbers of divergence events. The new method yields more robust estimates of posterior uncertainty, and thus greatly reduces the tendency to incorrectly estimate models of shared evolutionary history with strong support. PMID:24992937

Maximum Likelihood Estimations and EM Algorithms with Length-biased Data

PubMed Central

Qin, Jing; Ning, Jing; Liu, Hao; Shen, Yu

2012-01-01

SUMMARY Length-biased sampling has been well recognized in economics, industrial reliability, etiology applications, epidemiological, genetic and cancer screening studies. Length-biased right-censored data have a unique data structure different from traditional survival data. The nonparametric and semiparametric estimations and inference methods for traditional survival data are not directly applicable for length-biased right-censored data. We propose new expectation-maximization algorithms for estimations based on full likelihoods involving infinite dimensional parameters under three settings for length-biased data: estimating nonparametric distribution function, estimating nonparametric hazard function under an increasing failure rate constraint, and jointly estimating baseline hazards function and the covariate coefficients under the Cox proportional hazards model. Extensive empirical simulation studies show that the maximum likelihood estimators perform well with moderate sample sizes and lead to more efficient estimators compared to the estimating equation approaches. The proposed estimates are also more robust to various right-censoring mechanisms. We prove the strong consistency properties of the estimators, and establish the asymptotic normality of the semi-parametric maximum likelihood estimators under the Cox model using modern empirical processes theory. We apply the proposed methods to a prevalent cohort medical study. Supplemental materials are available online. PMID:22323840

Life under alien skies

NASA Astrophysics Data System (ADS)

Dartnell, Lewis

2012-04-01

As the number of confirmed extrasolar planets increases, so does the likelihood that some of them will harbour life. Lewis Dartnell describes some preliminary - but increasingly well founded - efforts to predict what alien plants and animals might look like.

The relationship of thought-action fusion to pathologicial worry and generalized anxiety disorder.

PubMed

Hazlett-Stevens, Holly; Zucker, Bonnie G; Craske, Michelle G

2002-10-01

Meta-cognitive beliefs associated with pathological worry and generalized anxiety disorder (GAD) may encompass the likelihood subtype of thought-action fusion (TAF), the belief that one's thoughts can influence outside events. In the current study of 494 undergraduate college students, positive correlations between scores on the Penn State Worry Questionnaire (PSWQ) and the two Likelihood subscales of the TAF Scale were found, and participants endorsing at least some DSM-IV diagnostic criteria for GAD scored significantly higher on both TAF-Likelihood subscales than participants reporting no GAD symptoms. However, these TAF scales did not predict GAD diagnostic status with PSWQ included as a predictor. In contrast to previous research, the TAF-Moral scale did not correlate with worry. Relationships between TAF, pathological worry, and meta-cognition are discussed in relation to GAD.

Computing maximum-likelihood estimates for parameters of the National Descriptive Model of Mercury in Fish

USGS Publications Warehouse

Donato, David I.

2012-01-01

This report presents the mathematical expressions and the computational techniques required to compute maximum-likelihood estimates for the parameters of the National Descriptive Model of Mercury in Fish (NDMMF), a statistical model used to predict the concentration of methylmercury in fish tissue. The expressions and techniques reported here were prepared to support the development of custom software capable of computing NDMMF parameter estimates more quickly and using less computer memory than is currently possible with available general-purpose statistical software. Computation of maximum-likelihood estimates for the NDMMF by numerical solution of a system of simultaneous equations through repeated Newton-Raphson iterations is described. This report explains the derivation of the mathematical expressions required for computational parameter estimation in sufficient detail to facilitate future derivations for any revised versions of the NDMMF that may be developed.

Analysis of regional scale risk to whirling disease in populations of Colorado and Rio Grande cutthroat trout using Bayesian belief network model

USGS Publications Warehouse

Kolb Ayre, Kimberley; Caldwell, Colleen A.; Stinson, Jonah; Landis, Wayne G.

2014-01-01

Introduction and spread of the parasite Myxobolus cerebralis, the causative agent of whirling disease, has contributed to the collapse of wild trout populations throughout the intermountain west. Of concern is the risk the disease may have on conservation and recovery of native cutthroat trout. We employed a Bayesian belief network to assess probability of whirling disease in Colorado River and Rio Grande cutthroat trout (Oncorhynchus clarkii pleuriticus and Oncorhynchus clarkii virginalis, respectively) within their current ranges in the southwest United States. Available habitat (as defined by gradient and elevation) for intermediate oligochaete worm host, Tubifex tubifex, exerted the greatest influence on the likelihood of infection, yet prevalence of stream barriers also affected the risk outcome. Management areas that had the highest likelihood of infected Colorado River cutthroat trout were in the eastern portion of their range, although the probability of infection was highest for populations in the southern, San Juan subbasin. Rio Grande cutthroat trout had a relatively low likelihood of infection, with populations in the southernmost Pecos management area predicted to be at greatest risk. The Bayesian risk assessment model predicted the likelihood of whirling disease infection from its principal transmission vector, fish movement, and suggested that barriers may be effective in reducing risk of exposure to native trout populations. Data gaps, especially with regard to location of spawning, highlighted the importance in developing monitoring plans that support future risk assessments and adaptive management for subspecies of cutthroat trout.

Migration, business formation, and the informal economy in urban Mexico.

PubMed

Sheehan, Connor M; Riosmena, Fernando

2013-07-01

Although the informal economy has grown rapidly in several developing nations, and migration and informality may be related to similar types of credit constraints and market failures, previous research has not systematically attempted to identify if migrant households are more likely to start informal and formal businesses alike and if this association varies across local contexts. We examine the relationship between prior US migration and the creation of both formal and informal businesses in urban Mexico using several criteria to indirectly assess sector location. We use data from 56 communities from the Mexican Migration Project to estimate multilevel survival and nonmultilevel competing risk models predicting the likelihood of informal, formal, and no business formation. The recent return migration of the household head is strongly associated with informal business creation, particularly in economically dynamic areas. On the other hand, migrants are only marginally more likely to start formal businesses in highly economically dynamic sending areas. Published by Elsevier Inc.

Porcupine quill injuries in dogs: A retrospective of 296 cases (1998–2002)

PubMed Central

Johnson, Matthew D.; Magnusson, Kristenn D.; Shmon, Cindy L.; Waldner, Cheryl

2006-01-01

Abstract The purpose of this retrospective study was to identify factors associated with quill injury in dogs. A second objective was to determine the risk of complications and any factors that would predict the likelihood of complications. Hospital records of 296 porcupine quill injuries in dogs from 1998 to 2002 were studied. There was an increased occurrence of porcupine encounters in the spring and fall months; Siberian huskies, rottweilers, and German shepherd crosses were significantly overrepresented for quill injuries. There was no association between risk of complications and either number of quills or antimicrobial use. Increasing time between quill injury and presentation was associated with an increased risk of complications. Because of the increased frequency of complication with a longer interval until presentation, clients should be strongly encouraged to bring the dog in as soon as the quill injury is discovered. Patients presented after 24 hours should be monitored closely during the first 3 weeks after injury, as most complications occurred during this time. PMID:16898110

Facilitating communication about sexual health between aging women and their health care providers.

PubMed

Hughes, Anne K; Lewinson, Terri D W

2015-04-01

Many women experience changes in sexual health as they age, and discussing these changes with health care providers is an essential component of optimal health management. The purpose of this study was to understand aging women's perspectives about communicating with providers about sexual health. We used the integrative model of behavioral prediction as a theoretical lens to explore women's attitudes, perceived norms, and perceived self-efficacy that promote or inhibit the likelihood of communicating about sexual health. In this theory-based qualitative study, we interviewed 28 community-dwelling older women in the Midwestern United States. Through thematic analysis, we identified both positive and negative attitudes about communicating with providers. Women seemed most inclined to discuss sexual health if they perceived that important patient-provider conditions, such as trust and rapport, were in place. Despite situational obstacles and perceived norms, these women held strong beliefs about their abilities to discuss sexual health topics with providers. © The Author(s) 2014.

The Influence of Antiobesity Media Content on Intention to Eat Healthily and Exercise: A Test of the Ordered Protection Motivation Theory

PubMed Central

Ritland, Raeann; Rodriguez, Lulu

2014-01-01

This study extended the ordered protection motivation framework to determine whether exposure and attention to antiobesity media content increases people's appraisals of threat and their ability to cope with it. It also assesses whether these cognitive processes, in turn, affected people's intention to abide by the practices recommended to prevent obesity. The results of a national online survey using a nonprobability sample indicate that attention to mediated obesity and related information significantly increased people's intention to exercise as well as their overall coping appraisals (the perceived effectiveness of the recommended behaviors and their ability to perform them). Likewise, increased threat and coping appraisals were both found to significantly influence people's intention to exercise and diet. Coping (rather than threat) appraisals more strongly predicted behavioral intent. Following the attitude-behavior literature, behavioral intention was used as the most proximate predictor of actual behavior (i.e., stronger intentions increase the likelihood of behavior change). PMID:25505981

The influence of antiobesity media content on intention to eat healthily and exercise: a test of the ordered protection motivation theory.

PubMed

Ritland, Raeann; Rodriguez, Lulu

2014-01-01

This study extended the ordered protection motivation framework to determine whether exposure and attention to antiobesity media content increases people's appraisals of threat and their ability to cope with it. It also assesses whether these cognitive processes, in turn, affected people's intention to abide by the practices recommended to prevent obesity. The results of a national online survey using a nonprobability sample indicate that attention to mediated obesity and related information significantly increased people's intention to exercise as well as their overall coping appraisals (the perceived effectiveness of the recommended behaviors and their ability to perform them). Likewise, increased threat and coping appraisals were both found to significantly influence people's intention to exercise and diet. Coping (rather than threat) appraisals more strongly predicted behavioral intent. Following the attitude-behavior literature, behavioral intention was used as the most proximate predictor of actual behavior (i.e., stronger intentions increase the likelihood of behavior change).

Global temperature change

PubMed Central

Hansen, James; Sato, Makiko; Ruedy, Reto; Lo, Ken; Lea, David W.; Medina-Elizade, Martin

2006-01-01

Global surface temperature has increased ≈0.2°C per decade in the past 30 years, similar to the warming rate predicted in the 1980s in initial global climate model simulations with transient greenhouse gas changes. Warming is larger in the Western Equatorial Pacific than in the Eastern Equatorial Pacific over the past century, and we suggest that the increased West–East temperature gradient may have increased the likelihood of strong El Niños, such as those of 1983 and 1998. Comparison of measured sea surface temperatures in the Western Pacific with paleoclimate data suggests that this critical ocean region, and probably the planet as a whole, is approximately as warm now as at the Holocene maximum and within ≈1°C of the maximum temperature of the past million years. We conclude that global warming of more than ≈1°C, relative to 2000, will constitute “dangerous” climate change as judged from likely effects on sea level and extermination of species. PMID:17001018

Early predictors of nonmarital first pregnancy and abortion.

PubMed

Udry, J R; Kovenock, J; Morris, N M

1996-01-01

Most research on abortion has focused on women's characteristics at the time of the procedure, but individuals' behavior may also be shaped by their experiences from younger ages. This study uses longitudinal data on 351 California white women aged 27-30 in 1990-1991 to identify characteristics in childhood and adolescence that predict who will have a nonmarital first pregnancy and, of those who do, which women will seek an abortion. Bivariate analyses reveal that psychosocial characteristics indicating a strong sense of autonomy, such as feeling it is important not to be tied down and engaging in socially undesirable behavior, are significantly associated with the likelihood of having a nonmarital first pregnancy (odds ratios of 1.7 and 1.5, respectively), but family characteristics are not. However, among women who have a first pregnancy out of wedlock, the odds of having an abortion are mostly influenced by family rather than psychological characteristics, particularly having been a good student and having a well-educated mother (2.0 and 1.7).

Mental models accurately predict emotion transitions

PubMed Central

Thornton, Mark A.; Tamir, Diana I.

2017-01-01

Successful social interactions depend on people’s ability to predict others’ future actions and emotions. People possess many mechanisms for perceiving others’ current emotional states, but how might they use this information to predict others’ future states? We hypothesized that people might capitalize on an overlooked aspect of affective experience: current emotions predict future emotions. By attending to regularities in emotion transitions, perceivers might develop accurate mental models of others’ emotional dynamics. People could then use these mental models of emotion transitions to predict others’ future emotions from currently observable emotions. To test this hypothesis, studies 1–3 used data from three extant experience-sampling datasets to establish the actual rates of emotional transitions. We then collected three parallel datasets in which participants rated the transition likelihoods between the same set of emotions. Participants’ ratings of emotion transitions predicted others’ experienced transitional likelihoods with high accuracy. Study 4 demonstrated that four conceptual dimensions of mental state representation—valence, social impact, rationality, and human mind—inform participants’ mental models. Study 5 used 2 million emotion reports on the Experience Project to replicate both of these findings: again people reported accurate models of emotion transitions, and these models were informed by the same four conceptual dimensions. Importantly, neither these conceptual dimensions nor holistic similarity could fully explain participants’ accuracy, suggesting that their mental models contain accurate information about emotion dynamics above and beyond what might be predicted by static emotion knowledge alone. PMID:28533373

The predictive utility of micro indicators of concern about smoking: findings from the International Tobacco Control Four Country study.

PubMed

Partos, Timea R; Borland, Ron; Thrasher, James F; Li, Lin; Yong, Hua-Hie; O'Connor, Richard J; Siahpush, Mohammad

2014-08-01

This study explored the association between six "micro indicators" of concern about smoking (1. stubbing out cigarettes before finishing; 2. forgoing cigarettes due to packet warning labels; thinking about... 3. the harms to oneself of smoking; 4. the harms to others of one's smoking; 5. the bad conduct of tobacco companies; and 6. money spent on cigarettes) and cessation outcomes (making quit attempts, and achieving at least six months of sustained abstinence) among adult smokers from Australia, Canada, the United Kingdom, and the United States of America. Participants were 12,049 individuals from five survey waves of the International Tobacco Control Four Country Survey (interviewed between 2002 and 2006, and followed-up approximately one year later). Generalized estimating equation logistic regression analysis was used, enabling us to control for within-participant correlations due to possible multiple responses by the same individual over different survey waves. The frequency of micro indicators predicted making quit attempts, with premature stubbing out, forgoing, and thinking about the harms to oneself of smoking being particularly strong predictors. An interaction effect with expressed intention to quit was observed, such that stubbing out and thinking about the harms on oneself predicted quit attempts more strongly among smokers with no expressed plans to quit. In contrast, there was a negative association between some micro indicators and sustained abstinence, with more frequent stubbing out, forgoing, and thinking about money spent on cigarettes associated with a reduced likelihood of subsequently achieving sustained abstinence. In countries with long-established tobacco control programs, micro indicators index both high motivation by smokers to do something about their smoking at least partly independent of espoused intention and, especially those indicators not part of a direct pathway to quitting, reduced capacity to quit successfully. Copyright © 2014 Elsevier Ltd. All rights reserved.

Assessing probabilistic predictions of ENSO phase and intensity from the North American Multimodel Ensemble

NASA Astrophysics Data System (ADS)

Tippett, Michael K.; Ranganathan, Meghana; L'Heureux, Michelle; Barnston, Anthony G.; DelSole, Timothy

2017-05-01

Here we examine the skill of three, five, and seven-category monthly ENSO probability forecasts (1982-2015) from single and multi-model ensemble integrations of the North American Multimodel Ensemble (NMME) project. Three-category forecasts are typical and provide probabilities for the ENSO phase (El Niño, La Niña or neutral). Additional forecast categories indicate the likelihood of ENSO conditions being weak, moderate or strong. The level of skill observed for differing numbers of forecast categories can help to determine the appropriate degree of forecast precision. However, the dependence of the skill score itself on the number of forecast categories must be taken into account. For reliable forecasts with same quality, the ranked probability skill score (RPSS) is fairly insensitive to the number of categories, while the logarithmic skill score (LSS) is an information measure and increases as categories are added. The ignorance skill score decreases to zero as forecast categories are added, regardless of skill level. For all models, forecast formats and skill scores, the northern spring predictability barrier explains much of the dependence of skill on target month and forecast lead. RPSS values for monthly ENSO forecasts show little dependence on the number of categories. However, the LSS of multimodel ensemble forecasts with five and seven categories show statistically significant advantages over the three-category forecasts for the targets and leads that are least affected by the spring predictability barrier. These findings indicate that current prediction systems are capable of providing more detailed probabilistic forecasts of ENSO phase and amplitude than are typically provided.

Measuring the Relational Aspects of Civic Engagement and Action

ERIC Educational Resources Information Center

Cohen, Alison K.; Fitzgerald, Jason C.

2017-01-01

Civic leaders who are highly and effectively engaged often have strong relationships with key stakeholders across institutions and communities. The prevalence and nature of these relationships is not known among those with more typical levels of civic engagement. We were interested in the perceptions of likelihood of individual versus community…

Dodging Dysfunctional Dynamics in Power Exchange

ERIC Educational Resources Information Center

Boyd, David P.

2010-01-01

In today's organizations, the impetus for employee empowerment remains strong. By developing an internal talent base, companies increase the likelihood of comprehensive contributions and also engender loyalty within the ranks. A proclivity for power dispersion is evident among many pundits, with some even decreeing it an ethical mandate. Yet, if…

School Organizational Effectiveness and Chronic Absenteeism: Implications for Accountability

ERIC Educational Resources Information Center

Lenhoff, Sarah Winchell; Pogodzinski, Ben

2018-01-01

Chronic absenteeism in K-12 schools is strongly associated with critical educational outcomes such as student achievement and graduation. Yet, the causes of chronic absenteeism are complex, with environmental, family/individual, and school factors all affecting the likelihood of a student attending school regularly. This exploratory study examines…

Spatial Prediction and Optimized Sampling Design for Sodium Concentration in Groundwater

PubMed Central

Shabbir, Javid; M. AbdEl-Salam, Nasser; Hussain, Tajammal

2016-01-01

Sodium is an integral part of water, and its excessive amount in drinking water causes high blood pressure and hypertension. In the present paper, spatial distribution of sodium concentration in drinking water is modeled and optimized sampling designs for selecting sampling locations is calculated for three divisions in Punjab, Pakistan. Universal kriging and Bayesian universal kriging are used to predict the sodium concentrations. Spatial simulated annealing is used to generate optimized sampling designs. Different estimation methods (i.e., maximum likelihood, restricted maximum likelihood, ordinary least squares, and weighted least squares) are used to estimate the parameters of the variogram model (i.e, exponential, Gaussian, spherical and cubic). It is concluded that Bayesian universal kriging fits better than universal kriging. It is also observed that the universal kriging predictor provides minimum mean universal kriging variance for both adding and deleting locations during sampling design. PMID:27683016

A Framework for Modeling Emerging Diseases to Inform Management

PubMed Central

Katz, Rachel A.; Richgels, Katherine L.D.; Walsh, Daniel P.; Grant, Evan H.C.

2017-01-01

The rapid emergence and reemergence of zoonotic diseases requires the ability to rapidly evaluate and implement optimal management decisions. Actions to control or mitigate the effects of emerging pathogens are commonly delayed because of uncertainty in the estimates and the predicted outcomes of the control tactics. The development of models that describe the best-known information regarding the disease system at the early stages of disease emergence is an essential step for optimal decision-making. Models can predict the potential effects of the pathogen, provide guidance for assessing the likelihood of success of different proposed management actions, quantify the uncertainty surrounding the choice of the optimal decision, and highlight critical areas for immediate research. We demonstrate how to develop models that can be used as a part of a decision-making framework to determine the likelihood of success of different management actions given current knowledge. PMID:27983501

ERPs and Psychopathology. I. Behavioral process issues.

PubMed

Roth, W T; Tecce, J J; Pfefferbaum, A; Rosenbloom, M; Callaway, E

1984-01-01

The clinical study of ERPs has an inherent defect--a self-selection of clinical populations that hampers equating of clinically defined groups on factors extraneous to the independent variables. Such ex post facto studies increase the likelihood of confounding variables in the interpretation of findings. Hence, the development of lawful relationships between clinical variables and ERPs is impeded and the fulfillment of description, explanation, prediction, and control in brain science is thwarted. Proper methodologies and theory development can increase the likelihood of establishing these lawful relationships. One methodology of potential value in the clinical application of ERPs, particularly in studies of aging, is that of divided attention. Two promising theoretical developments in the understanding of brain functioning and aging are the distraction-arousal hypothesis and the controlled-automatic attention model. The evaluation of ERPs in the study of brain-behavior relations in clinical populations might be facilitated by the differentiation of concurrent, predictive, content, and construct validities.

Dissociative effects of true and false recall as a function of different encoding strategies.

PubMed

Goodwin, Kerri A

2007-01-01

Goodwin, Meissner, and Ericsson (2001) proposed a path model in which elaborative encoding predicted the likelihood of verbalisation of critical, nonpresented words at encoding, which in turn predicted the likelihood of false recall. The present study tested this model of false recall experimentally with a manipulation of encoding strategy and the implementation of the process-tracing technique of protocol analysis. Findings indicated that elaborative encoding led to more verbalisations of critical items during encoding than rote rehearsal of list items, but false recall rates were reduced under elaboration conditions (Experiment 2). Interestingly, false recall was more likely to occur when items were verbalised during encoding than not verbalised (Experiment 1), and participants tended to reinstate their encoding strategies during recall, particularly after elaborative encoding (Experiment 1). Theoretical implications for the interplay of encoding and retrieval processes of false recall are discussed.

A Framework for Modeling Emerging Diseases to Inform Management.

PubMed

Russell, Robin E; Katz, Rachel A; Richgels, Katherine L D; Walsh, Daniel P; Grant, Evan H C

2017-01-01

The rapid emergence and reemergence of zoonotic diseases requires the ability to rapidly evaluate and implement optimal management decisions. Actions to control or mitigate the effects of emerging pathogens are commonly delayed because of uncertainty in the estimates and the predicted outcomes of the control tactics. The development of models that describe the best-known information regarding the disease system at the early stages of disease emergence is an essential step for optimal decision-making. Models can predict the potential effects of the pathogen, provide guidance for assessing the likelihood of success of different proposed management actions, quantify the uncertainty surrounding the choice of the optimal decision, and highlight critical areas for immediate research. We demonstrate how to develop models that can be used as a part of a decision-making framework to determine the likelihood of success of different management actions given current knowledge.

Treatment decision making and adjustment to breast cancer: a longitudinal study.

PubMed

Stanton, A L; Estes, M A; Estes, N C; Cameron, C L; Danoff-Burg, S; Irving, L M

1998-04-01

This study monitored women (N = 76) with breast cancer from diagnosis through 1 year, and tested constructs from subjective expected utility theory with regard to their ability to predict patients' choice of surgical treatment as well as psychological distress and well-being over time. Women's positive expectancies for the consequences of treatment generally were maintained in favorable perceptions of outcome in several realms (i.e., physician agreement, likelihood of cancer cure or recurrence, self-evaluation, likelihood of additional treatment, partner support for option, attractiveness to partner). Assessed before the surgical decision-making appointment, women's expectancies for consequences of the treatment options, along with age, correctly classified 94% of the sample with regard to election of mastectomy versus breast-conserving procedures. Calculated from the point of decision making to 3 months later, expectancy disconfirmations and value discrepancies concerning particular treatment consequences predicted psychological adjustment 3 months and 1 year after diagnosis.

A framework for modeling emerging diseases to inform management

USGS Publications Warehouse

Russell, Robin E.; Katz, Rachel A.; Richgels, Katherine L. D.; Walsh, Daniel P.; Grant, Evan H. Campbell

2017-01-01

The rapid emergence and reemergence of zoonotic diseases requires the ability to rapidly evaluate and implement optimal management decisions. Actions to control or mitigate the effects of emerging pathogens are commonly delayed because of uncertainty in the estimates and the predicted outcomes of the control tactics. The development of models that describe the best-known information regarding the disease system at the early stages of disease emergence is an essential step for optimal decision-making. Models can predict the potential effects of the pathogen, provide guidance for assessing the likelihood of success of different proposed management actions, quantify the uncertainty surrounding the choice of the optimal decision, and highlight critical areas for immediate research. We demonstrate how to develop models that can be used as a part of a decision-making framework to determine the likelihood of success of different management actions given current knowledge.

Predicting microRNA-disease associations using label propagation based on linear neighborhood similarity.

PubMed

Li, Guanghui; Luo, Jiawei; Xiao, Qiu; Liang, Cheng; Ding, Pingjian

2018-05-12

Interactions between microRNAs (miRNAs) and diseases can yield important information for uncovering novel prognostic markers. Since experimental determination of disease-miRNA associations is time-consuming and costly, attention has been given to designing efficient and robust computational techniques for identifying undiscovered interactions. In this study, we present a label propagation model with linear neighborhood similarity, called LPLNS, to predict unobserved miRNA-disease associations. Additionally, a preprocessing step is performed to derive new interaction likelihood profiles that will contribute to the prediction since new miRNAs and diseases lack known associations. Our results demonstrate that the LPLNS model based on the known disease-miRNA associations could achieve impressive performance with an AUC of 0.9034. Furthermore, we observed that the LPLNS model based on new interaction likelihood profiles could improve the performance to an AUC of 0.9127. This was better than other comparable methods. In addition, case studies also demonstrated our method's outstanding performance for inferring undiscovered interactions between miRNAs and diseases, especially for novel diseases. Copyright © 2018. Published by Elsevier Inc.

Racial differences in parenting dimensions and adolescent condom use at sexual debut.

PubMed

Cox, Mary F

2006-01-01

Parenting style may be a determinant in reducing adolescent risk behavior. Previous studies have relied on a typological parenting approach, with classification into four groups: authoritative, authoritarian, permissive, and neglectful. In this study, two distinct parenting dimensions, demandingness and responsiveness, were examined as independent predictors of adolescent condom use. This study used a subsample of the National Longitudinal Study of Adolescent Health (Add Health) that included 153 adolescent-mother pairs. Maternal demandingness and responsiveness were measured using Wave I mother interviews. Logistic regression analyses were used to predict adolescent condom use at sexual debut at Wave II and to assess moderation by gender and race. (1) Maternal demandingness predicted increased likelihood of condom use in African American adolescents but decreased likelihood of condom use in White adolescents; (2) maternal responsiveness did not predict condom use; and (3) gender moderation was not present. To provide appropriate family counseling, public health nurses need to consider racial differences in contraceptive practices. Education regarding parental supervision practices should be considered as part of nursing interventions intended to increase condom use in African American adolescents.

Explaining the effect of event valence on unrealistic optimism.

PubMed

Gold, Ron S; Brown, Mark G

2009-05-01

People typically exhibit 'unrealistic optimism' (UO): they believe they have a lower chance of experiencing negative events and a higher chance of experiencing positive events than does the average person. UO has been found to be greater for negative than positive events. This 'valence effect' has been explained in terms of motivational processes. An alternative explanation is provided by the 'numerosity model', which views the valence effect simply as a by-product of a tendency for likelihood estimates pertaining to the average member of a group to increase with the size of the group. Predictions made by the numerosity model were tested in two studies. In each, UO for a single event was assessed. In Study 1 (n = 115 students), valence was manipulated by framing the event either negatively or positively, and participants estimated their own likelihood and that of the average student at their university. In Study 2 (n = 139 students), valence was again manipulated and participants again estimated their own likelihood; additionally, group size was manipulated by having participants estimate the likelihood of the average student in a small, medium-sized, or large group. In each study, the valence effect was found, but was due to an effect on estimates of own likelihood, not the average person's likelihood. In Study 2, valence did not interact with group size. The findings contradict the numerosity model, but are in accord with the motivational explanation. Implications for health education are discussed.

Characteristics of mother-child conflict and child sex predicting resolution.

PubMed

Nelson, Jackie A; Boyer, Brittany P; Sang, Samantha A; Wilson, Elizabeth K

2014-04-01

Data from 190 mothers and their 5- to 7-year-old children were used to evaluate how characteristics of mother-child conflict discussions contribute to the likelihood of reaching a compromise, a win-loss resolution, or a standoff. Dyads discussed 2 topics they reported having disagreements about that were emotionally arousing. Coders rated global measurements of mothers' emotional responsiveness, intrusiveness, and negativity; children's negativity; and the frequency of mothers' and children's constructive and oppositional comments. Child sex was examined as a moderator of the relation between discussion characteristics and resolution reached. Results indicated that more constructive comments by mothers and children increased the likelihood of reaching a resolution versus a standoff, but only children's constructive comments differentiated between a compromise and a win-loss resolution favoring mothers. Dyads with more emotionally responsive mothers who made fewer oppositional comments were also more likely to reach a compromise versus a win-loss resolution. A significant interaction with child sex revealed that, for boys, the use of more child oppositional comments was associated with a higher likelihood of reaching a standoff versus a compromise. Girls' oppositional comments did not predict resolution type. These results are discussed in terms of the children's developmental level and parents' socialization goals. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Empirical best linear unbiased prediction method for small areas with restricted maximum likelihood and bootstrap procedure to estimate the average of household expenditure per capita in Banjar Regency

NASA Astrophysics Data System (ADS)

Aminah, Agustin Siti; Pawitan, Gandhi; Tantular, Bertho

2017-03-01

So far, most of the data published by Statistics Indonesia (BPS) as data providers for national statistics are still limited to the district level. Less sufficient sample size for smaller area levels to make the measurement of poverty indicators with direct estimation produced high standard error. Therefore, the analysis based on it is unreliable. To solve this problem, the estimation method which can provide a better accuracy by combining survey data and other auxiliary data is required. One method often used for the estimation is the Small Area Estimation (SAE). There are many methods used in SAE, one of them is Empirical Best Linear Unbiased Prediction (EBLUP). EBLUP method of maximum likelihood (ML) procedures does not consider the loss of degrees of freedom due to estimating β with β ^. This drawback motivates the use of the restricted maximum likelihood (REML) procedure. This paper proposed EBLUP with REML procedure for estimating poverty indicators by modeling the average of household expenditures per capita and implemented bootstrap procedure to calculate MSE (Mean Square Error) to compare the accuracy EBLUP method with the direct estimation method. Results show that EBLUP method reduced MSE in small area estimation.

Display size effects in visual search: analyses of reaction time distributions as mixtures.

PubMed

Reynolds, Ann; Miller, Jeff

2009-05-01

In a reanalysis of data from Cousineau and Shiffrin (2004) and two new visual search experiments, we used a likelihood ratio test to examine the full distributions of reaction time (RT) for evidence that the display size effect is a mixture-type effect that occurs on only a proportion of trials, leaving RT in the remaining trials unaffected, as is predicted by serial self-terminating search models. Experiment 1 was a reanalysis of Cousineau and Shiffrin's data, for which a mixture effect had previously been established by a bimodal distribution of RTs, and the results confirmed that the likelihood ratio test could also detect this mixture. Experiment 2 applied the likelihood ratio test within a more standard visual search task with a relatively easy target/distractor discrimination, and Experiment 3 applied it within a target identification search task within the same types of stimuli. Neither of these experiments provided any evidence for the mixture-type display size effect predicted by serial self-terminating search models. Overall, these results suggest that serial self-terminating search models may generally be applicable only with relatively difficult target/distractor discriminations, and then only for some participants. In addition, they further illustrate the utility of analysing full RT distributions in addition to mean RT.

The Many Faces of Affect: A Multilevel Model of Drinking Frequency/Quantity and Alcohol Dependence Symptoms Among Young Adults

PubMed Central

Simons, Jeffrey S.; Wills, Thomas A.; Neal, Dan J.

2016-01-01

This research tested a multilevel structural equation model of associations between 3 aspects of affective functioning (state affect, trait affect, and affective lability) and 3 alcohol outcomes (likelihood of drinking, quantity on drinking days, and dependence symptoms) in a sample of 263 college students. Participants provided 49 days of experience sampling data over 1.3 years in a longitudinal burst design. Within-person results: At the daily level, positive affect was directly associated with greater likelihood and quantity of alcohol consumption. Daily negative affect was directly associated with higher consumption on drinking days and with higher dependence symptoms. Between-person direct effects: Affect lability was associated with higher trait negative, but not positive, affect. Trait positive affect was inversely associated with the proportion of drinking days, whereas negative affectivity predicted a greater proportion of drinking days. Affect lability exhibited a direct association with dependence symptoms. Between-person indirect effects: Trait positive affect was associated with fewer dependence symptoms via proportion of drinking days. Trait negative affect was associated with greater dependence symptoms via proportion of drinking days. The results distinguish relations of positive and negative affect to likelihood versus amount of drinking and state versus trait drinking outcomes, and highlight the importance of affect variability for predicting alcohol dependence symptoms. PMID:24933278

NOAA National Ocean Service Remote Sensing Applications and Concept of Operations

DTIC Science & Technology

2007-01-01

remote sensing technologies to monitor harmful algal blooms, hypoxia, coral bleaching , contamination, land use changes and bathymetry, and making the...NOAA’s Polar Environmental Satellites are used to help predict the likelihood of mass coral bleaching events. Both intensity and duration of...abnormally warm surface temperatures are used to help predict coral bleaching events. When a temperature anomaly reaches a critically high value or

Maximum likelihood estimation for predicting the probability of obtaining variable shortleaf pine regeneration densities

Treesearch

Thomas B. Lynch; Jean Nkouka; Michael M. Huebschmann; James M. Guldin

2003-01-01

A logistic equation is the basis for a model that predicts the probability of obtaining regeneration at specified densities. The density of regeneration (trees/ha) for which an estimate of probability is desired can be specified by means of independent variables in the model. When estimating parameters, the dependent variable is set to 1 if the regeneration density (...

Predictive model for risk of cesarean section in pregnant women after induction of labor.

PubMed

Hernández-Martínez, Antonio; Pascual-Pedreño, Ana I; Baño-Garnés, Ana B; Melero-Jiménez, María R; Tenías-Burillo, José M; Molina-Alarcón, Milagros

2016-03-01

To develop a predictive model for risk of cesarean section in pregnant women after induction of labor. A retrospective cohort study was conducted of 861 induced labors during 2009, 2010, and 2011 at Hospital "La Mancha-Centro" in Alcázar de San Juan, Spain. Multivariate analysis was used with binary logistic regression and areas under the ROC curves to determine predictive ability. Two predictive models were created: model A predicts the outcome at the time the woman is admitted to the hospital (before the decision to of the method of induction); and model B predicts the outcome at the time the woman is definitely admitted to the labor room. The predictive factors in the final model were: maternal height, body mass index, nulliparity, Bishop score, gestational age, macrosomia, gender of fetus, and the gynecologist's overall cesarean section rate. The predictive ability of model A was 0.77 [95% confidence interval (CI) 0.73-0.80] and model B was 0.79 (95% CI 0.76-0.83). The predictive ability for pregnant women with previous cesarean section with model A was 0.79 (95% CI 0.64-0.94) and with model B was 0.80 (95% CI 0.64-0.96). For a probability of estimated cesarean section ≥80%, the models A and B presented a positive likelihood ratio (+LR) for cesarean section of 22 and 20, respectively. Also, for a likelihood of estimated cesarean section ≤10%, the models A and B presented a +LR for vaginal delivery of 13 and 6, respectively. These predictive models have a good discriminative ability, both overall and for all subgroups studied. This tool can be useful in clinical practice, especially for pregnant women with previous cesarean section and diabetes.

Odor Emotional Quality Predicts Odor Identification.

PubMed

Bestgen, Anne-Kathrin; Schulze, Patrick; Kuchinke, Lars

2015-09-01

It is commonly agreed upon a strong link between emotion and olfaction. Odor-evoked memories are experienced as more emotional compared with verbal, visual, and tactile stimuli. Moreover, the emotional quality of odor cues increases memory performance, but contrary to this, odors are poor retrieval cues for verbal labels. To examine the relation between the emotional quality of an odor and its likelihood of identification, this study evaluates how normative emotion ratings based on the 3-dimensional affective space model (that includes valence, arousal, and dominance), using the Self-Assessment Manikin by Bradley and Lang (Bradley MM, Lang PJ. 1994. Measuring emotion: the Self-Assessment Manikin and the Semantic Differential. J Behav Ther Exp Psychiatry. 25(1):49-59.) and the Positive and Negative Affect Schedule (Watson D, Clark LA, Tellegen A. 1988. Development and validation of brief measures of positive and negative affect: the PANAS scales. J Pers Soc Psychol. 54(6):1063-1070.) predict the identification of odors in a multiple choice condition. The best fitting logistic regression model includes squared valence and dominance and thus, points to a significant role of specific emotional features of odors as a main clue for odor identification. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Young women's education and behavioural risk trajectories: clarifying their association with unintended-pregnancy resolution.

PubMed

Gomez-Scott, Jessica; Cooney, Teresa M

2014-06-01

In the USA, most pregnancies occurring to teenage women are unplanned, making both the decisions regarding their resolution and the consequences of those decisions important topics of inquiry. Substantial debate surrounds the potential consequences for young women of either carrying an unintended pregnancy to term or voluntarily terminating it. The present study utilises data from The US National Longitudinal Study of Adolescent Health prospectively to examine the predictors of pregnancy resolution decisions in terms of young women's educational goals and their engagement in risk behaviours. Additionally, the long-term consequences of these decisions for education and risk-taking behaviours are identified. Results indicate that young women with strong educational goals have a greater likelihood of terminating an unintended pregnancy than those with low aspirations, and that pregnancy termination predicts higher educational attainment compared to motherhood. Risk behaviours did not predict pregnancy-resolution decisions, but young women who became mothers reported lower rates of subsequent substance use and fewer sexual partners post-pregnancy than those who terminated the pregnancy or who had never been pregnant. Motherhood appears to be a catalyst for lifestyle change among young women, limiting substance use and sexual partnering, in contrast to abortion, which appears to allow adolescents to continue risk-taking trajectories.

Influenza virus drug resistance: a time-sampled population genetics perspective.

PubMed

Foll, Matthieu; Poh, Yu-Ping; Renzette, Nicholas; Ferrer-Admetlla, Anna; Bank, Claudia; Shim, Hyunjin; Malaspinas, Anna-Sapfo; Ewing, Gregory; Liu, Ping; Wegmann, Daniel; Caffrey, Daniel R; Zeldovich, Konstantin B; Bolon, Daniel N; Wang, Jennifer P; Kowalik, Timothy F; Schiffer, Celia A; Finberg, Robert W; Jensen, Jeffrey D

2014-02-01

The challenge of distinguishing genetic drift from selection remains a central focus of population genetics. Time-sampled data may provide a powerful tool for distinguishing these processes, and we here propose approximate Bayesian, maximum likelihood, and analytical methods for the inference of demography and selection from time course data. Utilizing these novel statistical and computational tools, we evaluate whole-genome datasets of an influenza A H1N1 strain in the presence and absence of oseltamivir (an inhibitor of neuraminidase) collected at thirteen time points. Results reveal a striking consistency amongst the three estimation procedures developed, showing strongly increased selection pressure in the presence of drug treatment. Importantly, these approaches re-identify the known oseltamivir resistance site, successfully validating the approaches used. Enticingly, a number of previously unknown variants have also been identified as being positively selected. Results are interpreted in the light of Fisher's Geometric Model, allowing for a quantification of the increased distance to optimum exerted by the presence of drug, and theoretical predictions regarding the distribution of beneficial fitness effects of contending mutations are empirically tested. Further, given the fit to expectations of the Geometric Model, results suggest the ability to predict certain aspects of viral evolution in response to changing host environments and novel selective pressures.

The association between parental mental health and behavioral disorders in pre-school children

PubMed Central

Karimzadeh, Mansoureh; Rostami, Mohammad; Teymouri, Robab; Moazzen, Zahra; Tahmasebi, Siyamak

2017-01-01

Background and Aim Behavioral disorders among children reflect psychological problems of parents, as mental illness of either parent would increase the likelihood of mental disorder in the child. In view of the negative relationship between parents’ and children’s illness, the current study intended to determine the correlation between mental health of parents and behavioral disorders of pre-school children. Methods The present descriptive-correlational research studied 80 children registered at pre-school centers in Pardis Township, Tehran, Iran during 2014–2015 using convenience sampling. The research tools included General Health Questionnaire (GHQ) and Preschool Behavior Questionnaire (PBQ). The resulted data were analyzed using Pearson Product-moment Correlation Coefficient and regression analysis in SPSS 21. Results The research results showed that there was a significant positive correlation between all dimensions of mental health of parents with general behavioral disorders (p<0.001). The results of the regression analysis showed that parents’ depression was the first and the only predictive variable of behavioral disorders in children with 26.8% predictive strength. Conclusion Given the strong relationship between children’s behavioral disorders and parents’ general health, and the significant role of parents’ depression in children’s behavioral disorders, it seems necessary to take measures to decrease the impact of parents’ disorders on children. PMID:28848622

Modeling summer month hydrological drought probabilities in the United States using antecedent flow conditions

USGS Publications Warehouse

Austin, Samuel H.; Nelms, David L.

2017-01-01

Climate change raises concern that risks of hydrological drought may be increasing. We estimate hydrological drought probabilities for rivers and streams in the United States (U.S.) using maximum likelihood logistic regression (MLLR). Streamflow data from winter months are used to estimate the chance of hydrological drought during summer months. Daily streamflow data collected from 9,144 stream gages from January 1, 1884 through January 9, 2014 provide hydrological drought streamflow probabilities for July, August, and September as functions of streamflows during October, November, December, January, and February, estimating outcomes 5-11 months ahead of their occurrence. Few drought prediction methods exploit temporal links among streamflows. We find MLLR modeling of drought streamflow probabilities exploits the explanatory power of temporally linked water flows. MLLR models with strong correct classification rates were produced for streams throughout the U.S. One ad hoc test of correct prediction rates of September 2013 hydrological droughts exceeded 90% correct classification. Some of the best-performing models coincide with areas of high concern including the West, the Midwest, Texas, the Southeast, and the Mid-Atlantic. Using hydrological drought MLLR probability estimates in a water management context can inform understanding of drought streamflow conditions, provide warning of future drought conditions, and aid water management decision making.

Comparison of different risk stratification systems in predicting short-term serious outcome of syncope patients.

PubMed

Safari, Saeed; Baratloo, Alireza; Hashemi, Behrooz; Rahmati, Farhad; Forouzanfar, Mohammad Mehdi; Motamedi, Maryam; Mirmohseni, Ladan

2016-01-01

Determining etiologic causes and prognosis can significantly improve management of syncope patients. The present study aimed to compare the values of San Francisco, Osservatorio Epidemiologico sulla Sincope nel Lazio (OESIL), Boston, and Risk Stratification of Syncope in the Emergency Department (ROSE) score clinical decision rules in predicting the short-term serious outcome of syncope patients. The present diagnostic accuracy study with 1-week follow-up was designed to evaluate the predictive values of the four mentioned clinical decision rules. Screening performance characteristics of each model in predicting mortality, myocardial infarction (MI), and cerebrovascular accidents (CVAs) were calculated and compared. To evaluate the value of each aforementioned model in predicting the outcome, sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio were calculated and receiver-operating curve (ROC) curve analysis was done. A total of 187 patients (mean age: 64.2 ± 17.2 years) were enrolled in the study. Mortality, MI, and CVA were seen in 19 (10.2%), 12 (6.4%), and 36 (19.2%) patients, respectively. Area under the ROC curve for OESIL, San Francisco, Boston, and ROSE models in prediction the risk of 1-week mortality, MI, and CVA was in the 30-70% range, with no significant difference among models ( P > 0.05). The pooled model did not show higher accuracy in prediction of mortality, MI, and CVA compared to others ( P > 0.05). This study revealed the weakness of all four evaluated models in predicting short-term serious outcome of syncope patients referred to the emergency department without any significant advantage for one among others.

Predictive validity of cannabis consumption measures: Results from a national longitudinal study.

PubMed

Buu, Anne; Hu, Yi-Han; Pampati, Sanjana; Arterberry, Brooke J; Lin, Hsien-Chang

2017-10-01

Validating the utility of cannabis consumption measures for predicting later cannabis related symptomatology or progression to cannabis use disorder (CUD) is crucial for prevention and intervention work that may use consumption measures for quick screening. This study examined whether cannabis use quantity and frequency predicted CUD symptom counts, progression to onset of CUD, and persistence of CUD. Data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) at Wave 1 (2001-2002) and Wave 2 (2004-2005) were used to identify three risk samples: (1) current cannabis users at Wave 1 who were at risk for having CUD symptoms at Wave 2; (2) current users without lifetime CUD who were at risk for incident CUD; and (3) current users with past-year CUD who were at risk for persistent CUD. Logistic regression and zero-inflated Poisson models were used to examine the longitudinal effect of cannabis consumption on CUD outcomes. Higher frequency of cannabis use predicted lower likelihood of being symptom-free but it did not predict the severity of CUD symptomatology. Higher frequency of cannabis use also predicted higher likelihood of progression to onset of CUD and persistence of CUD. Cannabis use quantity, however, did not predict any of the developmental stages of CUD symptomatology examined in this study. This study has provided a new piece of evidence to support the predictive validity of cannabis use frequency based on national longitudinal data. The result supports the common practice of including frequency items in cannabis screening tools. Copyright © 2017 Elsevier Ltd. All rights reserved.

Constraints on Omega_0 and cluster evolution using the ROSAT log N-log S relation

NASA Astrophysics Data System (ADS)

Mathiesen, B.; Evrard, A. E.

1998-04-01

We examine the likelihoods of different cosmological models and cluster evolutionary histories by comparing semi-analytical predictions of X-ray cluster number counts with observational data from the ROSAT satellite. We model cluster abundance as a function of mass and redshift using a Press-Schechter distribution, and assume that the temperature T(M,z) and bolometric luminosity L_X(M,z) scale as power laws in mass and epoch, in order to construct expected counts as a function of X-ray flux. The L_X-M scaling is fixed using the local luminosity function, while the degree of evolution in the X-ray luminosity with redshift L_X~(1+z)^s is left open, with s an interesting free parameter which we investigate. We examine open and flat cosmologies with initial, scale-free fluctuation spectra having indices n=0, -1 and -2. An independent constraint arising from the slope of the luminosity-temperature relation strongly favours the n=-2 spectrum. The expected counts demonstrate a strong dependence on Omega_0 and s, with lesser dependence on lambda_0 and n. Comparison with the observed counts reveals a `ridge' of acceptable models in the Omega_0-s plane, roughly following the relation s~6Omega_0 and spanning low-density models with a small degree of evolution to Omega=1 models with strong evolution. Models with moderate evolution are revealed to have a strong lower limit of Omega_0>~0.3, and low-evolution models imply that Omega_0<1 at a very high confidence level. We suggest observational tests for breaking the degeneracy along this ridge, and discuss implications for evolutionary histories of the intracluster medium.

Influences to post-graduation career aspirations and attainment in STEM doctoral candidates and recipients

NASA Astrophysics Data System (ADS)

Barry, Deborah S.

As the realities of the academic job market have forced some PhD recipients to accept less-preferable position types, there has been increasing concerns that these students are not prepared for their careers, especially in STEM fields. However, aside from the labor market, few studies have explored the influences on career aspiration and attainment among doctoral degree holders. This study utilized the socialization theory framework to identify aspects of the doctoral education process that are predictive of the likelihood of certain career aspirations among science and engineering doctoral candidates and career attainment among STEM doctoral recipients by utilizing nationally representative datasets: The National Research Council's Assessment of Research Doctorate Programs student questionnaire and the National Science Foundation's Survey of Earned Doctorates. This study identified field of study, research productivity rank of doctoral programs, primary type of finding doctoral students received, level of satisfaction with research experiences, and their sense of belonging within their doctoral program as factors that predict the likelihood of certain career aspirations compared with a career in education. Doctoral candidates' background characteristics that were significant predictors of career aspirations were gender, marital status, dependent status, race, age, and citizenship status. Further, this study identified participant's field of study, the Carnegie Rank of institutions attended, primary type of funding received, length of time to PhD, gender, marital status, dependent status, race, citizenship stats, and age as factors that predict the likelihood of the career outcomes investigated in this study, including doctoral recipients' employment field and primary work activity.

Outcomes of Spontaneous Labor in Women Undergoing Trial of Labor after Cesarean as Compared with Nulliparous Women: A Retrospective Cohort Study.

PubMed

Lassey, Sarah C; Robinson, Julian N; Kaimal, Anjali J; Little, Sarah E

2018-01-24

 The objective of this study was to compare spontaneous labor outcomes in women undergoing trial of labor after cesarean (TOLAC) and nulliparas to better counsel women.  A 4-year retrospective cohort. We included women at term in spontaneous labor with vertex singletons and no more than one prior cesarean delivery. In planned secondary analysis, we focused on a subset of women with a prior cesarean and a predicted likelihood of a successful vaginal delivery of 70% or more based on the Maternal-Fetal Medicine Units-vaginal birth after cesarean (VBAC) calculator.  Our cohort included 606 TOLACS and 606 nulliparas. Women undergoing TOLAC were more likely to undergo cesarean delivery (25.7 vs. 14.7%; p  < 0.001). Severe maternal hemorrhage (1.5 vs. 0.2%; p  = 0.02) and uterine rupture (1.9 vs. 0.0%; p  < 0.01) were more likely in the TOLAC group. For the subset of women with a predicted likelihood of VBAC of 70% or more, there were no differences in cesarean delivery (16.7 vs. 14.7%; p  = 0.51), maternal, or immediate neonatal complications.  Women undergoing TOLAC were more likely to have a cesarean delivery, hemorrhage, or uterine rupture. Those with more than 70% predicted likelihood of VBAC were no more likely to experience these outcomes. These findings help contextualize the risks of TOLAC for women considering this option. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Prevalence of Visual Impairment among 4- to 6-years-old Children in Khon Kaen City Municipality, Thailand.

PubMed

Wongwai, Phanthipha; Anupongongarch, Pacharapan; Suwannaraj, Sirinya; Asawaphureekorn, Somkiat

2016-08-01

To evaluate the prevalence of visual impairment of children aged four to six years in Khon Kaen City Municipality, Thailand. The visual acuity test was performed on 1,286 children in kindergarten schools located in Khon Kaen Municipality. The first test of visual acuity was done by trained teachers and the second test by the pediatric ophthalmologist. The prevalence of visual impairment of both tests was recorded including sensitivity, specificity, likelihood ratio, and predictive value of the test by teachers. The causes of visual impairment were also recorded. There were 39 children with visual impairment from the test by the teacher and 12 children from the test by the ophthalmologist. Myopia is the single cause of visual impairment. Mean spherical equivalence is 1.375 diopters (SD = 0.53). Median spherical equivalence is 1.375 diopters (minimum = 0.5, maximum =4). The detection of visual impairment by trained teachers had a sensitivity of 1.00 (95% CI 0.76-1.00), specificity of 0.98 (95% CI 0.97-0.99), likelihood ratio for a positive test 44.58 (95% CI 30.32-65.54), likelihood ratio for a negative test 0.04 (95% CI 0.003-0.60), positive predictive value of 0.31 (95% CI 0.19-0.47), and negative predictive value of 1.00 (95% CI 0.99-1.00). The prevalence of visual impairment among children aged four to six year old is 0.9%. Trained teachers can be examiners for screening purpose.

The development of a tool to predict team performance.

PubMed

Sinclair, M A; Siemieniuch, C E; Haslam, R A; Henshaw, M J D C; Evans, L

2012-01-01

The paper describes the development of a tool to predict quantitatively the success of a team when executing a process. The tool was developed for the UK defence industry, though it may be useful in other domains. It is expected to be used by systems engineers in initial stages of systems design, when concepts are still fluid, including the structure of the team(s) which are expected to be operators within the system. It enables answers to be calculated for questions such as "What happens if I reduce team size?" and "Can I reduce the qualifications necessary to execute this process and still achieve the required level of success?". The tool has undergone verification and validation; it predicts fairly well and shows promise. An unexpected finding is that the tool creates a good a priori argument for significant attention to Human Factors Integration in systems projects. The simulations show that if a systems project takes full account of human factors integration (selection, training, process design, interaction design, culture, etc.) then the likelihood of team success will be in excess of 0.95. As the project derogates from this state, the likelihood of team success will drop as low as 0.05. If the team has good internal communications and good individuals in key roles, the likelihood of success rises towards 0.25. Even with a team comprising the best individuals, p(success) will not be greater than 0.35. It is hoped that these results will be useful for human factors professionals involved in systems design. Copyright © 2011 Elsevier Ltd and The Ergonomics Society. All rights reserved.

Neural Networks Involved in Adolescent Reward Processing: An Activation Likelihood Estimation Meta-Analysis of Functional Neuroimaging Studies

PubMed Central

Silverman, Merav H.; Jedd, Kelly; Luciana, Monica

2015-01-01

Behavioral responses to, and the neural processing of, rewards change dramatically during adolescence and may contribute to observed increases in risk-taking during this developmental period. Functional MRI (fMRI) studies suggest differences between adolescents and adults in neural activation during reward processing, but findings are contradictory, and effects have been found in non-predicted directions. The current study uses an activation likelihood estimation (ALE) approach for quantitative meta-analysis of functional neuroimaging studies to: 1) confirm the network of brain regions involved in adolescents’ reward processing, 2) identify regions involved in specific stages (anticipation, outcome) and valence (positive, negative) of reward processing, and 3) identify differences in activation likelihood between adolescent and adult reward-related brain activation. Results reveal a subcortical network of brain regions involved in adolescent reward processing similar to that found in adults with major hubs including the ventral and dorsal striatum, insula, and posterior cingulate cortex (PCC). Contrast analyses find that adolescents exhibit greater likelihood of activation in the insula while processing anticipation relative to outcome and greater likelihood of activation in the putamen and amygdala during outcome relative to anticipation. While processing positive compared to negative valence, adolescents show increased likelihood for activation in the posterior cingulate cortex (PCC) and ventral striatum. Contrasting adolescent reward processing with the existing ALE of adult reward processing (Liu et al., 2011) reveals increased likelihood for activation in limbic, frontolimbic, and striatal regions in adolescents compared with adults. Unlike adolescents, adults also activate executive control regions of the frontal and parietal lobes. These findings support hypothesized elevations in motivated activity during adolescence. PMID:26254587

Silence That Can Be Dangerous: A Vignette Study to Assess Healthcare Professionals’ Likelihood of Speaking up about Safety Concerns

PubMed Central

Schwappach, David L. B.; Gehring, Katrin

2014-01-01

Purpose To investigate the likelihood of speaking up about patient safety in oncology and to clarify the effect of clinical and situational context factors on the likelihood of voicing concerns. Patients and Methods 1013 nurses and doctors in oncology rated four clinical vignettes describing coworkers’ errors and rule violations in a self-administered factorial survey (65% response rate). Multiple regression analysis was used to model the likelihood of speaking up as outcome of vignette attributes, responder’s evaluations of the situation and personal characteristics. Results Respondents reported a high likelihood of speaking up about patient safety but the variation between and within types of errors and rule violations was substantial. Staff without managerial function provided significantly higher levels of decision difficulty and discomfort to speak up. Based on the information presented in the vignettes, 74%−96% would speak up towards a supervisor failing to check a prescription, 45%−81% would point a coworker to a missed hand disinfection, 82%−94% would speak up towards nurses who violate a safety rule in medication preparation, and 59%−92% would question a doctor violating a safety rule in lumbar puncture. Several vignette attributes predicted the likelihood of speaking up. Perceived potential harm, anticipated discomfort, and decision difficulty were significant predictors of the likelihood of speaking up. Conclusions Clinicians’ willingness to speak up about patient safety is considerably affected by contextual factors. Physicians and nurses without managerial function report substantial discomfort with speaking up. Oncology departments should provide staff with clear guidance and trainings on when and how to voice safety concerns. PMID:25116338

The reliability of differentiating neurogenic claudication from vascular claudication based on symptomatic presentation.

PubMed

Nadeau, Mélissa; Rosas-Arellano, M Patricia; Gurr, Kevin R; Bailey, Stewart I; Taylor, David C; Grewal, Ruby; Lawlor, D Kirk; Bailey, Chris S

2013-12-01

Intermittent claudication can be neurogenic or vascular. Physicians use a profile based on symptom attributes to differentiate the 2 types of claudication, and this guides their investigations for diagnosis of the underlying pathology. We evaluated the validity of these symptom attributes in differentiating neurogenic from vascular claudication. Patients with a diagnosis of lumbar spinal stenosis (LSS) or peripheral vascular disease (PVD) who reported claudication answered 14 questions characterizing their symptoms. We determined the sensitivity, specificity and positive and negative likelihood ratios (PLR and NLR) for neurogenic and vascular claudication for each symptom attribute. We studied 53 patients. The most sensitive symptom attribute to rule out LSS was the absence of "triggering of pain with standing alone" (sensitivity 0.97, NLR 0.050). Pain alleviators and symptom location data showed a weak clinical significance for LSS and PVD. Constellation of symptoms yielded the strongest associations: patients with a positive shopping cart sign whose symptoms were located above the knees, triggered with standing alone and relieved with sitting had a strong likelihood of neurogenic claudication (PLR 13). Patients with symptoms in the calf that were relieved with standing alone had a strong likelihood of vascular claudication (PLR 20.0). The classic symptom attributes used to differentiate neurogenic from vascular claudication are at best weakly valid independently. However, certain constellation of symptoms are much more indicative of etiology. These results can guide general practitioners in their evaluation of and investigation for claudication.

Factors associated with oral hygiene practices among adults with systemic sclerosis

PubMed Central

Yuen, Hon K.; Hant, Faye N.; Hatfield, Corey; Summerlin, Lisa M.; Smith, Edwin A.; Silver, Richard M.

2013-01-01

OBJECTIVE To identify factors associated with oral hygiene practices in adults with systemic sclerosis (SSc) METHODS In this cross-sectional study, 178 dentate adults with SSc received an oral examination which included measurement of oral aperture, assessment of manual dexterity to perform oral hygiene, as well as completion of the Center of Epidemiological Studies Depression (CES-D) Scale, and an oral health-related questionnaire. RESULTS Multivariable logistic regression modeling showed male, minority and high CES-D scores (i.e., clinically significant symptoms of depression) were associated with less likelihood of participants brushing teeth at least twice daily, but the presence of self-reported dry mouth symptoms increased the likelihood of toothbrushing. Having a dental visit in the past 12 months, and use of an adapted flossing or interdental cleaning device were significantly associated with daily dental flossing; however, having difficulty flossing teeth reduced the likelihood of daily flossing. CONCLUSIONS Overall, demographic variables were strongly associated with toothbrushing frequency, whereas, flossing self-efficacy and barriers were strongly associated with dental flossing frequency in adults with SSc. The results suggest that dental health professionals should take mental health into consideration when educating patients with SSc to improve their oral hygiene, and consider making referrals for patients exhibiting suspected clinically significant depressive symptoms to mental health professionals for further evaluation and treatment. In addition, an appropriate adapted flossing or interdental cleaning device should be recommended to increase dental flossing practices in this patient population. PMID:24128049

[Evaluation of T-SPOT.TB assay in the diagnosis of pulmonary tuberculosis within different age groups].

PubMed

Pan, Liping; Jia, Hongyan; Liu, Fei; Gao, Mengqiu; Sun, Huishan; Du, Boping; Sun, Qi; Xing, Aiying; Wei, Rongrong; Zhang, Zongde

2015-12-01

To evaluate the value of T-SPOT.TB assay in the diagnosis of pulmonary tuberculosis within different age groups. We analyzed 1 518 suspected pulmonary tuberculosis (PTB) patients who were admitted to the Beijing Chest Hospital from November 2012 to February 2014 and had valid T-SPOT.TB tests before anti-tuberculosis therapy. The 599 microbiologically and/or histopathologically-confirmed PTB patients (16-89 years old, 388 males and 211 females) and 235 non-TB patients (14-85 years old, 144 males and 91 females) were enrolled for the analysis of diagnostic performance of T-SPOT.TB, while patients with uncertain diagnosis or diagnosis based on clinical impression (n=684) were excluded from the analysis. The sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, and negative likelihood ratio of the T-SPOT.TB were analyzed according to the final diagnosis. Furthermore, the diagnostic performance of T-SPOT.TB assay in the younger patients (14-59 years old) and elderly patients (60-89 years old) were also analyzed respectively. Categorical variables were compared by Pearson's Chi-square test, while continuous variables were compared by the Mann-Whitney U-test. The sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, and negative likelihood ratio of the T-SPOT.TB in diagnosis of PTB were 90.1% (540/599), 65.5% (154/235), 86.9% (540/621), 72.3% (154/213), 2.61, and 0.15, respectively. The sensitivity and specificity of T-SPOT.TB assay were 92.6% (375/405) and 75.6% (99/131), respectively in the younger patients, and 85.0% (165/194), 52.9% (55/104) respectively in the elderly patients. The sensitivity and specificity of T-SPOT.TB assay in the younger patients were significantly higher than those in the elderly patients (P<0.01), and the spot forming cells in the younger PTB patients were significantly higher than in the elderly PTB patients [300 (126, 666)/10(6) PBMCs vs. 258 (79, 621)/10(6) PBMCs, P=0.037]. T-SPOT.TB is a promising test in the diagnosis of younger patients (14-59 years old) with suspected PTB, but the diagnostic performance in elderly patients (60-89 years old) is relatively reduced.

Determinants of NCI Cancer Center attendance in Medicare patients with lung, breast, colorectal, or prostate cancer.

PubMed

Onega, Tracy; Duell, Eric J; Shi, Xun; Demidenko, Eugene; Goodman, David

2009-02-01

Geographic access to NCI-Cancer Centers varies by region, race/ethnicity, and place of residence, but utilization of these specialized centers has not been examined at the national level in the U.S. This study identified determinants of NCI-Cancer Center attendance in Medicare cancer patients. SEER-Medicare (Surveillance Epidemiology and End Results) data were used to identify individuals with an incident cancer of the breast, lung, colon/rectum, or prostate from 1998-2002. NCI-Cancer Center attendance was determined based on utilization claims from 1998-2003. Demographic, clinical, and geographic factors were examined in multilevel models. We performed sensitivity analyses for the NCI-Cancer Center attendance definition. Overall, 7.3% of this SEER-Medicare cohort (N = 211,048) attended an NCI-Cancer Center. Travel-time to the nearest NCI-Cancer Center was inversely related to attendance, showing 11% decreased likelihood of attendance for every 10 minutes of additional travel-time (OR = 0.89, 95%CI 0.88-0.90). Receiving predominantly generalist care prior to diagnosis was associated with a lower likelihood of attendance (OR = 0.79, 95%CI 0.77-0.82). The other factors associated with greater NCI-Cancer attendance were later stage at diagnosis, fewer comorbidities, and urban residence in conjunction with African-American race. Attendance at NCI-Cancer Centers is low among Medicare beneficiaries, but is strongly influenced by proximity and general provider care prior to diagnosis. Other patient factors are predictive of NCI-Cancer Center attendance and may be important in better understanding cancer care utilization.

Nicotine Dependence, “Background” and Cue-Induced Craving and Smoking in the Laboratory

PubMed Central

Dunbar, Michael S.; Shiffman, Saul; Kirchner, Thomas; Tindle, Hilary; Scholl, Sarah

2014-01-01

Background Nicotine dependence has been associated with higher “background” craving and smoking, independent of situational cues. Due in part to conceptual and methodological differences across past studies, the relationship between dependence and cue-reactivity (CR; e.g., cue-induced craving and smoking) remains unclear. Methods 207 daily smokers completed six pictorial CR sessions (smoking, negative affect, positive affect, alcohol, smoking prohibitions, and neutral). Individuals rated craving before (background craving) and after cues, and could smoke following cue exposure. Session videos were coded to assess smoking. Participants completed four nicotine dependence measures. Regression models assessed the relationship of dependence to cue-independent (i.e., pre-cue) and cue-specific (i.e., pre-post cue change for each cue, relative to neutral) craving and smoking (likelihood of smoking, latency to smoke, puff count). Results Dependence was associated with background craving and smoking, but did not predict change in craving across the entire sample for any cue. Among alcohol drinkers, dependence was associated with greater increases in craving following the alcohol cue. Only one dependence measure (Wisconsin Inventory of Smoking Dependence Motives) was consistently associated with smoking reactivity (higher likelihood of smoking, shorter latency to smoke, greater puff count) in response to cues. Conclusion While related to cue-independent background craving and smoking, dependence is not strongly associated with laboratory cue-induced craving under conditions of minimal deprivation. Dependence measures that incorporate situational influences on smoking correlate with greater cue-provoked smoking. This may suggest independent roles for CR and traditional dependence as determinants of smoking, and highlights the importance of assessing behavioral CR outcomes. PMID:25028339

Nicotine dependence, "background" and cue-induced craving and smoking in the laboratory.

PubMed

Dunbar, Michael S; Shiffman, Saul; Kirchner, Thomas R; Tindle, Hilary A; Scholl, Sarah M

2014-09-01

Nicotine dependence has been associated with higher "background" craving and smoking, independent of situational cues. Due in part to conceptual and methodological differences across past studies, the relationship between dependence and cue-reactivity (CR; e.g., cue-induced craving and smoking) remains unclear. 207 daily smokers completed six pictorial CR sessions (smoking, negative affect, positive affect, alcohol, smoking prohibitions, and neutral). Individuals rated craving before (background craving) and after cues, and could smoke following cue exposure. Session videos were coded to assess smoking. Participants completed four nicotine dependence measures. Regression models assessed the relationship of dependence to cue-independent (i.e., pre-cue) and cue-specific (i.e., pre-post cue change for each cue, relative to neutral) craving and smoking (likelihood of smoking, latency to smoke, puff count). Dependence was associated with background craving and smoking, but did not predict change in craving across the entire sample for any cue. Among alcohol drinkers, dependence was associated with greater increases in craving following the alcohol cue. Only one dependence measure (Wisconsin Inventory of Smoking Dependence Motives) was consistently associated with smoking reactivity (higher likelihood of smoking, shorter latency to smoke, greater puff count) in response to cues. While related to cue-independent background craving and smoking, dependence is not strongly associated with laboratory cue-induced craving under conditions of minimal deprivation. Dependence measures that incorporate situational influences on smoking correlate with greater cue-provoked smoking. This may suggest independent roles for CR and traditional dependence as determinants of smoking, and highlights the importance of assessing behavioral CR outcomes. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Modulation/demodulation techniques for satellite communications. Part 2: Advanced techniques. The linear channel

NASA Technical Reports Server (NTRS)

Omura, J. K.; Simon, M. K.

1982-01-01

A theory is presented for deducing and predicting the performance of transmitter/receivers for bandwidth efficient modulations suitable for use on the linear satellite channel. The underlying principle used is the development of receiver structures based on the maximum-likelihood decision rule. The application of the performance prediction tools, e.g., channel cutoff rate and bit error probability transfer function bounds to these modulation/demodulation techniques.

Comparative prediction of nonepileptic events using MMPI-2 clinical scales, Harris Lingoes subscales, and restructured clinical scales.

PubMed

Yamout, Karim Z; Heinrichs, Robin J; Baade, Lyle E; Soetaert, Dana K; Liow, Kore K

2017-03-01

The Minnesota Multiphasic Personality Inventory-2 (MMPI-2) is a psychological testing tool used to measure psychological and personality constructs. The MMPI-2 has proven helpful in identifying individuals with nonepileptic events/nonepileptic seizures. However, the MMPI-2 has had some updates that enhanced its original scales. The aim of this article was to test the utility of updated MMPI-2 scales in predicting the likelihood of non-epileptic seizures in individuals admitted to an EEG video monitoring unit. We compared sensitivity, specificity, and likelihood ratios of traditional MMPI-2 Clinical Scales against more homogenous MMPI-2 Harris-Lingoes subscales and the newer Restructured Clinical (RC) scales. Our results showed that the Restructured Scales did not show significant improvement over the original Clinical scales. However, one Harris-Lingoes subscale (HL4 of Clinical Scale 3) did show improved predictive utility over the original Clinical scales as well as over the newer Restructured Clinical scales. Our study suggests that the predictive utility of the MMPI-2 can be improved using already existing scales. This is particularly useful for those practitioners who are not invested in switching over to the newly developed MMPI-2 Restructured Form (MMPI-2 RF). Copyright © 2016 Elsevier Inc. All rights reserved.

Using Emotion as Information in Future-Oriented Cognition: Individual Differences in the Context of State Negative Affect

PubMed Central

Marroquín, Brett; Boyle, Chloe C.; Nolen-Hoeksema, Susan; Stanton, Annette L.

2016-01-01

Predictions about the future are susceptible to mood-congruent influences of emotional state. However, recent work suggests individuals also differ in the degree to which they incorporate emotion into cognition. This study examined the role of such individual differences in the context of state negative emotion. We examined whether trait tendencies to use negative or positive emotion as information affect individuals' predictions of what will happen in the future (likelihood estimation) and how events will feel (affective forecasting), and whether trait influences depend on emotional state. Participants (N=119) reported on tendencies to use emotion as information (“following feelings”), underwent an emotion induction (negative versus neutral), and made likelihood estimates and affective forecasts for future events. Views of the future were predicted by both emotional state and individual differences in following feelings. Whereas following negative feelings affected most future-oriented cognition across emotional states, following positive feelings specifically buffered individuals' views of the future in the negative emotion condition, and specifically for positive future events, a category of future-event prediction especially important in psychological health. Individual differences may confer predisposition toward optimistic or pessimistic expectations of the future in the context of acute negative emotion, with implications for adaptive and maladaptive functioning. PMID:27041783

Development of a wound healing index for patients with chronic wounds.

PubMed

Horn, Susan D; Fife, Caroline E; Smout, Randall J; Barrett, Ryan S; Thomson, Brett

2013-01-01

Randomized controlled trials in wound care generalize poorly because they exclude patients with significant comorbid conditions. Research using real-world wound care patients is hindered by lack of validated methods to stratify patients according to severity of underlying illnesses. We developed a comprehensive stratification system for patients with wounds that predicts healing likelihood. Complete medical record data on 50,967 wounds from the United States Wound Registry were assigned a clear outcome (healed, amputated, etc.). Factors known to be associated with healing were evaluated using logistic regression models. Significant variables (p < 0.05) were determined and subsequently tested on a holdout sample of data. A different model predicted healing for each wound type. Some variables predicted significantly in nearly all models: wound size, wound age, number of wounds, evidence of bioburden, tissue type exposed (Wagner grade or stage), being nonambulatory, and requiring hospitalization during the course of care. Variables significant in some models included renal failure, renal transplant, malnutrition, autoimmune disease, and cardiovascular disease. All models validated well when applied to the holdout sample. The "Wound Healing Index" can validly predict likelihood of wound healing among real-world patients and can facilitate comparative effectiveness research to identify patients needing advanced therapeutics. © 2013 by the Wound Healing Society.

Object-Based Attention Overrides Perceptual Load to Modulate Visual Distraction

ERIC Educational Resources Information Center

Cosman, Joshua D.; Vecera, Shaun P.

2012-01-01

The ability to ignore task-irrelevant information and overcome distraction is central to our ability to efficiently carry out a number of tasks. One factor shown to strongly influence distraction is the perceptual load of the task being performed; as the perceptual load of task-relevant information processing increases, the likelihood that…

Stage-structured transmission of phocine distemper virus in the Dutch 2002 outbreak

PubMed Central

Klepac, Petra; Pomeroy, Laura W.; Bjørnstad, Ottar N.; Kuiken, Thijs; Osterhaus, Albert D.M.E.; Rijks, Jolianne M.

2009-01-01

Heterogeneities in transmission among hosts can be very important in shaping infectious disease dynamics. In mammals with strong social organization, such heterogeneities are often structured by functional stage: juveniles, subadults and adults. We investigate the importance of such stage-related heterogeneities in shaping the 2002 phocine distemper virus (PDV) outbreak in the Dutch Wadden Sea, when more than 40 per cent of the harbour seals were killed. We do this by comparing the statistical fit of a hierarchy of models with varying transmission complexity: homogeneous versus heterogeneous mixing and density- versus frequency-dependent transmission. We use the stranding data as a proxy for incidence and use Poisson likelihoods to estimate the ‘who acquires infection from whom’ (WAIFW) matrix. Statistically, the model with strong heterogeneous mixing and density-dependent transmission was found to best describe the transmission dynamics. However, patterns of incidence support a model of frequency-dependent transmission among adults and juveniles. Based on the maximum-likelihood WAIFW matrix estimates, we use the next-generation formalism to calculate an R0 between 2 and 2.5 for the Dutch 2002 PDV epidemic. PMID:19364743

Clinical Prediction Rule for Declines in Activities of Daily Living at 6 Months After Surgery for Hip Fracture Repair.

PubMed

Tanaka, Ryo; Umehara, Takuya; Fujimura, Takafumi; Ozawa, Junya

2016-12-01

To develop and assess a clinical prediction rule (CPR) to predict declines in activities of daily living (ADL) at 6 months after surgery for hip fracture repair. Prospective, cohort study. From hospital to home. Patients (N=104) with hip fractures after surgery. Not applicable. ADL were assessed using the Barthel Index at 6 months after surgery. At 6 months after surgery, 86 patients (82.6%) were known to be alive, 1 patient (1.0%) had died, and 17 (16.3%) were lost to follow-up. Thirty-two patients (37.2%) did not recover their ADL at 6 months after surgery to levels before fracture. The classification and regression trees methodology was used to develop 2 models to predict a decline in ADL: (1) model 1 included age, type of fracture, and care level before fracture (sensitivity=75.0%, specificity=81.5%, positive predictive value=70.6%, positive likelihood ratio=4.050); and (2) model 2 included the degree of independence 2 weeks postsurgery for ADL chair transfer, ADL ambulation, and age (sensitivity=65.6%, specificity=87.0%, positive predictive value=75.0%, positive likelihood ratio=5.063). The areas under the receiver operating characteristic curves of both CPR models were .825 (95% confidential interval, .728-.923) and .790 (95% confidence interval, .683-.897), respectively. CPRs with moderate accuracy were developed to predict declines in ADL at 6 months after surgery for hip fracture repair. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Fetal Tricuspid Regurgitation in the First Trimester as a Screening Marker for Congenital Heart Defects: Systematic Review and Meta-Analysis.

PubMed

Scala, Carolina; Morlando, Maddalena; Familiari, Alessandra; Leone Roberti Maggiore, Umberto; Ferrero, Simone; D'Antonio, Francesco; Khalil, Asma

2017-01-01

Assessment of tricuspid flow has been reported to improve the performance of screening for aneuploidies and congenital heart defects (CHD). However, the performance of tricuspid regurgitation (TR) as a screening marker for CHD in euploid fetuses is yet to be established. The main aim of this meta-analysis was to establish the predictive accuracy of TR for CHD. MEDLINE, Embase, and the Cochrane Library were searched electronically utilizing combinations of the relevant medical subject heading for "fetus," "tricuspid regurgitation," and "first trimester." The outcomes explored were prevalence of TR in an euploid population, strength of association between TR and CHD, and predictive accuracy of TR for CHD in euploid fetuses. Summary estimates of sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratio for the overall predictive accuracy of TR for the detection of CHD were computed using the hierarchical summary receiver-operating characteristics model. A total of 452 articles were identified; 60 were assessed with respect to their eligibility for inclusion and a total of 4 studies were included in the study. TR was associated with an increased risk of CHD (RR: 9.6, 95% CI 2.8-33.5; I2: 92.7%). The strength of association between TR and CHD persisted when considering fetuses at risk for CHD, such as those with increased nuchal translucency (RR: 7.2, 95% CI 5.2-9.8; I2: 0%), while TR did not show any association with CHD when detected in a population at low risk for cardiac defects (RR: 9.3, 95% CI 0.8-111.8; I2: 93%). The overall diagnostic performance of TR in detecting CHD was poor in detecting CHD (sROC: 0.684, SE: 0.61) with a sensitivity of 35.2% (95% CI 26.9-44.1) and a specificity of 98.6% (95% CI 98.5-98.7). Detection of TR at the 11-14 weeks' scan showed a positive likelihood ratio of 7.2 (95% CI 5.3-9.8) in detecting CHD when applied to a population at risk for CHD such as fetuses with an increased nuchal translucency. The detection of TR in the first trimester increases the risk of CHD. However, isolated TR in the first trimester does not seem to be a strong predictor for CHD. © 2017 S. Karger AG, Basel.

Inter-annual rainfall variations and suicide in New South Wales, Australia, 1964-2001

NASA Astrophysics Data System (ADS)

Nicholls, Neville; Butler, Colin D.; Hanigan, Ivan

2006-01-01

The suicide rate in New South Wales is shown to be related to annual precipitation, supporting a widespread and long-held assumption that drought in Australia increases the likelihood of suicide. The relationship, although statistically significant, is not especially strong and is confounded by strong, long-term variations in the suicide rate not related to precipitation variations. A decrease in precipitation of about 300 mm would lead to an increase in the suicide rate of approximately 8% of the long-term mean suicide rate.

Determinants of Informal Care, Burden, and Risk of Burnout in Caregivers of Stroke Survivors: The CONOCES Study.

PubMed

Oliva-Moreno, Juan; Peña-Longobardo, Luz María; Mar, Javier; Masjuan, Jaime; Soulard, Stéphane; Gonzalez-Rojas, Nuria; Becerra, Virginia; Casado, Miguel Ángel; Torres, Covadonga; Yebenes, María; Quintana, Manuel; Alvarez-Sabín, Jose

2018-01-01

The aim of this article was to analyze the likelihood of receiving informal care after a stroke and to study the burden and risk of burnout of primary caregivers in Spain. The CONOCES study is an epidemiological, observational, prospective, multicenter study of patients diagnosed with stroke and admitted to a Stroke Unit in the Spanish healthcare system. At 3 and 12 months post-event, we estimated the time spent caring for the patient and the burden borne by primary caregivers. Several multivariate models were applied to estimate the likelihood of receiving informal caregiving, the burden, and the likelihood of caregivers being at a high risk of burnout. Eighty percent of those still alive at 3 and 12 months poststroke were receiving informal care. More than 40% of those receiving care needed a secondary caregiver at 3 months poststroke. The likelihood of receiving informal care was associated with stroke severity and the individual's health-related quality of life. When informal care was provided, both the burden borne by caregivers and the likelihood of caregivers being at a high risk of burnout was associated with (1) caregiving hours; (2) the patient's health-related quality of life; (3) the severity of the stroke measured at discharge; (4) the patient having atrial fibrillation; and (5) the degree of dependence. This study reveals the heavy burden borne by the caregivers of stroke survivors. Our analysis also identifies explanatory and predictive variables for the likelihood of receiving informal care, caregiver burden, and high risk of burnout. © 2017 American Heart Association, Inc.

Regional Earthquake Likelihood Models: A realm on shaky grounds?

NASA Astrophysics Data System (ADS)

Kossobokov, V.

2005-12-01

Seismology is juvenile and its appropriate statistical tools to-date may have a "medievil flavor" for those who hurry up to apply a fuzzy language of a highly developed probability theory. To become "quantitatively probabilistic" earthquake forecasts/predictions must be defined with a scientific accuracy. Following the most popular objectivists' viewpoint on probability, we cannot claim "probabilities" adequate without a long series of "yes/no" forecast/prediction outcomes. Without "antiquated binary language" of "yes/no" certainty we cannot judge an outcome ("success/failure"), and, therefore, quantify objectively a forecast/prediction method performance. Likelihood scoring is one of the delicate tools of Statistics, which could be worthless or even misleading when inappropriate probability models are used. This is a basic loophole for a misuse of likelihood as well as other statistical methods on practice. The flaw could be avoided by an accurate verification of generic probability models on the empirical data. It is not an easy task in the frames of the Regional Earthquake Likelihood Models (RELM) methodology, which neither defines the forecast precision nor allows a means to judge the ultimate success or failure in specific cases. Hopefully, the RELM group realizes the problem and its members do their best to close the hole with an adequate, data supported choice. Regretfully, this is not the case with the erroneous choice of Gerstenberger et al., who started the public web site with forecasts of expected ground shaking for `tomorrow' (Nature 435, 19 May 2005). Gerstenberger et al. have inverted the critical evidence of their study, i.e., the 15 years of recent seismic record accumulated just in one figure, which suggests rejecting with confidence above 97% "the generic California clustering model" used in automatic calculations. As a result, since the date of publication in Nature the United States Geological Survey website delivers to the public, emergency planners and the media, a forecast product, which is based on wrong assumptions that violate the best-documented earthquake statistics in California, which accuracy was not investigated, and which forecasts were not tested in a rigorous way.

The diagnostic accuracy of physical examination compared to lung ultrasound for determining lung congestion in hemodialysis patients who have reached their dry weight

NASA Astrophysics Data System (ADS)

Rahardjo, K. D.; Dharmaeizar; Nainggolan, G.; Harimurti, K.

2017-08-01

Research has shown that hemodialysis patients with lung congestion have high morbidity and mortality. Patients were assumed to be free of lung congestion if they had reached their post-dialysis dry weight. Most often, to determine if the patient was free of lung congestion, physical examination was used. However, the accuracy of physical examination in detecting lung congestion has not been established. To compare the capabilities of physical examination and lung ultrasound in detection of lung congestion, cross-sectional data collection was conducted on hemodialysis patients. Analysis was done to obtain proportion, sensitivity, specificity, positive predictive value, negative predictive value, and positive likelihood ratio. Sixty patients participated in this study. The inter observer variation of 20 patients revealed a kappa value of 0.828. When all 60 patients were taken into account, we found that 36 patients (57.1%) had lung congestion. Mild lung congestion was found in 24 (38.1%), and 12 (19%) had a moderate degree of congestion. In the analysis comparing jugular venous pressure to lung ultrasound, we found that sensitivity was 0.47 (0.31-0.63), specificity was 0.73 (0.54-0.86), positive predictive value (PPV) was 0.51 (0.36-0.67), negative predictive value (NPV) was 0.70 (0.49-0.84), positive likelihood ratio (PLR) was 1.75 (0.88-3.47), and the negative likelihood ratio (NLR) was 0.72 (0.47-1.12). In terms of lung auscultation, we found that sensitivity was 0.56 (0.39-0.71), specificity was 0.54 (0.35-0.71), PPV was 0.61 (0.44-0.76), NPV was 0.48 (0.31-0.66), PLR was 1.21 (0.73-2.0), and NLR was 0.82 (0.49-1.38). The results of our study showed that jugular venous distention and lung auscultation examination are not reliable means of detecting lung congestion.

A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer.

PubMed

Paik, Soonmyung; Shak, Steven; Tang, Gong; Kim, Chungyeul; Baker, Joffre; Cronin, Maureen; Baehner, Frederick L; Walker, Michael G; Watson, Drew; Park, Taesung; Hiller, William; Fisher, Edwin R; Wickerham, D Lawrence; Bryant, John; Wolmark, Norman

2004-12-30

The likelihood of distant recurrence in patients with breast cancer who have no involved lymph nodes and estrogen-receptor-positive tumors is poorly defined by clinical and histopathological measures. We tested whether the results of a reverse-transcriptase-polymerase-chain-reaction (RT-PCR) assay of 21 prospectively selected genes in paraffin-embedded tumor tissue would correlate with the likelihood of distant recurrence in patients with node-negative, tamoxifen-treated breast cancer who were enrolled in the National Surgical Adjuvant Breast and Bowel Project clinical trial B-14. The levels of expression of 16 cancer-related genes and 5 reference genes were used in a prospectively defined algorithm to calculate a recurrence score and to determine a risk group (low, intermediate, or high) for each patient. Adequate RT-PCR profiles were obtained in 668 of 675 tumor blocks. The proportions of patients categorized as having a low, intermediate, or high risk by the RT-PCR assay were 51, 22, and 27 percent, respectively. The Kaplan-Meier estimates of the rates of distant recurrence at 10 years in the low-risk, intermediate-risk, and high-risk groups were 6.8 percent (95 percent confidence interval, 4.0 to 9.6), 14.3 percent (95 percent confidence interval, 8.3 to 20.3), and 30.5 percent (95 percent confidence interval, 23.6 to 37.4). The rate in the low-risk group was significantly lower than that in the high-risk group (P<0.001). In a multivariate Cox model, the recurrence score provided significant predictive power that was independent of age and tumor size (P<0.001). The recurrence score was also predictive of overall survival (P<0.001) and could be used as a continuous function to predict distant recurrence in individual patients. The recurrence score has been validated as quantifying the likelihood of distant recurrence in tamoxifen-treated patients with node-negative, estrogen-receptor-positive breast cancer. Copyright 2004 Massachusetts Medical Society.

Comparison of different risk stratification systems in predicting short-term serious outcome of syncope patients

PubMed Central

Safari, Saeed; Baratloo, Alireza; Hashemi, Behrooz; Rahmati, Farhad; Forouzanfar, Mohammad Mehdi; Motamedi, Maryam; Mirmohseni, Ladan

2016-01-01

Background: Determining etiologic causes and prognosis can significantly improve management of syncope patients. The present study aimed to compare the values of San Francisco, Osservatorio Epidemiologico sulla Sincope nel Lazio (OESIL), Boston, and Risk Stratification of Syncope in the Emergency Department (ROSE) score clinical decision rules in predicting the short-term serious outcome of syncope patients. Materials and Methods: The present diagnostic accuracy study with 1-week follow-up was designed to evaluate the predictive values of the four mentioned clinical decision rules. Screening performance characteristics of each model in predicting mortality, myocardial infarction (MI), and cerebrovascular accidents (CVAs) were calculated and compared. To evaluate the value of each aforementioned model in predicting the outcome, sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio were calculated and receiver-operating curve (ROC) curve analysis was done. Results: A total of 187 patients (mean age: 64.2 ± 17.2 years) were enrolled in the study. Mortality, MI, and CVA were seen in 19 (10.2%), 12 (6.4%), and 36 (19.2%) patients, respectively. Area under the ROC curve for OESIL, San Francisco, Boston, and ROSE models in prediction the risk of 1-week mortality, MI, and CVA was in the 30–70% range, with no significant difference among models (P > 0.05). The pooled model did not show higher accuracy in prediction of mortality, MI, and CVA compared to others (P > 0.05). Conclusion: This study revealed the weakness of all four evaluated models in predicting short-term serious outcome of syncope patients referred to the emergency department without any significant advantage for one among others. PMID:27904602

Prealbumin, platelet factor 4 and S100A12 combination at baseline predicts good response to TNF alpha inhibitors in Rheumatoid Arthritis.

PubMed

Nguyen, Minh Vu Chuong; Baillet, Athan; Romand, Xavier; Trocmé, Candice; Courtier, Anaïs; Marotte, Hubert; Thomas, Thierry; Soubrier, Martin; Miossec, Pierre; Tébib, Jacques; Grange, Laurent; Toussaint, Bertrand; Lequerré, Thierry; Vittecoq, Olivier; Gaudin, Philippe

2018-06-06

Tumour necrosis factor-alpha inhibitors (TNFi) are effective treatments for Rheumatoid Arthritis (RA). Responses to treatment are barely predictable. As these treatments are costly and may induce a number of side effects, we aimed at identifying a panel of protein biomarkers that could be used to predict clinical response to TNFi for RA patients. Baseline blood levels of C-reactive protein, platelet factor 4, apolipoprotein A1, prealbumin, α1-antitrypsin, haptoglobin, S100A8/A9 and S100A12 proteins in bDMARD naive patients at the time of TNFi treatment initiation were assessed in a multicentric prospective French cohort. Patients fulfilling good EULAR response at 6 months were considered as responders. Logistic regression was used to determine best biomarker set that could predict good clinical response to TNFi. A combination of biomarkers (prealbumin, platelet factor 4 and S100A12) was identified and could predict response to TNFi in RA with sensitivity of 78%, specificity of 77%, positive predictive values (PPV) of 72%, negative predictive values (NPV) of 82%, positive likelihood ratio (LR+) of 3.35 and negative likelihood ratio (LR-) of 0.28. Lower levels of prealbumin and S100A12 and higher level of platelet factor 4 than the determined cutoff at baseline in RA patients are good predictors for response to TNFi treatment globally as well as to Infliximab, Etanercept and Adalimumab individually. A multivariate model combining 3 biomarkers (prealbumin, platelet factor 4 and S100A12) accurately predicted response of RA patients to TNFi and has potential in a daily practice personalized treatment. Copyright © 2018. Published by Elsevier Masson SAS.

Efffect of Aeroallergen Sensitization on Asthma Control in African-American Teens with Persistent Asthma

EPA Science Inventory

In African-American adolescents with persistent asthma, allergic profile predicted the likelihood of having poorly controlled asthma despite guidelines-directed therapies. Our results suggest that tree and weed pollen sensitization are independent risk factors for poorly controll...

Participation motives in physical education: an expectancy-value approach.

PubMed

Goudas, Marios; Dermitzaki, Irini

2004-12-01

This study applied an expectancy-value approach in examining participation motives of students in physical education. As predicted outcome expectancy, a variable formed by the combination of outcome value and outcome likelihood correlated significantly higher with motivational indices than these two factors.

Likelihood parameter estimation for calibrating a soil moisture using radar backscatter

USDA-ARS?s Scientific Manuscript database

Assimilating soil moisture information contained in synthetic aperture radar imagery into land surface model predictions can be done using a calibration, or parameter estimation, approach. The presence of speckle, however, necessitates aggregating backscatter measurements over large land areas in or...

An Observational Study of Children's Involvement in Informed Consent for Exome Sequencing Research.

PubMed

Miller, Victoria A; Werner-Lin, Allison; Walser, Sarah A; Biswas, Sawona; Bernhardt, Barbara A

2017-02-01

The goal of this study was to examine children's involvement in consent sessions for exome sequencing research and associations of involvement with provider and parent communication. Participants included 44 children (8-17 years) from five cohorts who were offered participation in an exome sequencing study. The consent sessions were audiotaped, transcribed, and coded. Providers attempted to facilitate the child's involvement in the majority (73%) of sessions, and most (75%) children also verbally participated. Provider facilitation was strongly associated with likelihood of child participation. These findings underscore that strategies such as asking for children's opinions and soliciting their questions show respect for children and may increase the likelihood that they are engaged and involved in decisions about research participation.

A hybrid model for combining case-control and cohort studies in systematic reviews of diagnostic tests

PubMed Central

Chen, Yong; Liu, Yulun; Ning, Jing; Cormier, Janice; Chu, Haitao

2014-01-01

Systematic reviews of diagnostic tests often involve a mixture of case-control and cohort studies. The standard methods for evaluating diagnostic accuracy only focus on sensitivity and specificity and ignore the information on disease prevalence contained in cohort studies. Consequently, such methods cannot provide estimates of measures related to disease prevalence, such as population averaged or overall positive and negative predictive values, which reflect the clinical utility of a diagnostic test. In this paper, we propose a hybrid approach that jointly models the disease prevalence along with the diagnostic test sensitivity and specificity in cohort studies, and the sensitivity and specificity in case-control studies. In order to overcome the potential computational difficulties in the standard full likelihood inference of the proposed hybrid model, we propose an alternative inference procedure based on the composite likelihood. Such composite likelihood based inference does not suffer computational problems and maintains high relative efficiency. In addition, it is more robust to model mis-specifications compared to the standard full likelihood inference. We apply our approach to a review of the performance of contemporary diagnostic imaging modalities for detecting metastases in patients with melanoma. PMID:25897179

Hungry for love: the influence of self-regulation on infidelity.

PubMed

Ciarocco, Natalie J; Echevarria, Jessica; Lewandowski, Gary W

2012-01-01

The current research examines the effect of self-regulation on the likelihood of committing infidelity. Thirty-two college students in exclusive romantic relationships interacted through a private chat room with an opposite-sex confederate. Prior to this interaction, a food-restriction task depleted half the participants of self-control. As predicted, depleted levels of self-regulation increased the likelihood of infidelity. Specifically, depleted participants were more likely to both accept a coffee date from and supply a personal telephone number to the confederate than non-depleted participants. Weakened self-control may be one potential cause for the levels of infidelity occurring in romantic partnerships today.

Using Positive Youth Development to Predict Contribution and Risk Behaviors in Early Adolescence: Findings from the First Two Waves of the 4-H Study of Positive Youth Development

ERIC Educational Resources Information Center

Jelicic, Helena; Bobek, Deborah L.; Phelps, Erin; Lerner, Richard M.; Lerner, Jacqueline V.

2007-01-01

Theories of positive youth development (PYD) regard such development as bases of both community contributions and lessened likelihood of risk/problem behaviors. Using data from the 4-H Study of PYD, we tested these expectations by examining if PYD in Grade 5 predicted both youth contributions and risk behaviors and depression in Grade 6. Results…

Situational cues and momentary food environment predict everyday eating behavior in adults with overweight and obesity.

PubMed

Elliston, Katherine G; Ferguson, Stuart G; Schüz, Natalie; Schüz, Benjamin

2017-04-01

Individual eating behavior is a risk factor for obesity and highly dependent on internal and external cues. Many studies also suggest that the food environment (i.e., food outlets) influences eating behavior. This study therefore examines the momentary food environment (at the time of eating) and the role of cues simultaneously in predicting everyday eating behavior in adults with overweight and obesity. Intensive longitudinal study using ecological momentary assessment (EMA) over 14 days in 51 adults with overweight and obesity (average body mass index = 30.77; SD = 4.85) with a total of 745 participant days of data. Multiple daily assessments of eating (meals, high- or low-energy snacks) and randomly timed assessments. Cues and the momentary food environment were assessed during both assessment types. Random effects multinomial logistic regression shows that both internal (affect) and external (food availability, social situation, observing others eat) cues were associated with increased likelihood of eating. The momentary food environment predicted meals and snacking on top of cues, with a higher likelihood of high-energy snacks when fast food restaurants were close by (odds ratio [OR] = 1.89, 95% confidence interval [CI] = 1.22, 2.93) and a higher likelihood of low-energy snacks in proximity to supermarkets (OR = 2.29, 95% CI = 1.38, 3.82). Real-time eating behavior, both in terms of main meals and snacks, is associated with internal and external cues in adults with overweight and obesity. In addition, perceptions of the momentary food environment influence eating choices, emphasizing the importance of an integrated perspective on eating behavior and obesity prevention. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Diagnosing diabetic foot osteomyelitis: is the combination of probe-to-bone test and plain radiography sufficient for high-risk inpatients?

PubMed

Aragón-Sánchez, J; Lipsky, Benjamin A; Lázaro-Martínez, J L

2011-02-01

To investigate the accuracy of the sequential combination of the probe-to-bone test and plain X-rays for diagnosing osteomyelitis in the foot of patients with diabetes. We prospectively compiled data on a series of 338 patients with diabetes with 356 episodes of foot infection who were hospitalized in the Diabetic Foot Unit of La Paloma Hospital from 1 October 2002 to 31 April 2010. For each patient we did a probe-to-bone test at the time of the initial evaluation and then obtained plain X-rays of the involved foot. All patients with positive results on either the probe-to-bone test or plain X-ray underwent an appropriate surgical procedure, which included obtaining a bone specimen that was processed for histology and culture. We calculated the sensitivity, specificity, predictive values and likelihood ratios of the procedures, using the histopathological diagnosis of osteomyelitis as the criterion standard. Overall, 72.4% of patients had histologically proven osteomyelitis, 85.2% of whom had positive bone culture. The performance characteristics of both the probe-to-bone test and plain X-rays were excellent. The sequential diagnostic approach had a sensitivity of 0.97, specificity of 0.92, positive predictive value of 0.97, negative predictive value of 0.93, positive likelihood ratio of 12.8 and negative likelihood ratio of 0.02. Only 6.6% of patients with negative results on both diagnostic studies had osteomyelitis. Clinicians seeing patients in a setting similar to ours (specialized diabetic foot unit with a high prevalence of osteomyelitis) can confidently diagnose diabetic foot osteomyelitis when either the probe-to-bone test or a plain X-ray, or especially both, are positive. © 2011 The Authors. Diabetic Medicine © 2011 Diabetes UK.

The meta-Gaussian Bayesian Processor of forecasts and associated preliminary experiments

NASA Astrophysics Data System (ADS)

Chen, Fajing; Jiao, Meiyan; Chen, Jing

2013-04-01

Public weather services are trending toward providing users with probabilistic weather forecasts, in place of traditional deterministic forecasts. Probabilistic forecasting techniques are continually being improved to optimize available forecasting information. The Bayesian Processor of Forecast (BPF), a new statistical method for probabilistic forecast, can transform a deterministic forecast into a probabilistic forecast according to the historical statistical relationship between observations and forecasts generated by that forecasting system. This technique accounts for the typical forecasting performance of a deterministic forecasting system in quantifying the forecast uncertainty. The meta-Gaussian likelihood model is suitable for a variety of stochastic dependence structures with monotone likelihood ratios. The meta-Gaussian BPF adopting this kind of likelihood model can therefore be applied across many fields, including meteorology and hydrology. The Bayes theorem with two continuous random variables and the normal-linear BPF are briefly introduced. The meta-Gaussian BPF for a continuous predictand using a single predictor is then presented and discussed. The performance of the meta-Gaussian BPF is tested in a preliminary experiment. Control forecasts of daily surface temperature at 0000 UTC at Changsha and Wuhan stations are used as the deterministic forecast data. These control forecasts are taken from ensemble predictions with a 96-h lead time generated by the National Meteorological Center of the China Meteorological Administration, the European Centre for Medium-Range Weather Forecasts, and the US National Centers for Environmental Prediction during January 2008. The results of the experiment show that the meta-Gaussian BPF can transform a deterministic control forecast of surface temperature from any one of the three ensemble predictions into a useful probabilistic forecast of surface temperature. These probabilistic forecasts quantify the uncertainty of the control forecast; accordingly, the performance of the probabilistic forecasts differs based on the source of the underlying deterministic control forecasts.

Using artificial intelligence to predict the risk for posterior capsule opacification after phacoemulsification.

PubMed

Mohammadi, Seyed-Farzad; Sabbaghi, Mostafa; Z-Mehrjardi, Hadi; Hashemi, Hassan; Alizadeh, Somayeh; Majdi, Mercede; Taee, Farough

2012-03-01

To apply artificial intelligence models to predict the occurrence of posterior capsule opacification (PCO) after phacoemulsification. Farabi Eye Hospital, Tehran, Iran. Clinical-based cross-sectional study. The posterior capsule status of eyes operated on for age-related cataract and the need for laser capsulotomy were determined. After a literature review, data polishing, and expert consultation, 10 input variables were selected. The QUEST algorithm was used to develop a decision tree. Three back-propagation artificial neural networks were constructed with 4, 20, and 40 neurons in 2 hidden layers and trained with the same transfer functions (log-sigmoid and linear transfer) and training protocol with randomly selected eyes. They were then tested on the remaining eyes and the networks compared for their performance. Performance indices were used to compare resultant models with the results of logistic regression analysis. The models were trained using 282 randomly selected eyes and then tested using 70 eyes. Laser capsulotomy for clinically significant PCO was indicated or had been performed 2 years postoperatively in 40 eyes. A sample decision tree was produced with accuracy of 50% (likelihood ratio 0.8). The best artificial neural network, which showed 87% accuracy and a positive likelihood ratio of 8, was achieved with 40 neurons. The area under the receiver-operating-characteristic curve was 0.71. In comparison, logistic regression reached accuracy of 80%; however, the likelihood ratio was not measurable because the sensitivity was zero. A prototype artificial neural network was developed that predicted posterior capsule status (requiring capsulotomy) with reasonable accuracy. No author has a financial or proprietary interest in any material or method mentioned. Copyright © 2012 ASCRS and ESCRS. Published by Elsevier Inc. All rights reserved.

Whole blood gene expression testing for coronary artery disease in nondiabetic patients: major adverse cardiovascular events and interventions in the PREDICT trial.

PubMed

Rosenberg, Steven; Elashoff, Michael R; Lieu, Hsiao D; Brown, Bradley O; Kraus, William E; Schwartz, Robert S; Voros, Szilard; Ellis, Stephen G; Waksman, Ron; McPherson, John A; Lansky, Alexandra J; Topol, Eric J

2012-06-01

The majority of first-time angiography patients are without obstructive coronary artery disease (CAD). A blood gene expression score (GES) for obstructive CAD likelihood was validated in the PREDICT study, but its relation to major adverse cardiovascular events (MACE) and revascularization was not assessed. Patients (N = 1,160) were followed up for MACE and revascularization 1 year post-index angiography and GES, with 1,116 completing follow-up. The 30-day event rate was 23% and a further 2.2% at 12 months. The GES was associated with MACE/revascularizations (p < 0.001) and added to clinical risk scores. Patients with GES >15 trended towards increased >30 days MACE/revascularization likelihood (odds ratio = 2.59, 95% confidence interval = 0.89-9.14, p = 0.082). MACE incidence overall was 1.5% (17 of 1,116) and 3 of 17 patients had GES ≤ 15. For the total low GES group (N = 396), negative predictive value was 90% for MACE/revascularization and >99% for MACE alone, identifying a group of patients without obstructive CAD and highly unlikely to suffer MACE within 12 months.

Hindsight Bias.

PubMed

Roese, Neal J; Vohs, Kathleen D

2012-09-01

Hindsight bias occurs when people feel that they "knew it all along," that is, when they believe that an event is more predictable after it becomes known than it was before it became known. Hindsight bias embodies any combination of three aspects: memory distortion, beliefs about events' objective likelihoods, or subjective beliefs about one's own prediction abilities. Hindsight bias stems from (a) cognitive inputs (people selectively recall information consistent with what they now know to be true and engage in sensemaking to impose meaning on their own knowledge), (b) metacognitive inputs (the ease with which a past outcome is understood may be misattributed to its assumed prior likelihood), and (c) motivational inputs (people have a need to see the world as orderly and predictable and to avoid being blamed for problems). Consequences of hindsight bias include myopic attention to a single causal understanding of the past (to the neglect of other reasonable explanations) as well as general overconfidence in the certainty of one's judgments. New technologies for visualizing and understanding data sets may have the unintended consequence of heightening hindsight bias, but an intervention that encourages people to consider alternative causal explanations for a given outcome can reduce hindsight bias. © The Author(s) 2012.

The impact of receiving predictive genetic information about Lynch syndrome on individual colonoscopy and smoking behaviors

PubMed Central

Kim, Joanne Soo-Min; Coyte, Peter C.; Cotterchio, Michelle; Keogh, Louise A.; Flander, Louisa B.; Gaff, Clara; Laporte, Audrey

2016-01-01

Background This study investigated whether receiving the results of predictive genetic testing for Lynch syndrome—indicating the presence or absence of an inherited predisposition to various cancers, including colorectal cancer—was associated with change in individual colonoscopy and smoking behaviours, which could prevent colorectal cancer. Methods The study population included individuals with no previous diagnosis of colorectal cancer, whose families had already-identified deleterious mutations in the mismatch repair or EPCAM genes. Hypotheses were generated from a simple health economics model and tested against individual-level panel data from the Australasian Colorectal Cancer Family Registry. Results The empirical analysis revealed evidence consistent with some of the hypotheses, with a higher likelihood of undergoing colonoscopy in those who discovered their genetic predisposition to colorectal cancer and a lower likelihood of quitting smoking in those who discovered their lack thereof. Conclusion Predictive genetic information about Lynch syndrome was associated with change in individual colonoscopy and smoking behaviours but not necessarily in ways to improve population health. Impact The study findings suggest that the impact of personalized medicine on disease prevention is intricate, warranting further analyses to determine the net benefits and costs. PMID:27528600

Oxygen isotope geochemistry of the amphiboles: isotope effects of cation substitutions in minerals

NASA Astrophysics Data System (ADS)

Kohn, Matthew J.; Valley, John W.

1998-06-01

The occurrence of coexisting amphiboles in rocks and the likelihood of concurrent isotope closure allows equilibrium oxygen isotope fractionations among the amphiboles to be recovered from natural samples. Oxygen isotope analyses of mineral separates using laser fluorination show that coexisting amphiboles increasingly partition 18O in the order: hornblende ≪ gedrite < cummingtonite ≤ anthophyllite. The observed fractionations at ˜575°C are: Δ(Ged-Hbl) = 0.8‰, Δ(Cum-Hbl) = 0.9, Δ(Cum-Ged) = 0.2, Δ(Ath-Ged) = 0.3, and Δ(Ath-Hbl) > 0.9. Previously published data for hornblende, actinolite, glaucophane, and garnet show that Δ(Act-Hbl) ˜ 0.2, Δ(Gln-Grt) ≫ 1, and Δ(Hbl-Grt) ˜ 0. Thus, glaucophane strongly partitions 18O relative to the calcic amphiboles. The fractionation between two amphiboles of arbitrary composition can be predicted from the known fractionations for mica endmembers, pyroxene endmembers, and exchange components such as CaAl(NaSi) -1, NaAl(CaMg) -1, CaMg -1, MgFe -1, FeMn -1, KNa -1, KAl( Si) -1, and Fe 3+Al -1. Applications of the exchange component method reproduce measured amphibole fractionations to within ±0.1 to ±0.2‰, whereas other predictive methods cause misfit for typical metamorphic hornblende of ≥0.5‰ at 575°C. Although the isotope effects of cation exchanges may be small at high-T, they magnify dramatically for minerals formed in surficial, diagenetic, and low-T metamorphic environments. Different composition clays are predicted to have equilibrium δ 18O differences of 2-9‰. If the isotope fractionation can be determined for one mineral endmember, then calibrated exchanges allow accurate prediction of the isotope fractionations for intermediate compositions of most ortho-, ring-, chain-, and sheet-silicates.

The dynamics of male brooding, mating patterns, and sex roles in pipefishes and seahorses (family Syngnathidae).

PubMed

Wilson, Anthony B; Ahnesjö, Ingrid; Vincent, Amanda C J; Meyer, Axel

2003-06-01

Modern theory predicts that relative parental investment of the sexes in their young is a key factor responsible for sexual selection. Seahorses and pipefishes (family Syngnathidae) are extraordinary among fishes in their remarkable adaptations for paternal care and frequent occurrences of sex-role reversals (i.e., female-female competition for mates), offering exceptional opportunities to test predictions of sexual selection theory. During mating, the female transfers eggs into or onto specialized egg-brooding structures that are located on either the male's abdomen or its tail, where they are osmoregulated, aerated, and nourished by specially adapted structures. All syngnathid males exhibit this form of parental care but the brooding structures vary, ranging from the simple ventral gluing areas of some pipefishes to the completely enclosed pouches found in seahorses. We present a molecular phylogeny that indicates that the diversification of pouch types is positively correlated with the major evolutionary radiation of the group, suggesting that this extreme development and diversification of paternal care may have been an important evolutionary innovation of the Syngnathidae. Based on recent studies that show that the complexity of brooding structures reflects the degree of paternal investment in several syngnathid species, we predicted sex-role reversals to be more common among species with more complex brooding structures. In contrast to this prediction, however, both parsimony- and likelihood-based reconstructions of the evolution of sex-role reversal in pipefishes and seahorses suggest multiple shifts in sex roles in the group, independent from the degree of brood pouch development. At the same time, our data demonstrate that sex-role reversal is positively associated with polygamous mating patterns, whereas most nonreversed species mate monogamously, suggesting that selection for polygamy or monogamy in pipefishes and seahorses may strongly influence sex roles in the wild.

A novel multilayer model for missing link prediction and future link forecasting in dynamic complex networks

NASA Astrophysics Data System (ADS)

Yasami, Yasser; Safaei, Farshad

2018-02-01

The traditional complex network theory is particularly focused on network models in which all network constituents are dealt with equivalently, while fail to consider the supplementary information related to the dynamic properties of the network interactions. This is a main constraint leading to incorrect descriptions of some real-world phenomena or incomplete capturing the details of certain real-life problems. To cope with the problem, this paper addresses the multilayer aspects of dynamic complex networks by analyzing the properties of intrinsically multilayered co-authorship networks, DBLP and Astro Physics, and presenting a novel multilayer model of dynamic complex networks. The model examines the layers evolution (layers birth/death process and lifetime) throughout the network evolution. Particularly, this paper models the evolution of each node's membership in different layers by an Infinite Factorial Hidden Markov Model considering feature cascade, and thereby formulates the link generation process for intra-layer and inter-layer links. Although adjacency matrixes are useful to describe the traditional single-layer networks, such a representation is not sufficient to describe and analyze the multilayer dynamic networks. This paper also extends a generalized mathematical infrastructure to address the problems issued by multilayer complex networks. The model inference is performed using some Markov Chain Monte Carlo sampling strategies, given synthetic and real complex networks data. Experimental results indicate a tremendous improvement in the performance of the proposed multilayer model in terms of sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, F1-score, Matthews correlation coefficient, and accuracy for two important applications of missing link prediction and future link forecasting. The experimental results also indicate the strong predictivepower of the proposed model for the application of cascade prediction in terms of accuracy.

Estimating drought risk across Europe from reported drought impacts, drought indices, and vulnerability factors

NASA Astrophysics Data System (ADS)

Blauhut, Veit; Stahl, Kerstin; Stagge, James Howard; Tallaksen, Lena M.; De Stefano, Lucia; Vogt, Jürgen

2016-07-01

Drought is one of the most costly natural hazards in Europe. Due to its complexity, drought risk, meant as the combination of the natural hazard and societal vulnerability, is difficult to define and challenging to detect and predict, as the impacts of drought are very diverse, covering the breadth of socioeconomic and environmental systems. Pan-European maps of drought risk could inform the elaboration of guidelines and policies to address its documented severity and impact across borders. This work tests the capability of commonly applied drought indices and vulnerability factors to predict annual drought impact occurrence for different sectors and macro regions in Europe and combines information on past drought impacts, drought indices, and vulnerability factors into estimates of drought risk at the pan-European scale. This hybrid approach bridges the gap between traditional vulnerability assessment and probabilistic impact prediction in a statistical modelling framework. Multivariable logistic regression was applied to predict the likelihood of impact occurrence on an annual basis for particular impact categories and European macro regions. The results indicate sector- and macro-region-specific sensitivities of drought indices, with the Standardized Precipitation Evapotranspiration Index (SPEI) for a 12-month accumulation period as the overall best hazard predictor. Vulnerability factors have only limited ability to predict drought impacts as single predictors, with information about land use and water resources being the best vulnerability-based predictors. The application of the hybrid approach revealed strong regional and sector-specific differences in drought risk across Europe. The majority of the best predictor combinations rely on a combination of SPEI for shorter and longer accumulation periods, and a combination of information on land use and water resources. The added value of integrating regional vulnerability information with drought risk prediction could be proven. Thus, the study contributes to the overall understanding of drivers of drought impacts, appropriateness of drought indices selection for specific applications, and drought risk assessment.

Long terms trends in CD4+ cell counts, CD8+ cell counts, and the CD4+ : CD8+ ratio

PubMed Central

Hughes, Rachael A.; May, Margaret T.; Tilling, Kate; Taylor, Ninon; Wittkop, Linda; Reiss, Peter; Gill, John; Schommers, Philipp; Costagliola, Dominique; Guest, Jodie L.; Lima, Viviane D.; d’Arminio Monforte, Antonella; Smith, Colette; Cavassini, Matthias; Saag, Michael; Castilho, Jessica L.; Sterne, Jonathan A.C.

2018-01-01

Objective: Model trajectories of CD4+ and CD8+ cell counts after starting combination antiretroviral therapy (ART) and use the model to predict trends in these counts and the CD4+ : CD8+ ratio. Design: Cohort study of antiretroviral-naïve HIV-positive adults who started ART after 1997 (ART Cohort Collaboration) with more than 6 months of follow-up data. Methods: We jointly estimated CD4+ and CD8+ cell count trends and their correlation using a bivariate random effects model, with linear splines describing their population trends, and predicted the CD4+ : CD8+ ratio trend from this model. We assessed whether CD4+ and CD8+ cell count trends and the CD4+ : CD8+ ratio trend varied according to CD4+ cell count at start of ART (baseline), and, whether these trends differed in patients with and without virological failure more than 6 months after starting ART. Results: A total of 39 979 patients were included (median follow-up was 53 months). Among patients with baseline CD4+ cell count at least 50 cells/μl, predicted mean CD8+ cell counts continued to decrease between 3 and 15 years post-ART, partly driving increases in the predicted mean CD4+ : CD8+ ratio. During 15 years of follow-up, normalization of the predicted mean CD4+ : CD8+ ratio (to >1) was only observed among patients with baseline CD4+ cell count at least 200 cells/μl. A higher baseline CD4+ cell count predicted a shorter time to normalization. Conclusion: Declines in CD8+ cell count and increases in CD4+ : CD8+ ratio occurred up to 15 years after starting ART. The likelihood of normalization of the CD4+ : CD8+ ratio is strongly related to baseline CD4+ cell count. PMID:29851663

Education and Obesity in Four OECD Countries. OECD Education Working Papers, No. 39

ERIC Educational Resources Information Center

Sassi, Franco; Devaux, Marion; Church, Jody; Cecchini, Michele; Borgonovi, Francesca

2009-01-01

An epidemic of obesity has been developing in virtually all OECD countries over the last 30 years. Existing evidence provides strong suggestions that such epidemic has affected certain social groups more than others. In particular, education appears to be associated with a lower likelihood of obesity, especially among women. A range of analyses of…

Why Common Sense Goes Out the Window: Effects of Alcohol on Intentions to Use Condoms.

ERIC Educational Resources Information Center

MacDonald, Tara K.; And Others

1996-01-01

Four studies tested the hypothesis that alcohol decreases the likelihood of condom use during casual sex. Results are consistent with "alcohol myopia," the notion that alcohol decreases cognitive capacity, such that intoxicated people are more likely to attend to the most salient cues in a situation. Provides strong evidence that alcohol…

76 FR 41463 - Takes of Marine Mammals Incidental to Specified Activities; Taking Marine Mammals Incidental to a...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-14

... mysticetes. For this proposed study, UAGI expects no cases of TTS given the strong likelihood that baleen... addresses other than the one provided here. Comments sent via e-mail, including all attachments, must not... Personal Identifying Information (for example, name, address, etc.) voluntarily submitted by the commenter...

Analysis of strain distribution, migratory potential, and invasion history of fall armyworm populations in northern Sub-Saharan Africa

USDA-ARS?s Scientific Manuscript database

Fall armyworm (Spodoptera frugiperda, J.E. Smith) is a noctuid moth pest endemic throughout the Western Hemisphere that has recently become widespread in Sub-Saharan Africa. There is a strong expectation of significant damage to African maize crop yield and a high likelihood of further dispersal, pu...

Pramipexole and compulsive masturbation.

PubMed

Sansone, Randy A; Ferlan, Mark

2007-09-01

Exploration of a possible relationship between pramipexole and compulsive masturbation. We present a case report. Given the temporal overlap between pramipexole prescription and its discontinuation, and the onset and cessation of the patient's hypersexual behavior, there appears to be a strong likelihood of association. Like other dopamine agonists, pramipexole may precipitate compulsive behaviors, including hypersexual behavior in the form of compulsive masturbation.

Curricula, Competition and Conventional Bonds: The Educational Role in Drug Control.

ERIC Educational Resources Information Center

Norland, Stephen; And Others

1996-01-01

Evaluations of school curricular drug control efforts show they are only modestly successful because they are based on an inaccurate theory of drug taking. Social control theory is suggested as a better model of drug taking and drug resistance. Asserts strong bonds to school decrease the likelihood of interaction with delinquent peers and thereby…

Anticipatory activity in anterior cingulate cortex can be independent of conflict and error likelihood.

PubMed

Aarts, Esther; Roelofs, Ardi; van Turennout, Miranda

2008-04-30

Previous studies have found no agreement on whether anticipatory activity in the anterior cingulate cortex (ACC) reflects upcoming conflict, error likelihood, or actual control adjustments. Using event-related functional magnetic resonance imaging, we investigated the nature of preparatory activity in the ACC. Informative cues told the participants whether an upcoming target would or would not involve conflict in a Stroop-like task. Uninformative cues provided no such information. Behavioral responses were faster after informative than after uninformative cues, indicating cue-based adjustments in control. ACC activity was larger after informative than uninformative cues, as would be expected if the ACC is involved in anticipatory control. Importantly, this activation in the ACC was observed for informative cues even when the information conveyed by the cue was that the upcoming target evokes no response conflict and has low error likelihood. This finding demonstrates that the ACC is involved in anticipatory control processes independent of upcoming response conflict or error likelihood. Moreover, the response of the ACC to the target stimuli was critically dependent on whether the cue was informative or not. ACC activity differed among target conditions after uninformative cues only, indicating ACC involvement in actual control adjustments. Together, these findings argue strongly for a role of the ACC in anticipatory control independent of anticipated conflict and error likelihood, and also show that such control can eliminate conflict-related ACC activity during target processing. Models of frontal cortex conflict-detection and conflict-resolution mechanisms require modification to include consideration of these anticipatory control properties of the ACC.

Estimation of parameters of dose volume models and their confidence limits

NASA Astrophysics Data System (ADS)

van Luijk, P.; Delvigne, T. C.; Schilstra, C.; Schippers, J. M.

2003-07-01

Predictions of the normal-tissue complication probability (NTCP) for the ranking of treatment plans are based on fits of dose-volume models to clinical and/or experimental data. In the literature several different fit methods are used. In this work frequently used methods and techniques to fit NTCP models to dose response data for establishing dose-volume effects, are discussed. The techniques are tested for their usability with dose-volume data and NTCP models. Different methods to estimate the confidence intervals of the model parameters are part of this study. From a critical-volume (CV) model with biologically realistic parameters a primary dataset was generated, serving as the reference for this study and describable by the NTCP model. The CV model was fitted to this dataset. From the resulting parameters and the CV model, 1000 secondary datasets were generated by Monte Carlo simulation. All secondary datasets were fitted to obtain 1000 parameter sets of the CV model. Thus the 'real' spread in fit results due to statistical spreading in the data is obtained and has been compared with estimates of the confidence intervals obtained by different methods applied to the primary dataset. The confidence limits of the parameters of one dataset were estimated using the methods, employing the covariance matrix, the jackknife method and directly from the likelihood landscape. These results were compared with the spread of the parameters, obtained from the secondary parameter sets. For the estimation of confidence intervals on NTCP predictions, three methods were tested. Firstly, propagation of errors using the covariance matrix was used. Secondly, the meaning of the width of a bundle of curves that resulted from parameters that were within the one standard deviation region in the likelihood space was investigated. Thirdly, many parameter sets and their likelihood were used to create a likelihood-weighted probability distribution of the NTCP. It is concluded that for the type of dose response data used here, only a full likelihood analysis will produce reliable results. The often-used approximations, such as the usage of the covariance matrix, produce inconsistent confidence limits on both the parameter sets and the resulting NTCP values.

Population genetics inference for longitudinally-sampled mutants under strong selection.

PubMed

Lacerda, Miguel; Seoighe, Cathal

2014-11-01

Longitudinal allele frequency data are becoming increasingly prevalent. Such samples permit statistical inference of the population genetics parameters that influence the fate of mutant variants. To infer these parameters by maximum likelihood, the mutant frequency is often assumed to evolve according to the Wright-Fisher model. For computational reasons, this discrete model is commonly approximated by a diffusion process that requires the assumption that the forces of natural selection and mutation are weak. This assumption is not always appropriate. For example, mutations that impart drug resistance in pathogens may evolve under strong selective pressure. Here, we present an alternative approximation to the mutant-frequency distribution that does not make any assumptions about the magnitude of selection or mutation and is much more computationally efficient than the standard diffusion approximation. Simulation studies are used to compare the performance of our method to that of the Wright-Fisher and Gaussian diffusion approximations. For large populations, our method is found to provide a much better approximation to the mutant-frequency distribution when selection is strong, while all three methods perform comparably when selection is weak. Importantly, maximum-likelihood estimates of the selection coefficient are severely attenuated when selection is strong under the two diffusion models, but not when our method is used. This is further demonstrated with an application to mutant-frequency data from an experimental study of bacteriophage evolution. We therefore recommend our method for estimating the selection coefficient when the effective population size is too large to utilize the discrete Wright-Fisher model. Copyright © 2014 by the Genetics Society of America.

Idea Project Final Report, A Prototype System For Real-Time Incident Likelihood Prediction

DOT National Transportation Integrated Search

1995-02-28

THIS INVESTIGATION WAS COMPLETED AS PART OF THE ITS-IDEA PROGRAM WHICH IS ONE OF THREE IDEA PROGRAMS MANAGED BY THE TRANSPORTATION RESEARCH BOARD (TRB) TO FOSTER INNOVATIONS IN SURFACE TRANSPORTATION. IT FOCUSES ON PRODUCTS AND RESULT FOR THE DEVELOP...

Using the Health Belief Model for Bulimia Prevention.

ERIC Educational Resources Information Center

Grodner, Michele

1991-01-01

Discusses application of the Health Belief Model to the prevention of bulimia, describing each model component. The article considers the individual's beliefs about bulimia and bulimic-like behaviors as a means of predicting the likelihood of behavior change to prevent clinically diagnosable bulimia. (SM)

Capturing and Displaying Uncertainty in the Common Tactical/Environmental Picture

DTIC Science & Technology

2003-09-30

multistatic active detection, and incorporated this characterization into a Bayesian track - before - detect system called, the Likelihood Ratio Tracker (LRT...prediction uncertainty in a track before detect system for multistatic active sonar. The approach has worked well on limited simulation data. IMPACT

Academic Underachievement: The Relationship between Motivation and Study Skills

ERIC Educational Resources Information Center

Melton, Rebecca Mindigo

2013-01-01

Research indicates that students underachieve in college settings, in spite of intellect and other abilities. This research tested the likelihood of self-efficacy for learning, conscientiousness, impulsivity, procrastination and temporal discounting to predict academic achievement in an online competency-based university. Undergraduate students (N…

Predicting Intended Unethical Behavior of Business Students

ERIC Educational Resources Information Center

Wilson, Barbara A.

2008-01-01

What is the likelihood that students would intend to act unethically in the work environment? The author measured business students' intended behavior for 4 hypothetical unethical situations by investigating the following determinants: belief toward the behavior, subjective norms (i.e., pressure), perceived behavioral control, perceived personal…

Should I Stay or Should I Go? Predicting Dating Relationship Stability from Four Aspects of Commitment

PubMed Central

Rhoades, Galena K.; Stanley, Scott M.; Markman, Howard J.

2010-01-01

Many have argued that it is important to examine different aspects of commitment in romantic relationships, but few studies have done so. Using a large, national sample of unmarried adults in relationships (N = 1184), this study examined four aspects of relationship commitment and their associations with relationship adjustment and stability. We examined dedication (i.e., interpersonal commitment) as well as three types of constraint commitment: perceived constraints (e.g., social pressure to stay together or difficulty of termination procedures, measured using Stanley and Markman’s (1992) Commitment Inventory), material constraints (e.g., signing a lease, owning a pet), and felt constraint (i.e., feeling trapped). Cross-sectionally, these four facets of commitment were associated in expected directions with relationship adjustment, as well as perceived likelihood of relationship termination and of marriage. Longitudinally, each facet uniquely predicted relationship stability. More dedication, more material and perceived constraints and less felt constraint were uniquely associated with a higher likelihood of staying together over an eight-month period. PMID:20954764

Meta-Analysis and Systematic Review to Assess the Role of Soluble FMS-Like Tyrosine Kinase-1 and Placenta Growth Factor Ratio in Prediction of Preeclampsia: The SaPPPhirE Study.

PubMed

Agrawal, Swati; Cerdeira, Ana Sofia; Redman, Christopher; Vatish, Manu

2018-02-01

Preeclampsia is a major cause of morbidity and mortality worldwide. Numerous candidate biomarkers have been proposed for diagnosis and prediction of preeclampsia. Measurement of maternal circulating angiogenesis biomarker as the ratio of sFlt-1 (soluble FMS-like tyrosine kinase-1; an antiangiogenic factor)/PlGF (placental growth factor; an angiogenic factor) reflects the antiangiogenic balance that characterizes incipient or overt preeclampsia. The ratio increases before the onset of the disease and thus may help in predicting preeclampsia. We conducted a meta-analysis to explore the predictive accuracy of sFlt-1/PlGF ratio in preeclampsia. We included 15 studies with 534 cases with preeclampsia and 19 587 controls. The ratio has a pooled sensitivity of 80% (95% confidence interval, 0.68-0.88), specificity of 92% (95% confidence interval, 0.87-0.96), positive likelihood ratio of 10.5 (95% confidence interval, 6.2-18.0), and a negative likelihood ratio of 0.22 (95% confidence interval, 0.13-0.35) in predicting preeclampsia in both high- and low-risk patients. Most of the studies have not made a distinction between early- and late-onset disease, and therefore, the analysis for it could not be done. It can prove to be a valuable screening tool for preeclampsia and may also help in decision-making, treatment stratification, and better resource allocation. © 2017 American Heart Association, Inc.

Serum Adiponectin, Vitamin D, and Alpha-Fetoprotein in Children with Chronic Hepatitis C: Can They Predict Treatment Response?

PubMed Central

Khedr, Mohamed Ahmed; Sira, Ahmad Mohamed; Saber, Magdy Anwar; Raia, Gamal Yousef

2015-01-01

Background & Aims. The currently available treatment for chronic hepatitis C (CHC) in children is costly and with much toxicity. So, predicting the likelihood of response before starting therapy is important. Methods. Serum adiponectin, vitamin D, and alpha-fetoprotein (AFP) were measured before starting pegylated-interferon/ribavirin therapy for 50 children with CHC. Another 21 healthy children were recruited as controls. Results. Serum adiponectin, vitamin D, and AFP were higher in the CHC group than healthy controls (p < 0.0001, p = 0.071, and p = 0.87, resp.). In univariate analysis, serum adiponectin was significantly higher in responders than nonresponders (p < 0.0001) and at a cutoff value ≥8.04 ng/mL it can predict treatment response by 77.8% sensitivity and 92.9% specificity, while both AFP and viremia were significantly lower in responders than nonresponders, p < 0.0001 and p = 0.0003, respectively, and at cutoff values ≤3.265 ng/mL and ≤235,384 IU/mL, respectively, they can predict treatment response with a sensitivity of 83.3% for both and specificity of 85.7% and 78.6%, respectively. In multivariate analysis, adiponectin was found to be the only independent predictor of treatment response (p = 0.044). Conclusions. The pretreatment serum level of adiponectin can predict the likelihood of treatment response, thus avoiding toxicities for those unlikely to respond to therapy. PMID:26640716

Serum Adiponectin, Vitamin D, and Alpha-Fetoprotein in Children with Chronic Hepatitis C: Can They Predict Treatment Response?

PubMed

Khedr, Mohamed Ahmed; Sira, Ahmad Mohamed; Saber, Magdy Anwar; Raia, Gamal Yousef

2015-01-01

Background & Aims. The currently available treatment for chronic hepatitis C (CHC) in children is costly and with much toxicity. So, predicting the likelihood of response before starting therapy is important. Methods. Serum adiponectin, vitamin D, and alpha-fetoprotein (AFP) were measured before starting pegylated-interferon/ribavirin therapy for 50 children with CHC. Another 21 healthy children were recruited as controls. Results. Serum adiponectin, vitamin D, and AFP were higher in the CHC group than healthy controls (p < 0.0001, p = 0.071, and p = 0.87, resp.). In univariate analysis, serum adiponectin was significantly higher in responders than nonresponders (p < 0.0001) and at a cutoff value ≥8.04 ng/mL it can predict treatment response by 77.8% sensitivity and 92.9% specificity, while both AFP and viremia were significantly lower in responders than nonresponders, p < 0.0001 and p = 0.0003, respectively, and at cutoff values ≤3.265 ng/mL and ≤235,384 IU/mL, respectively, they can predict treatment response with a sensitivity of 83.3% for both and specificity of 85.7% and 78.6%, respectively. In multivariate analysis, adiponectin was found to be the only independent predictor of treatment response (p = 0.044). Conclusions. The pretreatment serum level of adiponectin can predict the likelihood of treatment response, thus avoiding toxicities for those unlikely to respond to therapy.

Impact of the spread of mass education on married women's experience with domestic violence.

PubMed

Ghimire, Dirgha J; Axinn, William G; Smith-Greenaway, Emily

2015-11-01

This paper investigates the association between mass education and married women's experience with domestic violence in rural Nepal. Previous research on domestic violence in South Asian societies emphasizes patriarchal ideology and the widespread subordinate status of women within their communities and families. The recent spread of mass education is likely to shift these gendered dynamics, thereby lowering women's likelihood of experiencing domestic violence. Using data from 1775 currently married women from the Chitwan Valley Family Study in Nepal, we provide a thorough analysis of how the spread of mass education is associated with domestic violence among married women. The results show that women's childhood access to school, their parents' schooling, their own schooling, and their husbands' schooling are each associated with their lower likelihood of experiencing domestic violence. Indeed, husbands' education has a particularly strong, inverse association with women's likelihood of experiencing domestic violence. These associations suggest that the proliferation of mass education will lead to a marked decline in women's experience with domestic violence in Nepal. Copyright © 2015 Elsevier Inc. All rights reserved.

Impact of the Spread of Mass Education on Married Women’s Experience with Domestic Violence

PubMed Central

Ghimire, Dirgha J.; Axinn, William G.; Smith-Greenaway, Emily

2015-01-01

This paper investigates the association between mass education and married women’s experience with domestic violence in rural Nepal. Previous research on domestic violence in South Asian societies emphasizes patriarchal ideology and the widespread subordinate status of women within their communities and families. The recent spread of mass education is likely to shift these gendered dynamics, thereby lowering women’s likelihood of experiencing domestic violence. Using data from 1,775 currently married women from the Chitwan Valley Family Study in Nepal, we provide a thorough analysis of how the spread of mass education is associated with domestic violence among married women. The results show that women’s childhood access to school, their parents’ schooling, their own schooling, and their husbands’ schooling are each associated with their lower likelihood of experiencing domestic violence. Indeed, husbands’ education has a particularly strong, inverse association with women’s likelihood of experiencing domestic violence. These associations suggest that the proliferation of mass education will lead to a marked decline in women’s experience with domestic violence in Nepal. PMID:26463551

Unified neural field theory of brain dynamics underlying oscillations in Parkinson's disease and generalized epilepsies.

PubMed

Müller, E J; van Albada, S J; Kim, J W; Robinson, P A

2017-09-07

The mechanisms underlying pathologically synchronized neural oscillations in Parkinson's disease (PD) and generalized epilepsies are explored in parallel via a physiologically-based neural field model of the corticothalamic-basal ganglia (CTBG) system. The basal ganglia (BG) are approximated as a single effective population and their roles in the modulation of oscillatory dynamics of the corticothalamic (CT) system and vice versa are analyzed. In addition to normal EEG rhythms, enhanced activity around 4 Hz and 20 Hz exists in the model, consistent with the characteristic frequencies observed in PD. These rhythms result from resonances in loops formed between the BG and CT populations, analogous to those that underlie epileptic oscillations in a previous CT model, and which are still present in the combined CTBG system. Dopamine depletion is argued to weaken the dampening of these loop resonances in PD, and network connections then explain the significant coherence observed between BG, thalamic, and cortical population activity around 4-8 Hz and 20 Hz. Parallels between the afferent and efferent connection sites of the thalamic reticular nucleus (TRN) and BG predict low dopamine to correspond to a reduced likelihood of tonic-clonic (grand mal) seizures, which agrees with experimental findings. Furthermore, the model predicts an increased likelihood of absence (petit mal) seizure resulting from pathologically low dopamine levels in accordance with experimental observations. Suppression of absence seizure activity is demonstrated when afferent and efferent BG connections to the CT system are strengthened, which is consistent with other CTBG modeling studies. The BG are demonstrated to have a suppressive effect on activity of the CTBG system near tonic-clonic seizure states, which provides insight into the reported efficacy of current treatments in BG circuits. Sleep states of the TRN are also found to suppress pathological PD activity in accordance with observations. Overall, the findings demonstrate strong parallels between coherent oscillations in generalized epilepsies and PD, and provide insights into possible comorbidities. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multifactorial risk index for prediction of intraoperative blood transfusion in endovascular aneurysm repair.

PubMed

Mahmood, Eitezaz; Matyal, Robina; Mueller, Ariel; Mahmood, Feroze; Tung, Avery; Montealegre-Gallegos, Mario; Schermerhorn, Marc; Shahul, Sajid

2018-03-01

In some institutions, the current blood ordering practice does not discriminate minimally invasive endovascular aneurysm repair (EVAR) from open procedures, with consequent increasing costs and likelihood of blood product wastage for EVARs. This limitation in practice can possibly be addressed with the development of a reliable prediction model for transfusion risk in EVAR patients. We used the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) database to create a model for prediction of intraoperative blood transfusion occurrence in patients undergoing EVAR. Afterward, we tested our predictive model on the Vascular Study Group of New England (VSGNE) database. We used the ACS NSQIP database for patients who underwent EVAR from 2011 to 2013 (N = 4709) as our derivation set for identifying a risk index for predicting intraoperative blood transfusion. We then developed a clinical risk score and validated this model using patients who underwent EVAR from 2003 to 2014 in the VSGNE database (N = 4478). The transfusion rates were 8.4% and 6.1% for the ACS NSQIP (derivation set) and VSGNE (validation) databases, respectively. Hemoglobin concentration, American Society of Anesthesiologists class, age, and aneurysm diameter predicted blood transfusion in the derivation set. When it was applied on the validation set, our risk index demonstrated good discrimination in both the derivation and validation set (C statistic = 0.73 and 0.70, respectively) and calibration using the Hosmer-Lemeshow test (P = .27 and 0.31) for both data sets. We developed and validated a risk index for predicting the likelihood of intraoperative blood transfusion in EVAR patients. Implementation of this index may facilitate the blood management strategies specific for EVAR. Copyright © 2017 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Maximum likelihood Bayesian model averaging and its predictive analysis for groundwater reactive transport models

USGS Publications Warehouse

Curtis, Gary P.; Lu, Dan; Ye, Ming

2015-01-01

While Bayesian model averaging (BMA) has been widely used in groundwater modeling, it is infrequently applied to groundwater reactive transport modeling because of multiple sources of uncertainty in the coupled hydrogeochemical processes and because of the long execution time of each model run. To resolve these problems, this study analyzed different levels of uncertainty in a hierarchical way, and used the maximum likelihood version of BMA, i.e., MLBMA, to improve the computational efficiency. This study demonstrates the applicability of MLBMA to groundwater reactive transport modeling in a synthetic case in which twenty-seven reactive transport models were designed to predict the reactive transport of hexavalent uranium (U(VI)) based on observations at a former uranium mill site near Naturita, CO. These reactive transport models contain three uncertain model components, i.e., parameterization of hydraulic conductivity, configuration of model boundary, and surface complexation reactions that simulate U(VI) adsorption. These uncertain model components were aggregated into the alternative models by integrating a hierarchical structure into MLBMA. The modeling results of the individual models and MLBMA were analyzed to investigate their predictive performance. The predictive logscore results show that MLBMA generally outperforms the best model, suggesting that using MLBMA is a sound strategy to achieve more robust model predictions relative to a single model. MLBMA works best when the alternative models are structurally distinct and have diverse model predictions. When correlation in model structure exists, two strategies were used to improve predictive performance by retaining structurally distinct models or assigning smaller prior model probabilities to correlated models. Since the synthetic models were designed using data from the Naturita site, the results of this study are expected to provide guidance for real-world modeling. Limitations of applying MLBMA to the synthetic study and future real-world modeling are discussed.

CURB-65 Performance Among Admitted and Discharged Emergency Department Patients With Community-acquired Pneumonia.

PubMed

Sharp, Adam L; Jones, Jason P; Wu, Ivan; Huynh, Dan; Kocher, Keith E; Shah, Nirav R; Gould, Michael K

2016-04-01

Pneumonia severity tools were primarily developed in cohorts of hospitalized patients, limiting their applicability to the emergency department (ED). We describe current community ED admission practices and examine the accuracy of the CURB-65 to predict 30-day mortality for patients, either discharged or admitted with community-acquired pneumonia (CAP). A retrospective, observational study of adult CAP encounters in 14 community EDs within an integrated healthcare system. We calculated CURB-65 scores for all encounters and described the use of hospitalization, stratified by each score (0-5). We then used each score as a cutoff to calculate sensitivity, specificity, positive predictive value, negative predictive value (NPV), positive likelihood ratios, and negative likelihood ratios for predicting 30-day mortality. The sample included 21,183 ED encounters for CAP (7,952 discharged and 13,231 admitted). The C-statistic describing the accuracy of CURB-65 for predicting 30-day mortality in the full sample was 0.761 (95% confidence interval [CI], 0.747-0.774). The C-statistic was 0.864 (95% CI, 0.821-0.906) among patients discharged from the ED compared with 0.689 (95% CI, 0.672-0.705) among patients who were admitted. Among all ED encounters a CURB-65 threshold of ≥1 was 92.8% sensitive and 38.0% specific for predicting mortality, with a 99.9% NPV. Among all encounters, 62.5% were admitted, including 36.2% of those at lowest risk (CURB-65 = 0). CURB-65 had very good accuracy for predicting 30-day mortality among patients discharged from the ED. This severity tool may help ED providers risk stratify patients to assist with disposition decisions and identify unwarranted variation in patient care. © 2016 by the Society for Academic Emergency Medicine.

Exact likelihood evaluations and foreground marginalization in low resolution WMAP data

NASA Astrophysics Data System (ADS)

Slosar, Anže; Seljak, Uroš; Makarov, Alexey

2004-06-01

The large scale anisotropies of Wilkinson Microwave Anisotropy Probe (WMAP) data have attracted a lot of attention and have been a source of controversy, with many favorite cosmological models being apparently disfavored by the power spectrum estimates at low l. All the existing analyses of theoretical models are based on approximations for the likelihood function, which are likely to be inaccurate on large scales. Here we present exact evaluations of the likelihood of the low multipoles by direct inversion of the theoretical covariance matrix for low resolution WMAP maps. We project out the unwanted galactic contaminants using the WMAP derived maps of these foregrounds. This improves over the template based foreground subtraction used in the original analysis, which can remove some of the cosmological signal and may lead to a suppression of power. As a result we find an increase in power at low multipoles. For the quadrupole the maximum likelihood values are rather uncertain and vary between 140 and 220 μK2. On the other hand, the probability distribution away from the peak is robust and, assuming a uniform prior between 0 and 2000 μK2, the probability of having the true value above 1200 μK2 (as predicted by the simplest cold dark matter model with a cosmological constant) is 10%, a factor of 2.5 higher than predicted by the WMAP likelihood code. We do not find the correlation function to be unusual beyond the low quadrupole value. We develop a fast likelihood evaluation routine that can be used instead of WMAP routines for low l values. We apply it to the Markov chain Monte Carlo analysis to compare the cosmological parameters between the two cases. The new analysis of WMAP either alone or jointly with the Sloan Digital Sky Survey (SDSS) and the Very Small Array (VSA) data reduces the evidence for running to less than 1σ, giving αs=-0.022±0.033 for the combined case. The new analysis prefers about a 1σ lower value of Ωm, a consequence of an increased integrated Sachs-Wolfe (ISW) effect contribution required by the increase in the spectrum at low l. These results suggest that the details of foreground removal and full likelihood analysis are important for parameter estimation from the WMAP data. They are robust in the sense that they do not change significantly with frequency, mask, or details of foreground template marginalization. The marginalization approach presented here is the most conservative method to remove the foregrounds and should be particularly useful in the analysis of polarization, where foreground contamination may be much more severe.

Predicting likelihood of seeking help through the employee assistance program among salaried and union hourly employees.

PubMed

Delaney, W; Grube, J W; Ames, G M

1998-03-01

This research investigated belief, social support and background predictors of employee likelihood to use an Employee Assistance Program (EAP) for a drinking problem. An anonymous cross-sectional survey was administered in the home. Bivariate analyses and simultaneous equations path analysis were used to explore a model of EAP use. Survey and ethnographic research were conducted in a unionized heavy machinery manufacturing plant in the central states of the United States. A random sample of 852 hourly and salaried employees was selected. In addition to background variables, measures included: likelihood of going to an EAP for a drinking problem, belief the EAP can help, social support for the EAP from co-workers/others, belief that EAP use will harm employment, and supervisor encourages the EAP for potential drinking problems. Belief in EAP efficacy directly increased the likelihood of going to an EAP. Greater perceived social support and supervisor encouragement increased the likelihood of going to an EAP both directly and indirectly through perceived EAP efficacy. Black and union hourly employees were more likely to say they would use an EAP. Males and those who reported drinking during working hours were less likely to say they would use an EAP for a drinking problem. EAP beliefs and social support have significant effects on likelihood to go to an EAP for a drinking problem. EAPs may wish to focus their efforts on creating an environment where there is social support from coworkers and encouragement from supervisors for using EAP services. Union networks and team members have an important role to play in addition to conventional supervisor intervention.

A long-term earthquake rate model for the central and eastern United States from smoothed seismicity

USGS Publications Warehouse

Moschetti, Morgan P.

2015-01-01

I present a long-term earthquake rate model for the central and eastern United States from adaptive smoothed seismicity. By employing pseudoprospective likelihood testing (L-test), I examined the effects of fixed and adaptive smoothing methods and the effects of catalog duration and composition on the ability of the models to forecast the spatial distribution of recent earthquakes. To stabilize the adaptive smoothing method for regions of low seismicity, I introduced minor modifications to the way that the adaptive smoothing distances are calculated. Across all smoothed seismicity models, the use of adaptive smoothing and the use of earthquakes from the recent part of the catalog optimizes the likelihood for tests with M≥2.7 and M≥4.0 earthquake catalogs. The smoothed seismicity models optimized by likelihood testing with M≥2.7 catalogs also produce the highest likelihood values for M≥4.0 likelihood testing, thus substantiating the hypothesis that the locations of moderate-size earthquakes can be forecast by the locations of smaller earthquakes. The likelihood test does not, however, maximize the fraction of earthquakes that are better forecast than a seismicity rate model with uniform rates in all cells. In this regard, fixed smoothing models perform better than adaptive smoothing models. The preferred model of this study is the adaptive smoothed seismicity model, based on its ability to maximize the joint likelihood of predicting the locations of recent small-to-moderate-size earthquakes across eastern North America. The preferred rate model delineates 12 regions where the annual rate of M≥5 earthquakes exceeds 2×10−3. Although these seismic regions have been previously recognized, the preferred forecasts are more spatially concentrated than the rates from fixed smoothed seismicity models, with rate increases of up to a factor of 10 near clusters of high seismic activity.

Understanding multiple levels of norms about teen pregnancy and their relationships to teens' sexual behaviors.

PubMed

Mollborn, Stefanie; Domingue, Benjamin W; Boardman, Jason D

2014-06-01

Researchers seeking to understand teen sexual behaviors often turn to age norms, but they are difficult to measure quantitatively. Previous work has usually inferred norms from behavioral patterns or measured group-level norms at the individual level, ignoring multiple reference groups. Capitalizing on the multilevel design of the Add Health survey, we measure teen pregnancy norms perceived by teenagers, as well as average norms at the school and peer network levels. School norms predict boys' perceived norms, while peer network norms predict girls' perceived norms. Peer network and individually perceived norms against teen pregnancy independently and negatively predict teens' likelihood of sexual intercourse. Perceived norms against pregnancy predict increased likelihood of contraception among sexually experienced girls, but sexually experienced boys' contraceptive behavior is more complicated: When both the boy and his peers or school have stronger norms against teen pregnancy he is more likely to contracept, and in the absence of school or peer norms against pregnancy, boys who are embarrassed are less likely to contracept. We conclude that: (1) patterns of behavior cannot adequately operationalize teen pregnancy norms, (2) norms are not simply linked to behaviors through individual perceptions, and (3) norms at different levels can operate independently of each other, interactively, or in opposition. This evidence creates space for conceptualizations of agency, conflict, and change that can lead to progress in understanding age norms and sexual behaviors.

Understanding multiple levels of norms about teen pregnancy and their relationships to teens’ sexual behaviors

PubMed Central

Mollborn, Stefanie; Domingue, Benjamin W.; Boardman, Jason D.

2014-01-01

Researchers seeking to understand teen sexual behaviors often turn to age norms, but they are difficult to measure quantitatively. Previous work has usually inferred norms from behavioral patterns or measured group-level norms at the individual level, ignoring multiple reference groups. Capitalizing on the multilevel design of the Add Health survey, we measure teen pregnancy norms perceived by teenagers, as well as average norms at the school and peer network levels. School norms predict boys’ perceived norms, while peer network norms predict girls’ perceived norms. Peer network and individually perceived norms against teen pregnancy independently and negatively predict teens’ likelihood of sexual intercourse. Perceived norms against pregnancy predict increased likelihood of contraception among sexually experienced girls, but sexually experienced boys’ contraceptive behavior is more complicated: When both the boy and his peers or school have stronger norms against teen pregnancy he is more likely to contracept, and in the absence of school or peer norms against pregnancy, boys who are embarrassed are less likely to contracept. We conclude that: (1) patterns of behavior cannot adequately operationalize teen pregnancy norms, (2) norms are not simply linked to behaviors through individual perceptions, and (3) norms at different levels can operate independently of each other, interactively, or in opposition. This evidence creates space for conceptualizations of agency, conflict, and change that can lead to progress in understanding age norms and sexual behaviors. PMID:25104920

Small-scale deflagration cylinder test with velocimetry wall-motion diagnostics

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

Hooks, Daniel E; Hill, Larry G; Pierce, Timothy H

Predicting the likelihood and effects of outcomes resultant from thermal initiation of explosives remains a significant challenge. For certain explosive formulations, the general outcome can be broadly predicted given knowledge of certain conditions. However, there remain unexplained violent events, and increased statistical understanding of outcomes as a function of many variables, or 'violence categorization,' is needed. Additionally, the development of an equation of state equivalent for deflagration would be very useful in predicting possible detailed event consequences using traditional hydrodynamic detonation moders. For violence categorization, it is desirable that testing be efficient, such that it is possible to statistically definemore » outcomes reliant on the processes of initiation of deflagration, steady state deflagration, and deflagration to detonation transitions. If the test simultaneously acquires information to inform models of violent deflagration events, overall predictive capabilities for event likelihood and consequence might improve remarkably. In this paper we describe an economical scaled deflagration cylinder test. The cyclotetramethylene tetranitramine (HMX) based explosive formu1lation PBX 9501 was tested using different temperature profiles in a thick-walled copper cylindrical confiner. This test is a scaled version of a recently demonstrated deflagration cylinder test, and is similar to several other thermal explosion tests. The primary difference is the passive velocimetry diagnostic, which enables measurement of confinement vessel wall velocities at failure, regardless of the timing and location of ignition.« less

Crystal Structure Prediction via Deep Learning.

PubMed

Ryan, Kevin; Lengyel, Jeff; Shatruk, Michael

2018-06-06

We demonstrate the application of deep neural networks as a machine-learning tool for the analysis of a large collection of crystallographic data contained in the crystal structure repositories. Using input data in the form of multi-perspective atomic fingerprints, which describe coordination topology around unique crystallographic sites, we show that the neural-network model can be trained to effectively distinguish chemical elements based on the topology of their crystallographic environment. The model also identifies structurally similar atomic sites in the entire dataset of ~50000 crystal structures, essentially uncovering trends that reflect the periodic table of elements. The trained model was used to analyze templates derived from the known binary and ternary crystal structures in order to predict the likelihood to form new compounds that could be generated by placing elements into these structural templates in combinatorial fashion. Statistical analysis of predictive performance of the neural-network model, which was applied to a test set of structures never seen by the model during training, indicates its ability to predict known elemental compositions with a high likelihood of success. In ~30% of cases, the known compositions were found among top-10 most likely candidates proposed by the model. These results suggest that the approach developed in this work can be used to effectively guide the synthetic efforts in the discovery of new materials, especially in the case of systems composed of 3 or more chemical elements.

An Examination of Behavioral Responses to Stereotypical Deceptive Displays.

ERIC Educational Resources Information Center

Huddleston, Bill M.

A study investigated whether receivers who detect senders behaving deceitfully will automatically become more resistent to the message being presented. By developing predictions derived from the Elaboration Likelihood Model (ELM), the study hypothesized that only noninvolved receivers would respond negatively to deceptive nonverbal cues in a…

The Forgotten 90%: Adult Nonparticipation in Education

ERIC Educational Resources Information Center

Patterson, Margaret Becker

2018-01-01

Despite a highly developed U.S. adult education system, 90% of adults aged 20 years and older considered the least educated did not participate recently in formal or nonformal education. What are nonparticipants' characteristics, learning backgrounds, and skill levels? What predicts their likelihood of "not" participating in recent…

Predicting Significant Reductions in Instructional Expenditures by School Districts

ERIC Educational Resources Information Center

Trussel, John M.; Patrick, Patricia A.

2012-01-01

This article uses survival analysis to investigate the symptoms of fiscal distress that can lead to significant reductions in instructional expenditures by independent public school districts in the United States. We hypothesize that the likelihood of significant reductions in instructional expenditures is positively correlated with revenue…

Autistic traits, but not schizotypy, predict increased weighting of sensory information in Bayesian visual integration.

PubMed

Karvelis, Povilas; Seitz, Aaron R; Lawrie, Stephen M; Seriès, Peggy

2018-05-14

Recent theories propose that schizophrenia/schizotypy and autistic spectrum disorder are related to impairments in Bayesian inference that is, how the brain integrates sensory information (likelihoods) with prior knowledge. However existing accounts fail to clarify: (i) how proposed theories differ in accounts of ASD vs. schizophrenia and (ii) whether the impairments result from weaker priors or enhanced likelihoods. Here, we directly address these issues by characterizing how 91 healthy participants, scored for autistic and schizotypal traits, implicitly learned and combined priors with sensory information. This was accomplished through a visual statistical learning paradigm designed to quantitatively assess variations in individuals' likelihoods and priors. The acquisition of the priors was found to be intact along both traits spectra. However, autistic traits were associated with more veridical perception and weaker influence of expectations. Bayesian modeling revealed that this was due, not to weaker prior expectations, but to more precise sensory representations. © 2018, Karvelis et al.

Two models for evaluating landslide hazards

USGS Publications Warehouse

Davis, J.C.; Chung, C.-J.; Ohlmacher, G.C.

2006-01-01

Two alternative procedures for estimating landslide hazards were evaluated using data on topographic digital elevation models (DEMs) and bedrock lithologies in an area adjacent to the Missouri River in Atchison County, Kansas, USA. The two procedures are based on the likelihood ratio model but utilize different assumptions. The empirical likelihood ratio model is based on non-parametric empirical univariate frequency distribution functions under an assumption of conditional independence while the multivariate logistic discriminant model assumes that likelihood ratios can be expressed in terms of logistic functions. The relative hazards of occurrence of landslides were estimated by an empirical likelihood ratio model and by multivariate logistic discriminant analysis. Predictor variables consisted of grids containing topographic elevations, slope angles, and slope aspects calculated from a 30-m DEM. An integer grid of coded bedrock lithologies taken from digitized geologic maps was also used as a predictor variable. Both statistical models yield relative estimates in the form of the proportion of total map area predicted to already contain or to be the site of future landslides. The stabilities of estimates were checked by cross-validation of results from random subsamples, using each of the two procedures. Cell-by-cell comparisons of hazard maps made by the two models show that the two sets of estimates are virtually identical. This suggests that the empirical likelihood ratio and the logistic discriminant analysis models are robust with respect to the conditional independent assumption and the logistic function assumption, respectively, and that either model can be used successfully to evaluate landslide hazards. ?? 2006.

Predicting the likelihood of live birth for elective oocyte cryopreservation: a counseling tool for physicians and patients.

PubMed

Goldman, R H; Racowsky, C; Farland, L V; Munné, S; Ribustello, L; Fox, J H

2017-04-01

Can a counseling tool be developed for women desiring elective oocyte cryopreservation to predict the likelihood of live birth based on age and number of oocytes frozen? Using data from ICSI cycles of a population of women with uncompromised ovarian reserve, an evidence-based counseling tool was created to guide women and their physicians regarding the number of oocytes needed to freeze for future family-building goals. Elective oocyte cryopreservation is increasing in popularity as more women delay family building. By undertaking elective oocyte freezing at a younger age, women hope to optimize their likelihood of successful live birth(s) using their thawed oocytes at a future date. Questions often arise in clinical practice regarding the number of cryopreserved oocytes sufficient to achieve live birth(s) and whether or not additional stimulation cycles are likely to result in a meaningful increase in the likelihood of live birth. As relatively few women who have electively cryopreserved oocytes have returned to use them, available data for counseling patients wishing to undergo fertility preservation are limited. A model was developed to determine the proportion of mature oocytes that fertilize and then form blastocysts as a function of age, using women with presumably normal ovarian reserve based on standard testing who underwent ICSI cycles in our program from January, 2011 through March, 2015 (n = 520). These included couples diagnosed exclusively with male-factor and/or tubal-factor infertility, as well as cycles utilizing egg donation. Age-specific probabilities of euploidy were estimated from 14 500 PGS embryo results from an external testing laboratory. Assuming survival of thawed oocytes at 95% for women <36 y and for egg donors, and 85% for women ≥36 y, and 60% live birth rate per transferred euploid blastocyst, probabilities of having at least one, two or three live birth(s) were calculated. First fresh male-factor and/or tubal-factor only autologous ICSI cycles (n = 466) were analyzed using Poisson regression to calculate the probability that a mature oocyte will become a blastocyst based on age. Egg donation cycles (n = 54) were analyzed and incorporated into the model separately. The proportion of blastocysts expected to be euploid was determined using PGS results of embryos analyzed via array comparative genomic hybridization. A counseling tool was developed to predict the likelihood of live birth, based on individual patient age and number of mature oocytes. This study provides an evidence-based model to predict the probability of a woman having at least one, two or three live birth(s) based on her age at egg retrieval and the number of mature oocytes frozen. The model is derived from a surrogate population of ICSI patients with uncompromised ovarian reserve. A user-friendly counseling tool was designed using the model to help guide physicians and patients. The data used to develop the prediction model are, of necessity, retrospective and not based on patients who have returned to use their cryopreserved oocytes. The assumptions used to create the model, albeit reasonable and data-driven, vary by study and will likely vary by center. Centers are therefore encouraged to consider their own blastocyst formation and thaw survival rates when counseling patients. Our model will provide a counseling resource that may help inform women desiring elective fertility preservation regarding their likelihood of live birth(s), how many cycles to undergo, and when additional cycles would bring diminishing returns. None. Not applicable. © The Author 2017. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Cancer predisposition syndromes: lessons for truly precision medicine.

PubMed

Glaire, Mark A; Brown, Matthew; Church, David N; Tomlinson, Ian

2017-01-01

Cancer predisposition syndromes are typically uncommon, monogenic, high-penetrance disorders. Despite their rarity, they have proven to be highly clinically relevant in directing cancer prevention strategies. As such, they share notable similarities with an expanding class of low-frequency somatic mutations that are associated with a striking prognostic or predictive effect in the tumours in which they occur. In this review, we highlight these commonalities, with particular reference to mutations in the proofreading domain of replicative DNA polymerases. These molecular phenotypes may occur as either germline or somatic events, and in the latter case, have been shown to confer a favourable prognosis and potential increased benefit from immune checkpoint inhibition. We note that incorporation of these variants into clinical management algorithms will help refine patient management, and that this will be further improved by the inclusion of other germline variants, such as those that determine the likelihood of benefit or toxicity from anti-neoplastic therapy. Finally, we propose that such integrated patient and tumour profiling will be essential if we are to deliver truly precision medicine for cancer patients, but in a similar way to rare germline mutations, we must ensure that we identify and utilize rare somatic mutations with strong predictive and prognostic effects. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

The Impacts of Climate-Induced Drought on Biogeochemical Cycles

NASA Astrophysics Data System (ADS)

Peng, C.

2014-12-01

Terrestrial ecosystems and, in particular, forests exert strong controls on the global biogeochemical cycles and influence regional hydrology and climatology directly through water and surface energy budgets. Recent studies indicated that forest mortality caused by rising temperature and drought from around the world have unexpectedly increased in the past decade and they collectively illustrate the vulnerability of many forested ecosystems to rapid increases in tree mortality due to warmer temperatures and more severe drought. Persistent changes in tree mortality rates can alter forest structure, composition, and ecosystem services (such as albedo and carbon sequestration). Quantifying potential impacts of tree mortality on ecosystem processes requires research into mortality effects on carbon, energy, and water budgets at both site and regional levels. Despite recent progress, the uncertainty around mortality responses still limits our ability to predict the likelihood and anticipate the impacts of tree die-off. Studies are needed that explore tree death physiology for a wide variety of functional types, connect patterns of mortality with climate events, and quantify the impacts on carbon, energy, and water flux. In this presentation, I will highlight recent research progress, and identify key research needs and future challenges to predict the consequence and impacts of drought-induced large-scale forest mortality on biogeochemical cycles. I will focus on three main forest ecosystems (tropic rainforest in Amazon, temperate forest in Western USA, and boreal forest in Canada) as detailed case studies.

Beliefs and behavioural intentions towards pharmacotherapy for stuttering: A survey of adults who stutter.

PubMed

McGroarty, Allan; McCartan, Rebecca

Although considerable efforts have been made to investigate the effectiveness of pharmacological treatments for stuttering, little is known about how the stuttering community perceives these treatments. This study aimed to assess and quantify beliefs regarding pharmacotherapy for adults who stutter and to establish whether behavioural intentions to undertake treatment were related to these beliefs. An adapted version of the Beliefs about Medicine Questionnaire was completed by adults who stutter. Participants also reported perceptions of their stuttering including its overall impact, ratings of previous speech therapy, and behavioural intentions to initiate pharmacotherapy and speech therapy in future. Necessity and concern beliefs were distributed widely across the sample and in a pattern indicating a relatively balanced perception of the benefits and costs of medication prescribed specifically for stuttering. Of the study's measures, the necessity-concerns differential most strongly predicted the behavioural intention to initiate pharmacotherapy. The overall impact of stuttering predicted intentions to seek both pharmacotherapy and speech therapy. Participants reported the likelihood of pursuing pharmacotherapy and speech therapy in equal measure. The theoretical model of medication representations appears to be a useful framework for understanding the beliefs of adults who stutter towards the medical treatment of their disorder. The findings of this study may be of interest to clinicians and researchers working in the field of stuttering treatment and to people who stutter considering pharmacotherapy. Copyright © 2018 Elsevier Inc. All rights reserved.

Synchronization in Random Pulse Oscillator Networks

NASA Astrophysics Data System (ADS)

Brown, Kevin; Hermundstad, Ann

Motivated by synchronization phenomena in neural systems, we study synchronization of random networks of coupled pulse oscillators. We begin by considering binomial random networks whose nodes have intrinsic linear dynamics. We quantify order in the network spiking dynamics using a new measure: the normalized Lev-Zimpel complexity (LZC) of the nodes' spike trains. Starting from a globally-synchronized state, we see two broad classes of behaviors. In one (''temporally random''), the LZC is high and nodes spike independently with no coherent pattern. In another (''temporally regular''), the network does not globally synchronize but instead forms coherent, repeating population firing patterns with low LZC. No topological feature of the network reliably predicts whether an individual network will show temporally random or regular behavior; however, we find evidence that degree heterogeneity in binomial networks has a strong effect on the resulting state. To confirm these findings, we generate random networks with independently-adjustable degree mean and variance. We find that the likelihood of temporally-random behavior increases as degree variance increases. Our results indicate the subtle and complex relationship between network structure and dynamics.

Ensemble classification for identifying neighbourhood sources of fugitive dust and associations with observed PM10

NASA Astrophysics Data System (ADS)

Khuluse-Makhanya, Sibusisiwe; Stein, Alfred; Breytenbach, André; Gxumisa, Athi; Dudeni-Tlhone, Nontembeko; Debba, Pravesh

2017-10-01

In urban areas the deterioration of air quality as a result of fugitive dust receives less attention than the more prominent traffic and industrial emissions. We assessed whether fugitive dust emission sources in the neighbourhood of an air quality monitor are predictors of ambient PM10 concentrations on days characterized by strong local winds. An ensemble maximum likelihood method is developed for land cover mapping in the vicinity of an air quality station using SPOT 6 multi-spectral images. The ensemble maximum likelihood classifier is developed through multiple training iterations for improved accuracy of the bare soil class. Five primary land cover classes are considered, namely built-up areas, vegetation, bare soil, water and 'mixed bare soil' which denotes areas where soil is mixed with either vegetation or synthetic materials. Preliminary validation of the ensemble classifier for the bare soil class results in an accuracy range of 65-98%. Final validation of all classes results in an overall accuracy of 78%. Next, cluster analysis and a varying intercepts regression model are used to assess the statistical association between land cover, a fugitive dust emissions proxy and observed PM10. We found that land cover patterns in the neighbourhood of an air quality station are significant predictors of observed average PM10 concentrations on days when wind speeds are conducive for dust emissions. This study concludes that in the absence of an emissions inventory for ambient particulate matter, PM10 emitted from dust reservoirs can be statistically accounted for by land cover characteristics. This supports the use of land cover data for improved prediction of PM10 at locations without air quality monitoring stations.

Point-of-care test identifies diabetic ketoacidosis at triage.

PubMed

Naunheim, Rosanne; Jang, Timothy J; Banet, Gerald; Richmond, Alec; McGill, Janet

2006-06-01

Diabetic ketoacidosis (DKA) is a common, life-threatening complication of diabetes. The diagnosis of DKA relies on signs and symptoms, plus laboratory findings of blood glucose (BG) of > 250 mg/dL, an anion gap (AG) of > or = 15 mmol/L, and carbon dioxide (CO2) of < or = 18 mmol/L when other causes of acidosis are excluded. To compare the results of a point-of-care test for the ketone beta-hydroxybutyrate (beta-OHB) with standard measures for accuracy in predicting DKA. After providing informed consent, 160 patients who presented with BG of > 250 mg/dL underwent testing for beta-OHB with the Precision Xtra meter (Abbott Laboratories, North Chicago, IL) at triage in a large urban hospital emergency department. The diagnosis of DKA was made by clinicians by using standard clinical criteria without knowledge of the beta-OHB test. A diagnosis of DKA was made in 57 of 160 subjects. The beta-OHB values correlated strongly with AG (r = 0.66, p < 0.001) and with CO2 (r = -0.69, p < 0.001), as well as with glucose (r = 0.31, p < 0.001). Cross-classification of DKA vs. beta-OHB yielded sensitivity of 98% (95% CI = 91% to 100%), specificity of 85% (95% CI = 78% to 91%), with a positive likelihood ratio of 6.7 (95% CI = 4.22 to 10.78), and negative likelihood ratio of 0.021 (95% CI = 0.003 to 0.144) at the manufacturer-suggested beta-OHB level of 1.5. The point-of-care test for beta-OHB was as sensitive as more established indicators of DKA. It is more useful than glucose alone for the diagnosis of DKA and offers immediate diagnosis of patients at triage.

The role of multisensory interplay in enabling temporal expectations.

PubMed

Ball, Felix; Michels, Lara E; Thiele, Carsten; Noesselt, Toemme

2018-01-01

Temporal regularities can guide our attention to focus on a particular moment in time and to be especially vigilant just then. Previous research provided evidence for the influence of temporal expectation on perceptual processing in unisensory auditory, visual, and tactile contexts. However, in real life we are often exposed to a complex and continuous stream of multisensory events. Here we tested - in a series of experiments - whether temporal expectations can enhance perception in multisensory contexts and whether this enhancement differs from enhancements in unisensory contexts. Our discrimination paradigm contained near-threshold targets (subject-specific 75% discrimination accuracy) embedded in a sequence of distractors. The likelihood of target occurrence (early or late) was manipulated block-wise. Furthermore, we tested whether spatial and modality-specific target uncertainty (i.e. predictable vs. unpredictable target position or modality) would affect temporal expectation (TE) measured with perceptual sensitivity (d ' ) and response times (RT). In all our experiments, hidden temporal regularities improved performance for expected multisensory targets. Moreover, multisensory performance was unaffected by spatial and modality-specific uncertainty, whereas unisensory TE effects on d ' but not RT were modulated by spatial and modality-specific uncertainty. Additionally, the size of the temporal expectation effect, i.e. the increase in perceptual sensitivity and decrease of RT, scaled linearly with the likelihood of expected targets. Finally, temporal expectation effects were unaffected by varying target position within the stream. Together, our results strongly suggest that participants quickly adapt to novel temporal contexts, that they benefit from multisensory (relative to unisensory) stimulation and that multisensory benefits are maximal if the stimulus-driven uncertainty is highest. We propose that enhanced informational content (i.e. multisensory stimulation) enables the robust extraction of temporal regularities which in turn boost (uni-)sensory representations. Copyright © 2017 Elsevier B.V. All rights reserved.

Predicting the "usefulness" of 5-ALA-derived tumor fluorescence for fluorescence-guided resections in pediatric brain tumors: a European survey.

PubMed

Stummer, Walter; Rodrigues, Floriano; Schucht, Philippe; Preuss, Matthias; Wiewrodt, Dorothee; Nestler, Ulf; Stein, Marco; Artero, José Manuel Cabezudo; Platania, Nunzio; Skjøth-Rasmussen, Jane; Della Puppa, Alessandro; Caird, John; Cortnum, Søren; Eljamel, Sam; Ewald, Christian; González-García, Laura; Martin, Andrew J; Melada, Ante; Peraud, Aurelia; Brentrup, Angela; Santarius, Thomas; Steiner, Hans Herbert

2014-12-01

Five-aminolevulinic acid (Gliolan, medac, Wedel, Germany, 5-ALA) is approved for fluorescence-guided resections of adult malignant gliomas. Case reports indicate that 5-ALA can be used for children, yet no prospective study has been conducted as of yet. As a basis for a study, we conducted a survey among certified European Gliolan users to collect data on their experiences with children. Information on patient characteristics, MRI characteristics of tumors, histology, fluorescence qualities, and outcomes were requested. Surgeons were further asked to indicate whether fluorescence was "useful", i.e., leading to changes in surgical strategy or identification of residual tumor. Recursive partitioning analysis (RPA) was used for defining cohorts with high or low likelihoods for useful fluorescence. Data on 78 patients <18 years of age were submitted by 20 centers. Fluorescence was found useful in 12 of 14 glioblastomas (85 %), four of five anaplastic astrocytomas (60 %), and eight of ten ependymomas grades II and III (80 %). Fluorescence was found inconsistently useful in PNETs (three of seven; 43 %), gangliogliomas (two of five; 40 %), medulloblastomas (two of eight, 25 %) and pilocytic astrocytomas (two of 13; 15 %). RPA of pre-operative factors showed tumors with supratentorial location, strong contrast enhancement and first operation to have a likelihood of useful fluorescence of 64.3 %, as opposed to infratentorial tumors with first surgery (23.1 %). Our survey demonstrates 5-ALA as being used in pediatric brain tumors. 5-ALA may be especially useful for contrast-enhancing supratentorial tumors. These data indicate controlled studies to be necessary and also provide a basis for planning such a study.

Robust logistic regression to narrow down the winner's curse for rare and recessive susceptibility variants.

PubMed

Kesselmeier, Miriam; Lorenzo Bermejo, Justo

2017-11-01

Logistic regression is the most common technique used for genetic case-control association studies. A disadvantage of standard maximum likelihood estimators of the genotype relative risk (GRR) is their strong dependence on outlier subjects, for example, patients diagnosed at unusually young age. Robust methods are available to constrain outlier influence, but they are scarcely used in genetic studies. This article provides a non-intimidating introduction to robust logistic regression, and investigates its benefits and limitations in genetic association studies. We applied the bounded Huber and extended the R package 'robustbase' with the re-descending Hampel functions to down-weight outlier influence. Computer simulations were carried out to assess the type I error rate, mean squared error (MSE) and statistical power according to major characteristics of the genetic study and investigated markers. Simulations were complemented with the analysis of real data. Both standard and robust estimation controlled type I error rates. Standard logistic regression showed the highest power but standard GRR estimates also showed the largest bias and MSE, in particular for associated rare and recessive variants. For illustration, a recessive variant with a true GRR=6.32 and a minor allele frequency=0.05 investigated in a 1000 case/1000 control study by standard logistic regression resulted in power=0.60 and MSE=16.5. The corresponding figures for Huber-based estimation were power=0.51 and MSE=0.53. Overall, Hampel- and Huber-based GRR estimates did not differ much. Robust logistic regression may represent a valuable alternative to standard maximum likelihood estimation when the focus lies on risk prediction rather than identification of susceptibility variants. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Childhood Lead Exposure After the Phaseout of Leaded Gasoline: An Ecological Study of School-Age Children in Kampala, Uganda

PubMed Central

Graber, Lauren K.; Asher, Daniel; Anandaraja, Natasha; Bopp, Richard F.; Merrill, Karen; Cullen, Mark R.; Luboga, Samuel; Trasande, Leonardo

2010-01-01

Background Tetraethyl lead was phased out of gasoline in Uganda in 2005. Recent mitigation of an important source of lead exposure suggests examination and re-evaluation of the prevalence of childhood lead poisoning in this country. Ongoing concerns persist about exposure from the Kiteezi landfill in Kampala, the country’s capital. Objectives We determined blood lead distributions among Kampala schoolchildren and identified risk factors for elevated blood lead levels (EBLLs; ≥ 10 μg/dL). Analytical approach Using a stratified, cross-sectional design, we obtained blood samples, questionnaire data, and soil and dust samples from the homes and schools of 163 4- to 8-year-old children representing communities with different risks of exposure. Results The mean blood lead level (BLL) was 7.15 μg/dL; 20.5% of the children were found to have EBLL. Multivariable analysis found participants whose families owned fewer household items, ate canned food, or used the community water supply as their primary water source to have higher BLLs and likelihood of EBLLs. Distance < 0.5 mi from the landfill was the factor most strongly associated with increments in BLL (5.51 μg/dL, p < 0.0001) and likelihood of EBLL (OR = 4.71, p = 0.0093). Dust/soil lead was not significantly predictive of BLL/EBLL. Conclusions Lead poisoning remains highly prevalent among school-age children in Kampala. Confirmatory studies are needed, but further efforts are indicated to limit lead exposure from the landfill, whether through water contamination or through another mechanism. Although African nations are to be lauded for the removal of lead from gasoline, this study serves as a reminder that other sources of exposure to this potent neurotoxicant merit ongoing attention. PMID:20194080

Client-Friendly Forecasting: Seasonal Runoff Predictions Using Out-of-the-Box Indices

NASA Astrophysics Data System (ADS)

Weil, P.

2013-12-01

For more than a century, statistical relationships have been recognized between atmospheric conditions at locations separated by thousands of miles, referred to as teleconnections. Some of the recognized teleconnections provide useful information about expected hydrologic conditions, so certain records of atmospheric conditions are quantified and published as hydroclimate indices. Certain hydroclimate indices can serve as strong leading indicators of climate patterns over North America and can be used to make skillful forecasts of seasonal runoff. The methodology described here creates a simple-to-use model that utilizes easily accessed data to make forecasts of April through September runoff months before the runoff season begins. For this project, forecasting models were developed for two snowmelt-driven river systems in Colorado and Wyoming. In addition to the global hydroclimate indices, the methodology uses several local hydrologic variables including the previous year's drought severity, headwater snow water equivalent and the reservoir contents for the major reservoirs in each basin. To improve the skill of the forecasts, logistic regression is used to develop a model that provides the likelihood that a year will fall into the upper, middle or lower tercile of historical flows. Categorical forecasting has two major advantages over modeling of specific flow amounts: (1) with less prediction outcomes models tend to have better predictive skill and (2) categorical models are very useful to clients and agencies with specific flow thresholds that dictate major changes in water resources management. The resulting methodology and functional forecasting model product is highly portable, applicable to many major river systems and easily explained to a non-technical audience.

Coronary Calcium Scores 6 Years After Bariatric Surgery

PubMed Central

Priester, Tiffany; Ault, Travis G.; Davidson, Lance; Gress, Richard; Adams, Ted D.; Hunt, Steven C.; Litwin, Sheldon E.

2014-01-01

Background Obesity is associated with elevated coronary artery calcium (CAC), a marker of coronary atherosclerosis that is strongly predictive of cardiovascular events. we evaluated the effects of marked weight loss achieved through roux-en-Y gastric bypass surgery (GBS) on CAC scores. Methods We performed echocardiography and computed tomography of the heart in 149 subjects 6 years after enrollment in a prospective registry evaluating the cardiovascular effects of GBS. coronary calcium scores, left ventricular ejection fraction and left ventricular mass were measured. Results At baseline most coronary risk factors were similar between the GBS and nonsurgical groups including current smoking, systolic blood pressure, LDL-C, HDL-C, and TG. However, GBS patients were younger (4.7 years), less likely to be diabetic and less likely to be postmenopausal. At 6 years after enrollment, CAC score was significantly lower in patients who underwent GBS than those without surgery (p<0.01). GBS subjects had a lower likelihood of having measureable coronary calcium (odds ratio of CAC > zero = 0.39; 95% CI of (0.17, 0.90)). Significant predictors of zero CAC were GBS, female gender, younger age, baseline BMI, and baseline LDL-C. Substituting change in BMI for group status as a predictor variable showed that BMI change also predicted CAC (p=0.045). Changes in LDL-C did not predict the CAC differences between groups (p=0.67). Conclusions Sustained weight loss achieved through bariatric surgery is associated with less coronary calcification. This effect, which appears to be independent of changes in LDL-C, may contribute to lower cardiac mortality in patients with successful GBS. PMID:24927692

Study of CP Symmetry Violation in the Charmonium-K*(892) Channel By a Complete Time Dependent Angular Analysis (BaBar Experiment) (in French)

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

T'Jampens, Stephane; /Orsay

2006-09-18

This thesis presents the full-angular time-dependent analysis of the vector-vector channel B{sub d}{sup 0} {yields} J/{psi}(K{sub S}{sup 0}{pi}{sup 0})*{sup 0}. After a review of the CP violation in the B meson system, the phenomenology of the charmonium-K*(892) channels is exposed. The method for the measurement of the transversity amplitudes of the B {yields} J/{psi}K*(892), based on a pseudo-likelihood method, is then exposed. The results from a 81.9 fb{sup -1} of collected data by the BABAR detector at the {Upsilon}(4S) resonance peak are |A{sub 0}|{sup 2} = 0.565 {+-} 0.011 {+-} 0.004, |A{sub {parallel}}|{sup 2} = 0.206 {+-} 0.016 {+-} 0.007,more » |A{sub {perpendicular}}|{sup 2} = 0.228 {+-} 0.016 {+-} 0.007, {delta}{sub {parallel}} = -2.766 {+-} 0.105 {+-} 0.040 and {delta}{sub {perpendicular}} = 2.935 {+-} 0.067 {+-} 0.040. Note that ({delta}{sub {parallel}}, {delta}{sub {perpendicular}}) {yields} (-{delta}{sub {parallel}}, {pi} - {delta}{sub {perpendicular}}) is also a solution. The strong phases {delta}{sub {parallel}} and {delta}{sub {perpendicular}} are at {approx}> 3{sigma} from {+-}{pi}, signing the presence of final state interactions and the breakdown of the factorization hypothesis. The forward-backward analysis of the K{pi} mass spectrum revealed the presence of a coherent S-wave interfering with the K*(892). It is the first evidence of this wave in the K{pi} system coming from a B meson. The particularity of the B{sub d}{sup 0} {yields} J/{psi}(K{sub S}{sup 0}{pi}{sup 0})*{sup 0} channel is to have a time-dependent but also an angular distribution which allows to measure sin 2{beta} but also cos2{beta}. The results from an unbinned maximum likelihood fit are sin 2{beta} = -0.10 {+-} 0.57 {+-} 0.14 and cos 2{beta} = 3.32{sub -0.96}{sup +0.76} {+-} 0.27 with the transversity amplitudes fixed to the values given above. The other solution for the strong phases flips the sign of cos 2{beta}. Theoretical considerations based on the s-quark helicity conservation favor the choice of the strong phases given above, leading to a positive sign for cos 2{beta}. The sign of cos 2{beta} is the one predicted by the Standard Model.« less

The relationships among perceived peer acceptance of sexual aggression, punishment certainty, and sexually aggressive behavior.

PubMed

Strang, Emily; Peterson, Zoë D

2013-12-01

Researching the correlates of men's sexually aggressive behavior (i.e., verbal coercion and rape) is critical to both understanding and preventing sexual aggression. This study examined 120 men who completed an anonymous online questionnaire. The study aimed to determine the relative importance of two potential correlates of men's self-reported use of sexual aggression: (a) perceptions that male peers use and support sexual aggression and (b) perceptions of punishment likelihood associated with sexual aggression. Results revealed that perceptions of male friends' acceptance of sexual aggression were strongly associated with individual men's reports of using verbal coercion and rape. Perceptions of punishment likelihood were negatively correlated with verbal coercion but not with rape through intoxication and force. Implications for sexual aggression prevention are discussed.

Predicting critical transitions in dynamical systems from time series using nonstationary probability density modeling.

PubMed

Kwasniok, Frank

2013-11-01

A time series analysis method for predicting the probability density of a dynamical system is proposed. A nonstationary parametric model of the probability density is estimated from data within a maximum likelihood framework and then extrapolated to forecast the future probability density and explore the system for critical transitions or tipping points. A full systematic account of parameter uncertainty is taken. The technique is generic, independent of the underlying dynamics of the system. The method is verified on simulated data and then applied to prediction of Arctic sea-ice extent.

Fuzzy fractals, chaos, and noise

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

Zardecki, A.

1997-05-01

To distinguish between chaotic and noisy processes, the authors analyze one- and two-dimensional chaotic mappings, supplemented by the additive noise terms. The predictive power of a fuzzy rule-based system allows one to distinguish ergodic and chaotic time series: in an ergodic series the likelihood of finding large numbers is small compared to the likelihood of finding them in a chaotic series. In the case of two dimensions, they consider the fractal fuzzy sets whose {alpha}-cuts are fractals, arising in the context of a quadratic mapping in the extended complex plane. In an example provided by the Julia set, the conceptmore » of Hausdorff dimension enables one to decide in favor of chaotic or noisy evolution.« less

Greenery in the university environment: Students’ preferences and perceived restoration likelihood

PubMed Central

2018-01-01

A large body of evidence shows that interaction with greenery can be beneficial for human stress reduction, emotional states, and improved cognitive function. It can, therefore, be expected that university students might benefit from greenery in the university environment. Before investing in real-life interventions in a university environment, it is necessary to first explore students’ perceptions of greenery in the university environment. This study examined (1) preference for university indoor and outdoor spaces with and without greenery (2) perceived restoration likelihood of university outdoor spaces with and without greenery and (3) if preference and perceived restoration likelihood ratings were modified by demographic characteristics or connectedness to nature in Dutch university students (N = 722). Digital photographic stimuli represented four university spaces (lecture hall, classroom, study area, university outdoor space). For each of the three indoor spaces there were four or five stimuli conditions: (1) the standard design (2) the standard design with a colorful poster (3) the standard design with a nature poster (4) the standard design with a green wall (5) the standard design with a green wall plus interior plants. The university outdoor space included: (1) the standard design (2) the standard design with seating (3) the standard design with colorful artifacts (4) the standard design with green elements (5) the standard design with extensive greenery. Multi-level analyses showed that students gave higher preference ratings to the indoor spaces with a nature poster, a green wall, or a green wall plus interior plants than to the standard designs and the designs with the colorful posters. Students also rated preference and perceived restoration likelihood of the outdoor spaces that included greenery higher than those without. Preference and perceived restoration likelihood were not modified by demographic characteristics, but students with strong connectedness to nature rated preference and perceived restoration likelihood overall higher than students with weak connectedness to nature. The findings suggest that students would appreciate the integration of greenery in the university environment. PMID:29447184

Greenery in the university environment: Students' preferences and perceived restoration likelihood.

PubMed

van den Bogerd, Nicole; Dijkstra, S Coosje; Seidell, Jacob C; Maas, Jolanda

2018-01-01

A large body of evidence shows that interaction with greenery can be beneficial for human stress reduction, emotional states, and improved cognitive function. It can, therefore, be expected that university students might benefit from greenery in the university environment. Before investing in real-life interventions in a university environment, it is necessary to first explore students' perceptions of greenery in the university environment. This study examined (1) preference for university indoor and outdoor spaces with and without greenery (2) perceived restoration likelihood of university outdoor spaces with and without greenery and (3) if preference and perceived restoration likelihood ratings were modified by demographic characteristics or connectedness to nature in Dutch university students (N = 722). Digital photographic stimuli represented four university spaces (lecture hall, classroom, study area, university outdoor space). For each of the three indoor spaces there were four or five stimuli conditions: (1) the standard design (2) the standard design with a colorful poster (3) the standard design with a nature poster (4) the standard design with a green wall (5) the standard design with a green wall plus interior plants. The university outdoor space included: (1) the standard design (2) the standard design with seating (3) the standard design with colorful artifacts (4) the standard design with green elements (5) the standard design with extensive greenery. Multi-level analyses showed that students gave higher preference ratings to the indoor spaces with a nature poster, a green wall, or a green wall plus interior plants than to the standard designs and the designs with the colorful posters. Students also rated preference and perceived restoration likelihood of the outdoor spaces that included greenery higher than those without. Preference and perceived restoration likelihood were not modified by demographic characteristics, but students with strong connectedness to nature rated preference and perceived restoration likelihood overall higher than students with weak connectedness to nature. The findings suggest that students would appreciate the integration of greenery in the university environment.

Modeling gene expression measurement error: a quasi-likelihood approach

PubMed Central

Strimmer, Korbinian

2003-01-01

Background Using suitable error models for gene expression measurements is essential in the statistical analysis of microarray data. However, the true probabilistic model underlying gene expression intensity readings is generally not known. Instead, in currently used approaches some simple parametric model is assumed (usually a transformed normal distribution) or the empirical distribution is estimated. However, both these strategies may not be optimal for gene expression data, as the non-parametric approach ignores known structural information whereas the fully parametric models run the risk of misspecification. A further related problem is the choice of a suitable scale for the model (e.g. observed vs. log-scale). Results Here a simple semi-parametric model for gene expression measurement error is presented. In this approach inference is based an approximate likelihood function (the extended quasi-likelihood). Only partial knowledge about the unknown true distribution is required to construct this function. In case of gene expression this information is available in the form of the postulated (e.g. quadratic) variance structure of the data. As the quasi-likelihood behaves (almost) like a proper likelihood, it allows for the estimation of calibration and variance parameters, and it is also straightforward to obtain corresponding approximate confidence intervals. Unlike most other frameworks, it also allows analysis on any preferred scale, i.e. both on the original linear scale as well as on a transformed scale. It can also be employed in regression approaches to model systematic (e.g. array or dye) effects. Conclusions The quasi-likelihood framework provides a simple and versatile approach to analyze gene expression data that does not make any strong distributional assumptions about the underlying error model. For several simulated as well as real data sets it provides a better fit to the data than competing models. In an example it also improved the power of tests to identify differential expression. PMID:12659637

With All My Relations: Counseling American Indians and Alaska Natives within a Familial Context

ERIC Educational Resources Information Center

Harper, Faith G.

2011-01-01

Statistics show that two thirds of American Indians and Alaska Natives (AIs/ANs) live outside of tribal areas, and 50% of those individuals who seek counseling services will not use tribal resources. There is a strong likelihood that counselors will have the opportunity to provide services to AI/AN clients. The review of the academic literature…

Cabin location and the likelihood of motion sickness in cruise ship passengers.

PubMed

Gahlinger , P M

2000-01-01

The prevalence of motion sickness approaches 100% on rough seas. Some previous studies have reported a strong association between location on a ship and the risk of motion sickness, whereas other studies found no association. This study was undertaken to determine if there is a statistical association between the location of the passenger cabin on a ship and the risk of motion sickness in unadapted passengers. Data were collected on 260 passengers on an expedition ship traversing the Drake Passage between South America and Antarctica, during rough sea conditions. A standard scale was employed to record motion sickness severity. The risk of motion sickness was found to be statistically associated with age and sex. However, no association was found with the location of the passenger cabin. Previous research reporting a strong association of motion sickness and passenger location on a ship, studied passengers in the seated position. Passengers who are able to lie in a supine position are at considerably reduced risk of motion sickness. Expedition or cruise ships that provide ready access to berths, allow passengers to avoid the most nauseogenic positions. The location of the passenger cabin does not appear to be related to the likelihood of seasickness.

Psychosocial Predictors of Breast Self-Examination among Female Students in Malaysia: A Study to Assess the Roles of Body Image, Self-efficacy and Perceived Barriers.

PubMed

Ahmadian, Maryam; Carmack, Suzie; Samah, Asnarulkhadi Abu; Kreps, Gary; Saidu, Mohammed Bashir

2016-01-01

Early detection is a critical part of reducing the burden of breast cancer and breast selfexamination (BSE) has been found to be an especially important early detection strategy in low and middle income countries such as Malaysia. Although reports indicate that Malaysian women report an increase in BSE activity in recent years, additional research is needed to explore factors that may help to increase this behavior among Southeastern Asian women. This study is the first of its kind to explore how the predicting variables of self-efficacy, perceived barriers, and body image factors correlate with self-reports of past BSE, and intention to conduct future breast self-exams among female students in Malaysia. Through the analysis of data collected from a prior study of female students from nine Malaysian universities (n=842), this study found that self-efficacy, perceived barriers and specific body image sub-constructs (MBSRQ-Appearance Scales) were correlated with, and at times predicted, both the likelihood of past BSE and the intention to conduct breast self-exams in the future. Self-efficacy (SE) positively predicted the likelihood of past self-exam behavior, and intention to conduct future breast self-exams. Perceived barriers (BR) negatively predicted past behavior and future intention of breast self-exams. The body image sub-constructs of appearance evaluation (AE) and overweight preoccupation (OWP) predicted the likelihood of past behavior but did not predict intention for future behavior. Appearance orientation (AO) had a somewhat opposite effect: AO did not correlate with or predict past behavior but did correlate with intention to conduct breast self-exams in the future. The body image sub-constructs of body area satisfaction (BASS) and self-classified weight (SCW) showed no correlation with the subjects' past breast self-exam behavior nor with their intention to conduct breast self-exams in the future. Findings from this study indicate that both self-efficacy and perceived barriers to BSE are significant psychosocial factors that influence BSE behavior. These results suggest that health promotion interventions that help enhance self-efficacy and reduce perceived barriers have the potential to increase the intentions of Malaysian women to perform breast self-exams, which can promote early detection of breast cancers. Future research should evaluate targeted communication interventions for addressing self-efficacy and perceived barriers to breast self-exams with at-risk Malaysian women. and further explore the relationship between BSE and body image.

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

Zhang, Jing, E-mail: jing.zhang2@duke.edu; Ghate, Sujata V.; Yoon, Sora C.

Purpose: Mammography is the most widely accepted and utilized screening modality for early breast cancer detection. Providing high quality mammography education to radiology trainees is essential, since excellent interpretation skills are needed to ensure the highest benefit of screening mammography for patients. The authors have previously proposed a computer-aided education system based on trainee models. Those models relate human-assessed image characteristics to trainee error. In this study, the authors propose to build trainee models that utilize features automatically extracted from images using computer vision algorithms to predict likelihood of missing each mass by the trainee. This computer vision-based approach tomore » trainee modeling will allow for automatically searching large databases of mammograms in order to identify challenging cases for each trainee. Methods: The authors’ algorithm for predicting the likelihood of missing a mass consists of three steps. First, a mammogram is segmented into air, pectoral muscle, fatty tissue, dense tissue, and mass using automated segmentation algorithms. Second, 43 features are extracted using computer vision algorithms for each abnormality identified by experts. Third, error-making models (classifiers) are applied to predict the likelihood of trainees missing the abnormality based on the extracted features. The models are developed individually for each trainee using his/her previous reading data. The authors evaluated the predictive performance of the proposed algorithm using data from a reader study in which 10 subjects (7 residents and 3 novices) and 3 experts read 100 mammographic cases. Receiver operating characteristic (ROC) methodology was applied for the evaluation. Results: The average area under the ROC curve (AUC) of the error-making models for the task of predicting which masses will be detected and which will be missed was 0.607 (95% CI,0.564-0.650). This value was statistically significantly different from 0.5 (p < 0.0001). For the 7 residents only, the AUC performance of the models was 0.590 (95% CI,0.537-0.642) and was also significantly higher than 0.5 (p = 0.0009). Therefore, generally the authors’ models were able to predict which masses were detected and which were missed better than chance. Conclusions: The authors proposed an algorithm that was able to predict which masses will be detected and which will be missed by each individual trainee. This confirms existence of error-making patterns in the detection of masses among radiology trainees. Furthermore, the proposed methodology will allow for the optimized selection of difficult cases for the trainees in an automatic and efficient manner.« less

Elimination of trait blocks from multiple trait mixed model equations with singular (Co)variance parameter matrices

USDA-ARS?s Scientific Manuscript database

Transformations to multiple trait mixed model equations (MME) which are intended to improve computational efficiency in best linear unbiased prediction (BLUP) and restricted maximum likelihood (REML) are described. It is shown that traits that are expected or estimated to have zero residual variance...

Updating The Navy’s Recruit Quality Matrix: An Analysis of Educational Credentials and the Success of First-Term Sailors

DTIC Science & Technology

2004-03-01

Allison , Logistic Regression: Using the SAS System (Cary, NC: SAS Institute, Inc, 2001), 57. 23 using the likelihood ratio that SAS generates...21, respectively. 33 Jesse M. Rothstein, College Performance Predictions and the SAT ( Berkely , CA: UC

What Do the Stats Tell Us? Engaging Elementary Children in Probabilistic Reasoning Based on Data Analysis

ERIC Educational Resources Information Center

Hourigan, Mairéad; Leavy, Aisling

2016-01-01

As part of Japanese Lesson study research focusing on "comparing and describing likelihoods", fifth grade elementary students used real-world data in decision-making. Sporting statistics facilitated opportunities for informal inference, where data were used to make and justify predictions.

Information loss in approximately bayesian data assimilation: a comparison of generative and discriminative approaches to estimating agricultural yield

USDA-ARS?s Scientific Manuscript database

Data assimilation and regression are two commonly used methods for predicting agricultural yield from remote sensing observations. Data assimilation is a generative approach because it requires explicit approximations of the Bayesian prior and likelihood to compute the probability density function...

Cotton defense induction patterns under spatially, temporally and quantitatively varying herbivory levels

USDA-ARS?s Scientific Manuscript database

The optimal defense theory (ODT) predicts that plants allocate defense compounds to their tissues depending on its value and the likelihood of herbivore attack. Whereas ODT has been confirmed for static damage levels it remains poorly understood if ODT holds true for defense organization of inducibl...

Factors Associated with Living in Developmental Centers in California

ERIC Educational Resources Information Center

Harrington, Charlene; Kang, Taewoon; Chang, Jamie

2009-01-01

This study examined need, predisposing, market, and regional factors that predicted the likelihood of individuals with developmental disabilities living in state developmental centers (DCs) compared with living at home, in community care, or in intermediate care (ICFs) and other facilities. Secondary data analysis using logistic regression models…

Severe Pain Predicts Greater Likelihood of Subsequent Suicide

ERIC Educational Resources Information Center

Ilgen, Mark A.; Zivin, Kara; Austin, Karen L.; Bohnert, Amy S. B.; Czyz, Ewa K.; Valenstein, Marcia; Kilbourne, Amy M.

2010-01-01

Using data from the 1999 Large Health Survey of Veterans, Veterans Affairs' medical records, and the National Death Index (N = 260,254), the association between self-reported pain severity and suicide among veterans as examined, after accounting for demographic variables and psychiatric diagnoses. A Cox proportional hazards regression demonstrated…

Do Peers Contribute to the Likelihood of Secondary School Graduation among Disadvantaged Boys?

ERIC Educational Resources Information Center

Veronneau, Marie-Helene; Vitaro, Frank; Pedersen, Sara; Tremblay, Richard E.

2008-01-01

This 17-year longitudinal study tested whether low peer-perceived acceptance and association with aggressive-disruptive friends during preadolescence predicted students' failure to graduate from secondary school. Participants were 997 Caucasian, French-speaking boys from low-socioeconomic status, urban neighborhoods. The boys were recruited in…

Learning in Reverse: Eight-Month-Old Infants Track Backward Transitional Probabilities

ERIC Educational Resources Information Center

Pelucchi, Bruna; Hay, Jessica F.; Saffran, Jenny R.

2009-01-01

Numerous recent studies suggest that human learners, including both infants and adults, readily track sequential statistics computed between adjacent elements. One such statistic, transitional probability, is typically calculated as the likelihood that one element predicts another. However, little is known about whether listeners are sensitive to…

Competitive Embeddedness and the Emergence of Interfirm Cooperation

ERIC Educational Resources Information Center

Trapido, Denis

2007-01-01

How does a history of competition between two economic actors affect their willingness and ability to work together for mutual benefit? Existing theory and research offer mixed predictions and answers. The competitive embeddedness hypothesis suggested here postulates that the likelihood of cooperation between two firms is positively related to the…

20180312 - Ensemble QSAR Modeling to Predict Multispecies Fish Toxicity Points of Departure (SOT)

EPA Science Inventory

Due to the large quantity of new chemicals being developed and potentially introduced into aquatic ecosystems, there is a need to prioritize chemicals with the greatest likelihood of ecological hazard for further research. To this end, a useful in silico estimation of ecotoxicity...

Estimating Likelihood of Fetal In Vivo Interactions Using In Vitro HTS Data (Teratology meeting)

EPA Science Inventory

Tox21/ToxCast efforts provide in vitro concentration-response data for thousands of compounds. Predicting whether chemical-biological interactions observed in vitro will occur in vivo is challenging. We hypothesize that using a modified model from the FDA guidance for drug intera...

Predicting medical complications after spine surgery: a validated model using a prospective surgical registry.

PubMed

Lee, Michael J; Cizik, Amy M; Hamilton, Deven; Chapman, Jens R

2014-02-01

The possibility and likelihood of a postoperative medical complication after spine surgery undoubtedly play a major role in the decision making of the surgeon and patient alike. Although prior study has determined relative risk and odds ratio values to quantify risk factors, these values may be difficult to translate to the patient during counseling of surgical options. Ideally, a model that predicts absolute risk of medical complication, rather than relative risk or odds ratio values, would greatly enhance the discussion of safety of spine surgery. To date, there is no risk stratification model that specifically predicts the risk of medical complication. The purpose of this study was to create and validate a predictive model for the risk of medical complication during and after spine surgery. Statistical analysis using a prospective surgical spine registry that recorded extensive demographic, surgical, and complication data. Outcomes examined are medical complications that were specifically defined a priori. This analysis is a continuation of statistical analysis of our previously published report. Using a prospectively collected surgical registry of more than 1,476 patients with extensive demographic, comorbidity, surgical, and complication detail recorded for 2 years after surgery, we previously identified several risk factor for medical complications. Using the beta coefficients from those log binomial regression analyses, we created a model to predict the occurrence of medical complication after spine surgery. We split our data into two subsets for internal and cross-validation of our model. We created two predictive models: one predicting the occurrence of any medical complication and the other predicting the occurrence of a major medical complication. The final predictive model for any medical complications had a receiver operator curve characteristic of 0.76, considered to be a fair measure. The final predictive model for any major medical complications had receiver operator curve characteristic of 0.81, considered to be a good measure. The final model has been uploaded for use on SpineSage.com. We present a validated model for predicting medical complications after spine surgery. The value in this model is that it gives the user an absolute percent likelihood of complication after spine surgery based on the patient's comorbidity profile and invasiveness of surgery. Patients are far more likely to understand an absolute percentage, rather than relative risk and confidence interval values. A model such as this is of paramount importance in counseling patients and enhancing the safety of spine surgery. In addition, a tool such as this can be of great use particularly as health care trends toward pay-for-performance, quality metrics, and risk adjustment. To facilitate the use of this model, we have created a website (SpineSage.com) where users can enter in patient data to determine likelihood of medical complications after spine surgery. Copyright © 2014 Elsevier Inc. All rights reserved.

Grandparental investment and reproductive decisions in the longitudinal 1970 British cohort study.

PubMed

Waynforth, David

2012-03-22

There has been a recent increase in interest among evolutionary researchers in the hypothesis that humans evolved as cooperative breeders, using extended family support to help decrease offspring mortality and increase the number of children that can be successfully reared. In this study, data drawn from the 1970 longitudinal British cohort study were analysed to determine whether extended family support encourages fertility in contemporary Britain. The results showed that at age 30, reported frequency that participants saw their own parents (but not in-laws) and the closeness of the bond between the participant and their own parents were associated with an increased likelihood of having a child between ages 30 and 34. Financial help and reported grandparental childcare were not significantly positively associated with births from age 30 to 34. Men's income was positively associated with likelihood of birth, whereas women's income increased likelihood of birth only for working women with at least one child. While it was predicted that grandparental financial and childcare help would increase the likelihood of reproduction by lowering the cost to the parent of having a child, it appears that the mere physical presence of supportive parents rather than their financial or childcare help encouraged reproduction in the 1970 British birth cohort sample.

Likelihood-based methods for evaluating principal surrogacy in augmented vaccine trials.

PubMed

Liu, Wei; Zhang, Bo; Zhang, Hui; Zhang, Zhiwei

2017-04-01

There is growing interest in assessing immune biomarkers, which are quick to measure and potentially predictive of long-term efficacy, as surrogate endpoints in randomized, placebo-controlled vaccine trials. This can be done under a principal stratification approach, with principal strata defined using a subject's potential immune responses to vaccine and placebo (the latter may be assumed to be zero). In this context, principal surrogacy refers to the extent to which vaccine efficacy varies across principal strata. Because a placebo recipient's potential immune response to vaccine is unobserved in a standard vaccine trial, augmented vaccine trials have been proposed to produce the information needed to evaluate principal surrogacy. This article reviews existing methods based on an estimated likelihood and a pseudo-score (PS) and proposes two new methods based on a semiparametric likelihood (SL) and a pseudo-likelihood (PL), for analyzing augmented vaccine trials. Unlike the PS method, the SL method does not require a model for missingness, which can be advantageous when immune response data are missing by happenstance. The SL method is shown to be asymptotically efficient, and it performs similarly to the PS and PL methods in simulation experiments. The PL method appears to have a computational advantage over the PS and SL methods.

Office gel sonovaginography for the prediction of posterior deep infiltrating endometriosis: a multicenter prospective observational study.

PubMed

Reid, S; Lu, C; Hardy, N; Casikar, I; Reid, G; Cario, G; Chou, D; Almashat, D; Condous, G

2014-12-01

To use office gel sonovaginography (SVG) to predict posterior deep infiltrating endometriosis (DIE) in women undergoing laparoscopy. This was a multicenter prospective observational study carried out between January 2009 and February 2013. All women were of reproductive age, had a history of chronic pelvic pain and underwent office gel SVG assessment for the prediction of posterior compartment DIE prior to laparoscopic endometriosis surgery. Gel SVG findings were compared with laparoscopic findings to determine the diagnostic accuracy of office gel SVG for the prediction of posterior compartment DIE. In total, 189 women underwent preoperative gel SVG and laparoscopy for endometriosis. At laparoscopy, 57 (30%) women had posterior DIE and 43 (23%) had rectosigmoid/anterior rectal DIE. For the prediction of rectosigmoid/anterior rectal (i.e. bowel) DIE, gel SVG had an accuracy of 92%, sensitivity of 88%, specificity of 93%, positive predictive value (PPV) of 79%, negative predictive value (NPV) of 97%, positive likelihood ratio (LR+) of 12.9 and negative likelihood ratio (LR-) of 0.12 (P = 3.98E-25); for posterior vaginal wall and rectovaginal septum (RVS) DIE, respectively, the accuracy was 95% and 95%, sensitivity was 18% and 18%, specificity was 99% and 100%, PPV was 67% and 100%, NPV was 95% and 95%, LR+ was 32.4 and infinity and LR- was 0.82 and 0.82 (P = 0.009 and P = 0.003). Office gel SVG appears to be an effective outpatient imaging technique for the prediction of bowel DIE, with a higher accuracy for the prediction of rectosigmoid compared with anterior rectal DIE. Although the sensitivity for vaginal and RVS DIE was limited, gel SVG had a high specificity and NPV for all forms of posterior DIE, indicating that a negative gel SVG examination is highly suggestive of the absence of DIE at laparoscopy. Copyright © 2014 ISUOG. Published by John Wiley & Sons Ltd.

Predicting symptomatic cerebral vasospasm after aneurysmal subarachnoid hemorrhage with an artificial neural network in a pediatric population.

PubMed

Skoch, Jesse; Tahir, Rizwan; Abruzzo, Todd; Taylor, John M; Zuccarello, Mario; Vadivelu, Sudhakar

2017-12-01

Artificial neural networks (ANN) are increasingly applied to complex medical problem solving algorithms because their outcome prediction performance is superior to existing multiple regression models. ANN can successfully identify symptomatic cerebral vasospasm (SCV) in adults presenting after aneurysmal subarachnoid hemorrhage (aSAH). Although SCV is unusual in children with aSAH, the clinical consequences are severe. Consequently, reliable tools to predict patients at greatest risk for SCV may have significant value. We applied ANN modeling to a consecutive cohort of pediatric aSAH cases to assess its ability to predict SCV. A retrospective chart review was conducted to identify patients < 21 years of age who presented with spontaneously ruptured, non-traumatic, non-mycotic, non-flow-related intracranial arterial aneurysms to our institution between January 2002 and January 2015. Demographics, clinical, radiographic, and outcome data were analyzed using an adapted ANN model using learned value nodes from the adult aneurysmal SAH dataset previously reported. The strength of the ANN prediction was measured between - 1 and 1 with - 1 representing no likelihood of SCV and 1 representing high likelihood of SCV. Sixteen patients met study inclusion criteria. The median age for aSAH patients was 15 years. Ten underwent surgical clipping and 6 underwent endovascular coiling for definitive treatment. One patient experienced SCV and 15 did not. The ANN applied here was able to accurately predict all 16 outcomes. The mean strength of prediction for those who did not exhibit SCV was - 0.86. The strength for the one patient who did exhibit SCV was 0.93. Adult-derived aneurysmal SAH value nodes can be applied to a simple AAN model to accurately predict SCV in children presenting with aSAH. Further work is needed to determine if ANN models can prospectively predict SCV in the pediatric aSAH population in toto; adapted to include mycotic, traumatic, and flow-related origins as well.

Relationship between two indicators of coronary risk estimated by the Framingham Risk Score and the number of metabolic syndrome components in Japanese male manufacturing workers.

PubMed

Kawada, Tomoyuki; Otsuka, Toshiaki; Inagaki, Hirofumi; Wakayama, Yoko; Li, Qing; Katsumata, Masao

2009-10-01

The Framingham Risk Score (FRS) has frequently been used in the United States to predict the 10-year risk of coronary heart disease (CHD). Components of the metabolic syndrome and several lifestyle factors have also been evaluated to estimate the risk of CHD. To determine the relationship between the FRS and components of metabolic syndrome as coronary risk indicators, the authors conducted a cross-sectional study of 2,619 Japanese male workers, ranging in age from 40 to 64 years, at a single workplace. Although the estimation by the FRS and metabolic syndrome involved some different factors, significant association of the risk estimated by the 2 methods was observed. When logistic regression analysis was conducted with adjustment for several lifestyle factors, the FRS and serum insulin were found to be significantly associated with the risk of likelihood of metabolic syndrome. The odds ratios and 95% confidence intervals of FRS by per standard deviation increment and serum insulin by increasing 1 microIU/mL for the prediction of metabolic syndrome were 2.50 (2.17-2.88) and 1.24 (1.20-1.27), respectively. A preventive effect of abstaining from drinking every day and eating breakfast almost daily against the likelihood of metabolic syndrome was also observed. In conclusion, the FRS and insulin were found to be significantly associated with the risk of likelihood of metabolic syndrome, even after controlling for weight change.

Predicting In-State Workforce Retention After Graduate Medical Education Training.

PubMed

Koehler, Tracy J; Goodfellow, Jaclyn; Davis, Alan T; Spybrook, Jessaca; vanSchagen, John E; Schuh, Lori

2017-02-01

There is a paucity of literature when it comes to identifying predictors of in-state retention of graduate medical education (GME) graduates, such as the demographic and educational characteristics of these physicians. The purpose was to use demographic and educational predictors to identify graduates from a single Michigan GME sponsoring institution, who are also likely to practice medicine in Michigan post-GME training. We included all residents and fellows who graduated between 2000 and 2014 from 1 of 18 GME programs at a Michigan-based sponsoring institution. Predictor variables identified by logistic regression with cross-validation were used to create a scoring tool to determine the likelihood of a GME graduate to practice medicine in the same state post-GME training. A 6-variable model, which included 714 observations, was identified. The predictor variables were birth state, program type (primary care versus non-primary care), undergraduate degree location, medical school location, state in which GME training was completed, and marital status. The positive likelihood ratio (+LR) for the scoring tool was 5.31, while the negative likelihood ratio (-LR) was 0.46, with an accuracy of 74%. The +LR indicates that the scoring tool was useful in predicting whether graduates who trained in a Michigan-based GME sponsoring institution were likely to practice medicine in Michigan following training. Other institutions could use these techniques to identify key information that could help pinpoint matriculating residents/fellows likely to practice medicine within the state in which they completed their training.

Clarifying the Hubble constant tension with a Bayesian hierarchical model of the local distance ladder

NASA Astrophysics Data System (ADS)

Feeney, Stephen M.; Mortlock, Daniel J.; Dalmasso, Niccolò

2018-05-01

Estimates of the Hubble constant, H0, from the local distance ladder and from the cosmic microwave background (CMB) are discrepant at the ˜3σ level, indicating a potential issue with the standard Λ cold dark matter (ΛCDM) cosmology. A probabilistic (i.e. Bayesian) interpretation of this tension requires a model comparison calculation, which in turn depends strongly on the tails of the H0 likelihoods. Evaluating the tails of the local H0 likelihood requires the use of non-Gaussian distributions to faithfully represent anchor likelihoods and outliers, and simultaneous fitting of the complete distance-ladder data set to ensure correct uncertainty propagation. We have hence developed a Bayesian hierarchical model of the full distance ladder that does not rely on Gaussian distributions and allows outliers to be modelled without arbitrary data cuts. Marginalizing over the full ˜3000-parameter joint posterior distribution, we find H0 = (72.72 ± 1.67) km s-1 Mpc-1 when applied to the outlier-cleaned Riess et al. data, and (73.15 ± 1.78) km s-1 Mpc-1 with supernova outliers reintroduced (the pre-cut Cepheid data set is not available). Using our precise evaluation of the tails of the H0 likelihood, we apply Bayesian model comparison to assess the evidence for deviation from ΛCDM given the distance-ladder and CMB data. The odds against ΛCDM are at worst ˜10:1 when considering the Planck 2015 XIII data, regardless of outlier treatment, considerably less dramatic than naïvely implied by the 2.8σ discrepancy. These odds become ˜60:1 when an approximation to the more-discrepant Planck Intermediate XLVI likelihood is included.

Estimating drought risk across Europe from reported drought impacts, hazard indicators and vulnerability factors

NASA Astrophysics Data System (ADS)

Blauhut, V.; Stahl, K.; Stagge, J. H.; Tallaksen, L. M.; De Stefano, L.; Vogt, J.

2015-12-01

Drought is one of the most costly natural hazards in Europe. Due to its complexity, drought risk, the combination of the natural hazard and societal vulnerability, is difficult to define and challenging to detect and predict, as the impacts of drought are very diverse, covering the breadth of socioeconomic and environmental systems. Pan-European maps of drought risk could inform the elaboration of guidelines and policies to address its documented severity and impact across borders. This work (1) tests the capability of commonly applied hazard indicators and vulnerability factors to predict annual drought impact occurrence for different sectors and macro regions in Europe and (2) combines information on past drought impacts, drought hazard indicators, and vulnerability factors into estimates of drought risk at the pan-European scale. This "hybrid approach" bridges the gap between traditional vulnerability assessment and probabilistic impact forecast in a statistical modelling framework. Multivariable logistic regression was applied to predict the likelihood of impact occurrence on an annual basis for particular impact categories and European macro regions. The results indicate sector- and macro region specific sensitivities of hazard indicators, with the Standardised Precipitation Evapotranspiration Index for a twelve month aggregation period (SPEI-12) as the overall best hazard predictor. Vulnerability factors have only limited ability to predict drought impacts as single predictor, with information about landuse and water resources as best vulnerability-based predictors. (3) The application of the "hybrid approach" revealed strong regional (NUTS combo level) and sector specific differences in drought risk across Europe. The majority of best predictor combinations rely on a combination of SPEI for shorter and longer aggregation periods, and a combination of information on landuse and water resources. The added value of integrating regional vulnerability information with drought risk prediction could be proven. Thus, the study contributes to the overall understanding of drivers of drought impacts, current practice of drought indicators selection for specific application, and drought risk assessment.

Multidimensional assessment of patient condition and mutational analysis in peripheral blood, as tools to improve outcome prediction in myelodysplastic syndromes: A prospective study of the Spanish MDS group.

PubMed

Ramos, Fernando; Robledo, Cristina; Pereira, Arturo; Pedro, Carmen; Benito, Rocío; de Paz, Raquel; Del Rey, Mónica; Insunza, Andrés; Tormo, Mar; Díez-Campelo, María; Xicoy, Blanca; Salido, Eduardo; Sánchez-Del-Real, Javier; Arenillas, Leonor; Florensa, Lourdes; Luño, Elisa; Del Cañizo, Consuelo; Sanz, Guillermo F; María Hernández-Rivas, Jesús

2017-09-01

The International Prognostic Scoring System and its revised form (IPSS-R) are the most widely used indices for prognostic assessment of patients with myelodysplastic syndromes (MDS), but can only partially account for the observed variation in patient outcomes. This study aimed to evaluate the relative contribution of patient condition and mutational status in peripheral blood when added to the IPSS-R, for estimating overall survival and the risk of leukemic transformation in patients with MDS. A prospective cohort (2006-2015) of 200 consecutive patients with MDS were included in the study series and categorized according to the IPSS-R. Patients were further stratified according to patient condition (assessed using the multidimensional Lee index for older adults) and genetic mutations (peripheral blood samples screened using next-generation sequencing). The change in likelihood-ratio was tested in Cox models after adding individual covariates. The addition of the Lee index to the IPSS-R significantly improved prediction of overall survival [hazard ratio (HR) 3.02, 95% confidence interval (CI) 1.96-4.66, P < 0.001), and mutational analysis significantly improved prediction of leukemic evolution (HR 2.64, 1.56-4.46, P < 0.001). Non-leukemic death was strongly linked to patient condition (HR 2.71, 1.72-4.25, P < 0.001), but not to IPSS-R score (P = 0.35) or mutational status (P = 0.75). Adjustment for exposure to disease-modifying therapy, evaluated as a time-dependent covariate, had no effect on the proposed model's predictive ability. In conclusion, patient condition, assessed by the multidimensional Lee index and patient mutational status can improve the prediction of clinical outcomes of patients with MDS already stratified by IPSS-R. © 2017 Wiley Periodicals, Inc.

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

Ranganathan, V; Kumar, P; Bzdusek, K

Purpose: We propose a novel data-driven method to predict the achievability of clinical objectives upfront before invoking the IMRT optimization. Methods: A new metric called “Geometric Complexity (GC)” is used to estimate the achievability of clinical objectives. Here, GC is the measure of the number of “unmodulated” beamlets or rays that intersect the Region-of-interest (ROI) and the target volume. We first compute the geometric complexity ratio (GCratio) between the GC of a ROI (say, parotid) in a reference plan and the GC of the same ROI in a given plan. The GCratio of a ROI indicates the relative geometric complexitymore » of the ROI as compared to the same ROI in the reference plan. Hence GCratio can be used to predict if a defined clinical objective associated with the ROI can be met by the optimizer for a given case. Basically a higher GCratio indicates a lesser likelihood for the optimizer to achieve the clinical objective defined for a given ROI. Similarly, a lower GCratio indicates a higher likelihood for the optimizer to achieve the clinical objective defined for the given ROI. We have evaluated the proposed method on four Head and Neck cases using Pinnacle3 (version 9.10.0) Treatment Planning System (TPS). Results: Out of the total of 28 clinical objectives from four head and neck cases included in the study, 25 were in agreement with the prediction, which implies an agreement of about 85% between predicted and obtained results. The Pearson correlation test shows a positive correlation between predicted and obtained results (Correlation = 0.82, r2 = 0.64, p < 0.005). Conclusion: The study demonstrates the feasibility of the proposed method in head and neck cases for predicting the achievability of clinical objectives with reasonable accuracy.« less

Fast integration-based prediction bands for ordinary differential equation models.

PubMed

Hass, Helge; Kreutz, Clemens; Timmer, Jens; Kaschek, Daniel

2016-04-15

To gain a deeper understanding of biological processes and their relevance in disease, mathematical models are built upon experimental data. Uncertainty in the data leads to uncertainties of the model's parameters and in turn to uncertainties of predictions. Mechanistic dynamic models of biochemical networks are frequently based on nonlinear differential equation systems and feature a large number of parameters, sparse observations of the model components and lack of information in the available data. Due to the curse of dimensionality, classical and sampling approaches propagating parameter uncertainties to predictions are hardly feasible and insufficient. However, for experimental design and to discriminate between competing models, prediction and confidence bands are essential. To circumvent the hurdles of the former methods, an approach to calculate a profile likelihood on arbitrary observations for a specific time point has been introduced, which provides accurate confidence and prediction intervals for nonlinear models and is computationally feasible for high-dimensional models. In this article, reliable and smooth point-wise prediction and confidence bands to assess the model's uncertainty on the whole time-course are achieved via explicit integration with elaborate correction mechanisms. The corresponding system of ordinary differential equations is derived and tested on three established models for cellular signalling. An efficiency analysis is performed to illustrate the computational benefit compared with repeated profile likelihood calculations at multiple time points. The integration framework and the examples used in this article are provided with the software package Data2Dynamics, which is based on MATLAB and freely available at http://www.data2dynamics.org helge.hass@fdm.uni-freiburg.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A machine learning approach using EEG data to predict response to SSRI treatment for major depressive disorder.

PubMed

Khodayari-Rostamabad, Ahmad; Reilly, James P; Hasey, Gary M; de Bruin, Hubert; Maccrimmon, Duncan J

2013-10-01

The problem of identifying, in advance, the most effective treatment agent for various psychiatric conditions remains an elusive goal. To address this challenge, we investigate the performance of the proposed machine learning (ML) methodology (based on the pre-treatment electroencephalogram (EEG)) for prediction of response to treatment with a selective serotonin reuptake inhibitor (SSRI) medication in subjects suffering from major depressive disorder (MDD). A relatively small number of most discriminating features are selected from a large group of candidate features extracted from the subject's pre-treatment EEG, using a machine learning procedure for feature selection. The selected features are fed into a classifier, which was realized as a mixture of factor analysis (MFA) model, whose output is the predicted response in the form of a likelihood value. This likelihood indicates the extent to which the subject belongs to the responder vs. non-responder classes. The overall method was evaluated using a "leave-n-out" randomized permutation cross-validation procedure. A list of discriminating EEG biomarkers (features) was found. The specificity of the proposed method is 80.9% while sensitivity is 94.9%, for an overall prediction accuracy of 87.9%. There is a 98.76% confidence that the estimated prediction rate is within the interval [75%, 100%]. These results indicate that the proposed ML method holds considerable promise in predicting the efficacy of SSRI antidepressant therapy for MDD, based on a simple and cost-effective pre-treatment EEG. The proposed approach offers the potential to improve the treatment of major depression and to reduce health care costs. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Novel CPR system that predicts return of spontaneous circulation from amplitude spectral area before electric shock in ventricular fibrillation.

PubMed

Nakagawa, Yoshihide; Amino, Mari; Inokuchi, Sadaki; Hayashi, Satoshi; Wakabayashi, Tsutomu; Noda, Tatsuya

2017-04-01

Amplitude spectral area (AMSA), an index for analysing ventricular fibrillation (VF) waveforms, is thought to predict the return of spontaneous circulation (ROSC) after electric shocks, but its validity is unconfirmed. We developed an equation to predict ROSC, where the change in AMSA (ΔAMSA) is added to AMSA measured immediately before the first shock (AMSA1). We examine the validity of this equation by comparing it with the conventional AMSA1-only equation. We retrospectively investigated 285 VF patients given prehospital electric shocks by emergency medical services. ΔAMSA was calculated by subtracting AMSA1 from last AMSA immediately before the last prehospital electric shock. Multivariate logistic regression analysis was performed using post-shock ROSC as a dependent variable. Analysis data were subjected to receiver operating characteristic curve analysis, goodness-of-fit testing using a likelihood ratio test, and the bootstrap method. AMSA1 (odds ratio (OR) 1.151, 95% confidence interval (CI) 1.086-1.220) and ΔAMSA (OR 1.289, 95% CI 1.156-1.438) were independent factors influencing ROSC induction by electric shock. Area under the curve (AUC) for predicting ROSC was 0.851 for AMSA1-only and 0.891 for AMSA1+ΔAMSA. Compared with the AMSA1-only equation, the AMSA1+ΔAMSA equation had significantly better goodness-of-fit (likelihood ratio test P<0.001) and showed good fit in the bootstrap method. Post-shock ROSC was accurately predicted by adding ΔAMSA to AMSA1. AMSA-based ROSC prediction enables application of electric shock to only those patients with high probability of ROSC, instead of interrupting chest compressions and delivering unnecessary shocks to patients with low probability of ROSC. Copyright © 2017 Elsevier B.V. All rights reserved.

Early improvement as a resilience signal predicting later remission to antidepressant treatment in patients with Major Depressive Disorder: Systematic review and meta-analysis.

PubMed

Wagner, Stefanie; Engel, Alice; Engelmann, Jan; Herzog, David; Dreimüller, Nadine; Müller, Marianne B; Tadić, André; Lieb, Klaus

2017-11-01

Early improvement of depressive symptoms during the first two weeks of antidepressant treatment has been discussed to be a resilience signal predicting a later positive treatment outcome in patients with Major Depressive Disorder (MDD). However, the predictive value of early improvement varies between studies, and the use of different antidepressants may explain heterogeneous results. The objective of this review was to assess the predictive value of early improvement on later response and remission and to identify antidepressants with the highest chance of early improvement. We included 17 randomized controlled trials investigating early improvement in 14,779 adult patients with MDD comparing monotherapy with an antidepressant against placebo or another antidepressant drug. 62% (range: 35-85%) of patients treated with an antidepressant and 47% (range: 21-69%) with placebo were early improver, defined as a >20%/25% symptom reduction after two weeks of treatment. Early improvement predicted response and remission after 5-12 weeks of treatment with high sensitivity (85%; 95%-CI: 84.3 to 85.7) and low to moderate specificity (54%; 95%-CI: 53.1 to 54.9). Early improver had a 8.37 fold (6.97-10.05) higher likelihood to become responder and a 6.38 fold (5.07-8.02) higher likelihood to be remitter at endpoint than non-improver. The highest early improver rates were achieved in patients treated with mirtazapine or a tricyclic antidepressant. This finding of a high predictive value of early improvement on treatment outcome may be important for treatment decisions in the early course of antidepressant treatment. Further studies should test the efficacy of such early treatment decisions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Papillary Thyroid Microcarcinomas: Big Decisions for a Small Tumor

PubMed Central

Haymart, Megan Rist; Cayo, Max; Chen, Herbert

2016-01-01

Background The clinical significance of papillary thyroid microcarcinoma (PTMC) is debated, and therefore the rise in incidence of PTMC creates management dilemmas. The following study evaluates factors influencing decisions to treat. Materials and Methods Between 1994 and 2007, 1361 patients underwent thyroid surgery at a single institution. Of these patients, 107 were diagnosed with PTMC. The type of surgical intervention, likelihood of referral to an endocrinologist, use of radioactive iodine, and administration of suppressive doses of levothyroxine (LT4) were analyzed in relation to patient and tumor characteristics. Results Multifocality and larger size were predictive of which patients underwent total thyroidectomy on multivariable logistic regression (P = .004 and P = .001, respectively). Larger mean tumor size, 0.62 ± 0.004 versus 0.34 ± 0.006 cm, was independently associated with increased likelihood of endocrine referral (P = .029). Multifocality, diagnosis via FNA preoperatively, larger mean size of PTMC, and endocrine referral were independently associated with increased likelihood of receiving radioactive iodine (RAI). On multivariable analysis, only total thyroidectomy and endocrine referral were independently associated with treatment with suppressive doses of LT4 (P = .001 and .001, respectively). In the 47 patients with unifocal PTMC <0.8 cm diameter, the mean size of tumor focus was larger in the subgroup undergoing total thyroidectomy (P = .004). Surprisingly, in these very low risk PTMC patients, the likelihood of RAI for remnant ablation was independently associated with younger patient age (P = .029). In the subgroup with unifocal <0.8 cm disease, the mean age of patients receiving RAI was 34 ± 3.3 years versus 48 ± 2.3 years in those not receiving RAI (P = .003). Conclusions The decision tree in the management of PTMC is beginning at the time of surgery, and referral to endocrinology is associated with a more aggressive course. Younger age is predictive of RAI administration in the lowest-risk PTMC patients. PMID:19653044

Probabilistic Modeling and Evaluation of Surf Zone Injury Occurrence along the Delaware Coast

NASA Astrophysics Data System (ADS)

Doelp, M.; Puleo, J. A.

2017-12-01

Beebe Healthcare in Lewes, DE collected along the DE coast surf zone injury (SZI) data for seven summer seasons from 2010 through 2016. Data include, but are not limited to, time of injury, gender, age, and activity. Over 2000 injuries were recorded over the seven year period, including 116 spinal injuries and three fatalities. These injuries are predominantly wave related incidents including wading (41%), bodysurfing (26%), and body-boarding (20%). Despite the large number of injuries, beach associated hazards do not receive the same level of awareness that rip currents receive. Injury population statistics revealed those between the ages of 11 and 15 years old suffered the greatest proportion of injuries (18.8%). Male water users were twice as likely to sustain injury as their female counterparts. Also, non-locals were roughly six times more likely to sustain injury than locals. In 2016, five or more injuries occurred for 18.5% of the days sampled, and no injuries occurred for 31.4% of the sample days. The episodic nature of injury occurrence and population statistics indicate the importance of environmental conditions and human behavior on surf zone injuries. Higher order statistics are necessary to effectively assess SZI cause and likelihood of occurrence on a particular day. A Bayesian network using Netica software (Norsys) was constructed to model SZI and predict changes in injury likelihood on an hourly basis. The network incorporates environmental data collected by weather stations, NDBC buoy #44009, USACE buoy at Bethany Beach, and by researcher personnel on the beach. The Bayesian model includes prior (e.g., historic) information to infer relationships between provided parameters. Sensitivity analysis determined the most influential variables to injury likelihood are population, water temperature, nearshore wave height, beach slope, and the day of the week. Forecasting during the 2017 summer season will test model ability to predict injury likelihood.

A Sequential Ensemble Prediction System at Convection Permitting Scales

NASA Astrophysics Data System (ADS)

Milan, M.; Simmer, C.

2012-04-01

A Sequential Assimilation Method (SAM) following some aspects of particle filtering with resampling, also called SIR (Sequential Importance Resampling), is introduced and applied in the framework of an Ensemble Prediction System (EPS) for weather forecasting on convection permitting scales, with focus to precipitation forecast. At this scale and beyond, the atmosphere increasingly exhibits chaotic behaviour and non linear state space evolution due to convectively driven processes. One way to take full account of non linear state developments are particle filter methods, their basic idea is the representation of the model probability density function by a number of ensemble members weighted by their likelihood with the observations. In particular particle filter with resampling abandons ensemble members (particles) with low weights restoring the original number of particles adding multiple copies of the members with high weights. In our SIR-like implementation we substitute the likelihood way to define weights and introduce a metric which quantifies the "distance" between the observed atmospheric state and the states simulated by the ensemble members. We also introduce a methodology to counteract filter degeneracy, i.e. the collapse of the simulated state space. To this goal we propose a combination of resampling taking account of simulated state space clustering and nudging. By keeping cluster representatives during resampling and filtering, the method maintains the potential for non linear system state development. We assume that a particle cluster with initially low likelihood may evolve in a state space with higher likelihood in a subsequent filter time thus mimicking non linear system state developments (e.g. sudden convection initiation) and remedies timing errors for convection due to model errors and/or imperfect initial condition. We apply a simplified version of the resampling, the particles with highest weights in each cluster are duplicated; for the model evolution for each particle pair one particle evolves using the forward model; the second particle, however, is nudged to the radar and satellite observation during its evolution based on the forward model.

Prospectively Evaluating the Collaboratory for the Study of Earthquake Predictability: An Evaluation of the UCERF2 and Updated Five-Year RELM Forecasts

NASA Astrophysics Data System (ADS)

Strader, Anne; Schneider, Max; Schorlemmer, Danijel; Liukis, Maria

2016-04-01

The Collaboratory for the Study of Earthquake Predictability (CSEP) was developed to rigorously test earthquake forecasts retrospectively and prospectively through reproducible, completely transparent experiments within a controlled environment (Zechar et al., 2010). During 2006-2011, thirteen five-year time-invariant prospective earthquake mainshock forecasts developed by the Regional Earthquake Likelihood Models (RELM) working group were evaluated through the CSEP testing center (Schorlemmer and Gerstenberger, 2007). The number, spatial, and magnitude components of the forecasts were compared to the respective observed seismicity components using a set of consistency tests (Schorlemmer et al., 2007, Zechar et al., 2010). In the initial experiment, all but three forecast models passed every test at the 95% significance level, with all forecasts displaying consistent log-likelihoods (L-test) and magnitude distributions (M-test) with the observed seismicity. In the ten-year RELM experiment update, we reevaluate these earthquake forecasts over an eight-year period from 2008-2016, to determine the consistency of previous likelihood testing results over longer time intervals. Additionally, we test the Uniform California Earthquake Rupture Forecast (UCERF2), developed by the U.S. Geological Survey (USGS), and the earthquake rate model developed by the California Geological Survey (CGS) and the USGS for the National Seismic Hazard Mapping Program (NSHMP) against the RELM forecasts. Both the UCERF2 and NSHMP forecasts pass all consistency tests, though the Helmstetter et al. (2007) and Shen et al. (2007) models exhibit greater information gain per earthquake according to the T- and W- tests (Rhoades et al., 2011). Though all but three RELM forecasts pass the spatial likelihood test (S-test), multiple forecasts fail the M-test due to overprediction of the number of earthquakes during the target period. Though there is no significant difference between the UCERF2 and NSHMP models, residual scores show that the NSHMP model is preferred in locations with earthquake occurrence, due to the lower seismicity rates forecasted by the UCERF2 model.

The predictive value of magnetic resonance imaging of retinoblastoma for the likelihood of high-risk pathologic features.

PubMed

Hiasat, Jamila G; Saleh, Alaa; Al-Hussaini, Maysa; Al Nawaiseh, Ibrahim; Mehyar, Mustafa; Qandeel, Monther; Mohammad, Mona; Deebajah, Rasha; Sultan, Iyad; Jaradat, Imad; Mansour, Asem; Yousef, Yacoub A

2018-06-01

To evaluate the predictive value of magnetic resonance imaging in retinoblastoma for the likelihood of high-risk pathologic features. A retrospective study of 64 eyes enucleated from 60 retinoblastoma patients. Contrast-enhanced magnetic resonance imaging was performed before enucleation. Main outcome measures included demographics, laterality, accuracy, sensitivity, and specificity of magnetic resonance imaging in detecting high-risk pathologic features. Optic nerve invasion and choroidal invasion were seen microscopically in 34 (53%) and 28 (44%) eyes, respectively, while they were detected in magnetic resonance imaging in 22 (34%) and 15 (23%) eyes, respectively. The accuracy of magnetic resonance imaging in detecting prelaminar invasion was 77% (sensitivity 89%, specificity 98%), 56% for laminar invasion (sensitivity 27%, specificity 94%), 84% for postlaminar invasion (sensitivity 42%, specificity 98%), and 100% for optic cut edge invasion (sensitivity100%, specificity 100%). The accuracy of magnetic resonance imaging in detecting focal choroidal invasion was 48% (sensitivity 33%, specificity 97%), and 84% for massive choroidal invasion (sensitivity 53%, specificity 98%), and the accuracy in detecting extrascleral extension was 96% (sensitivity 67%, specificity 98%). Magnetic resonance imaging should not be the only method to stratify patients at high risk from those who are not, eventhough it can predict with high accuracy extensive postlaminar optic nerve invasion, massive choroidal invasion, and extrascleral tumor extension.

Development and validation of a parent-report measure for detection of cognitive delay in infancy.

PubMed

Schafer, Graham; Genesoni, Lucia; Boden, Greg; Doll, Helen; Jones, Rosamond A K; Gray, Ron; Adams, Eleri; Jefferson, Ros

2014-12-01

To develop a brief, parent-completed instrument (ERIC - Early Report by Infant Caregivers) for detection of cognitive delay in 10- to 24-month-olds born preterm, or of low birthweight, or with perinatal complications, and to establish ERIC's diagnostic properties. Scores for ERIC were collected from the parents of 317 children meeting ≥inclusion criterion (birthweight <1500 g, gestational age <34 completed weeks, 5 min Apgar score <7, or presence of hypoxic-ischaemic encephalopathy) and no exclusion criteria. Children were assessed using a criterion score of below 80 on the Bayley Scales of Infant and Toddler Development-III cognitive scale. Items were retained according to their individual associations with delay. Sensitivity, specificity, and positive and negative predictive values were estimated and a truncated ERIC was developed for use in children <14 months old. ERIC correctly detected developmental delay in 17 out of 18 children in the sample, with 94.4% sensitivity, 76.9% specificity, 19.8% positive predictive value, 99.6% negative predictive value, 4.09 likelihood ratio positive, and 0.07 likelihood ratio negative. ERIC has potential value as a quickly administered diagnostic instrument for the absence of early cognitive delay in 10- to 24-month-old preterm infants and as a screen for cognitive delay. © 2014 Mac Keith Press.

The Influence of Subjective Social Status on Vulnerability to Postpartum Smoking Among Young Pregnant Women

PubMed Central

Reitzel, Lorraine R.; Vidrine, Jennifer I.; Li, Yisheng; Mullen, Patricia D.; Velasquez, Mary M.; Cinciripini, Paul M.; Cofta-Woerpel, Ludmila; Greisinger, Anthony; Wetter, David W.

2007-01-01

Objectives. Associations between subjective social status, a subjective measure of socioeconomic status, and predictors of risk for postpartum smoking were examined among 123 pregnant women (aged 18–24 years) who stopped smoking because of pregnancy. The goal was to identify how subjective social status might influence the risk for postpartum smoking and to elucidate targets for intervention. Methods. We used multiple regression equations to examine the predictive relations between subjective social status and tobacco dependence, self-rated likelihood of postpartum smoking, confidence, temptations, positive and negative affect, depression, stress, and social support. Adjusted analyses were also conducted with control for race/ethnicity, education, income, and whether participant had a partner or not (partner status). Results. In unadjusted and adjusted analyses, subjective social status predicted tobacco dependence, likelihood of postpartum smoking, confidence, temptations, positive affect, negative affect, and social support. Adjusted analyses predicting depression and stress approached significance. Conclusions. Among young pregnant women who quit smoking because of pregnancy, low subjective social status was associated with a constellation of characteristics indicative of increased vulnerability to postpartum smoking. Subjective social status provided unique information on risk for postpartum smoking over and above the effects of race/ethnicity, objective socioeconomic status, and partner status. PMID:17600249

Diagnostic strategies using physical examination are minimally useful in defining carpal tunnel syndrome in population-based research studies.

PubMed

Descatha, A; Dale, A-M; Franzblau, A; Coomes, J; Evanoff, B

2010-02-01

We evaluated the utility of physical examination manoeuvres in the prediction of carpal tunnel syndrome (CTS) in a population-based research study. We studied a cohort of 1108 newly employed workers in several industries. Each worker completed a symptom questionnaire, a structured physical examination and nerve conduction study. For each hand, our CTS case definition required both median nerve conduction abnormality and symptoms classified as "classic" or "probable" on a hand diagram. We calculated the positive predictive values and likelihood ratios for physical examination manoeuvres in subjects with and without symptoms. The prevalence of CTS in our cohort was 1.2% for the right hand and 1.0% for the left hand. The likelihood ratios of a positive test for physical provocative tests ranged from 2.0 to 3.3, and those of a negative test from 0.3 to 0.9. The post-test probability of positive testing was <50% for all strategies tested. Our study found that physical examination, alone or in combination with symptoms, was not predictive of CTS in a working population. We suggest using specific symptoms as a first-level screening tool, and nerve conduction study as a confirmatory test, as a case definition strategy in research settings.

Prediction of antiepileptic drug treatment outcomes using machine learning.

PubMed

Colic, Sinisa; Wither, Robert G; Lang, Min; Zhang, Liang; Eubanks, James H; Bardakjian, Berj L

2017-02-01

Antiepileptic drug (AED) treatments produce inconsistent outcomes, often necessitating patients to go through several drug trials until a successful treatment can be found. This study proposes the use of machine learning techniques to predict epilepsy treatment outcomes of commonly used AEDs. Machine learning algorithms were trained and evaluated using features obtained from intracranial electroencephalogram (iEEG) recordings of the epileptiform discharges observed in Mecp2-deficient mouse model of the Rett Syndrome. Previous work have linked the presence of cross-frequency coupling (I CFC ) of the delta (2-5 Hz) rhythm with the fast ripple (400-600 Hz) rhythm in epileptiform discharges. Using the I CFC to label post-treatment outcomes we compared support vector machines (SVMs) and random forest (RF) machine learning classifiers for providing likelihood scores of successful treatment outcomes. (a) There was heterogeneity in AED treatment outcomes, (b) machine learning techniques could be used to rank the efficacy of AEDs by estimating likelihood scores for successful treatment outcome, (c) I CFC features yielded the most effective a priori identification of appropriate AED treatment, and (d) both classifiers performed comparably. Machine learning approaches yielded predictions of successful drug treatment outcomes which in turn could reduce the burdens of drug trials and lead to substantial improvements in patient quality of life.

Prediction of antiepileptic drug treatment outcomes using machine learning

NASA Astrophysics Data System (ADS)

Colic, Sinisa; Wither, Robert G.; Lang, Min; Zhang, Liang; Eubanks, James H.; Bardakjian, Berj L.

2017-02-01

Objective. Antiepileptic drug (AED) treatments produce inconsistent outcomes, often necessitating patients to go through several drug trials until a successful treatment can be found. This study proposes the use of machine learning techniques to predict epilepsy treatment outcomes of commonly used AEDs. Approach. Machine learning algorithms were trained and evaluated using features obtained from intracranial electroencephalogram (iEEG) recordings of the epileptiform discharges observed in Mecp2-deficient mouse model of the Rett Syndrome. Previous work have linked the presence of cross-frequency coupling (I CFC) of the delta (2-5 Hz) rhythm with the fast ripple (400-600 Hz) rhythm in epileptiform discharges. Using the I CFC to label post-treatment outcomes we compared support vector machines (SVMs) and random forest (RF) machine learning classifiers for providing likelihood scores of successful treatment outcomes. Main results. (a) There was heterogeneity in AED treatment outcomes, (b) machine learning techniques could be used to rank the efficacy of AEDs by estimating likelihood scores for successful treatment outcome, (c) I CFC features yielded the most effective a priori identification of appropriate AED treatment, and (d) both classifiers performed comparably. Significance. Machine learning approaches yielded predictions of successful drug treatment outcomes which in turn could reduce the burdens of drug trials and lead to substantial improvements in patient quality of life.

Relationships between the Survey of Organizational Research Climate (SORC) and self-reported research practices.

PubMed

Crain, A Lauren; Martinson, Brian C; Thrush, Carol R

2013-09-01

The Survey of Organizational Research Climate (SORC) is a validated tool to facilitate promotion of research integrity and research best practices. This work uses the SORC to assess shared and individual perceptions of the research climate in universities and academic departments and relate these perceptions to desirable and undesirable research practices. An anonymous web- and mail-based survey was administered to randomly selected biomedical and social science faculty and postdoctoral fellows in the United States. Respondents reported their perceptions of the research climates at their universities and primary departments, and the frequency with which they engaged in desirable and undesirable research practices. More positive individual perceptions of the research climate in one's university or department were associated with higher likelihoods of desirable, and lower likelihoods of undesirable, research practices. Shared perceptions of the research climate tended to be similarly predictive of both desirable and undesirable research practices as individuals' deviations from these shared perceptions. Study results supported the central prediction that more positive SORC-measured perceptions of the research climate were associated with more positive reports of research practices. There were differences with respect to whether shared or individual climate perceptions were related to desirable or undesirable practices but the general pattern of results provide empirical evidence that the SORC is predictive of self-reported research behavior.

An original approach was used to better evaluate the capacity of a prognostic marker using published survival curves.

PubMed

Dantan, Etienne; Combescure, Christophe; Lorent, Marine; Ashton-Chess, Joanna; Daguin, Pascal; Classe, Jean-Marc; Giral, Magali; Foucher, Yohann

2014-04-01

Predicting chronic disease evolution from a prognostic marker is a key field of research in clinical epidemiology. However, the prognostic capacity of a marker is not systematically evaluated using the appropriate methodology. We proposed the use of simple equations to calculate time-dependent sensitivity and specificity based on published survival curves and other time-dependent indicators as predictive values, likelihood ratios, and posttest probability ratios to reappraise prognostic marker accuracy. The methodology is illustrated by back calculating time-dependent indicators from published articles presenting a marker as highly correlated with the time to event, concluding on the high prognostic capacity of the marker, and presenting the Kaplan-Meier survival curves. The tools necessary to run these direct and simple computations are available online at http://www.divat.fr/en/online-calculators/evalbiom. Our examples illustrate that published conclusions about prognostic marker accuracy may be overoptimistic, thus giving potential for major mistakes in therapeutic decisions. Our approach should help readers better evaluate clinical articles reporting on prognostic markers. Time-dependent sensitivity and specificity inform on the inherent prognostic capacity of a marker for a defined prognostic time. Time-dependent predictive values, likelihood ratios, and posttest probability ratios may additionally contribute to interpret the marker's prognostic capacity. Copyright © 2014 Elsevier Inc. All rights reserved.

Rehabilitation services after the implementation of the nursing home prospective payment system: differences related to patient and nursing home characteristics.

PubMed

Murray, Patrick K; Love, Thomas E; Dawson, Neal V; Thomas, Charles L; Cebul, Randall D

2005-11-01

The prospective payment system (PPS) for nursing homes was designed to curtail the rapid expansion of Medicare costs for skilled nursing care. This study examines the changes that occurred in nursing home patients and rehabilitation services following the PPS. Free-standing Medicare and/or Medicaid certified nursing homes in Ohio. The percent of new admissions receiving therapy and the amount of rehabilitation therapy provided. A total of 7006 first admissions in 1994-6 (pre-PPS) and 61,569 first admissions in 2000-1 (post-PPS). A logistic model predicting likelihood of rehabilitation was developed and validated in pre-PPS admissions and applied to the post-PPS patients. Rehabilitation services were compared in the pre-PPS and post-PPS cohorts overall, stratified by quintile of predicted score, diagnosis group, and by nursing home profit status. Post-PPS patients had less cognitive impairment, more depression, and more family support. The amount of rehabilitation services declined the most in the higher quintiles of predicted likelihood of rehabilitation and among patients with stroke. The percent of patients receiving rehabilitation services increased the most in the lowest quintile and among patients with medical conditions. These changes were greater in for-profit nursing homes. The implementation of the PPS in nursing homes has been associated with a decrease in the amount of rehabilitation services, targeted at those predicted to receive higher amounts and an increased frequency of providing services targeted at those predicted to be less likely to receive them. The outcomes of the changes deserve further study.

Predicting the Timing of Maturational Spurts in Skeletal Age

PubMed Central

Nahhas, Ramzi W.; Sherwood, Richard J.; Chumlea, Wm. Cameron; Towne, Bradford; Duren, Dana L.

2014-01-01

Measures of maturity provide windows into the timing and tempo of childhood growth and maturation. Delayed maturation in a single child, or systemically in a population, can result from either genetic or environmental factors. In terms of the skeleton, delayed maturation may result in short stature or indicate another underlying issue. Thus, prediction of the timing of a maturational spurt is often desirable in order to determine the likelihood that a child will catch up to their chronological age peers. Serial data from the Fels Longitudinal Study were used to predict future skeletal age conditional on current skeletal age and to predict the timing of maturational spurts. For children who were delayed relative to their chronological age peers, the like-lihood of catch-up maturation increased through the average age of onset of puberty and decreased prior to the average age of peak height velocity. For boys, the probability of an imminent maturational spurt was higher for those who were less mature. For girls aged 11 to 13 years, however, this probability was higher for those who were more mature, potentially indicating the presence of a skeletal maturation plateau between multiple spurts. The prediction model, available on the web, is most relevant to children of European ancestry living in the Midwestern US. Our model may also provide insight into the tempo of maturation for children in other populations, but must be applied with caution if those populations are known to have high burdens of environmental stressors not typical of the Midwestern US. Am J Phys Anthropol 150:68–75, 2013. PMID:23283666

Mallampati test as a predictor of laryngoscopic view.

PubMed

Adamus, Milan; Fritscherova, Sarka; Hrabalek, Lumir; Gabrhelik, Tomas; Zapletalova, Jana; Janout, Vladimir

2010-12-01

To determine the accuracy of the modified Mallampati test for predicting difficult tracheal intubation. A cross-sectional, clinical, observational, non-blinded study. A quality analysis of anesthetic care. Operating theatres and department of anesthesiology in a university hospital. Following the local ethics committee approval and patients' informed consent to anesthesia, all adult patients (> 18 yrs) presenting for any type of non-emergency surgical procedures under general anesthesia requiring endotracheal intubation were enrolled. Prior to anesthesia, Samsoon and Young's modification of the Mallampati test (modified Mallampati test) was performed. Following induction, the anesthesiologist described the laryngoscopic view using the Cormack-Lehane scale. Classes 3 or 4 of the modified Mallampati test were considered a predictor of difficult intubation. Grades 3 or 4 of the Cormack-Lehane classification of the laryngoscopic view were defined as impaired glottic exposure. The sensitivity, specificity, positive and negative predictive value, relative risk, likelihood ratio and accuracy of the modified Mallampati test were calculated on 2x2 contingency tables. Of the total 1,518 patients enrolled, 48 had difficult intubation (3.2%). We failed to detect as many as 35.4% patients in whom glottis exposure during direct laryngoscopy was inadequate (sensitivity 0.646). Compared to the original article by Mallampati, we found lower specificity (0.824 vs. 0.995), lower positive predictive value (0.107 vs. 0.933), higher negative predictive value (0.986 vs. 0.928), lower likelihood ratio (3.68 vs. 91.0) and accuracy (0.819 vs. 0.929). When used as a single examination, the modified Mallampati test is of limited value in predicting difficult intubation.

Therapeutic Misconception in Research Subjects: Development and Validation of a Measure

PubMed Central

Appelbaum, Paul S.; Anatchkova, Milena; Albert, Karen; Dunn, Laura B.; Lidz, Charles W.

2013-01-01

Background Therapeutic misconception (TM), which occurs when research subjects fail to appreciate the distinction between the imperatives of clinical research and ordinary treatment, may undercut the process of obtaining meaningful consent to clinical research participation. Previous studies have found TM is widespread, but progress in addressing TM has been stymied by the absence of a validated method for assessing its presence. Purpose The goal of this study was to develop and validate a theoretically grounded measure of TM, assess its diagnostic accuracy, and test previous findings regarding its prevalence. Methods 220 participants were recruited from clinical trials at 4 academic medical centers in the U.S. Participants completed a 28-item Likert-type questionnaire to assess the presence of beliefs associated with TM, and a semi-structured TM interview designed to elicit their perceptions of the nature of the clinical trial in which they were participating. Data from the questionnaires were subjected to factor analysis and items with poor factor loadings were excluded. This resulted in a 10-item scale, with 3 strongly correlated factors and excellent internal consistency; the fit indices of the model across 10 training sets were consistent with the original results, suggesting a stable factor solution. Results The scale was validated against the TM interview, with significantly higher scores among subjects coded as displaying evidence of TM. ROC analysis based on a 10-fold internal cross-validation yielded AUC=.682 for any evidence of TM. When sensitivity (0.72) and specificity (0.61) were both optimized, Positive Predictive Value was 0.65 and Negative Predictive Value was 0.68, with a Positive Likelihood Ratio of 1.89, and a Negative Likelihood Ratio of 0.47. 50.5% (n=101) of participants manifested evidence of TM on the TM interview, a somewhat lower rate than in most previous studies. Limitations The predictive value of the scale compared with the “gold standard” clinical interview is modest, although similar to other instruments based on self-report assessing states of mind rather than discrete symptoms. Thus, although the scale can offer evidence of which subjects are at risk for distortions in their decisions and to what degree, it will not allow researchers to conclude definitively that TM is present in a given subject. Conclusions The development of a reliable and valid TM scale, even with modest predictive power, should permit investigators in clinical trials to identify subjects with tendencies to misinterpret the nature of the situation and to provide additional information to them. It should also stimulate research on how best to decrease TM and facilitate meaningful informed consent to clinical research. PMID:22942217

Bilirubin nomogram for prediction of significant hyperbilirubinemia in north Indian neonates.

PubMed

Pathak, Umesh; Chawla, Deepak; Kaur, Saranjit; Jain, Suksham

2013-04-01

(i) To construct hour-specific serum total bilirubin (STB) nomogram in neonates born at =35 weeks of gestation; (ii)To evaluate efficacy of pre-discharge bilirubin measurement in predicting hyperbilirubinemia needing treatment. Diagnostic test performance in a prospective cohort study. Teaching hospital in Northern India. Healthy neonates with gestation =35 weeks or birth weight =2000 g. Serum total bilirubin was measured in all enrolled neonates at 24 ± 6, 72-96 and 96-144 h of postnatal age and when indicated clinically. Neonates were followed up during hospital stay and after discharge till completion of 7th postnatal day. Key outcome was significant hyperbilirubinemia (SHB) defined as need of phototherapy based on modified American Academy of Pediatrics (AAP) guidelines. In neonates born at 38 or more weeks of gestation middle line and in neonates born at 37 or less completed weeks of gestation, lower line of phototherapy thresholds were used to initiate phototherapy. For construction of nomogram, STB values were clubbed in six-hour epochs (age ± 3 hours) for postnatal age up to 48 h and twelve-hour epochs (age ± 6 hours) for age beyond 48 h. Predictive ability of the nomogram was assessed by calculating sensitivity, specificity, positive predictive value, negative predictive value and likelihood ratio, by plotting receiver-operating characteristics (ROC) curve and calculating c-statistic. 997 neonates (birth weight: 2627 ± 536 g, gestation: 37.8 ± 1.5 weeks) were enrolled, of which 931 completed followup. Among enrolled neonates 344 (34.5%) were low birth weight. Rate of exclusive breastfeeding during hospital stay was more than 80%. Bilirubin nomogram was constructed using 40th, 75th and 95th percentile values of hour-specific bilirubin. Pre-discharge STB of =95th percentile was assigned to be in high-risk zone, between 75th and 94th centile in upper-intermediate risk zone, between 40th and 74th centile in lower-intermediate risk zone and below 40th percentile in low-risk zone. Among 49 neonates with pre-discharge STB in high risk zone. 34 developed SHB (positive predictive value: 69.4%, sensitivity: 17.1%, positive likelihood ratio: 8.26). Among 342 neonates with pre-discharge STB in low risk zone, 32 developed PHB (negative predictive value: 90.6% and specificity: 42.5%, positive likelihood ratio: 0.37). Area under curve for this risk assessment strategy was 0.73. Hour-specific bilirubin nomogram and STB measurement can be used for predicting subsequent need of phototherapy. Further studies are needed to validate performance of risk demarcation zones defined in this hour-specific bilirubin nomogram.

Towards Adaptive Educational Assessments: Predicting Student Performance using Temporal Stability and Data Analytics in Learning Management Systems

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

Thakur, Gautam; Olama, Mohammed M; McNair, Wade

Data-driven assessments and adaptive feedback are becoming a cornerstone research in educational data analytics and involve developing methods for exploring the unique types of data that come from the educational context. For example, predicting college student performance is crucial for both the students and educational institutions. It can support timely intervention to prevent students from failing a course, increasing efficacy of advising functions, and improving course completion rate. In this paper, we present our efforts in using data analytics that enable educationists to design novel data-driven assessment and feedback mechanisms. In order to achieve this objective, we investigate temporal stabilitymore » of students grades and perform predictive analytics on academic data collected from 2009 through 2013 in one of the most commonly used learning management systems, called Moodle. First, we have identified the data features useful for assessments and predicting student outcomes such as students scores in homework assignments, quizzes, exams, in addition to their activities in discussion forums and their total Grade Point Average(GPA) at the same term they enrolled in the course. Second, time series models in both frequency and time domains are applied to characterize the progression as well as overall projections of the grades. In particular, the model analyzed the stability as well as fluctuation of grades among students during the collegiate years (from freshman to senior) and disciplines. Third, Logistic Regression and Neural Network predictive models are used to identify students as early as possible who are in danger of failing the course they are currently enrolled in. These models compute the likelihood of any given student failing (or passing) the current course. The time series analysis indicates that assessments and continuous feedback are critical for freshman and sophomores (even with easy courses) than for seniors, and those assessments may be provided using the predictive models. Numerical results are presented to evaluate and compare the performance of the developed models and their predictive accuracy. Our results show that there are strong ties associated with the first few weeks for coursework and they have an impact on the design and distribution of individual modules.« less

Integrating data from randomized controlled trials and observational studies to predict the response to pregabalin in patients with painful diabetic peripheral neuropathy.

PubMed

Alexander, Joe; Edwards, Roger A; Savoldelli, Alberto; Manca, Luigi; Grugni, Roberto; Emir, Birol; Whalen, Ed; Watt, Stephen; Brodsky, Marina; Parsons, Bruce

2017-07-20

More patient-specific medical care is expected as more is learned about variations in patient responses to medical treatments. Analytical tools enable insights by linking treatment responses from different types of studies, such as randomized controlled trials (RCTs) and observational studies. Given the importance of evidence from both types of studies, our goal was to integrate these types of data into a single predictive platform to help predict response to pregabalin in individual patients with painful diabetic peripheral neuropathy (pDPN). We utilized three pivotal RCTs of pregabalin (398 North American patients) and the largest observational study of pregabalin (3159 German patients). We implemented a hierarchical cluster analysis to identify patient clusters in the Observational Study to which RCT patients could be matched using the coarsened exact matching (CEM) technique, thereby creating a matched dataset. We then developed autoregressive moving average models (ARMAXs) to estimate weekly pain scores for pregabalin-treated patients in each cluster in the matched dataset using the maximum likelihood method. Finally, we validated ARMAX models using Observational Study patients who had not matched with RCT patients, using t tests between observed and predicted pain scores. Cluster analysis yielded six clusters (287-777 patients each) with the following clustering variables: gender, age, pDPN duration, body mass index, depression history, pregabalin monotherapy, prior gabapentin use, baseline pain score, and baseline sleep interference. CEM yielded 1528 unique patients in the matched dataset. The reduction in global imbalance scores for the clusters after adding the RCT patients (ranging from 6 to 63% depending on the cluster) demonstrated that the process reduced the bias of covariates in five of the six clusters. ARMAX models of pain score performed well (R 2 : 0.85-0.91; root mean square errors: 0.53-0.57). t tests did not show differences between observed and predicted pain scores in the 1955 patients who had not matched with RCT patients. The combination of cluster analyses, CEM, and ARMAX modeling enabled strong predictive capabilities with respect to pain scores. Integrating RCT and Observational Study data using CEM enabled effective use of Observational Study data to predict patient responses.

Case complexity scores in congenital heart surgery: a comparative study of the Aristotle Basic Complexity score and the Risk Adjustment in Congenital Heart Surgery (RACHS-1) system.

PubMed

Al-Radi, Osman O; Harrell, Frank E; Caldarone, Christopher A; McCrindle, Brian W; Jacobs, Jeffrey P; Williams, M Gail; Van Arsdell, Glen S; Williams, William G

2007-04-01

The Aristotle Basic Complexity score and the Risk Adjustment in Congenital Heart Surgery system were developed by consensus to compare outcomes of congenital cardiac surgery. We compared the predictive value of the 2 systems. Of all index congenital cardiac operations at our institution from 1982 to 2004 (n = 13,675), we were able to assign an Aristotle Basic Complexity score, a Risk Adjustment in Congenital Heart Surgery score, and both scores to 13,138 (96%), 11,533 (84%), and 11,438 (84%) operations, respectively. Models of in-hospital mortality and length of stay were generated for Aristotle Basic Complexity and Risk Adjustment in Congenital Heart Surgery using an identical data set in which both Aristotle Basic Complexity and Risk Adjustment in Congenital Heart Surgery scores were assigned. The likelihood ratio test for nested models and paired concordance statistics were used. After adjustment for year of operation, the odds ratios for Aristotle Basic Complexity score 3 versus 6, 9 versus 6, 12 versus 6, and 15 versus 6 were 0.29, 2.22, 7.62, and 26.54 (P < .0001). Similarly, odds ratios for Risk Adjustment in Congenital Heart Surgery categories 1 versus 2, 3 versus 2, 4 versus 2, and 5/6 versus 2 were 0.23, 1.98, 5.80, and 20.71 (P < .0001). Risk Adjustment in Congenital Heart Surgery added significant predictive value over Aristotle Basic Complexity (likelihood ratio chi2 = 162, P < .0001), whereas Aristotle Basic Complexity contributed much less predictive value over Risk Adjustment in Congenital Heart Surgery (likelihood ratio chi2 = 13.4, P = .009). Neither system fully adjusted for the child's age. The Risk Adjustment in Congenital Heart Surgery scores were more concordant with length of stay compared with Aristotle Basic Complexity scores (P < .0001). The predictive value of Risk Adjustment in Congenital Heart Surgery is higher than that of Aristotle Basic Complexity. The use of Aristotle Basic Complexity or Risk Adjustment in Congenital Heart Surgery as risk stratification and trending tools to monitor outcomes over time and to guide risk-adjusted comparisons may be valuable.

Indocyanine Green Guided Pelvic Lymph Node Dissection: An Efficient Technique to Classify the Lymph Node Status of Patients with Prostate Cancer Who Underwent Radical Prostatectomy.

PubMed

Ramírez-Backhaus, Miguel; Mira Moreno, Alejandra; Gómez Ferrer, Alvaro; Calatrava Fons, Ana; Casanova, Juan; Solsona Narbón, Eduardo; Ortiz Rodríguez, Isabel María; Rubio Briones, José

2016-11-01

We evaluated the effectiveness of indocyanine green guided pelvic lymph node dissection for the optimal staging of prostate cancer and analyzed whether the technique could replace extended pelvic lymph node dissection. A solution of 25 mg indocyanine green in 5 ml sterile water was transperineally injected. Pelvic lymph node dissection was started with the indocyanine green stained nodes followed by extended pelvic lymph node dissection. Primary outcome measures were sensitivity, specificity, predictive value and likelihood ratio of a negative test of indocyanine green guided pelvic lymph node dissection. A total of 84 patients with a median age of 63.55 years and a median prostate specific antigen of 8.48 ng/ml were included in the study. Of these patients 60.7% had intermediate risk disease and 25% had high or very high risk disease. A median of 7 indocyanine green stained nodes per patient was detected (range 2 to 18) with a median of 22 nodes excised during extended pelvic lymph node dissection. Lymph node metastasis was identified in 25 patients, 23 of whom had disease properly classified by indocyanine green guided pelvic lymph node dissection. The most frequent location of indocyanine green stained nodes was the proximal internal iliac artery followed by the fossa of Marcille. The negative predictive value was 96.7% and the likelihood ratio of a negative test was 8%. Overall 1,856 nodes were removed and 603 were stained indocyanine green. Pathological examination revealed 82 metastatic nodes, of which 60% were indocyanine green stained. The negative predictive value was 97.4% but the likelihood ratio of a negative test was 58.5%. Indocyanine green guided pelvic lymph node dissection correctly staged 97% of cases. However, according to our data it cannot replace extended pelvic lymph node dissection. Nevertheless, its high negative predictive value could allow us to avoid extended pelvic lymph node dissection if we had an accurate intraoperative lymph fluorescent analysis. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Pramipexole and Compulsive Masturbation

PubMed Central

Ferlan, Mark

2007-01-01

Objective: Exploration of a possible relationship between pramipexole and compulsive masturbation. Methods: We present a case report. Results: Given the temporal overlap between pramipexole prescription and its discontinuation, and the onset and cessation of the patient's hypersexual behavior, there appears to be a strong likelihood of association. Conclusions: Like other dopamine agonists, pramipexole may precipitate compulsive behaviors, including hypersexual behavior in the form of compulsive masturbation. PMID:20532122

Proposing a tornado watch scale

NASA Astrophysics Data System (ADS)

Mason, Jonathan Brock

This thesis provides an overview of language used in tornado safety recommendations from various sources, along with developing a rubric for scaled tornado safety recommendations, and subsequent development and testing of a tornado watch scale. The rubric is used to evaluate tornado refuge/shelter adequacy responses of Tuscaloosa residents gathered following the April 27, 2011 Tuscaloosa, Alabama EF4 tornado. There was a significant difference in the counts of refuge adequacy for Tuscaloosa residents when holding the locations during the April 27th tornado constant and comparing adequacy ratings for weak (EF0-EF1), strong (EF2-EF3) and violent (EF4-EF5) tornadoes. There was also a significant difference when comparing future tornado refuge plans of those same participants to the adequacy ratings for weak, strong and violent tornadoes. The tornado refuge rubric is then revised into a six-class, hierarchical Tornado Watch Scale (TWS) from Level 0 to Level 5 based on the likelihood of high-impact or low-impact severe weather events containing weak, strong or violent tornadoes. These levels represent maximum expected tornado intensity and include tornado safety recommendations from the tornado refuge rubric. Audio recordings similar to those used in current National Oceanic and Atmospheric Administration (NOAA) weather radio communications were developed to correspond to three levels of the TWS, a current Storm Prediction Center (SPC) tornado watch and a particularly dangerous situation (PDS) tornado watch. These were then used in interviews of Alabama residents to determine how changes to the information contained in the watch statements would affect each participant's tornado safety actions and perception of event danger. Results from interview participants (n=38) indicate a strong preference (97.37%) for the TWS when compared to current tornado watch and PDS tornado watch statements. Results also show the TWS elicits more adequate safety decisions from participants along with a more appropriate perception of the danger being conveyed by each statement.

Evaluating marginal likelihood with thermodynamic integration method and comparison with several other numerical methods

DOE PAGES

Liu, Peigui; Elshall, Ahmed S.; Ye, Ming; ...

2016-02-05

Evaluating marginal likelihood is the most critical and computationally expensive task, when conducting Bayesian model averaging to quantify parametric and model uncertainties. The evaluation is commonly done by using Laplace approximations to evaluate semianalytical expressions of the marginal likelihood or by using Monte Carlo (MC) methods to evaluate arithmetic or harmonic mean of a joint likelihood function. This study introduces a new MC method, i.e., thermodynamic integration, which has not been attempted in environmental modeling. Instead of using samples only from prior parameter space (as in arithmetic mean evaluation) or posterior parameter space (as in harmonic mean evaluation), the thermodynamicmore » integration method uses samples generated gradually from the prior to posterior parameter space. This is done through a path sampling that conducts Markov chain Monte Carlo simulation with different power coefficient values applied to the joint likelihood function. The thermodynamic integration method is evaluated using three analytical functions by comparing the method with two variants of the Laplace approximation method and three MC methods, including the nested sampling method that is recently introduced into environmental modeling. The thermodynamic integration method outperforms the other methods in terms of their accuracy, convergence, and consistency. The thermodynamic integration method is also applied to a synthetic case of groundwater modeling with four alternative models. The application shows that model probabilities obtained using the thermodynamic integration method improves predictive performance of Bayesian model averaging. As a result, the thermodynamic integration method is mathematically rigorous, and its MC implementation is computationally general for a wide range of environmental problems.« less

Inequities in tobacco retailer sales to minors by neighborhood racial/ethnic composition, poverty, and segregation, USA, 2015

PubMed Central

Lee, Joseph G. L.; Landrine, Hope; Torres, Essie; Gregory, Kyle R.

2016-01-01

Objective Tobacco retailers are an important source of tobacco products for minors. Previous research shows racial discrimination in sales to minors, but no national study has examined neighborhood correlates of retailer underage sales. Methods We accessed publicly available results of 2015 FDA inspections of tobacco retailers (n=108,614). In this cross-sectional study, we used multilevel logistic regression to predict the likelihood of retailer sale to a minor based on tract characteristics. We assessed the proportion of residents identifying as American Indian, Asian, Black, Latino, and White; isolation index scores for each racial/ethnic group; the proportion of people less than age 65 living in poverty; and, the proportion of residents age 10–17 in relation to retailer inspection results. Results The proportion of American Indian residents, Black residents, Latino residents, and residents less than age 65 under the poverty line in a neighborhood are independently, positively associated with the likelihood that a retailer in that neighborhood will fail an underage buy inspection. The proportion of White residents and residents age 10–17 are independently, negatively associated with the likelihood of sale of tobacco products to a minor. Isolation index scores show a similar pattern. In multivariable models holding neighborhood characteristics constant, higher proportions of Black (+), Latino (+), and age 10–17 (−) residents remained significant predictors of the likelihood of underage sale. Discussion Regulatory agencies should consider oversampling retailers in areas with higher likelihood of sales to minors for inspection. Interventions with tobacco retailers to reduce inequities in youth access should be implemented. PMID:27609780

Organizational Predictors of Staff Stress, Satisfaction, and Intended Turnover in a Service for People with Multiple Disabilities.

ERIC Educational Resources Information Center

Hatton, Chris; Emerson, Eric

1993-01-01

Questionnaire data were collected from 64 direct-care staff members in a residential facility for people with multiple disabilities. Path analyses identified factors predicting levels of perceived stress, overall job satisfaction, overall life satisfaction, and perceived likelihood of leaving the organization. Factors included staff support, job…

On Study Habits on an Introductory Course on Programming

ERIC Educational Resources Information Center

Willman, Salla; Lindén, Rolf; Kaila, Erkki; Rajala, Teemu; Laakso, Mikko-Jussi; Salakoski, Tapio

2015-01-01

Computer aided assessment systems enable the collection of exact time and date information on students' activity on a course. These activity patterns reflect students' study habits and these study habits further predict students' likelihood to pass or fail a course. By identifying such patterns, those who design the courses can enforce positive…

Coping with Verbal and Social Bullying in Middle School

ERIC Educational Resources Information Center

Donoghue, Christopher; Almeida, Angela; Brandwein, David; Rocha, Gabriela; Callahan, Ian

2014-01-01

Becoming a victim of verbal and social bullying in middle school can lead to illness, psychological stress, and maladjustment. The coping strategies that students utilize when they are bullied may influence the likelihood and severity of these negative effects. In this study, we examined the predictions made by students in two middle schools about…

Exploring Organizational and Cultural Barriers to Developing Distance Learning

ERIC Educational Resources Information Center

Nadelman, Cindi A.

2014-01-01

Distance learning programs are being developed at many institutions of higher learning as a means of maintaining a competitive advantage. The problem is that college administrators have no reliable methods for predicting the likelihood of success or failure of these newly launched programs. There is a lack of information regarding attitudes and…

Application of artificial intelligence to risk analysis for forested ecosystems

Treesearch

Daniel L. Schmoldt

2001-01-01

Forest ecosystems are subject to a variety of natural and anthropogenic disturbances that extract a penalty from human population values. Such value losses (undesirable effects) combined with their likelihoods of occurrence constitute risk. Assessment or prediction of risk for various events is an important aid to forest management. Artificial intelligence (AI)...

College Student Characteristics and Experiences as Predictors of Interracial Dating

ERIC Educational Resources Information Center

Harper, Casandra E.; Yeung, Fanny P.

2015-01-01

This study utilized logistic regression to test whether students' personal characteristics and experiences significantly predict their likelihood of dating interracially in college. The data were drawn from the Campus Life in America Student Survey (CLASS), which was administered to freshmen who were then resurveyed as juniors (n = 513). The most…

Hazard rating forest stands for gypsy moth

Treesearch

Ray R., Jr. Hicks

1991-01-01

A gypsy moth hazard exists when forest conditions prevail that are conducive to extensive damage from gypsy moth. Combining forest hazard rating with information on insect population trends provides the basis for predicting the probability (risk) of an event occurring. The likelihood of defoliation is termed susceptibility and the probability of damage (mortality,...

Predictors of Home Radon Testing and Implications for Testing Promotion Programs.

ERIC Educational Resources Information Center

Sandman, Peter M.; Weinstein, Neil D.

1993-01-01

Analysis of 4 New Jersey studies of 3,329 homeowners found that (1) thinking about radon testing is predicted by general radon knowledge; (2) decision to test is related to perceived likelihood of risk; and (3) actual testing is influenced by situational factors such as locating and choosing test kits. (SK)