Sampling--how big a sample?

PubMed

Aitken, C G

1999-07-01

It is thought that, in a consignment of discrete units, a certain proportion of the units contain illegal material. A sample of the consignment is to be inspected. Various methods for the determination of the sample size are compared. The consignment will be considered as a random sample from some super-population of units, a certain proportion of which contain drugs. For large consignments, a probability distribution, known as the beta distribution, for the proportion of the consignment which contains illegal material is obtained. This distribution is based on prior beliefs about the proportion. Under certain specific conditions the beta distribution gives the same numerical results as an approach based on the binomial distribution. The binomial distribution provides a probability for the number of units in a sample which contain illegal material, conditional on knowing the proportion of the consignment which contains illegal material. This is in contrast to the beta distribution which provides probabilities for the proportion of a consignment which contains illegal material, conditional on knowing the number of units in the sample which contain illegal material. The interpretation when the beta distribution is used is much more intuitively satisfactory. It is also much more flexible in its ability to cater for prior beliefs which may vary given the different circumstances of different crimes. For small consignments, a distribution, known as the beta-binomial distribution, for the number of units in the consignment which are found to contain illegal material, is obtained, based on prior beliefs about the number of units in the consignment which are thought to contain illegal material. As with the beta and binomial distributions for large samples, it is shown that, in certain specific conditions, the beta-binomial and hypergeometric distributions give the same numerical results. However, the beta-binomial distribution, as with the beta distribution, has a more intuitively satisfactory interpretation and greater flexibility. The beta and the beta-binomial distributions provide methods for the determination of the minimum sample size to be taken from a consignment in order to satisfy a certain criterion. The criterion requires the specification of a proportion and a probability.

Sampling Plans for the Thrips Frankliniella schultzei (Thysanoptera: Thripidae) in Three Lettuce Varieties.

PubMed

Silva, Alisson R; Rodrigues-Silva, Nilson; Pereira, Poliana S; Sarmento, Renato A; Costa, Thiago L; Galdino, Tarcísio V S; Picanço, Marcelo C

2017-12-05

The common blossom thrips, Frankliniella schultzei Trybom (Thysanoptera: Thripidae), is an important lettuce pest worldwide. Conventional sampling plans are the first step in implementing decision-making systems into integrated pest management programs. However, this tool is not available for F. schultzei infesting lettuce crops. Thus, the objective of this work was to develop a conventional sampling plan for F. schultzei in lettuce crops. Two sampling techniques (direct counting and leaf beating on a white plastic tray) were compared in crisphead, looseleaf, and Boston lettuce varieties before and during head formation. The frequency distributions of F. schultzei densities in lettuce crops were assessed, and the number of samples required to compose the sampling plan was determined. Leaf beating on a white plastic tray was the best sampling technique. F. schultzei densities obtained with this technique were fitted to the negative binomial distribution with a common aggregation parameter (common K = 0.3143). The developed sampling plan is composed of 91 samples per field and presents low errors in its estimates (up to 20%), fast execution time (up to 47 min), and low cost (up to US $1.67 per sampling area). This sampling plan can be used as a tool for integrated pest management in lettuce crops, assisting with reliable decision making in different lettuce varieties before and during head formation. © The Author(s) 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Spatial Dependence and Sampling of Phytoseiid Populations on Hass Avocados in Southern California.

PubMed

Lara, Jesús R; Amrich, Ruth; Saremi, Naseem T; Hoddle, Mark S

2016-04-22

Research on phytoseiid mites has been critical for developing an effective biocontrol strategy for suppressing Oligonchus perseae Tuttle, Baker, and Abatiello (Acari: Tetranychidae) in California avocado orchards. However, basic understanding of the spatial ecology of natural populations of phytoseiids in relation to O. perseae infestations and the validation of research-based strategies for assessing densities of these predators has been limited. To address these shortcomings, cross-sectional and longitudinal observations consisting of >3,000 phytoseiids and 500,000 O. perseae counted on 11,341 leaves were collected across 10 avocado orchards during a 10-yr period. Subsets of these data were analyzed statistically to characterize the spatial distribution of phytoseiids in avocado orchards and to evaluate the merits of developing binomial and enumerative sampling strategies for these predators. Spatial correlation of phytoseiids between trees was detected at one site, and a strong association of phytoseiids with elevated O. perseae densities was detected at four sites. Sampling simulations revealed that enumeration-based sampling performed better than binomial sampling for estimating phytoseiid densities. The ecological implications of these findings and potential for developing a custom sampling plan to estimate densities of phytoseiids inhabiting sampled trees in avocado orchards in California are discussed. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

On the p, q-binomial distribution and the Ising model

NASA Astrophysics Data System (ADS)

Lundow, P. H.; Rosengren, A.

2010-08-01

We employ p, q-binomial coefficients, a generalisation of the binomial coefficients, to describe the magnetisation distributions of the Ising model. For the complete graph this distribution corresponds exactly to the limit case p = q. We apply our investigation to the simple d-dimensional lattices for d = 1, 2, 3, 4, 5 and fit p, q-binomial distributions to our data, some of which are exact but most are sampled. For d = 1 and d = 5, the magnetisation distributions are remarkably well-fitted by p,q-binomial distributions. For d = 4 we are only slightly less successful, while for d = 2, 3 we see some deviations (with exceptions!) between the p, q-binomial and the Ising distribution. However, at certain temperatures near T c the statistical moments of the fitted distribution agree with the moments of the sampled data within the precision of sampling. We begin the paper by giving results of the behaviour of the p, q-distribution and its moment growth exponents given a certain parameterisation of p, q. Since the moment exponents are known for the Ising model (or at least approximately for d = 3) we can predict how p, q should behave and compare this to our measured p, q. The results speak in favour of the p, q-binomial distribution's correctness regarding its general behaviour in comparison to the Ising model. The full extent to which they correctly model the Ising distribution, however, is not settled.

A comparison of observation-level random effect and Beta-Binomial models for modelling overdispersion in Binomial data in ecology & evolution.

PubMed

Harrison, Xavier A

2015-01-01

Overdispersion is a common feature of models of biological data, but researchers often fail to model the excess variation driving the overdispersion, resulting in biased parameter estimates and standard errors. Quantifying and modeling overdispersion when it is present is therefore critical for robust biological inference. One means to account for overdispersion is to add an observation-level random effect (OLRE) to a model, where each data point receives a unique level of a random effect that can absorb the extra-parametric variation in the data. Although some studies have investigated the utility of OLRE to model overdispersion in Poisson count data, studies doing so for Binomial proportion data are scarce. Here I use a simulation approach to investigate the ability of both OLRE models and Beta-Binomial models to recover unbiased parameter estimates in mixed effects models of Binomial data under various degrees of overdispersion. In addition, as ecologists often fit random intercept terms to models when the random effect sample size is low (<5 levels), I investigate the performance of both model types under a range of random effect sample sizes when overdispersion is present. Simulation results revealed that the efficacy of OLRE depends on the process that generated the overdispersion; OLRE failed to cope with overdispersion generated from a Beta-Binomial mixture model, leading to biased slope and intercept estimates, but performed well for overdispersion generated by adding random noise to the linear predictor. Comparison of parameter estimates from an OLRE model with those from its corresponding Beta-Binomial model readily identified when OLRE were performing poorly due to disagreement between effect sizes, and this strategy should be employed whenever OLRE are used for Binomial data to assess their reliability. Beta-Binomial models performed well across all contexts, but showed a tendency to underestimate effect sizes when modelling non-Beta-Binomial data. Finally, both OLRE and Beta-Binomial models performed poorly when models contained <5 levels of the random intercept term, especially for estimating variance components, and this effect appeared independent of total sample size. These results suggest that OLRE are a useful tool for modelling overdispersion in Binomial data, but that they do not perform well in all circumstances and researchers should take care to verify the robustness of parameter estimates of OLRE models.

Binomial leap methods for simulating stochastic chemical kinetics.

PubMed

Tian, Tianhai; Burrage, Kevin

2004-12-01

This paper discusses efficient simulation methods for stochastic chemical kinetics. Based on the tau-leap and midpoint tau-leap methods of Gillespie [D. T. Gillespie, J. Chem. Phys. 115, 1716 (2001)], binomial random variables are used in these leap methods rather than Poisson random variables. The motivation for this approach is to improve the efficiency of the Poisson leap methods by using larger stepsizes. Unlike Poisson random variables whose range of sample values is from zero to infinity, binomial random variables have a finite range of sample values. This probabilistic property has been used to restrict possible reaction numbers and to avoid negative molecular numbers in stochastic simulations when larger stepsize is used. In this approach a binomial random variable is defined for a single reaction channel in order to keep the reaction number of this channel below the numbers of molecules that undergo this reaction channel. A sampling technique is also designed for the total reaction number of a reactant species that undergoes two or more reaction channels. Samples for the total reaction number are not greater than the molecular number of this species. In addition, probability properties of the binomial random variables provide stepsize conditions for restricting reaction numbers in a chosen time interval. These stepsize conditions are important properties of robust leap control strategies. Numerical results indicate that the proposed binomial leap methods can be applied to a wide range of chemical reaction systems with very good accuracy and significant improvement on efficiency over existing approaches. (c) 2004 American Institute of Physics.

Choosing a Transformation in Analyses of Insect Counts from Contagious Distributions with Low Means

Treesearch

W.D. Pepper; S.J. Zarnoch; G.L. DeBarr; P. de Groot; C.D. Tangren

1997-01-01

Guidelines based on computer simulation are suggested for choosing a transformation of insect counts from negative binomial distributions with low mean counts and high levels of contagion. Typical values and ranges of negative binomial model parameters were determined by fitting the model to data from 19 entomological field studies. Random sampling of negative binomial...

Use of the binomial distribution to predict impairment: application in a nonclinical sample.

PubMed

Axelrod, Bradley N; Wall, Jacqueline R; Estes, Bradley W

2008-01-01

A mathematical model based on the binomial theory was developed to illustrate when abnormal score variations occur by chance in a multitest battery (Ingraham & Aiken, 1996). It has been successfully used as a comparison for obtained test scores in clinical samples, but not in nonclinical samples. In the current study, this model has been applied to demographically corrected scores on the Halstead-Reitan Neuropsychological Test Battery, obtained from a sample of 94 nonclinical college students. Results found that 15% of the sample had impairments suggested by the Halstead Impairment Index, using criteria established by Reitan and Wolfson (1993). In addition, one-half of the sample obtained impaired scores on one or two tests. These results were compared to that predicted by the binomial model and found to be consistent. The model therefore serves as a useful resource for clinicians considering the probability of impaired test performance.

Estimating relative risks in multicenter studies with a small number of centers - which methods to use? A simulation study.

PubMed

Pedroza, Claudia; Truong, Van Thi Thanh

2017-11-02

Analyses of multicenter studies often need to account for center clustering to ensure valid inference. For binary outcomes, it is particularly challenging to properly adjust for center when the number of centers or total sample size is small, or when there are few events per center. Our objective was to evaluate the performance of generalized estimating equation (GEE) log-binomial and Poisson models, generalized linear mixed models (GLMMs) assuming binomial and Poisson distributions, and a Bayesian binomial GLMM to account for center effect in these scenarios. We conducted a simulation study with few centers (≤30) and 50 or fewer subjects per center, using both a randomized controlled trial and an observational study design to estimate relative risk. We compared the GEE and GLMM models with a log-binomial model without adjustment for clustering in terms of bias, root mean square error (RMSE), and coverage. For the Bayesian GLMM, we used informative neutral priors that are skeptical of large treatment effects that are almost never observed in studies of medical interventions. All frequentist methods exhibited little bias, and the RMSE was very similar across the models. The binomial GLMM had poor convergence rates, ranging from 27% to 85%, but performed well otherwise. The results show that both GEE models need to use small sample corrections for robust SEs to achieve proper coverage of 95% CIs. The Bayesian GLMM had similar convergence rates but resulted in slightly more biased estimates for the smallest sample sizes. However, it had the smallest RMSE and good coverage across all scenarios. These results were very similar for both study designs. For the analyses of multicenter studies with a binary outcome and few centers, we recommend adjustment for center with either a GEE log-binomial or Poisson model with appropriate small sample corrections or a Bayesian binomial GLMM with informative priors.

C-5A Cargo Deck Low-Frequency Vibration Environment

DTIC Science & Technology

1975-02-01

SAMPLE VIBRATION CALCULATIONS 13 1. Normal Distribution 13 2. Binomial Distribution 15 IV CONCLUSIONS 17 -! V REFERENCES 18 t: FEiCENDIJJ PAGS 2LANKNOT...Calculation for Binomial Distribution 108 (Vertical Acceleration, Right Rear Cargo Deck) xi I. INTRODUCTION The availability of large transport...the end of taxi. These peaks could then be used directly to compile the probability of occurrence of specific values of acceleration using the binomial

Application of binomial-edited CPMG to shale characterization

USGS Publications Warehouse

Washburn, Kathryn E.; Birdwell, Justin E.

2014-01-01

Unconventional shale resources may contain a significant amount of hydrogen in organic solids such as kerogen, but it is not possible to directly detect these solids with many NMR systems. Binomial-edited pulse sequences capitalize on magnetization transfer between solids, semi-solids, and liquids to provide an indirect method of detecting solid organic materials in shales. When the organic solids can be directly measured, binomial-editing helps distinguish between different phases. We applied a binomial-edited CPMG pulse sequence to a range of natural and experimentally-altered shale samples. The most substantial signal loss is seen in shales rich in organic solids while fluids associated with inorganic pores seem essentially unaffected. This suggests that binomial-editing is a potential method for determining fluid locations, solid organic content, and kerogen–bitumen discrimination.

Diagnostic test accuracy and prevalence inferences based on joint and sequential testing with finite population sampling.

PubMed

Su, Chun-Lung; Gardner, Ian A; Johnson, Wesley O

2004-07-30

The two-test two-population model, originally formulated by Hui and Walter, for estimation of test accuracy and prevalence estimation assumes conditionally independent tests, constant accuracy across populations and binomial sampling. The binomial assumption is incorrect if all individuals in a population e.g. child-care centre, village in Africa, or a cattle herd are sampled or if the sample size is large relative to population size. In this paper, we develop statistical methods for evaluating diagnostic test accuracy and prevalence estimation based on finite sample data in the absence of a gold standard. Moreover, two tests are often applied simultaneously for the purpose of obtaining a 'joint' testing strategy that has either higher overall sensitivity or specificity than either of the two tests considered singly. Sequential versions of such strategies are often applied in order to reduce the cost of testing. We thus discuss joint (simultaneous and sequential) testing strategies and inference for them. Using the developed methods, we analyse two real and one simulated data sets, and we compare 'hypergeometric' and 'binomial-based' inferences. Our findings indicate that the posterior standard deviations for prevalence (but not sensitivity and specificity) based on finite population sampling tend to be smaller than their counterparts for infinite population sampling. Finally, we make recommendations about how small the sample size should be relative to the population size to warrant use of the binomial model for prevalence estimation. Copyright 2004 John Wiley & Sons, Ltd.

The Sequential Probability Ratio Test: An efficient alternative to exact binomial testing for Clean Water Act 303(d) evaluation.

PubMed

Chen, Connie; Gribble, Matthew O; Bartroff, Jay; Bay, Steven M; Goldstein, Larry

2017-05-01

The United States's Clean Water Act stipulates in section 303(d) that states must identify impaired water bodies for which total maximum daily loads (TMDLs) of pollution inputs into water bodies are developed. Decision-making procedures about how to list, or delist, water bodies as impaired, or not, per Clean Water Act 303(d) differ across states. In states such as California, whether or not a particular monitoring sample suggests that water quality is impaired can be regarded as a binary outcome variable, and California's current regulatory framework invokes a version of the exact binomial test to consolidate evidence across samples and assess whether the overall water body complies with the Clean Water Act. Here, we contrast the performance of California's exact binomial test with one potential alternative, the Sequential Probability Ratio Test (SPRT). The SPRT uses a sequential testing framework, testing samples as they become available and evaluating evidence as it emerges, rather than measuring all the samples and calculating a test statistic at the end of the data collection process. Through simulations and theoretical derivations, we demonstrate that the SPRT on average requires fewer samples to be measured to have comparable Type I and Type II error rates as the current fixed-sample binomial test. Policymakers might consider efficient alternatives such as SPRT to current procedure. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatial Distribution of Adult Anthonomus grandis Boheman (Coleoptera: Curculionidae) and Damage to Cotton Flower Buds Due to Feeding and Oviposition.

PubMed

Grigolli, J F J; Souza, L A; Fernandes, M G; Busoli, A C

2017-08-01

The cotton boll weevil Anthonomus grandis Boheman (Coleoptera: Curculionidae) is the main pest in cotton crop around the world, directly affecting cotton production. In order to establish a sequential sampling plan, it is crucial to understand the spatial distribution of the pest population and the damage it causes to the crop through the different developmental stages of cotton plants. Therefore, this study aimed to investigate the spatial distribution of adults in the cultivation area and their oviposition and feeding behavior throughout the development of the cotton plants. The experiment was conducted in Maracaju, Mato Grosso do Sul, Brazil, in the 2012/2013 and 2013/2014 growing seasons, in an area of 10,000 m 2 , planted with the cotton cultivar FM 993. The experimental area was divided into 100 plots of 100 m 2 (10 × 10 m) each, and five plants per plot were sampled weekly throughout the crop cycle. The number of flower buds with feeding and oviposition punctures and of adult A. grandis was recorded throughout the crop cycle in five plants per plot. After determining the aggregation indices (variance/mean ratio, Morisita's index, exponent k of the negative binomial distribution, and Green's coefficient) and adjusting the frequencies observed in the field to the distribution of frequencies (Poisson, negative binomial, and positive binomial) using the chi-squared test, it was observed that flower buds with punctures derived from feeding, oviposition, and feeding + oviposition showed an aggregated distribution in the cultivation area until 85 days after emergence and a random distribution after this stage. The adults of A. grandis presented a random distribution in the cultivation area.

Sequential sampling and biorational chemistries for management of lepidopteran pests of vegetable amaranth in the Caribbean.

PubMed

Clarke-Harris, Dionne; Fleischer, Shelby J

2003-06-01

Although vegetable amaranth, Amaranthus viridis L. and A. dubius Mart. ex Thell., production and economic importance is increasing in diversified peri-urban farms in Jamaica, lepidopteran herbivory is common even during weekly pyrethroid applications. We developed and validated a sampling plan, and investigated insecticides with new modes of action, for a complex of five species (Pyralidae: Spoladea recurvalis (F.), Herpetogramma bipunctalis (F.), Noctuidae: Spodoptera exigua (Hubner), S. frugiperda (J. E. Smith), and S. eridania Stoll). Significant within-plant variation occurred with H. bipunctalis, and a six-leaf sample unit including leaves from the inner and outer whorl was selected to sample all species. Larval counts best fit a negative binomial distribution. We developed a sequential sampling plan using a threshold of one larva per sample unit and the fitted distribution with a k(c) of 0.645. When compared with a fixed plan of 25 plants, sequential sampling recommended the same management decision on 87.5%, additional samples on 9.4%, and gave inaccurate recommendations on 3.1% of 32 farms, while reducing sample size by 46%. Insecticide frequency was reduced 33-60% when management decisions were based on sampled data compared with grower-standards, with no effect on crop damage. Damage remained high or variable (10-46%) with pyrethroid applications. Lepidopteran control was dramatically improved with ecdysone agonists (tebufenozide) or microbial metabolites (spinosyns and emamectin benzoate). This work facilitates resistance management efforts concurrent with the introduction of newer modes of action for lepidopteran control in leafy vegetable production in the Caribbean.

Marginalized zero-inflated negative binomial regression with application to dental caries

PubMed Central

Preisser, John S.; Das, Kalyan; Long, D. Leann; Divaris, Kimon

2015-01-01

The zero-inflated negative binomial regression model (ZINB) is often employed in diverse fields such as dentistry, health care utilization, highway safety, and medicine to examine relationships between exposures of interest and overdispersed count outcomes exhibiting many zeros. The regression coefficients of ZINB have latent class interpretations for a susceptible subpopulation at risk for the disease/condition under study with counts generated from a negative binomial distribution and for a non-susceptible subpopulation that provides only zero counts. The ZINB parameters, however, are not well-suited for estimating overall exposure effects, specifically, in quantifying the effect of an explanatory variable in the overall mixture population. In this paper, a marginalized zero-inflated negative binomial regression (MZINB) model for independent responses is proposed to model the population marginal mean count directly, providing straightforward inference for overall exposure effects based on maximum likelihood estimation. Through simulation studies, the finite sample performance of MZINB is compared to marginalized zero-inflated Poisson, Poisson, and negative binomial regression. The MZINB model is applied in the evaluation of a school-based fluoride mouthrinse program on dental caries in 677 children. PMID:26568034

Identifiability in N-mixture models: a large-scale screening test with bird data.

PubMed

Kéry, Marc

2018-02-01

Binomial N-mixture models have proven very useful in ecology, conservation, and monitoring: they allow estimation and modeling of abundance separately from detection probability using simple counts. Recently, doubts about parameter identifiability have been voiced. I conducted a large-scale screening test with 137 bird data sets from 2,037 sites. I found virtually no identifiability problems for Poisson and zero-inflated Poisson (ZIP) binomial N-mixture models, but negative-binomial (NB) models had problems in 25% of all data sets. The corresponding multinomial N-mixture models had no problems. Parameter estimates under Poisson and ZIP binomial and multinomial N-mixture models were extremely similar. Identifiability problems became a little more frequent with smaller sample sizes (267 and 50 sites), but were unaffected by whether the models did or did not include covariates. Hence, binomial N-mixture model parameters with Poisson and ZIP mixtures typically appeared identifiable. In contrast, NB mixtures were often unidentifiable, which is worrying since these were often selected by Akaike's information criterion. Identifiability of binomial N-mixture models should always be checked. If problems are found, simpler models, integrated models that combine different observation models or the use of external information via informative priors or penalized likelihoods, may help. © 2017 by the Ecological Society of America.

Temporary disaster debris management site identification using binomial cluster analysis and GIS.

PubMed

Grzeda, Stanislaw; Mazzuchi, Thomas A; Sarkani, Shahram

2014-04-01

An essential component of disaster planning and preparation is the identification and selection of temporary disaster debris management sites (DMS). However, since DMS identification is a complex process involving numerous variable constraints, many regional, county and municipal jurisdictions initiate this process during the post-disaster response and recovery phases, typically a period of severely stressed resources. Hence, a pre-disaster approach in identifying the most likely sites based on the number of locational constraints would significantly contribute to disaster debris management planning. As disasters vary in their nature, location and extent, an effective approach must facilitate scalability, flexibility and adaptability to variable local requirements, while also being generalisable to other regions and geographical extents. This study demonstrates the use of binomial cluster analysis in potential DMS identification in a case study conducted in Hamilton County, Indiana. © 2014 The Author(s). Disasters © Overseas Development Institute, 2014.

Sample size determination for a three-arm equivalence trial of Poisson and negative binomial responses.

PubMed

Chang, Yu-Wei; Tsong, Yi; Zhao, Zhigen

2017-01-01

Assessing equivalence or similarity has drawn much attention recently as many drug products have lost or will lose their patents in the next few years, especially certain best-selling biologics. To claim equivalence between the test treatment and the reference treatment when assay sensitivity is well established from historical data, one has to demonstrate both superiority of the test treatment over placebo and equivalence between the test treatment and the reference treatment. Thus, there is urgency for practitioners to derive a practical way to calculate sample size for a three-arm equivalence trial. The primary endpoints of a clinical trial may not always be continuous, but may be discrete. In this paper, the authors derive power function and discuss sample size requirement for a three-arm equivalence trial with Poisson and negative binomial clinical endpoints. In addition, the authors examine the effect of the dispersion parameter on the power and the sample size by varying its coefficient from small to large. In extensive numerical studies, the authors demonstrate that required sample size heavily depends on the dispersion parameter. Therefore, misusing a Poisson model for negative binomial data may easily lose power up to 20%, depending on the value of the dispersion parameter.

Sequential Sampling Plan of Anthonomus grandis (Coleoptera: Curculionidae) in Cotton Plants.

PubMed

Grigolli, J F J; Souza, L A; Mota, T A; Fernandes, M G; Busoli, A C

2017-04-01

The boll weevil, Anthonomus grandis grandis Boheman (Coleoptera: Curculionidae), is one of the most important pests of cotton production worldwide. The objective of this work was to develop a sequential sampling plan for the boll weevil. The studies were conducted in Maracaju, MS, Brazil, in two seasons with cotton cultivar FM 993. A 10,000-m2 area of cotton was subdivided into 100 of 10- by 10-m plots, and five plants per plot were evaluated weekly, recording the number of squares with feeding + oviposition punctures of A. grandis in each plant. A sequential sampling plan by the maximum likelihood ratio test was developed, using a 10% threshold level of squares attacked. A 5% security level was adopted for the elaboration of the sequential sampling plan. The type I and type II error used was 0.05, recommended for studies with insects. The adjustment of the frequency distributions used were divided into two phases, so that the model that best fit to the data was the negative binomial distribution up to 85 DAE (Phase I), and from there the best fit was Poisson distribution (Phase II). The equations that define the decision-making for Phase I are S0 = -5.1743 + 0.5730N and S1 = 5.1743 + 0.5730N, and for the Phase II are S0 = -4.2479 + 0.5771N and S1 = 4.2479 + 0.5771N. The sequential sampling plan developed indicated the maximum number of sample units expected for decision-making is ∼39 and 31 samples for Phases I and II, respectively. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Seasonal trends, sampling plans and parasitoid complex of the Chinese wax scale, Ceroplastes sinensis Del Guercio (Hemiptera: Coccidae), in Mediterranean citrus groves.

PubMed

Martínez-Ferrer, M T; Campos-Rivela, J M; Verdú, M J

2015-02-01

Seasonal trends and the parasitoid complex of Chinese wax scale (Ceroplastes sinensis) was studied from July 2010 to February 2013. Six commercial citrus groves located in northeastern Spain were sampled fortnightly. Chinese wax scale completed a single annual generation. Egg oviposition started in May and continued until mid-July. Egg hatching began in mid-June, and in the first quarter of August, the maximum percentage of hatched eggs was reached. In the same groves, the parasitoid species of C. sinensis were determined together with their seasonal trends, relative abundance and occurrence on C. sinensis. Four hymenoptera were found parasitizing C. sinensis, mainly on third instars and females: Coccophagus ceroplastae (Aphelinidae), Metaphycus helvolus (Encyrtidae), Scutellista caerulea (Pteromalidae) and Aprostocetus ceroplastae (Eulophidae). The most abundant species was A. ceroplastae, corresponding to 54% of the parasitoids emerged. Coccophagus ceroplastae and M. helvolus represented 19%, whereas S. caerulea comprised 8% of the total. This study is the first published record of C. ceroplastae in Spain and the first record of M. helvolus on C. sinensis in Spain. Concerning the economical thresholds normally used, sampling plans developed for the management of C. sinensis in citrus groves should target population densities of around 12-20% of invaded twigs, equivalent to 0.2-0.5 females per twig. The sample size necessary to achieve the desired integrated pest management precision is 90-160 twigs per grove for the enumerative plan and about 160-245 twigs per grove for the binomial plan.

Exact tests using two correlated binomial variables in contemporary cancer clinical trials.

PubMed

Yu, Jihnhee; Kepner, James L; Iyer, Renuka

2009-12-01

New therapy strategies for the treatment of cancer are rapidly emerging because of recent technology advances in genetics and molecular biology. Although newer targeted therapies can improve survival without measurable changes in tumor size, clinical trial conduct has remained nearly unchanged. When potentially efficacious therapies are tested, current clinical trial design and analysis methods may not be suitable for detecting therapeutic effects. We propose an exact method with respect to testing cytostatic cancer treatment using correlated bivariate binomial random variables to simultaneously assess two primary outcomes. The method is easy to implement. It does not increase the sample size over that of the univariate exact test and in most cases reduces the sample size required. Sample size calculations are provided for selected designs.

Bayesian inference for disease prevalence using negative binomial group testing

PubMed Central

Pritchard, Nicholas A.; Tebbs, Joshua M.

2011-01-01

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

Characterizing environmental risk factors for West Nile virus in Quebec, Canada, using clinical data in humans and serology in pet dogs.

PubMed

Rocheleau, J P; Michel, P; Lindsay, L R; Drebot, M; Dibernardo, A; Ogden, N H; Fortin, A; Arsenault, J

2017-10-01

The identification of specific environments sustaining emerging arbovirus amplification and transmission to humans is a key component of public health intervention planning. This study aimed at identifying environmental factors associated with West Nile virus (WNV) infections in southern Quebec, Canada, by modelling and jointly interpreting aggregated clinical data in humans and serological data in pet dogs. Environmental risk factors were estimated in humans by negative binomial regression based on a dataset of 191 human WNV clinical cases reported in the study area between 2011 and 2014. Risk factors for infection in dogs were evaluated by logistic and negative binomial models based on a dataset including WNV serological results from 1442 dogs sampled from the same geographical area in 2013. Forested lands were identified as low-risk environments in humans. Agricultural lands represented higher risk environments for dogs. Environments identified as impacting risk in the current study were somewhat different from those identified in other studies conducted in north-eastern USA, which reported higher risk in suburban environments. In the context of the current study, combining human and animal data allowed a more comprehensive and possibly a more accurate view of environmental WNV risk factors to be obtained than by studying aggregated human data alone.

Clustered lot quality assurance sampling to assess immunisation coverage: increasing rapidity and maintaining precision.

PubMed

Pezzoli, Lorenzo; Andrews, Nick; Ronveaux, Olivier

2010-05-01

Vaccination programmes targeting disease elimination aim to achieve very high coverage levels (e.g. 95%). We calculated the precision of different clustered lot quality assurance sampling (LQAS) designs in computer-simulated surveys to provide local health officers in the field with preset LQAS plans to simply and rapidly assess programmes with high coverage targets. We calculated sample size (N), decision value (d) and misclassification errors (alpha and beta) of several LQAS plans by running 10 000 simulations. We kept the upper coverage threshold (UT) at 90% or 95% and decreased the lower threshold (LT) progressively by 5%. We measured the proportion of simulations with < or =d individuals unvaccinated or lower if the coverage was set at the UT (pUT) to calculate beta (1-pUT) and the proportion of simulations with >d unvaccinated individuals if the coverage was LT% (pLT) to calculate alpha (1-pLT). We divided N in clusters (between 5 and 10) and recalculated the errors hypothesising that the coverage would vary in the clusters according to a binomial distribution with preset standard deviations of 0.05 and 0.1 from the mean lot coverage. We selected the plans fulfilling these criteria: alpha < or = 5% beta < or = 20% in the unclustered design; alpha < or = 10% beta < or = 25% when the lots were divided in five clusters. When the interval between UT and LT was larger than 10% (e.g. 15%), we were able to select precise LQAS plans dividing the lot in five clusters with N = 50 (5 x 10) and d = 4 to evaluate programmes with 95% coverage target and d = 7 to evaluate programmes with 90% target. These plans will considerably increase the feasibility and the rapidity of conducting the LQAS in the field.

Predictive accuracy of particle filtering in dynamic models supporting outbreak projections.

PubMed

Safarishahrbijari, Anahita; Teyhouee, Aydin; Waldner, Cheryl; Liu, Juxin; Osgood, Nathaniel D

2017-09-26

While a new generation of computational statistics algorithms and availability of data streams raises the potential for recurrently regrounding dynamic models with incoming observations, the effectiveness of such arrangements can be highly subject to specifics of the configuration (e.g., frequency of sampling and representation of behaviour change), and there has been little attempt to identify effective configurations. Combining dynamic models with particle filtering, we explored a solution focusing on creating quickly formulated models regrounded automatically and recurrently as new data becomes available. Given a latent underlying case count, we assumed that observed incident case counts followed a negative binomial distribution. In accordance with the condensation algorithm, each such observation led to updating of particle weights. We evaluated the effectiveness of various particle filtering configurations against each other and against an approach without particle filtering according to the accuracy of the model in predicting future prevalence, given data to a certain point and a norm-based discrepancy metric. We examined the effectiveness of particle filtering under varying times between observations, negative binomial dispersion parameters, and rates with which the contact rate could evolve. We observed that more frequent observations of empirical data yielded super-linearly improved accuracy in model predictions. We further found that for the data studied here, the most favourable assumptions to make regarding the parameters associated with the negative binomial distribution and changes in contact rate were robust across observation frequency and the observation point in the outbreak. Combining dynamic models with particle filtering can perform well in projecting future evolution of an outbreak. Most importantly, the remarkable improvements in predictive accuracy resulting from more frequent sampling suggest that investments to achieve efficient reporting mechanisms may be more than paid back by improved planning capacity. The robustness of the results on particle filter configuration in this case study suggests that it may be possible to formulate effective standard guidelines and regularized approaches for such techniques in particular epidemiological contexts. Most importantly, the work tentatively suggests potential for health decision makers to secure strong guidance when anticipating outbreak evolution for emerging infectious diseases by combining even very rough models with particle filtering method.

Partitioning Detectability Components in Populations Subject to Within-Season Temporary Emigration Using Binomial Mixture Models

PubMed Central

O’Donnell, Katherine M.; Thompson, Frank R.; Semlitsch, Raymond D.

2015-01-01

Detectability of individual animals is highly variable and nearly always < 1; imperfect detection must be accounted for to reliably estimate population sizes and trends. Hierarchical models can simultaneously estimate abundance and effective detection probability, but there are several different mechanisms that cause variation in detectability. Neglecting temporary emigration can lead to biased population estimates because availability and conditional detection probability are confounded. In this study, we extend previous hierarchical binomial mixture models to account for multiple sources of variation in detectability. The state process of the hierarchical model describes ecological mechanisms that generate spatial and temporal patterns in abundance, while the observation model accounts for the imperfect nature of counting individuals due to temporary emigration and false absences. We illustrate our model’s potential advantages, including the allowance of temporary emigration between sampling periods, with a case study of southern red-backed salamanders Plethodon serratus. We fit our model and a standard binomial mixture model to counts of terrestrial salamanders surveyed at 40 sites during 3–5 surveys each spring and fall 2010–2012. Our models generated similar parameter estimates to standard binomial mixture models. Aspect was the best predictor of salamander abundance in our case study; abundance increased as aspect became more northeasterly. Increased time-since-rainfall strongly decreased salamander surface activity (i.e. availability for sampling), while higher amounts of woody cover objects and rocks increased conditional detection probability (i.e. probability of capture, given an animal is exposed to sampling). By explicitly accounting for both components of detectability, we increased congruence between our statistical modeling and our ecological understanding of the system. We stress the importance of choosing survey locations and protocols that maximize species availability and conditional detection probability to increase population parameter estimate reliability. PMID:25775182

[Application of negative binomial regression and modified Poisson regression in the research of risk factors for injury frequency].

PubMed

Cao, Qingqing; Wu, Zhenqiang; Sun, Ying; Wang, Tiezhu; Han, Tengwei; Gu, Chaomei; Sun, Yehuan

2011-11-01

To Eexplore the application of negative binomial regression and modified Poisson regression analysis in analyzing the influential factors for injury frequency and the risk factors leading to the increase of injury frequency. 2917 primary and secondary school students were selected from Hefei by cluster random sampling method and surveyed by questionnaire. The data on the count event-based injuries used to fitted modified Poisson regression and negative binomial regression model. The risk factors incurring the increase of unintentional injury frequency for juvenile students was explored, so as to probe the efficiency of these two models in studying the influential factors for injury frequency. The Poisson model existed over-dispersion (P < 0.0001) based on testing by the Lagrangemultiplier. Therefore, the over-dispersion dispersed data using a modified Poisson regression and negative binomial regression model, was fitted better. respectively. Both showed that male gender, younger age, father working outside of the hometown, the level of the guardian being above junior high school and smoking might be the results of higher injury frequencies. On a tendency of clustered frequency data on injury event, both the modified Poisson regression analysis and negative binomial regression analysis can be used. However, based on our data, the modified Poisson regression fitted better and this model could give a more accurate interpretation of relevant factors affecting the frequency of injury.

Aggregation Patterns, Sampling Plan, and Economic Injury Levels for the New Citrus Pest Delottococcus aberiae (Hemiptera: Pseudococcidae).

PubMed

Pérez-Rodríguez, J; Martínez-Blay, V; Soto, A; Selfa, J; Monzó, C; Urbaneja, A; Tena, A

2017-12-05

Delottococcus aberiae De Lotto (Hemiptera: Pseudococcidae) is the latest exotic mealybug species introduced in citrus in the Mediterranean basin. It causes severe distortion and size reduction on developing fruits. Due to its first interaction with citrus, D. aberiae economic thresholds are still unknown for this crop and the current Integrated Pest Management programs have been disrupted. The objectives of this study were to determine the aggregation patterns of D. aberiae in citrus, develop an efficient sampling plan to assess its population density, and calculate its Economic and Economic Environmental Injury Levels (EIL and EEIL, respectively). Twelve and 19 orchards were sampled in 2014 and 2015, respectively. At each orchard, population densities were monitored fortnightly in leaves, twigs, and fruit, and fruit damage was determined at harvest. Our results showed a clumped aggregation of D. aberiae in all organs with no significant differences between generations on fruit. Fruit damage at harvest was strongly correlated with fruit occupation in spring. Based on these results and using chlorpyrifos as the insecticide of reference, the EIL and EEIL were calculated as 7.1 and 12.1% of occupied fruit in spring, respectively. With all this, we recommend sampling 275 fruits using a binomial sampling method or alternatively, 140 fruits with an enumerative method bimonthly between petal fall and July. © The Author(s) 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

QNB: differential RNA methylation analysis for count-based small-sample sequencing data with a quad-negative binomial model.

PubMed

Liu, Lian; Zhang, Shao-Wu; Huang, Yufei; Meng, Jia

2017-08-31

As a newly emerged research area, RNA epigenetics has drawn increasing attention recently for the participation of RNA methylation and other modifications in a number of crucial biological processes. Thanks to high throughput sequencing techniques, such as, MeRIP-Seq, transcriptome-wide RNA methylation profile is now available in the form of count-based data, with which it is often of interests to study the dynamics at epitranscriptomic layer. However, the sample size of RNA methylation experiment is usually very small due to its costs; and additionally, there usually exist a large number of genes whose methylation level cannot be accurately estimated due to their low expression level, making differential RNA methylation analysis a difficult task. We present QNB, a statistical approach for differential RNA methylation analysis with count-based small-sample sequencing data. Compared with previous approaches such as DRME model based on a statistical test covering the IP samples only with 2 negative binomial distributions, QNB is based on 4 independent negative binomial distributions with their variances and means linked by local regressions, and in the way, the input control samples are also properly taken care of. In addition, different from DRME approach, which relies only the input control sample only for estimating the background, QNB uses a more robust estimator for gene expression by combining information from both input and IP samples, which could largely improve the testing performance for very lowly expressed genes. QNB showed improved performance on both simulated and real MeRIP-Seq datasets when compared with competing algorithms. And the QNB model is also applicable to other datasets related RNA modifications, including but not limited to RNA bisulfite sequencing, m 1 A-Seq, Par-CLIP, RIP-Seq, etc.

How conservative is Fisher's exact test? A quantitative evaluation of the two-sample comparative binomial trial.

PubMed

Crans, Gerald G; Shuster, Jonathan J

2008-08-15

The debate as to which statistical methodology is most appropriate for the analysis of the two-sample comparative binomial trial has persisted for decades. Practitioners who favor the conditional methods of Fisher, Fisher's exact test (FET), claim that only experimental outcomes containing the same amount of information should be considered when performing analyses. Hence, the total number of successes should be fixed at its observed level in hypothetical repetitions of the experiment. Using conditional methods in clinical settings can pose interpretation difficulties, since results are derived using conditional sample spaces rather than the set of all possible outcomes. Perhaps more importantly from a clinical trial design perspective, this test can be too conservative, resulting in greater resource requirements and more subjects exposed to an experimental treatment. The actual significance level attained by FET (the size of the test) has not been reported in the statistical literature. Berger (J. R. Statist. Soc. D (The Statistician) 2001; 50:79-85) proposed assessing the conservativeness of conditional methods using p-value confidence intervals. In this paper we develop a numerical algorithm that calculates the size of FET for sample sizes, n, up to 125 per group at the two-sided significance level, alpha = 0.05. Additionally, this numerical method is used to define new significance levels alpha(*) = alpha+epsilon, where epsilon is a small positive number, for each n, such that the size of the test is as close as possible to the pre-specified alpha (0.05 for the current work) without exceeding it. Lastly, a sample size and power calculation example are presented, which demonstrates the statistical advantages of implementing the adjustment to FET (using alpha(*) instead of alpha) in the two-sample comparative binomial trial. 2008 John Wiley & Sons, Ltd

A comparison of methods for the analysis of binomial clustered outcomes in behavioral research.

PubMed

Ferrari, Alberto; Comelli, Mario

2016-12-01

In behavioral research, data consisting of a per-subject proportion of "successes" and "failures" over a finite number of trials often arise. This clustered binary data are usually non-normally distributed, which can distort inference if the usual general linear model is applied and sample size is small. A number of more advanced methods is available, but they are often technically challenging and a comparative assessment of their performances in behavioral setups has not been performed. We studied the performances of some methods applicable to the analysis of proportions; namely linear regression, Poisson regression, beta-binomial regression and Generalized Linear Mixed Models (GLMMs). We report on a simulation study evaluating power and Type I error rate of these models in hypothetical scenarios met by behavioral researchers; plus, we describe results from the application of these methods on data from real experiments. Our results show that, while GLMMs are powerful instruments for the analysis of clustered binary outcomes, beta-binomial regression can outperform them in a range of scenarios. Linear regression gave results consistent with the nominal level of significance, but was overall less powerful. Poisson regression, instead, mostly led to anticonservative inference. GLMMs and beta-binomial regression are generally more powerful than linear regression; yet linear regression is robust to model misspecification in some conditions, whereas Poisson regression suffers heavily from violations of the assumptions when used to model proportion data. We conclude providing directions to behavioral scientists dealing with clustered binary data and small sample sizes. Copyright © 2016 Elsevier B.V. All rights reserved.

Simplified pupal surveys of Aedes aegypti (L.) for entomologic surveillance and dengue control.

PubMed

Barrera, Roberto

2009-07-01

Pupal surveys of Aedes aegypti (L.) are useful indicators of risk for dengue transmission, although sample sizes for reliable estimations can be large. This study explores two methods for making pupal surveys more practical yet reliable and used data from 10 pupal surveys conducted in Puerto Rico during 2004-2008. The number of pupae per person for each sampling followed a negative binomial distribution, thus showing aggregation. One method found a common aggregation parameter (k) for the negative binomial distribution, a finding that enabled the application of a sequential sampling method requiring few samples to determine whether the number of pupae/person was above a vector density threshold for dengue transmission. A second approach used the finding that the mean number of pupae/person is correlated with the proportion of pupa-infested households and calculated equivalent threshold proportions of pupa-positive households. A sequential sampling program was also developed for this method to determine whether observed proportions of infested households were above threshold levels. These methods can be used to validate entomological thresholds for dengue transmission.

Application of binomial and multinomial probability statistics to the sampling design process of a global grain tracing and recall system

USDA-ARS?s Scientific Manuscript database

Small, coded, pill-sized tracers embedded in grain are proposed as a method for grain traceability. A sampling process for a grain traceability system was designed and investigated by applying probability statistics using a science-based sampling approach to collect an adequate number of tracers fo...

Multiple objective optimization in reliability demonstration test

DOE PAGES

Lu, Lu; Anderson-Cook, Christine Michaela; Li, Mingyang

2016-10-01

Reliability demonstration tests are usually performed in product design or validation processes to demonstrate whether a product meets specified requirements on reliability. For binomial demonstration tests, the zero-failure test has been most commonly used due to its simplicity and use of minimum sample size to achieve an acceptable consumer’s risk level. However, this test can often result in unacceptably high risk for producers as well as a low probability of passing the test even when the product has good reliability. This paper explicitly explores the interrelationship between multiple objectives that are commonly of interest when planning a demonstration test andmore » proposes structured decision-making procedures using a Pareto front approach for selecting an optimal test plan based on simultaneously balancing multiple criteria. Different strategies are suggested for scenarios with different user priorities and graphical tools are developed to help quantify the trade-offs between choices and to facilitate informed decision making. As a result, potential impacts of some subjective user inputs on the final decision are studied to offer insights and useful guidance for general applications.« less

Zero-truncated negative binomial - Erlang distribution

NASA Astrophysics Data System (ADS)

Bodhisuwan, Winai; Pudprommarat, Chookait; Bodhisuwan, Rujira; Saothayanun, Luckhana

2017-11-01

The zero-truncated negative binomial-Erlang distribution is introduced. It is developed from negative binomial-Erlang distribution. In this work, the probability mass function is derived and some properties are included. The parameters of the zero-truncated negative binomial-Erlang distribution are estimated by using the maximum likelihood estimation. Finally, the proposed distribution is applied to real data, the number of methamphetamine in the Bangkok, Thailand. Based on the results, it shows that the zero-truncated negative binomial-Erlang distribution provided a better fit than the zero-truncated Poisson, zero-truncated negative binomial, zero-truncated generalized negative-binomial and zero-truncated Poisson-Lindley distributions for this data.

Estimation of aquifer scale proportion using equal area grids: assessment of regional scale groundwater quality

USGS Publications Warehouse

Belitz, Kenneth; Jurgens, Bryant C.; Landon, Matthew K.; Fram, Miranda S.; Johnson, Tyler D.

2010-01-01

The proportion of an aquifer with constituent concentrations above a specified threshold (high concentrations) is taken as a nondimensional measure of regional scale water quality. If computed on the basis of area, it can be referred to as the aquifer scale proportion. A spatially unbiased estimate of aquifer scale proportion and a confidence interval for that estimate are obtained through the use of equal area grids and the binomial distribution. Traditionally, the confidence interval for a binomial proportion is computed using either the standard interval or the exact interval. Research from the statistics literature has shown that the standard interval should not be used and that the exact interval is overly conservative. On the basis of coverage probability and interval width, the Jeffreys interval is preferred. If more than one sample per cell is available, cell declustering is used to estimate the aquifer scale proportion, and Kish's design effect may be useful for estimating an effective number of samples. The binomial distribution is also used to quantify the adequacy of a grid with a given number of cells for identifying a small target, defined as a constituent that is present at high concentrations in a small proportion of the aquifer. Case studies illustrate a consistency between approaches that use one well per grid cell and many wells per cell. The methods presented in this paper provide a quantitative basis for designing a sampling program and for utilizing existing data.

Modeling abundance using multinomial N-mixture models

USGS Publications Warehouse

Royle, Andy

2016-01-01

Multinomial N-mixture models are a generalization of the binomial N-mixture models described in Chapter 6 to allow for more complex and informative sampling protocols beyond simple counts. Many commonly used protocols such as multiple observer sampling, removal sampling, and capture-recapture produce a multivariate count frequency that has a multinomial distribution and for which multinomial N-mixture models can be developed. Such protocols typically result in more precise estimates than binomial mixture models because they provide direct information about parameters of the observation process. We demonstrate the analysis of these models in BUGS using several distinct formulations that afford great flexibility in the types of models that can be developed, and we demonstrate likelihood analysis using the unmarked package. Spatially stratified capture-recapture models are one class of models that fall into the multinomial N-mixture framework, and we discuss analysis of stratified versions of classical models such as model Mb, Mh and other classes of models that are only possible to describe within the multinomial N-mixture framework.

Ultrasound: a subexploited tool for sample preparation in metabolomics.

PubMed

Luque de Castro, M D; Delgado-Povedano, M M

2014-01-02

Metabolomics, one of the most recently emerged "omics", has taken advantage of ultrasound (US) to improve sample preparation (SP) steps. The metabolomics-US assisted SP step binomial has experienced a dissimilar development that has depended on the area (vegetal or animal) and the SP step. Thus, vegetal metabolomics and US assisted leaching has received the greater attention (encompassing subdisciplines such as metallomics, xenometabolomics and, mainly, lipidomics), but also liquid-liquid extraction and (bio)chemical reactions in metabolomics have taken advantage of US energy. Also clinical and animal samples have benefited from US assisted SP in metabolomics studies but in a lesser extension. The main effects of US have been shortening of the time required for the given step, and/or increase of its efficiency or availability for automation; nevertheless, attention paid to potential degradation caused by US has been scant or nil. Achievements and weak points of the metabolomics-US assisted SP step binomial are discussed and possible solutions to the present shortcomings are exposed. Copyright © 2013 Elsevier B.V. All rights reserved.

Selecting a distributional assumption for modelling relative densities of benthic macroinvertebrates

USGS Publications Warehouse

Gray, B.R.

2005-01-01

The selection of a distributional assumption suitable for modelling macroinvertebrate density data is typically challenging. Macroinvertebrate data often exhibit substantially larger variances than expected under a standard count assumption, that of the Poisson distribution. Such overdispersion may derive from multiple sources, including heterogeneity of habitat (historically and spatially), differing life histories for organisms collected within a single collection in space and time, and autocorrelation. Taken to extreme, heterogeneity of habitat may be argued to explain the frequent large proportions of zero observations in macroinvertebrate data. Sampling locations may consist of habitats defined qualitatively as either suitable or unsuitable. The former category may yield random or stochastic zeroes and the latter structural zeroes. Heterogeneity among counts may be accommodated by treating the count mean itself as a random variable, while extra zeroes may be accommodated using zero-modified count assumptions, including zero-inflated and two-stage (or hurdle) approaches. These and linear assumptions (following log- and square root-transformations) were evaluated using 9 years of mayfly density data from a 52 km, ninth-order reach of the Upper Mississippi River (n = 959). The data exhibited substantial overdispersion relative to that expected under a Poisson assumption (i.e. variance:mean ratio = 23 ??? 1), and 43% of the sampling locations yielded zero mayflies. Based on the Akaike Information Criterion (AIC), count models were improved most by treating the count mean as a random variable (via a Poisson-gamma distributional assumption) and secondarily by zero modification (i.e. improvements in AIC values = 9184 units and 47-48 units, respectively). Zeroes were underestimated by the Poisson, log-transform and square root-transform models, slightly by the standard negative binomial model but not by the zero-modified models (61%, 24%, 32%, 7%, and 0%, respectively). However, the zero-modified Poisson models underestimated small counts (1 ??? y ??? 4) and overestimated intermediate counts (7 ??? y ??? 23). Counts greater than zero were estimated well by zero-modified negative binomial models, while counts greater than one were also estimated well by the standard negative binomial model. Based on AIC and percent zero estimation criteria, the two-stage and zero-inflated models performed similarly. The above inferences were largely confirmed when the models were used to predict values from a separate, evaluation data set (n = 110). An exception was that, using the evaluation data set, the standard negative binomial model appeared superior to its zero-modified counterparts using the AIC (but not percent zero criteria). This and other evidence suggest that a negative binomial distributional assumption should be routinely considered when modelling benthic macroinvertebrate data from low flow environments. Whether negative binomial models should themselves be routinely examined for extra zeroes requires, from a statistical perspective, more investigation. However, this question may best be answered by ecological arguments that may be specific to the sampled species and locations. ?? 2004 Elsevier B.V. All rights reserved.

Estimating spatial and temporal components of variation in count data using negative binomial mixed models

USGS Publications Warehouse

Irwin, Brian J.; Wagner, Tyler; Bence, James R.; Kepler, Megan V.; Liu, Weihai; Hayes, Daniel B.

2013-01-01

Partitioning total variability into its component temporal and spatial sources is a powerful way to better understand time series and elucidate trends. The data available for such analyses of fish and other populations are usually nonnegative integer counts of the number of organisms, often dominated by many low values with few observations of relatively high abundance. These characteristics are not well approximated by the Gaussian distribution. We present a detailed description of a negative binomial mixed-model framework that can be used to model count data and quantify temporal and spatial variability. We applied these models to data from four fishery-independent surveys of Walleyes Sander vitreus across the Great Lakes basin. Specifically, we fitted models to gill-net catches from Wisconsin waters of Lake Superior; Oneida Lake, New York; Saginaw Bay in Lake Huron, Michigan; and Ohio waters of Lake Erie. These long-term monitoring surveys varied in overall sampling intensity, the total catch of Walleyes, and the proportion of zero catches. Parameter estimation included the negative binomial scaling parameter, and we quantified the random effects as the variations among gill-net sampling sites, the variations among sampled years, and site × year interactions. This framework (i.e., the application of a mixed model appropriate for count data in a variance-partitioning context) represents a flexible approach that has implications for monitoring programs (e.g., trend detection) and for examining the potential of individual variance components to serve as response metrics to large-scale anthropogenic perturbations or ecological changes.

The Dirichlet-Multinomial Model for Multivariate Randomized Response Data and Small Samples

ERIC Educational Resources Information Center

Avetisyan, Marianna; Fox, Jean-Paul

2012-01-01

In survey sampling the randomized response (RR) technique can be used to obtain truthful answers to sensitive questions. Although the individual answers are masked due to the RR technique, individual (sensitive) response rates can be estimated when observing multivariate response data. The beta-binomial model for binary RR data will be generalized…

Assessing Trauma, Substance Abuse, and Mental Health in a Sample of Homeless Men

ERIC Educational Resources Information Center

Kim, Mimi M.; Ford, Julian D.; Howard, Daniel L.; Bradford, Daniel W.

2010-01-01

This study examined the impact of physical and sexual trauma on a sample of 239 homeless men. Study participants completed a self-administered survey that collected data on demographics, exposure to psychological trauma, physical health and mental health problems, and substance use or misuse. Binomial logistic regression analyses were used to…

Distinguishing between Binomial, Hypergeometric and Negative Binomial Distributions

ERIC Educational Resources Information Center

Wroughton, Jacqueline; Cole, Tarah

2013-01-01

Recognizing the differences between three discrete distributions (Binomial, Hypergeometric and Negative Binomial) can be challenging for students. We present an activity designed to help students differentiate among these distributions. In addition, we present assessment results in the form of pre- and post-tests that were designed to assess the…

Library Book Circulation and the Beta-Binomial Distribution.

ERIC Educational Resources Information Center

Gelman, E.; Sichel, H. S.

1987-01-01

Argues that library book circulation is a binomial rather than a Poisson process, and that individual book popularities are continuous beta distributions. Three examples demonstrate the superiority of beta over negative binomial distribution, and it is suggested that a bivariate-binomial process would be helpful in predicting future book…

Distribution pattern of phthirapterans infesting certain common Indian birds.

PubMed

Saxena, A K; Kumar, Sandeep; Gupta, Nidhi; Mitra, J D; Ali, S A; Srivastava, Roshni

2007-08-01

The prevalence and frequency distribution patterns of 10 phthirapteran species infesting house sparrows, Indian parakeets, common mynas, and white breasted kingfishers were recorded in the district of Rampur, India, during 2004-05. The sample mean abundances, mean intensities, range of infestations, variance to mean ratios, values of the exponent of the negative binomial distribution, and the indices of discrepancy were also computed. Frequency distribution patterns of all phthirapteran species were skewed, but the observed frequencies did not correspond to the negative binomial distribution. Thus, adult-nymph ratios varied in different species from 1:0.53 to 1:1.25. Sex ratios of different phthirapteran species ranged from 1:1.10 to 1:1.65 and were female biased.

Accident prediction model for public highway-rail grade crossings.

PubMed

Lu, Pan; Tolliver, Denver

2016-05-01

Considerable research has focused on roadway accident frequency analysis, but relatively little research has examined safety evaluation at highway-rail grade crossings. Highway-rail grade crossings are critical spatial locations of utmost importance for transportation safety because traffic crashes at highway-rail grade crossings are often catastrophic with serious consequences. The Poisson regression model has been employed to analyze vehicle accident frequency as a good starting point for many years. The most commonly applied variations of Poisson including negative binomial, and zero-inflated Poisson. These models are used to deal with common crash data issues such as over-dispersion (sample variance is larger than the sample mean) and preponderance of zeros (low sample mean and small sample size). On rare occasions traffic crash data have been shown to be under-dispersed (sample variance is smaller than the sample mean) and traditional distributions such as Poisson or negative binomial cannot handle under-dispersion well. The objective of this study is to investigate and compare various alternate highway-rail grade crossing accident frequency models that can handle the under-dispersion issue. The contributions of the paper are two-fold: (1) application of probability models to deal with under-dispersion issues and (2) obtain insights regarding to vehicle crashes at public highway-rail grade crossings. Copyright © 2016 Elsevier Ltd. All rights reserved.

Estimating relative risks for common outcome using PROC NLP.

PubMed

Yu, Binbing; Wang, Zhuoqiao

2008-05-01

In cross-sectional or cohort studies with binary outcomes, it is biologically interpretable and of interest to estimate the relative risk or prevalence ratio, especially when the response rates are not rare. Several methods have been used to estimate the relative risk, among which the log-binomial models yield the maximum likelihood estimate (MLE) of the parameters. Because of restrictions on the parameter space, the log-binomial models often run into convergence problems. Some remedies, e.g., the Poisson and Cox regressions, have been proposed. However, these methods may give out-of-bound predicted response probabilities. In this paper, a new computation method using the SAS Nonlinear Programming (NLP) procedure is proposed to find the MLEs. The proposed NLP method was compared to the COPY method, a modified method to fit the log-binomial model. Issues in the implementation are discussed. For illustration, both methods were applied to data on the prevalence of microalbuminuria (micro-protein leakage into urine) for kidney disease patients from the Diabetes Control and Complications Trial. The sample SAS macro for calculating relative risk is provided in the appendix.

Estimation of Multinomial Probabilities.

DTIC Science & Technology

1978-11-01

1971) and Alam (1978) have shown that the maximum likelihood estimator is admissible with respect to the quadratic loss. Steinhaus (1957) and Trybula...appear). Johnson, B. Mck. (1971). On admissible estimators for certain fixed sample binomial populations. Ann. Math. Statist. 92, 1579-1587. Steinhaus , H

Accounting for non-independent detection when estimating abundance of organisms with a Bayesian approach

USGS Publications Warehouse

Martin, Julien; Royle, J. Andrew; MacKenzie, Darryl I.; Edwards, Holly H.; Kery, Marc; Gardner, Beth

2011-01-01

Summary 1. Binomial mixture models use repeated count data to estimate abundance. They are becoming increasingly popular because they provide a simple and cost-effective way to account for imperfect detection. However, these models assume that individuals are detected independently of each other. This assumption may often be violated in the field. For instance, manatees (Trichechus manatus latirostris) may surface in turbid water (i.e. become available for detection during aerial surveys) in a correlated manner (i.e. in groups). However, correlated behaviour, affecting the non-independence of individual detections, may also be relevant in other systems (e.g. correlated patterns of singing in birds and amphibians). 2. We extend binomial mixture models to account for correlated behaviour and therefore to account for non-independent detection of individuals. We simulated correlated behaviour using beta-binomial random variables. Our approach can be used to simultaneously estimate abundance, detection probability and a correlation parameter. 3. Fitting binomial mixture models to data that followed a beta-binomial distribution resulted in an overestimation of abundance even for moderate levels of correlation. In contrast, the beta-binomial mixture model performed considerably better in our simulation scenarios. We also present a goodness-of-fit procedure to evaluate the fit of beta-binomial mixture models. 4. We illustrate our approach by fitting both binomial and beta-binomial mixture models to aerial survey data of manatees in Florida. We found that the binomial mixture model did not fit the data, whereas there was no evidence of lack of fit for the beta-binomial mixture model. This example helps illustrate the importance of using simulations and assessing goodness-of-fit when analysing ecological data with N-mixture models. Indeed, both the simulations and the goodness-of-fit procedure highlighted the limitations of the standard binomial mixture model for aerial manatee surveys. 5. Overestimation of abundance by binomial mixture models owing to non-independent detections is problematic for ecological studies, but also for conservation. For example, in the case of endangered species, it could lead to inappropriate management decisions, such as downlisting. These issues will be increasingly relevant as more ecologists apply flexible N-mixture models to ecological data.

Logit and probit model in toll sensitivity analysis of Solo-Ngawi, Kartasura-Palang Joglo segment based on Willingness to Pay (WTP)

NASA Astrophysics Data System (ADS)

Handayani, Dewi; Cahyaning Putri, Hera; Mahmudah, AMH

2017-12-01

Solo-Ngawi toll road project is part of the mega project of the Trans Java toll road development initiated by the government and is still under construction until now. PT Solo Ngawi Jaya (SNJ) as the Solo-Ngawi toll management company needs to determine the toll fare that is in accordance with the business plan. The determination of appropriate toll rates will affect progress in regional economic sustainability and decrease the traffic congestion. These policy instruments is crucial for achieving environmentally sustainable transport. Therefore, the objective of this research is to find out how the toll fare sensitivity of Solo-Ngawi toll road based on Willingness To Pay (WTP). Primary data was obtained by distributing stated preference questionnaires to four wheeled vehicle users in Kartasura-Palang Joglo artery road segment. Further data obtained will be analysed with logit and probit model. Based on the analysis, it is found that the effect of fare change on the amount of WTP on the binomial logit model is more sensitive than the probit model on the same travel conditions. The range of tariff change against values of WTP on the binomial logit model is 20% greater than the range of values in the probit model . On the other hand, the probability results of the binomial logit model and the binary probit have no significant difference (less than 1%).

Modeling avian abundance from replicated counts using binomial mixture models

USGS Publications Warehouse

Kery, Marc; Royle, J. Andrew; Schmid, Hans

2005-01-01

Abundance estimation in ecology is usually accomplished by capture–recapture, removal, or distance sampling methods. These may be hard to implement at large spatial scales. In contrast, binomial mixture models enable abundance estimation without individual identification, based simply on temporally and spatially replicated counts. Here, we evaluate mixture models using data from the national breeding bird monitoring program in Switzerland, where some 250 1-km2 quadrats are surveyed using the territory mapping method three times during each breeding season. We chose eight species with contrasting distribution (wide–narrow), abundance (high–low), and detectability (easy–difficult). Abundance was modeled as a random effect with a Poisson or negative binomial distribution, with mean affected by forest cover, elevation, and route length. Detectability was a logit-linear function of survey date, survey date-by-elevation, and sampling effort (time per transect unit). Resulting covariate effects and parameter estimates were consistent with expectations. Detectability per territory (for three surveys) ranged from 0.66 to 0.94 (mean 0.84) for easy species, and from 0.16 to 0.83 (mean 0.53) for difficult species, depended on survey effort for two easy and all four difficult species, and changed seasonally for three easy and three difficult species. Abundance was positively related to route length in three high-abundance and one low-abundance (one easy and three difficult) species, and increased with forest cover in five forest species, decreased for two nonforest species, and was unaffected for a generalist species. Abundance estimates under the most parsimonious mixture models were between 1.1 and 8.9 (median 1.8) times greater than estimates based on territory mapping; hence, three surveys were insufficient to detect all territories for each species. We conclude that binomial mixture models are an important new approach for estimating abundance corrected for detectability when only repeated-count data are available. Future developments envisioned include estimation of trend, occupancy, and total regional abundance.

Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach

PubMed Central

Chen, Yong; Hong, Chuan; Ning, Yang; Su, Xiao

2018-01-01

When conducting a meta-analysis of studies with bivariate binary outcomes, challenges arise when the within-study correlation and between-study heterogeneity should be taken into account. In this paper, we propose a marginal beta-binomial model for the meta-analysis of studies with binary outcomes. This model is based on the composite likelihood approach, and has several attractive features compared to the existing models such as bivariate generalized linear mixed model (Chu and Cole, 2006) and Sarmanov beta-binomial model (Chen et al., 2012). The advantages of the proposed marginal model include modeling the probabilities in the original scale, not requiring any transformation of probabilities or any link function, having closed-form expression of likelihood function, and no constraints on the correlation parameter. More importantly, since the marginal beta-binomial model is only based on the marginal distributions, it does not suffer from potential misspecification of the joint distribution of bivariate study-specific probabilities. Such misspecification is difficult to detect and can lead to biased inference using currents methods. We compare the performance of the marginal beta-binomial model with the bivariate generalized linear mixed model and the Sarmanov beta-binomial model by simulation studies. Interestingly, the results show that the marginal beta-binomial model performs better than the Sarmanov beta-binomial model, whether or not the true model is Sarmanov beta-binomial, and the marginal beta-binomial model is more robust than the bivariate generalized linear mixed model under model misspecifications. Two meta-analyses of diagnostic accuracy studies and a meta-analysis of case-control studies are conducted for illustration. PMID:26303591

Spatial distribution of single-nucleotide polymorphisms related to fungicide resistance and implications for sampling.

PubMed

Van der Heyden, H; Dutilleul, P; Brodeur, L; Carisse, O

2014-06-01

Spatial distribution of single-nucleotide polymorphisms (SNPs) related to fungicide resistance was studied for Botrytis cinerea populations in vineyards and for B. squamosa populations in onion fields. Heterogeneity in this distribution was characterized by performing geostatistical analyses based on semivariograms and through the fitting of discrete probability distributions. Two SNPs known to be responsible for boscalid resistance (H272R and H272Y), both located on the B subunit of the succinate dehydrogenase gene, and one SNP known to be responsible for dicarboximide resistance (I365S) were chosen for B. cinerea in grape. For B. squamosa in onion, one SNP responsible for dicarboximide resistance (I365S homologous) was chosen. One onion field was sampled in 2009 and another one was sampled in 2010 for B. squamosa, and two vineyards were sampled in 2011 for B. cinerea, for a total of four sampled sites. Cluster sampling was carried on a 10-by-10 grid, each of the 100 nodes being the center of a 10-by-10-m quadrat. In each quadrat, 10 samples were collected and analyzed by restriction fragment length polymorphism polymerase chain reaction (PCR) or allele specific PCR. Mean SNP incidence varied from 16 to 68%, with an overall mean incidence of 43%. In the geostatistical analyses, omnidirectional variograms showed spatial autocorrelation characterized by ranges of 21 to 1 m. Various levels of anisotropy were detected, however, with variograms computed in four directions (at 0°, 45°, 90°, and 135° from the within-row direction used as reference), indicating that spatial autocorrelation was prevalent or characterized by a longer range in one direction. For all eight data sets, the β-binomial distribution was found to fit the data better than the binomial distribution. This indicates local aggregation of fungicide resistance among sampling units, as supported by estimates of the parameter θ of the β-binomial distribution of 0.09 to 0.23 (overall median value = 0.20). On the basis of the observed spatial distribution patterns of SNP incidence, sampling curves were computed for different levels of reliability, emphasizing the importance of sample size for the detection of mutation incidence below the risk threshold for control failure.

Design and analysis of three-arm trials with negative binomially distributed endpoints.

PubMed

Mütze, Tobias; Munk, Axel; Friede, Tim

2016-02-20

A three-arm clinical trial design with an experimental treatment, an active control, and a placebo control, commonly referred to as the gold standard design, enables testing of non-inferiority or superiority of the experimental treatment compared with the active control. In this paper, we propose methods for designing and analyzing three-arm trials with negative binomially distributed endpoints. In particular, we develop a Wald-type test with a restricted maximum-likelihood variance estimator for testing non-inferiority or superiority. For this test, sample size and power formulas as well as optimal sample size allocations will be derived. The performance of the proposed test will be assessed in an extensive simulation study with regard to type I error rate, power, sample size, and sample size allocation. For the purpose of comparison, Wald-type statistics with a sample variance estimator and an unrestricted maximum-likelihood estimator are included in the simulation study. We found that the proposed Wald-type test with a restricted variance estimator performed well across the considered scenarios and is therefore recommended for application in clinical trials. The methods proposed are motivated and illustrated by a recent clinical trial in multiple sclerosis. The R package ThreeArmedTrials, which implements the methods discussed in this paper, is available on CRAN. Copyright © 2015 John Wiley & Sons, Ltd.

[Evaluation of estimation of prevalence ratio using bayesian log-binomial regression model].

PubMed

Gao, W L; Lin, H; Liu, X N; Ren, X W; Li, J S; Shen, X P; Zhu, S L

2017-03-10

To evaluate the estimation of prevalence ratio ( PR ) by using bayesian log-binomial regression model and its application, we estimated the PR of medical care-seeking prevalence to caregivers' recognition of risk signs of diarrhea in their infants by using bayesian log-binomial regression model in Openbugs software. The results showed that caregivers' recognition of infant' s risk signs of diarrhea was associated significantly with a 13% increase of medical care-seeking. Meanwhile, we compared the differences in PR 's point estimation and its interval estimation of medical care-seeking prevalence to caregivers' recognition of risk signs of diarrhea and convergence of three models (model 1: not adjusting for the covariates; model 2: adjusting for duration of caregivers' education, model 3: adjusting for distance between village and township and child month-age based on model 2) between bayesian log-binomial regression model and conventional log-binomial regression model. The results showed that all three bayesian log-binomial regression models were convergence and the estimated PRs were 1.130(95 %CI : 1.005-1.265), 1.128(95 %CI : 1.001-1.264) and 1.132(95 %CI : 1.004-1.267), respectively. Conventional log-binomial regression model 1 and model 2 were convergence and their PRs were 1.130(95 % CI : 1.055-1.206) and 1.126(95 % CI : 1.051-1.203), respectively, but the model 3 was misconvergence, so COPY method was used to estimate PR , which was 1.125 (95 %CI : 1.051-1.200). In addition, the point estimation and interval estimation of PRs from three bayesian log-binomial regression models differed slightly from those of PRs from conventional log-binomial regression model, but they had a good consistency in estimating PR . Therefore, bayesian log-binomial regression model can effectively estimate PR with less misconvergence and have more advantages in application compared with conventional log-binomial regression model.

Dynamic equilibrium of reconstituting hematopoietic stem cell populations.

PubMed

O'Quigley, John

2010-12-01

Clonal dominance in hematopoietic stem cell populations is an important question of interest but not one we can directly answer. Any estimates are based on indirect measurement. For marked populations, we can equate empirical and theoretical moments for binomial sampling, in particular we can use the well-known formula for the sampling variation of a binomial proportion. The empirical variance itself cannot always be reliably estimated and some caution is needed. We describe the difficulties here and identify ready solutions which only require appropriate use of variance-stabilizing transformations. From these we obtain estimators for the steady state, or dynamic equilibrium, of the number of hematopoietic stem cells involved in repopulating the marrow. The calculations themselves are not too involved. We give the distribution theory for the estimator as well as simple approximations for practical application. As an illustration, we rework on data recently gathered to address the question as to whether or not reconstitution of marrow grafts in the clinical setting might be considered to be oligoclonal.

Type I error probability spending for post-market drug and vaccine safety surveillance with binomial data.

PubMed

Silva, Ivair R

2018-01-15

Type I error probability spending functions are commonly used for designing sequential analysis of binomial data in clinical trials, but it is also quickly emerging for near-continuous sequential analysis of post-market drug and vaccine safety surveillance. It is well known that, for clinical trials, when the null hypothesis is not rejected, it is still important to minimize the sample size. Unlike in post-market drug and vaccine safety surveillance, that is not important. In post-market safety surveillance, specially when the surveillance involves identification of potential signals, the meaningful statistical performance measure to be minimized is the expected sample size when the null hypothesis is rejected. The present paper shows that, instead of the convex Type I error spending shape conventionally used in clinical trials, a concave shape is more indicated for post-market drug and vaccine safety surveillance. This is shown for both, continuous and group sequential analysis. Copyright © 2017 John Wiley & Sons, Ltd.

Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach.

PubMed

Chen, Yong; Hong, Chuan; Ning, Yang; Su, Xiao

2016-01-15

When conducting a meta-analysis of studies with bivariate binary outcomes, challenges arise when the within-study correlation and between-study heterogeneity should be taken into account. In this paper, we propose a marginal beta-binomial model for the meta-analysis of studies with binary outcomes. This model is based on the composite likelihood approach and has several attractive features compared with the existing models such as bivariate generalized linear mixed model (Chu and Cole, 2006) and Sarmanov beta-binomial model (Chen et al., 2012). The advantages of the proposed marginal model include modeling the probabilities in the original scale, not requiring any transformation of probabilities or any link function, having closed-form expression of likelihood function, and no constraints on the correlation parameter. More importantly, because the marginal beta-binomial model is only based on the marginal distributions, it does not suffer from potential misspecification of the joint distribution of bivariate study-specific probabilities. Such misspecification is difficult to detect and can lead to biased inference using currents methods. We compare the performance of the marginal beta-binomial model with the bivariate generalized linear mixed model and the Sarmanov beta-binomial model by simulation studies. Interestingly, the results show that the marginal beta-binomial model performs better than the Sarmanov beta-binomial model, whether or not the true model is Sarmanov beta-binomial, and the marginal beta-binomial model is more robust than the bivariate generalized linear mixed model under model misspecifications. Two meta-analyses of diagnostic accuracy studies and a meta-analysis of case-control studies are conducted for illustration. Copyright © 2015 John Wiley & Sons, Ltd.

A Simulation Approach to Assessing Sampling Strategies for Insect Pests: An Example with the Balsam Gall Midge

PubMed Central

Carleton, R. Drew; Heard, Stephen B.; Silk, Peter J.

2013-01-01

Estimation of pest density is a basic requirement for integrated pest management in agriculture and forestry, and efficiency in density estimation is a common goal. Sequential sampling techniques promise efficient sampling, but their application can involve cumbersome mathematics and/or intensive warm-up sampling when pests have complex within- or between-site distributions. We provide tools for assessing the efficiency of sequential sampling and of alternative, simpler sampling plans, using computer simulation with “pre-sampling” data. We illustrate our approach using data for balsam gall midge (Paradiplosis tumifex) attack in Christmas tree farms. Paradiplosis tumifex proved recalcitrant to sequential sampling techniques. Midge distributions could not be fit by a common negative binomial distribution across sites. Local parameterization, using warm-up samples to estimate the clumping parameter k for each site, performed poorly: k estimates were unreliable even for samples of n∼100 trees. These methods were further confounded by significant within-site spatial autocorrelation. Much simpler sampling schemes, involving random or belt-transect sampling to preset sample sizes, were effective and efficient for P. tumifex. Sampling via belt transects (through the longest dimension of a stand) was the most efficient, with sample means converging on true mean density for sample sizes of n∼25–40 trees. Pre-sampling and simulation techniques provide a simple method for assessing sampling strategies for estimating insect infestation. We suspect that many pests will resemble P. tumifex in challenging the assumptions of sequential sampling methods. Our software will allow practitioners to optimize sampling strategies before they are brought to real-world applications, while potentially avoiding the need for the cumbersome calculations required for sequential sampling methods. PMID:24376556

Studying the Binomial Distribution Using LabVIEW

ERIC Educational Resources Information Center

George, Danielle J.; Hammer, Nathan I.

2015-01-01

This undergraduate physical chemistry laboratory exercise introduces students to the study of probability distributions both experimentally and using computer simulations. Students perform the classic coin toss experiment individually and then pool all of their data together to study the effect of experimental sample size on the binomial…

Factors related to the number of fast food meals obtained by college meal plan students.

PubMed

Dingman, Deirdre A; Schulz, Mark R; Wyrick, David L; Bibeau, Daniel L; Gupta, Sat N

2014-01-01

This study tested whether days on campus, financial access through a meal plan, and health consciousness were associated with number of meals that college students obtained from fast food restaurants. In April 2013, all students currently enrolled in a meal plan were invited to participate in an online survey (N = 1,246). Students were asked to report the total number of meals eaten in the past week and where they obtained them. Negative binomial regression was used, and it was found that the number of meals obtained from fast food restaurants was positively associated with financial access and negatively associated with health consciousness. An association between days on campus and the number of meals obtained from fast food restaurants was not found. Increasing levels of health consciousness and reducing access to fast food restaurants through flex plans may reduce college students' consumption of fast food.

M-Bonomial Coefficients and Their Identities

ERIC Educational Resources Information Center

Asiru, Muniru A.

2010-01-01

In this note, we introduce M-bonomial coefficients or (M-bonacci binomial coefficients). These are similar to the binomial and the Fibonomial (or Fibonacci-binomial) coefficients and can be displayed in a triangle similar to Pascal's triangle from which some identities become obvious.

Performance and structure of single-mode bosonic codes

NASA Astrophysics Data System (ADS)

Albert, Victor V.; Noh, Kyungjoo; Duivenvoorden, Kasper; Young, Dylan J.; Brierley, R. T.; Reinhold, Philip; Vuillot, Christophe; Li, Linshu; Shen, Chao; Girvin, S. M.; Terhal, Barbara M.; Jiang, Liang

2018-03-01

The early Gottesman, Kitaev, and Preskill (GKP) proposal for encoding a qubit in an oscillator has recently been followed by cat- and binomial-code proposals. Numerically optimized codes have also been proposed, and we introduce codes of this type here. These codes have yet to be compared using the same error model; we provide such a comparison by determining the entanglement fidelity of all codes with respect to the bosonic pure-loss channel (i.e., photon loss) after the optimal recovery operation. We then compare achievable communication rates of the combined encoding-error-recovery channel by calculating the channel's hashing bound for each code. Cat and binomial codes perform similarly, with binomial codes outperforming cat codes at small loss rates. Despite not being designed to protect against the pure-loss channel, GKP codes significantly outperform all other codes for most values of the loss rate. We show that the performance of GKP and some binomial codes increases monotonically with increasing average photon number of the codes. In order to corroborate our numerical evidence of the cat-binomial-GKP order of performance occurring at small loss rates, we analytically evaluate the quantum error-correction conditions of those codes. For GKP codes, we find an essential singularity in the entanglement fidelity in the limit of vanishing loss rate. In addition to comparing the codes, we draw parallels between binomial codes and discrete-variable systems. First, we characterize one- and two-mode binomial as well as multiqubit permutation-invariant codes in terms of spin-coherent states. Such a characterization allows us to introduce check operators and error-correction procedures for binomial codes. Second, we introduce a generalization of spin-coherent states, extending our characterization to qudit binomial codes and yielding a multiqudit code.

Problems on Divisibility of Binomial Coefficients

ERIC Educational Resources Information Center

Osler, Thomas J.; Smoak, James

2004-01-01

Twelve unusual problems involving divisibility of the binomial coefficients are represented in this article. The problems are listed in "The Problems" section. All twelve problems have short solutions which are listed in "The Solutions" section. These problems could be assigned to students in any course in which the binomial theorem and Pascal's…

Non-stochastic sampling error in quantal analyses for Campylobacter species on poultry products

USDA-ARS?s Scientific Manuscript database

Using primers and fluorescent probes specific for the most common foodborne Campylobacter species (C. jejuni = Cj and C. coli = Cc), we developed a multiplex, most probable number (MPN) assay using quantitative PCR (qPCR) as the determinant for binomial detection: number of p positives out of n = 6 ...

CUMBIN - CUMULATIVE BINOMIAL PROGRAMS

NASA Technical Reports Server (NTRS)

Bowerman, P. N.

1994-01-01

The cumulative binomial program, CUMBIN, is one of a set of three programs which calculate cumulative binomial probability distributions for arbitrary inputs. The three programs, CUMBIN, NEWTONP (NPO-17556), and CROSSER (NPO-17557), can be used independently of one another. CUMBIN can be used by statisticians and users of statistical procedures, test planners, designers, and numerical analysts. The program has been used for reliability/availability calculations. CUMBIN calculates the probability that a system of n components has at least k operating if the probability that any one operating is p and the components are independent. Equivalently, this is the reliability of a k-out-of-n system having independent components with common reliability p. CUMBIN can evaluate the incomplete beta distribution for two positive integer arguments. CUMBIN can also evaluate the cumulative F distribution and the negative binomial distribution, and can determine the sample size in a test design. CUMBIN is designed to work well with all integer values 0 < k <= n. To run the program, the user simply runs the executable version and inputs the information requested by the program. The program is not designed to weed out incorrect inputs, so the user must take care to make sure the inputs are correct. Once all input has been entered, the program calculates and lists the result. The CUMBIN program is written in C. It was developed on an IBM AT with a numeric co-processor using Microsoft C 5.0. Because the source code is written using standard C structures and functions, it should compile correctly with most C compilers. The program format is interactive. It has been implemented under DOS 3.2 and has a memory requirement of 26K. CUMBIN was developed in 1988.

Evaluation of the Johne's disease risk assessment and management plan on dairy farms in Ontario, Canada.

PubMed

Pieper, Laura; Sorge, Ulrike S; DeVries, Trevor J; Godkin, Ann; Lissemore, Kerry; Kelton, David F

2015-10-01

Johne's disease (JD) is a production-limiting gastrointestinal disease in cattle. To minimize the effects of JD, the Ontario dairy industry launched the Ontario Johne's Education and Management Assistance Program in 2010. As part of the program, trained veterinarians conducted a risk assessment and management plan (RAMP), an on-farm questionnaire where high RAMP scores are associated with high risk of JD transmission. Subsequently, veterinarians recommended farm-specific management practices for JD prevention. Milk or serum ELISA results from the milking herd were used to determine the herd ELISA status (HES) and within-herd prevalence. After 3.5 yr of implementation of the program, the aim of this study was to evaluate the associations among RAMP scores, HES, and recommendations. Data from 2,103 herds were available for the analyses. A zero-inflated negative binomial model for the prediction of the number of ELISA-positive animals per farm was built. The model included individual RAMP questions about purchasing animals in the logistic portion, indicating risks for between-herd transmission, and purchasing bulls, birth of calves outside the designated calving area, colostrum and milk feeding management, and adult cow environmental hygiene in the negative binomial portion, indicating risk factors for within-herd transmission. However, farms which fed low-risk milk compared with milk replacer had fewer seropositive animals. The model additionally included the JD herd history in the negative binomial and the logistic portion, indicating that herds with a JD herd history were more likely to have at least 1 positive animal and to have a higher number of positive animals. Generally, a positive association was noted between RAMP scores and the odds of receiving a recommendation for the respective risk area; however, the relationship was not always linear. For general JD risk and calving area risk, seropositive herds had higher odds of receiving recommendations compared with seronegative herds if the section scores were low. This study suggests that the RAMP is a valuable tool to assess the risk for JD transmission within and between herds and to determine farm-specific recommendations for JD prevention. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

A Three-Parameter Generalisation of the Beta-Binomial Distribution with Applications

DTIC Science & Technology

1987-07-01

York. Rust, R.T. and Klompmaker, J.E. (1981). Improving the estimation procedure for the beta binomial t.v. exposure model. Journal of Marketing ... Research . 18, 442-448. Sabavala, D.J. and Morrison, D.G. (1977). Television show loyalty: a beta- binomial model using recall data. Journal of Advertiuing

Distribution-free Inference of Zero-inated Binomial Data for Longitudinal Studies.

PubMed

He, H; Wang, W J; Hu, J; Gallop, R; Crits-Christoph, P; Xia, Y L

2015-10-01

Count reponses with structural zeros are very common in medical and psychosocial research, especially in alcohol and HIV research, and the zero-inflated poisson (ZIP) and zero-inflated negative binomial (ZINB) models are widely used for modeling such outcomes. However, as alcohol drinking outcomes such as days of drinkings are counts within a given period, their distributions are bounded above by an upper limit (total days in the period) and thus inherently follow a binomial or zero-inflated binomial (ZIB) distribution, rather than a Poisson or zero-inflated Poisson (ZIP) distribution, in the presence of structural zeros. In this paper, we develop a new semiparametric approach for modeling zero-inflated binomial (ZIB)-like count responses for cross-sectional as well as longitudinal data. We illustrate this approach with both simulated and real study data.

Jump-and-return sandwiches: A new family of binomial-like selective inversion sequences with improved performance

NASA Astrophysics Data System (ADS)

Brenner, Tom; Chen, Johnny; Stait-Gardner, Tim; Zheng, Gang; Matsukawa, Shingo; Price, William S.

2018-03-01

A new family of binomial-like inversion sequences, named jump-and-return sandwiches (JRS), has been developed by inserting a binomial-like sequence into a standard jump-and-return sequence, discovered through use of a stochastic Genetic Algorithm optimisation. Compared to currently used binomial-like inversion sequences (e.g., 3-9-19 and W5), the new sequences afford wider inversion bands and narrower non-inversion bands with an equal number of pulses. As an example, two jump-and-return sandwich 10-pulse sequences achieved 95% inversion at offsets corresponding to 9.4% and 10.3% of the non-inversion band spacing, compared to 14.7% for the binomial-like W5 inversion sequence, i.e., they afforded non-inversion bands about two thirds the width of the W5 non-inversion band.

Revealing Word Order: Using Serial Position in Binomials to Predict Properties of the Speaker

ERIC Educational Resources Information Center

Iliev, Rumen; Smirnova, Anastasia

2016-01-01

Three studies test the link between word order in binomials and psychological and demographic characteristics of a speaker. While linguists have already suggested that psychological, cultural and societal factors are important in choosing word order in binomials, the vast majority of relevant research was focused on general factors and on broadly…

DRME: Count-based differential RNA methylation analysis at small sample size scenario.

PubMed

Liu, Lian; Zhang, Shao-Wu; Gao, Fan; Zhang, Yixin; Huang, Yufei; Chen, Runsheng; Meng, Jia

2016-04-15

Differential methylation, which concerns difference in the degree of epigenetic regulation via methylation between two conditions, has been formulated as a beta or beta-binomial distribution to address the within-group biological variability in sequencing data. However, a beta or beta-binomial model is usually difficult to infer at small sample size scenario with discrete reads count in sequencing data. On the other hand, as an emerging research field, RNA methylation has drawn more and more attention recently, and the differential analysis of RNA methylation is significantly different from that of DNA methylation due to the impact of transcriptional regulation. We developed DRME to better address the differential RNA methylation problem. The proposed model can effectively describe within-group biological variability at small sample size scenario and handles the impact of transcriptional regulation on RNA methylation. We tested the newly developed DRME algorithm on simulated and 4 MeRIP-Seq case-control studies and compared it with Fisher's exact test. It is in principle widely applicable to several other RNA-related data types as well, including RNA Bisulfite sequencing and PAR-CLIP. The code together with an MeRIP-Seq dataset is available online (https://github.com/lzcyzm/DRME) for evaluation and reproduction of the figures shown in this article. Copyright © 2016 Elsevier Inc. All rights reserved.

An analytical framework for estimating aquatic species density from environmental DNA

USGS Publications Warehouse

Chambert, Thierry; Pilliod, David S.; Goldberg, Caren S.; Doi, Hideyuki; Takahara, Teruhiko

2018-01-01

Environmental DNA (eDNA) analysis of water samples is on the brink of becoming a standard monitoring method for aquatic species. This method has improved detection rates over conventional survey methods and thus has demonstrated effectiveness for estimation of site occupancy and species distribution. The frontier of eDNA applications, however, is to infer species density. Building upon previous studies, we present and assess a modeling approach that aims at inferring animal density from eDNA. The modeling combines eDNA and animal count data from a subset of sites to estimate species density (and associated uncertainties) at other sites where only eDNA data are available. As a proof of concept, we first perform a cross-validation study using experimental data on carp in mesocosms. In these data, fish densities are known without error, which allows us to test the performance of the method with known data. We then evaluate the model using field data from a study on a stream salamander species to assess the potential of this method to work in natural settings, where density can never be known with absolute certainty. Two alternative distributions (Normal and Negative Binomial) to model variability in eDNA concentration data are assessed. Assessment based on the proof of concept data (carp) revealed that the Negative Binomial model provided much more accurate estimates than the model based on a Normal distribution, likely because eDNA data tend to be overdispersed. Greater imprecision was found when we applied the method to the field data, but the Negative Binomial model still provided useful density estimates. We call for further model development in this direction, as well as further research targeted at sampling design optimization. It will be important to assess these approaches on a broad range of study systems.

Quantification of integrated HIV DNA by repetitive-sampling Alu-HIV PCR on the basis of poisson statistics.

PubMed

De Spiegelaere, Ward; Malatinkova, Eva; Lynch, Lindsay; Van Nieuwerburgh, Filip; Messiaen, Peter; O'Doherty, Una; Vandekerckhove, Linos

2014-06-01

Quantification of integrated proviral HIV DNA by repetitive-sampling Alu-HIV PCR is a candidate virological tool to monitor the HIV reservoir in patients. However, the experimental procedures and data analysis of the assay are complex and hinder its widespread use. Here, we provide an improved and simplified data analysis method by adopting binomial and Poisson statistics. A modified analysis method on the basis of Poisson statistics was used to analyze the binomial data of positive and negative reactions from a 42-replicate Alu-HIV PCR by use of dilutions of an integration standard and on samples of 57 HIV-infected patients. Results were compared with the quantitative output of the previously described Alu-HIV PCR method. Poisson-based quantification of the Alu-HIV PCR was linearly correlated with the standard dilution series, indicating that absolute quantification with the Poisson method is a valid alternative for data analysis of repetitive-sampling Alu-HIV PCR data. Quantitative outputs of patient samples assessed by the Poisson method correlated with the previously described Alu-HIV PCR analysis, indicating that this method is a valid alternative for quantifying integrated HIV DNA. Poisson-based analysis of the Alu-HIV PCR data enables absolute quantification without the need of a standard dilution curve. Implementation of the CI estimation permits improved qualitative analysis of the data and provides a statistical basis for the required minimal number of technical replicates. © 2014 The American Association for Clinical Chemistry.

Jump-and-return sandwiches: A new family of binomial-like selective inversion sequences with improved performance.

PubMed

Brenner, Tom; Chen, Johnny; Stait-Gardner, Tim; Zheng, Gang; Matsukawa, Shingo; Price, William S

2018-03-01

A new family of binomial-like inversion sequences, named jump-and-return sandwiches (JRS), has been developed by inserting a binomial-like sequence into a standard jump-and-return sequence, discovered through use of a stochastic Genetic Algorithm optimisation. Compared to currently used binomial-like inversion sequences (e.g., 3-9-19 and W5), the new sequences afford wider inversion bands and narrower non-inversion bands with an equal number of pulses. As an example, two jump-and-return sandwich 10-pulse sequences achieved 95% inversion at offsets corresponding to 9.4% and 10.3% of the non-inversion band spacing, compared to 14.7% for the binomial-like W5 inversion sequence, i.e., they afforded non-inversion bands about two thirds the width of the W5 non-inversion band. Copyright © 2018 Elsevier Inc. All rights reserved.

Comparison of multiplicity distributions to the negative binomial distribution in muon-proton scattering

NASA Astrophysics Data System (ADS)

Arneodo, M.; Arvidson, A.; Aubert, J. J.; Badełek, B.; Beaufays, J.; Bee, C. P.; Benchouk, C.; Berghoff, G.; Bird, I.; Blum, D.; Böhm, E.; de Bouard, X.; Brasse, F. W.; Braun, H.; Broll, C.; Brown, S.; Brück, H.; Calen, H.; Chima, J. S.; Ciborowski, J.; Clifft, R.; Coignet, G.; Combley, F.; Coughlan, J.; D'Agostini, G.; Dahlgren, S.; Dengler, F.; Derado, I.; Dreyer, T.; Drees, J.; Düren, M.; Eckardt, V.; Edwards, A.; Edwards, M.; Ernst, T.; Eszes, G.; Favier, J.; Ferrero, M. I.; Figiel, J.; Flauger, W.; Foster, J.; Ftáčnik, J.; Gabathuler, E.; Gajewski, J.; Gamet, R.; Gayler, J.; Geddes, N.; Grafström, P.; Grard, F.; Haas, J.; Hagberg, E.; Hasert, F. J.; Hayman, P.; Heusse, P.; Jaffré, M.; Jachołkowska, A.; Janata, F.; Jancsó, G.; Johnson, A. S.; Kabuss, E. M.; Kellner, G.; Korbel, V.; Krüger, J.; Kullander, S.; Landgraf, U.; Lanske, D.; Loken, J.; Long, K.; Maire, M.; Malecki, P.; Manz, A.; Maselli, S.; Mohr, W.; Montanet, F.; Montgomery, H. E.; Nagy, E.; Nassalski, J.; Norton, P. R.; Oakham, F. G.; Osborne, A. M.; Pascaud, C.; Pawlik, B.; Payre, P.; Peroni, C.; Peschel, H.; Pessard, H.; Pettinghale, J.; Pietrzyk, B.; Pietrzyk, U.; Pönsgen, B.; Pötsch, M.; Renton, P.; Ribarics, P.; Rith, K.; Rondio, E.; Sandacz, A.; Scheer, M.; Schlagböhmer, A.; Schiemann, H.; Schmitz, N.; Schneegans, M.; Schneider, A.; Scholz, M.; Schröder, T.; Schultze, K.; Sloan, T.; Stier, H. E.; Studt, M.; Taylor, G. N.; Thénard, J. M.; Thompson, J. C.; de La Torre, A.; Toth, J.; Urban, L.; Urban, L.; Wallucks, W.; Whalley, M.; Wheeler, S.; Williams, W. S. C.; Wimpenny, S. J.; Windmolders, R.; Wolf, G.

1987-09-01

The multiplicity distributions of charged hadrons produced in the deep inelastic muon-proton scattering at 280 GeV are analysed in various rapidity intervals, as a function of the total hadronic centre of mass energy W ranging from 4 20 GeV. Multiplicity distributions for the backward and forward hemispheres are also analysed separately. The data can be well parameterized by binomial distributions, extending their range of applicability to the case of lepton-proton scattering. The energy and the rapidity dependence of the parameters is presented and a smooth transition from the negative binomial distribution via Poissonian to the ordinary binomial is observed.

Censored Hurdle Negative Binomial Regression (Case Study: Neonatorum Tetanus Case in Indonesia)

NASA Astrophysics Data System (ADS)

Yuli Rusdiana, Riza; Zain, Ismaini; Wulan Purnami, Santi

2017-06-01

Hurdle negative binomial model regression is a method that can be used for discreate dependent variable, excess zero and under- and overdispersion. It uses two parts approach. The first part estimates zero elements from dependent variable is zero hurdle model and the second part estimates not zero elements (non-negative integer) from dependent variable is called truncated negative binomial models. The discrete dependent variable in such cases is censored for some values. The type of censor that will be studied in this research is right censored. This study aims to obtain the parameter estimator hurdle negative binomial regression for right censored dependent variable. In the assessment of parameter estimation methods used Maximum Likelihood Estimator (MLE). Hurdle negative binomial model regression for right censored dependent variable is applied on the number of neonatorum tetanus cases in Indonesia. The type data is count data which contains zero values in some observations and other variety value. This study also aims to obtain the parameter estimator and test statistic censored hurdle negative binomial model. Based on the regression results, the factors that influence neonatorum tetanus case in Indonesia is the percentage of baby health care coverage and neonatal visits.

Co-Infestation and Spatial Distribution of Bactrocera carambolae and Anastrepha spp. (Diptera: Tephritidae) in Common Guava in the Eastern Amazon

PubMed Central

Deus, E. G.; Godoy, W. A. C.; Sousa, M. S. M.; Lopes, G. N.; Jesus-Barros, C. R.; Silva, J. G.; Adaime, R.

2016-01-01

Field infestation and spatial distribution of introduced Bactrocera carambolae Drew and Hancock and native species of Anastrepha in common guavas [Psidium guajava (L.)] were investigated in the eastern Amazon. Fruit sampling was carried out in the municipalities of Calçoene and Oiapoque in the state of Amapá, Brazil. The frequency distribution of larvae in fruit was fitted to the negative binomial distribution. Anastrepha striata was more abundant in both sampled areas in comparison to Anastrepha fraterculus (Wiedemann) and B. carambolae. The frequency distribution analysis of adults revealed an aggregated pattern for B. carambolae as well as for A. fraterculus and Anastrepha striata Schiner, described by the negative binomial distribution. Although the populations of Anastrepha spp. may have suffered some impact due to the presence of B. carambolae, the results are still not robust enough to indicate effective reduction in the abundance of Anastrepha spp. caused by B. carambolae in a general sense. The high degree of aggregation observed for both species suggests interspecific co-occurrence with the simultaneous presence of both species in the analysed fruit. Moreover, a significant fraction of uninfested guavas also indicated absence of competitive displacement. PMID:27638949

Variability in results from negative binomial models for Lyme disease measured at different spatial scales.

PubMed

Tran, Phoebe; Waller, Lance

2015-01-01

Lyme disease has been the subject of many studies due to increasing incidence rates year after year and the severe complications that can arise in later stages of the disease. Negative binomial models have been used to model Lyme disease in the past with some success. However, there has been little focus on the reliability and consistency of these models when they are used to study Lyme disease at multiple spatial scales. This study seeks to explore how sensitive/consistent negative binomial models are when they are used to study Lyme disease at different spatial scales (at the regional and sub-regional levels). The study area includes the thirteen states in the Northeastern United States with the highest Lyme disease incidence during the 2002-2006 period. Lyme disease incidence at county level for the period of 2002-2006 was linked with several previously identified key landscape and climatic variables in a negative binomial regression model for the Northeastern region and two smaller sub-regions (the New England sub-region and the Mid-Atlantic sub-region). This study found that negative binomial models, indeed, were sensitive/inconsistent when used at different spatial scales. We discuss various plausible explanations for such behavior of negative binomial models. Further investigation of the inconsistency and sensitivity of negative binomial models when used at different spatial scales is important for not only future Lyme disease studies and Lyme disease risk assessment/management but any study that requires use of this model type in a spatial context. Copyright © 2014 Elsevier Inc. All rights reserved.

Binomial Baseball.

ERIC Educational Resources Information Center

Levin, Eugene M.

1981-01-01

Student access to programmable calculators and computer terminals, coupled with a familiarity with baseball, provides opportunities to enhance their understanding of the binomial distribution and other aspects of analysis. (MP)

Modeling the distribution of colonial species to improve estimation of plankton concentration in ballast water

NASA Astrophysics Data System (ADS)

Rajakaruna, Harshana; VandenByllaardt, Julie; Kydd, Jocelyn; Bailey, Sarah

2018-03-01

The International Maritime Organization (IMO) has set limits on allowable plankton concentrations in ballast water discharge to minimize aquatic invasions globally. Previous guidance on ballast water sampling and compliance decision thresholds was based on the assumption that probability distributions of plankton are Poisson when spatially homogenous, or negative binomial when heterogeneous. We propose a hierarchical probability model, which incorporates distributions at the level of particles (i.e., discrete individuals plus colonies per unit volume) and also within particles (i.e., individuals per particle) to estimate the average plankton concentration in ballast water. We examined the performance of the models using data for plankton in the size class ≥ 10 μm and < 50 μm, collected from five different depths of a ballast tank of a commercial ship in three independent surveys. We show that the data fit to the negative binomial and the hierarchical probability models equally well, with both models performing better than the Poisson model at the scale of our sampling. The hierarchical probability model, which accounts for both the individuals and the colonies in a sample, reduces the uncertainty associated with the concentration estimation, and improves the power of rejecting the decision on ship's compliance when a ship does not truly comply with the standard. We show examples of how to test ballast water compliance using the above models.

New Class of Quantum Error-Correcting Codes for a Bosonic Mode

NASA Astrophysics Data System (ADS)

Michael, Marios H.; Silveri, Matti; Brierley, R. T.; Albert, Victor V.; Salmilehto, Juha; Jiang, Liang; Girvin, S. M.

2016-07-01

We construct a new class of quantum error-correcting codes for a bosonic mode, which are advantageous for applications in quantum memories, communication, and scalable computation. These "binomial quantum codes" are formed from a finite superposition of Fock states weighted with binomial coefficients. The binomial codes can exactly correct errors that are polynomial up to a specific degree in bosonic creation and annihilation operators, including amplitude damping and displacement noise as well as boson addition and dephasing errors. For realistic continuous-time dissipative evolution, the codes can perform approximate quantum error correction to any given order in the time step between error detection measurements. We present an explicit approximate quantum error recovery operation based on projective measurements and unitary operations. The binomial codes are tailored for detecting boson loss and gain errors by means of measurements of the generalized number parity. We discuss optimization of the binomial codes and demonstrate that by relaxing the parity structure, codes with even lower unrecoverable error rates can be achieved. The binomial codes are related to existing two-mode bosonic codes, but offer the advantage of requiring only a single bosonic mode to correct amplitude damping as well as the ability to correct other errors. Our codes are similar in spirit to "cat codes" based on superpositions of the coherent states but offer several advantages such as smaller mean boson number, exact rather than approximate orthonormality of the code words, and an explicit unitary operation for repumping energy into the bosonic mode. The binomial quantum codes are realizable with current superconducting circuit technology, and they should prove useful in other quantum technologies, including bosonic quantum memories, photonic quantum communication, and optical-to-microwave up- and down-conversion.

Effects of Test Level Discrimination and Difficulty on Answer-Copying Indices

ERIC Educational Resources Information Center

Sunbul, Onder; Yormaz, Seha

2018-01-01

In this study Type I Error and the power rates of omega (?) and GBT (generalized binomial test) indices were investigated for several nominal alpha levels and for 40 and 80-item test lengths with 10,000-examinee sample size under several test level restrictions. As a result, Type I error rates of both indices were found to be below the acceptable…

Comparison of robustness to outliers between robust poisson models and log-binomial models when estimating relative risks for common binary outcomes: a simulation study.

PubMed

Chen, Wansu; Shi, Jiaxiao; Qian, Lei; Azen, Stanley P

2014-06-26

To estimate relative risks or risk ratios for common binary outcomes, the most popular model-based methods are the robust (also known as modified) Poisson and the log-binomial regression. Of the two methods, it is believed that the log-binomial regression yields more efficient estimators because it is maximum likelihood based, while the robust Poisson model may be less affected by outliers. Evidence to support the robustness of robust Poisson models in comparison with log-binomial models is very limited. In this study a simulation was conducted to evaluate the performance of the two methods in several scenarios where outliers existed. The findings indicate that for data coming from a population where the relationship between the outcome and the covariate was in a simple form (e.g. log-linear), the two models yielded comparable biases and mean square errors. However, if the true relationship contained a higher order term, the robust Poisson models consistently outperformed the log-binomial models even when the level of contamination is low. The robust Poisson models are more robust (or less sensitive) to outliers compared to the log-binomial models when estimating relative risks or risk ratios for common binary outcomes. Users should be aware of the limitations when choosing appropriate models to estimate relative risks or risk ratios.

Speech-discrimination scores modeled as a binomial variable.

PubMed

Thornton, A R; Raffin, M J

1978-09-01

Many studies have reported variability data for tests of speech discrimination, and the disparate results of these studies have not been given a simple explanation. Arguments over the relative merits of 25- vs 50-word tests have ignored the basic mathematical properties inherent in the use of percentage scores. The present study models performance on clinical tests of speech discrimination as a binomial variable. A binomial model was developed, and some of its characteristics were tested against data from 4120 scores obtained on the CID Auditory Test W-22. A table for determining significant deviations between scores was generated and compared to observed differences in half-list scores for the W-22 tests. Good agreement was found between predicted and observed values. Implications of the binomial characteristics of speech-discrimination scores are discussed.

Possibility and Challenges of Conversion of Current Virus Species Names to Linnaean Binomials

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

Postler, Thomas S.; Clawson, Anna N.; Amarasinghe, Gaya K.

Botanical, mycological, zoological, and prokaryotic species names follow the Linnaean format, consisting of an italicized Latinized binomen with a capitalized genus name and a lower case species epithet (e.g., Homo sapiens). Virus species names, however, do not follow a uniform format, and, even when binomial, are not Linnaean in style. In this thought exercise, we attempted to convert all currently official names of species included in the virus family Arenaviridae and the virus order Mononegavirales to Linnaean binomials, and to identify and address associated challenges and concerns. Surprisingly, this endeavor was not as complicated or time-consuming as even the authorsmore » of this article expected when conceiving the experiment. [Arenaviridae; binomials; ICTV; International Committee on Taxonomy of Viruses; Mononegavirales; virus nomenclature; virus taxonomy.]« less

The coverage of a random sample from a biological community.

PubMed

Engen, S

1975-03-01

A taxonomic group will frequently have a large number of species with small abundances. When a sample is drawn at random from this group, one is therefore faced with the problem that a large proportion of the species will not be discovered. A general definition of quantitative measures of "sample coverage" is proposed, and the problem of statistical inference is considered for two special cases, (1) the actual total relative abundance of those species that are represented in the sample, and (2) their relative contribution to the information index of diversity. The analysis is based on a extended version of the negative binomial species frequency model. The results are tabulated.

Statistical methods for the beta-binomial model in teratology.

PubMed Central

Yamamoto, E; Yanagimoto, T

1994-01-01

The beta-binomial model is widely used for analyzing teratological data involving littermates. Recent developments in statistical analyses of teratological data are briefly reviewed with emphasis on the model. For statistical inference of the parameters in the beta-binomial distribution, separation of the likelihood introduces an likelihood inference. This leads to reducing biases of estimators and also to improving accuracy of empirical significance levels of tests. Separate inference of the parameters can be conducted in a unified way. PMID:8187716

Modeling Tetanus Neonatorum case using the regression of negative binomial and zero-inflated negative binomial

NASA Astrophysics Data System (ADS)

Amaliana, Luthfatul; Sa'adah, Umu; Wayan Surya Wardhani, Ni

2017-12-01

Tetanus Neonatorum is an infectious disease that can be prevented by immunization. The number of Tetanus Neonatorum cases in East Java Province is the highest in Indonesia until 2015. Tetanus Neonatorum data contain over dispersion and big enough proportion of zero-inflation. Negative Binomial (NB) regression is an alternative method when over dispersion happens in Poisson regression. However, the data containing over dispersion and zero-inflation are more appropriately analyzed by using Zero-Inflated Negative Binomial (ZINB) regression. The purpose of this study are: (1) to model Tetanus Neonatorum cases in East Java Province with 71.05 percent proportion of zero-inflation by using NB and ZINB regression, (2) to obtain the best model. The result of this study indicates that ZINB is better than NB regression with smaller AIC.

Analysis of generalized negative binomial distributions attached to hyperbolic Landau levels

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

Chhaiba, Hassan, E-mail: chhaiba.hassan@gmail.com; Demni, Nizar, E-mail: nizar.demni@univ-rennes1.fr; Mouayn, Zouhair, E-mail: mouayn@fstbm.ac.ma

2016-07-15

To each hyperbolic Landau level of the Poincaré disc is attached a generalized negative binomial distribution. In this paper, we compute the moment generating function of this distribution and supply its atomic decomposition as a perturbation of the negative binomial distribution by a finitely supported measure. Using the Mandel parameter, we also discuss the nonclassical nature of the associated coherent states. Next, we derive a Lévy-Khintchine-type representation of its characteristic function when the latter does not vanish and deduce that it is quasi-infinitely divisible except for the lowest hyperbolic Landau level corresponding to the negative binomial distribution. By considering themore » total variation of the obtained quasi-Lévy measure, we introduce a new infinitely divisible distribution for which we derive the characteristic function.« less

Acceptance sampling for attributes via hypothesis testing and the hypergeometric distribution

NASA Astrophysics Data System (ADS)

Samohyl, Robert Wayne

2017-10-01

This paper questions some aspects of attribute acceptance sampling in light of the original concepts of hypothesis testing from Neyman and Pearson (NP). Attribute acceptance sampling in industry, as developed by Dodge and Romig (DR), generally follows the international standards of ISO 2859, and similarly the Brazilian standards NBR 5425 to NBR 5427 and the United States Standards ANSI/ASQC Z1.4. The paper evaluates and extends the area of acceptance sampling in two directions. First, by suggesting the use of the hypergeometric distribution to calculate the parameters of sampling plans avoiding the unnecessary use of approximations such as the binomial or Poisson distributions. We show that, under usual conditions, discrepancies can be large. The conclusion is that the hypergeometric distribution, ubiquitously available in commonly used software, is more appropriate than other distributions for acceptance sampling. Second, and more importantly, we elaborate the theory of acceptance sampling in terms of hypothesis testing rigorously following the original concepts of NP. By offering a common theoretical structure, hypothesis testing from NP can produce a better understanding of applications even beyond the usual areas of industry and commerce such as public health and political polling. With the new procedures, both sample size and sample error can be reduced. What is unclear in traditional acceptance sampling is the necessity of linking the acceptable quality limit (AQL) exclusively to the producer and the lot quality percent defective (LTPD) exclusively to the consumer. In reality, the consumer should also be preoccupied with a value of AQL, as should the producer with LTPD. Furthermore, we can also question why type I error is always uniquely associated with the producer as producer risk, and likewise, the same question arises with consumer risk which is necessarily associated with type II error. The resolution of these questions is new to the literature. The article presents R code throughout.

A powerful and flexible approach to the analysis of RNA sequence count data.

PubMed

Zhou, Yi-Hui; Xia, Kai; Wright, Fred A

2011-10-01

A number of penalization and shrinkage approaches have been proposed for the analysis of microarray gene expression data. Similar techniques are now routinely applied to RNA sequence transcriptional count data, although the value of such shrinkage has not been conclusively established. If penalization is desired, the explicit modeling of mean-variance relationships provides a flexible testing regimen that 'borrows' information across genes, while easily incorporating design effects and additional covariates. We describe BBSeq, which incorporates two approaches: (i) a simple beta-binomial generalized linear model, which has not been extensively tested for RNA-Seq data and (ii) an extension of an expression mean-variance modeling approach to RNA-Seq data, involving modeling of the overdispersion as a function of the mean. Our approaches are flexible, allowing for general handling of discrete experimental factors and continuous covariates. We report comparisons with other alternate methods to handle RNA-Seq data. Although penalized methods have advantages for very small sample sizes, the beta-binomial generalized linear model, combined with simple outlier detection and testing approaches, appears to have favorable characteristics in power and flexibility. An R package containing examples and sample datasets is available at http://www.bios.unc.edu/research/genomic_software/BBSeq yzhou@bios.unc.edu; fwright@bios.unc.edu Supplementary data are available at Bioinformatics online.

A Statistical Treatment of Bioassay Pour Fractions

NASA Technical Reports Server (NTRS)

Barengoltz, Jack; Hughes, David W.

2014-01-01

The binomial probability distribution is used to treat the statistics of a microbiological sample that is split into two parts, with only one part evaluated for spore count. One wishes to estimate the total number of spores in the sample based on the counts obtained from the part that is evaluated (pour fraction). Formally, the binomial distribution is recharacterized as a function of the observed counts (successes), with the total number (trials) an unknown. The pour fraction is the probability of success per spore (trial). This distribution must be renormalized in terms of the total number. Finally, the new renormalized distribution is integrated and mathematically inverted to yield the maximum estimate of the total number as a function of a desired level of confidence ( P(

Estimating the prevalence and intensity of Schistosoma mansoni infection among rural communities in Western Tanzania: The influence of sampling strategy and statistical approach

PubMed Central

Bakuza, Jared S.; Denwood, Matthew J.; Nkwengulila, Gamba

2017-01-01

Background Schistosoma mansoni is a parasite of major public health importance in developing countries, where it causes a neglected tropical disease known as intestinal schistosomiasis. However, the distribution of the parasite within many endemic regions is currently unknown, which hinders effective control. The purpose of this study was to characterize the prevalence and intensity of infection of S. mansoni in a remote area of western Tanzania. Methodology/Principal findings Stool samples were collected from 192 children and 147 adults residing in Gombe National Park and four nearby villages. Children were actively sampled in local schools, and adults were sampled passively by voluntary presentation at the local health clinics. The two datasets were therefore analysed separately. Faecal worm egg count (FWEC) data were analysed using negative binomial and zero-inflated negative binomial (ZINB) models with explanatory variables of site, sex, and age. The ZINB models indicated that a substantial proportion of the observed zero FWEC reflected a failure to detect eggs in truly infected individuals, meaning that the estimated true prevalence was much higher than the apparent prevalence as calculated based on the simple proportion of non-zero FWEC. For the passively sampled data from adults, the data were consistent with close to 100% true prevalence of infection. Both the prevalence and intensity of infection differed significantly between sites, but there were no significant associations with sex or age. Conclusions/Significance Overall, our data suggest a more widespread distribution of S. mansoni in this part of Tanzania than was previously thought. The apparent prevalence estimates substantially under-estimated the true prevalence as determined by the ZINB models, and the two types of sampling strategies also resulted in differing conclusions regarding prevalence of infection. We therefore recommend that future surveillance programmes designed to assess risk factors should use active sampling whenever possible, in order to avoid the self-selection bias associated with passive sampling. PMID:28934206

The Binomial Distribution in Shooting

ERIC Educational Resources Information Center

Chalikias, Miltiadis S.

2009-01-01

The binomial distribution is used to predict the winner of the 49th International Shooting Sport Federation World Championship in double trap shooting held in 2006 in Zagreb, Croatia. The outcome of the competition was definitely unexpected.

The Role of Economic Uncertainty on the Block Economic Value - a New Valuation Approach / Rola Czynnika Niepewności Przy Obliczaniu Wskaźnika Rentowności - Nowe Podejście

NASA Astrophysics Data System (ADS)

Dehghani, H.; Ataee-Pour, M.

2012-12-01

The block economic value (EV) is one of the most important parameters in mine evaluation. This parameter can affect significant factors such as mining sequence, final pit limit and net present value. Nowadays, the aim of open pit mine planning is to define optimum pit limits and an optimum life of mine production scheduling that maximizes the pit value under some technical and operational constraints. Therefore, it is necessary to calculate the block economic value at the first stage of the mine planning process, correctly. Unrealistic block economic value estimation may cause the mining project managers to make the wrong decision and thus may impose inexpiable losses to the project. The effective parameters such as metal price, operating cost, grade and so forth are always assumed certain in the conventional methods of EV calculation. While, obviously, these parameters have uncertain nature. Therefore, usually, the conventional methods results are far from reality. In order to solve this problem, a new technique is used base on an invented binomial tree which is developed in this research. This method can calculate the EV and project PV under economic uncertainty. In this paper, the EV and project PV were initially determined using Whittle formula based on certain economic parameters and a multivariate binomial tree based on the economic uncertainties such as the metal price and cost uncertainties. Finally the results were compared. It is concluded that applying the metal price and cost uncertainties causes the calculated block economic value and net present value to be more realistic than certain conditions.

Predicting length of stay from an electronic patient record system: a primary total knee replacement example.

PubMed

Carter, Evelene M; Potts, Henry W W

2014-04-04

To investigate whether factors can be identified that significantly affect hospital length of stay from those available in an electronic patient record system, using primary total knee replacements as an example. To investigate whether a model can be produced to predict the length of stay based on these factors to help resource planning and patient expectations on their length of stay. Data were extracted from the electronic patient record system for discharges from primary total knee operations from January 2007 to December 2011 (n=2,130) at one UK hospital and analysed for their effect on length of stay using Mann-Whitney and Kruskal-Wallis tests for discrete data and Spearman's correlation coefficient for continuous data. Models for predicting length of stay for primary total knee replacements were tested using the Poisson regression and the negative binomial modelling techniques. Factors found to have a significant effect on length of stay were age, gender, consultant, discharge destination, deprivation and ethnicity. Applying a negative binomial model to these variables was successful. The model predicted the length of stay of those patients who stayed 4-6 days (~50% of admissions) with 75% accuracy within 2 days (model data). Overall, the model predicted the total days stayed over 5 years to be only 88 days more than actual, a 6.9% uplift (test data). Valuable information can be found about length of stay from the analysis of variables easily extracted from an electronic patient record system. Models can be successfully created to help improve resource planning and from which a simple decision support system can be produced to help patient expectation on their length of stay.

The magnetisation distribution of the Ising model - a new approach

NASA Astrophysics Data System (ADS)

Hakan Lundow, Per; Rosengren, Anders

2010-03-01

A completely new approach to the Ising model in 1 to 5 dimensions is developed. We employ a generalisation of the binomial coefficients to describe the magnetisation distributions of the Ising model. For the complete graph this distribution is exact. For simple lattices of dimensions d=1 and d=5 the magnetisation distributions are remarkably well-fitted by the generalized binomial distributions. For d=4 we are only slightly less successful, while for d=2,3 we see some deviations (with exceptions!) between the generalized binomial and the Ising distribution. The results speak in favour of the generalized binomial distribution's correctness regarding their general behaviour in comparison to the Ising model. A theoretical analysis of the distribution's moments also lends support their being correct asymptotically, including the logarithmic corrections in d=4. The full extent to which they correctly model the Ising distribution, and for which graph families, is not settled though.

Phase transition and information cascade in a voting model

NASA Astrophysics Data System (ADS)

Hisakado, M.; Mori, S.

2010-08-01

In this paper, we introduce a voting model that is similar to a Keynesian beauty contest and analyse it from a mathematical point of view. There are two types of voters—copycat and independent—and two candidates. Our voting model is a binomial distribution (independent voters) doped in a beta binomial distribution (copycat voters). We find that the phase transition in this system is at the upper limit of t, where t is the time (or the number of the votes). Our model contains three phases. If copycats constitute a majority or even half of the total voters, the voting rate converges more slowly than it would in a binomial distribution. If independents constitute the majority of voters, the voting rate converges at the same rate as it would in a binomial distribution. We also study why it is difficult to estimate the conclusion of a Keynesian beauty contest when there is an information cascade.

Abstract knowledge versus direct experience in processing of binomial expressions

PubMed Central

Morgan, Emily; Levy, Roger

2016-01-01

We ask whether word order preferences for binomial expressions of the form A and B (e.g. bread and butter) are driven by abstract linguistic knowledge of ordering constraints referencing the semantic, phonological, and lexical properties of the constituent words, or by prior direct experience with the specific items in questions. Using forced-choice and self-paced reading tasks, we demonstrate that online processing of never-before-seen binomials is influenced by abstract knowledge of ordering constraints, which we estimate with a probabilistic model. In contrast, online processing of highly frequent binomials is primarily driven by direct experience, which we estimate from corpus frequency counts. We propose a trade-off wherein processing of novel expressions relies upon abstract knowledge, while reliance upon direct experience increases with increased exposure to an expression. Our findings support theories of language processing in which both compositional generation and direct, holistic reuse of multi-word expressions play crucial roles. PMID:27776281

On extinction time of a generalized endemic chain-binomial model.

PubMed

Aydogmus, Ozgur

2016-09-01

We considered a chain-binomial epidemic model not conferring immunity after infection. Mean field dynamics of the model has been analyzed and conditions for the existence of a stable endemic equilibrium are determined. The behavior of the chain-binomial process is probabilistically linked to the mean field equation. As a result of this link, we were able to show that the mean extinction time of the epidemic increases at least exponentially as the population size grows. We also present simulation results for the process to validate our analytical findings. Copyright © 2016 Elsevier Inc. All rights reserved.

Solar San Diego: The Impact of Binomial Rate Structures on Real PV Systems; Preprint

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

VanGeet, O.; Brown, E.; Blair, T.

2008-05-01

There is confusion in the marketplace regarding the impact of solar photovoltaics (PV) on the user's actual electricity bill under California Net Energy Metering, particularly with binomial tariffs (those that include both demand and energy charges) and time-of-use (TOU) rate structures. The City of San Diego has extensive real-time electrical metering on most of its buildings and PV systems, with interval data for overall consumption and PV electrical production available for multiple years. This paper uses 2007 PV-system data from two city facilities to illustrate the impacts of binomial rate designs. The analysis will determine the energy and demand savingsmore » that the PV systems are achieving relative to the absence of systems. A financial analysis of PV-system performance under various rate structures is presented. The data revealed that actual demand and energy use benefits of binomial tariffs increase in summer months, when solar resources allow for maximized electricity production. In a binomial tariff system, varying on- and semi-peak times can result in approximately $1,100 change in demand charges per month over not having a PV system in place, an approximate 30% cost savings. The PV systems are also shown to have a 30%-50% reduction in facility energy charges in 2007.« less

Clinical and MRI activity as determinants of sample size for pediatric multiple sclerosis trials

PubMed Central

Verhey, Leonard H.; Signori, Alessio; Arnold, Douglas L.; Bar-Or, Amit; Sadovnick, A. Dessa; Marrie, Ruth Ann; Banwell, Brenda

2013-01-01

Objective: To estimate sample sizes for pediatric multiple sclerosis (MS) trials using new T2 lesion count, annualized relapse rate (ARR), and time to first relapse (TTFR) endpoints. Methods: Poisson and negative binomial models were fit to new T2 lesion and relapse count data, and negative binomial time-to-event and exponential models were fit to TTFR data of 42 children with MS enrolled in a national prospective cohort study. Simulations were performed by resampling from the best-fitting model of new T2 lesion count, number of relapses, or TTFR, under various assumptions of the effect size, trial duration, and model parameters. Results: Assuming a 50% reduction in new T2 lesions over 6 months, 90 patients/arm are required, whereas 165 patients/arm are required for a 40% treatment effect. Sample sizes for 2-year trials using relapse-related endpoints are lower than that for 1-year trials. For 2-year trials and a conservative assumption of overdispersion (ϑ), sample sizes range from 70 patients/arm (using ARR) to 105 patients/arm (TTFR) for a 50% reduction in relapses, and 230 patients/arm (ARR) to 365 patients/arm (TTFR) for a 30% relapse reduction. Assuming a less conservative ϑ, 2-year trials using ARR require 45 patients/arm (60 patients/arm for TTFR) for a 50% reduction in relapses and 145 patients/arm (200 patients/arm for TTFR) for a 30% reduction. Conclusion: Six-month phase II trials using new T2 lesion count as an endpoint are feasible in the pediatric MS population; however, trials powered on ARR or TTFR will need to be 2 years in duration and will require multicentered collaboration. PMID:23966255

Using the Binomial Series to Prove the Arithmetic Mean-Geometric Mean Inequality

ERIC Educational Resources Information Center

Persky, Ronald L.

2003-01-01

In 1968, Leon Gerber compared (1 + x)[superscript a] to its kth partial sum as a binomial series. His result is stated and, as an application of this result, a proof of the arithmetic mean-geometric mean inequality is presented.

Four Bootstrap Confidence Intervals for the Binomial-Error Model.

ERIC Educational Resources Information Center

Lin, Miao-Hsiang; Hsiung, Chao A.

1992-01-01

Four bootstrap methods are identified for constructing confidence intervals for the binomial-error model. The extent to which similar results are obtained and the theoretical foundation of each method and its relevance and ranges of modeling the true score uncertainty are discussed. (SLD)

Possibility and Challenges of Conversion of Current Virus Species Names to Linnaean Binomials.

PubMed

Postler, Thomas S; Clawson, Anna N; Amarasinghe, Gaya K; Basler, Christopher F; Bavari, Sbina; Benko, Mária; Blasdell, Kim R; Briese, Thomas; Buchmeier, Michael J; Bukreyev, Alexander; Calisher, Charles H; Chandran, Kartik; Charrel, Rémi; Clegg, Christopher S; Collins, Peter L; Juan Carlos, De La Torre; Derisi, Joseph L; Dietzgen, Ralf G; Dolnik, Olga; Dürrwald, Ralf; Dye, John M; Easton, Andrew J; Emonet, Sébastian; Formenty, Pierre; Fouchier, Ron A M; Ghedin, Elodie; Gonzalez, Jean-Paul; Harrach, Balázs; Hewson, Roger; Horie, Masayuki; Jiang, Dàohóng; Kobinger, Gary; Kondo, Hideki; Kropinski, Andrew M; Krupovic, Mart; Kurath, Gael; Lamb, Robert A; Leroy, Eric M; Lukashevich, Igor S; Maisner, Andrea; Mushegian, Arcady R; Netesov, Sergey V; Nowotny, Norbert; Patterson, Jean L; Payne, Susan L; PaWeska, Janusz T; Peters, Clarence J; Radoshitzky, Sheli R; Rima, Bertus K; Romanowski, Victor; Rubbenstroth, Dennis; Sabanadzovic, Sead; Sanfaçon, Hélène; Salvato, Maria S; Schwemmle, Martin; Smither, Sophie J; Stenglein, Mark D; Stone, David M; Takada, Ayato; Tesh, Robert B; Tomonaga, Keizo; Tordo, Noël; Towner, Jonathan S; Vasilakis, Nikos; Volchkov, Viktor E; Wahl-Jensen, Victoria; Walker, Peter J; Wang, Lin-Fa; Varsani, Arvind; Whitfield, Anna E; Zerbini, F Murilo; Kuhn, Jens H

2017-05-01

Botanical, mycological, zoological, and prokaryotic species names follow the Linnaean format, consisting of an italicized Latinized binomen with a capitalized genus name and a lower case species epithet (e.g., Homo sapiens). Virus species names, however, do not follow a uniform format, and, even when binomial, are not Linnaean in style. In this thought exercise, we attempted to convert all currently official names of species included in the virus family Arenaviridae and the virus order Mononegavirales to Linnaean binomials, and to identify and address associated challenges and concerns. Surprisingly, this endeavor was not as complicated or time-consuming as even the authors of this article expected when conceiving the experiment. [Arenaviridae; binomials; ICTV; International Committee on Taxonomy of Viruses; Mononegavirales; virus nomenclature; virus taxonomy.]. Published by Oxford University Press on behalf of Society of Systematic Biologists 2016. This work is written by a US Government employee and is in the public domain in the US.

The arcsine is asinine: the analysis of proportions in ecology.

PubMed

Warton, David I; Hui, Francis K C

2011-01-01

The arcsine square root transformation has long been standard procedure when analyzing proportional data in ecology, with applications in data sets containing binomial and non-binomial response variables. Here, we argue that the arcsine transform should not be used in either circumstance. For binomial data, logistic regression has greater interpretability and higher power than analyses of transformed data. However, it is important to check the data for additional unexplained variation, i.e., overdispersion, and to account for it via the inclusion of random effects in the model if found. For non-binomial data, the arcsine transform is undesirable on the grounds of interpretability, and because it can produce nonsensical predictions. The logit transformation is proposed as an alternative approach to address these issues. Examples are presented in both cases to illustrate these advantages, comparing various methods of analyzing proportions including untransformed, arcsine- and logit-transformed linear models and logistic regression (with or without random effects). Simulations demonstrate that logistic regression usually provides a gain in power over other methods.

[The reentrant binomial model of nuclear anomalies growth in rhabdomyosarcoma RA-23 cell populations under increasing doze of rare ionizing radiation].

PubMed

Alekseeva, N P; Alekseev, A O; Vakhtin, Iu B; Kravtsov, V Iu; Kuzovatov, S N; Skorikova, T I

2008-01-01

Distributions of nuclear morphology anomalies in transplantable rabdomiosarcoma RA-23 cell populations were investigated under effect of ionizing radiation from 0 to 45 Gy. Internuclear bridges, nuclear protrusions and dumbbell-shaped nuclei were accepted for morphological anomalies. Empirical distributions of the number of anomalies per 100 nuclei were used. The adequate model of reentrant binomial distribution has been found. The sum of binomial random variables with binomial number of summands has such distribution. Averages of these random variables were named, accordingly, internal and external average reentrant components. Their maximum likelihood estimations were received. Statistical properties of these estimations were investigated by means of statistical modeling. It has been received that at equally significant correlation between the radiation dose and the average of nuclear anomalies in cell populations after two-three cellular cycles from the moment of irradiation in vivo the irradiation doze significantly correlates with internal average reentrant component, and in remote descendants of cell transplants irradiated in vitro - with external one.

On Models for Binomial Data with Random Numbers of Trials

PubMed Central

Comulada, W. Scott; Weiss, Robert E.

2010-01-01

Summary A binomial outcome is a count s of the number of successes out of the total number of independent trials n = s + f, where f is a count of the failures. The n are random variables not fixed by design in many studies. Joint modeling of (s, f) can provide additional insight into the science and into the probability π of success that cannot be directly incorporated by the logistic regression model. Observations where n = 0 are excluded from the binomial analysis yet may be important to understanding how π is influenced by covariates. Correlation between s and f may exist and be of direct interest. We propose Bayesian multivariate Poisson models for the bivariate response (s, f), correlated through random effects. We extend our models to the analysis of longitudinal and multivariate longitudinal binomial outcomes. Our methodology was motivated by two disparate examples, one from teratology and one from an HIV tertiary intervention study. PMID:17688514

The Difference Calculus and The NEgative Binomial Distribution

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

Bowman, Kimiko o; Shenton, LR

2007-01-01

In a previous paper we state the dominant term in the third central moment of the maximum likelihood estimator k of the parameter k in the negative binomial probability function where the probability generating function is (p + 1 - pt){sup -k}. A partial sum of the series {Sigma}1/(k + x){sup 3} is involved, where x is a negative binomial random variate. In expectation this sum can only be found numerically using the computer. Here we give a simple definite integral in (0,1) for the generalized case. This means that now we do have a valid expression for {radical}{beta}{sub 11}(k)more » and {radical}{beta}{sub 11}(p). In addition we use the finite difference operator {Delta}, and E = 1 + {Delta} to set up formulas for low order moments. Other examples of the operators are quoted relating to the orthogonal set of polynomials associated with the negative binomial probability function used as a weight function.« less

Psychotherapeutic and vocational interventions among young adults with work disability due to mental disorders in Finland.

PubMed

Mattila-Holappa, Pauliina; Joensuu, Matti; Ahola, Kirsi; Kivekäs, Teija; Kivimäki, Mika; Koskinen, Aki; Virtanen, Marianna

2018-05-01

Backround: Little is known about treatment and rehabilitation received and planned among young adults with work disability due to a mental disorder. To examine the implemented psychotherapeutic and vocational interventions and treatment plans among young adults with work disability due to a mental disorder. Data were collected from medical records of young Finnish adults aged 18-34 with a long-term work disability history due to a mental disorder (N = 1163). The participant characteristics associated with four types of interventions were analyzed using log-binomial regression analysis. In total, 34% had participated in a psychotherapeutic intervention. Of the non-students, 26% had participated in vocational intervention. For 46% of the non-students, neither type of intervention was planned. Both implemented and planned psychotherapeutic interventions were associated with female sex, high education, attachment to employment, and absence of substance abuse. Low education and childhood adversity were associated with implemented vocational interventions and absence of substance abuse with planned vocational interventions. There is an unmet need for psychotherapeutic interventions among men, among those with lower socio-economic status, and among those with poor attachment to labor market. In addition, there is a lack of vocational interventions for those with high education. People with substance abuse are largely excluded from both types of interventions.

Spiritual and ceremonial plants in North America: an assessment of Moerman's ethnobotanical database comparing Residual, Binomial, Bayesian and Imprecise Dirichlet Model (IDM) analysis.

PubMed

Turi, Christina E; Murch, Susan J

2013-07-09

Ethnobotanical research and the study of plants used for rituals, ceremonies and to connect with the spirit world have led to the discovery of many novel psychoactive compounds such as nicotine, caffeine, and cocaine. In North America, spiritual and ceremonial uses of plants are well documented and can be accessed online via the University of Michigan's Native American Ethnobotany Database. The objective of the study was to compare Residual, Bayesian, Binomial and Imprecise Dirichlet Model (IDM) analyses of ritual, ceremonial and spiritual plants in Moerman's ethnobotanical database and to identify genera that may be good candidates for the discovery of novel psychoactive compounds. The database was queried with the following format "Family Name AND Ceremonial OR Spiritual" for 263 North American botanical families. Spiritual and ceremonial flora consisted of 86 families with 517 species belonging to 292 genera. Spiritual taxa were then grouped further into ceremonial medicines and items categories. Residual, Bayesian, Binomial and IDM analysis were performed to identify over and under-utilized families. The 4 statistical approaches were in good agreement when identifying under-utilized families but large families (>393 species) were underemphasized by Binomial, Bayesian and IDM approaches for over-utilization. Residual, Binomial, and IDM analysis identified similar families as over-utilized in the medium (92-392 species) and small (<92 species) classes. The families Apiaceae, Asteraceae, Ericacea, Pinaceae and Salicaceae were identified as significantly over-utilized as ceremonial medicines in medium and large sized families. Analysis of genera within the Apiaceae and Asteraceae suggest that the genus Ligusticum and Artemisia are good candidates for facilitating the discovery of novel psychoactive compounds. The 4 statistical approaches were not consistent in the selection of over-utilization of flora. Residual analysis revealed overall trends that were supported by Binomial analysis when separated into small, medium and large families. The Bayesian, Binomial and IDM approaches identified different genera as potentially important. Species belonging to the genus Artemisia and Ligusticum were most consistently identified and may be valuable in future studies of the ethnopharmacology. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A powerful and flexible approach to the analysis of RNA sequence count data

PubMed Central

Zhou, Yi-Hui; Xia, Kai; Wright, Fred A.

2011-01-01

Motivation: A number of penalization and shrinkage approaches have been proposed for the analysis of microarray gene expression data. Similar techniques are now routinely applied to RNA sequence transcriptional count data, although the value of such shrinkage has not been conclusively established. If penalization is desired, the explicit modeling of mean–variance relationships provides a flexible testing regimen that ‘borrows’ information across genes, while easily incorporating design effects and additional covariates. Results: We describe BBSeq, which incorporates two approaches: (i) a simple beta-binomial generalized linear model, which has not been extensively tested for RNA-Seq data and (ii) an extension of an expression mean–variance modeling approach to RNA-Seq data, involving modeling of the overdispersion as a function of the mean. Our approaches are flexible, allowing for general handling of discrete experimental factors and continuous covariates. We report comparisons with other alternate methods to handle RNA-Seq data. Although penalized methods have advantages for very small sample sizes, the beta-binomial generalized linear model, combined with simple outlier detection and testing approaches, appears to have favorable characteristics in power and flexibility. Availability: An R package containing examples and sample datasets is available at http://www.bios.unc.edu/research/genomic_software/BBSeq Contact: yzhou@bios.unc.edu; fwright@bios.unc.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21810900

Inference for binomial probability based on dependent Bernoulli random variables with applications to meta‐analysis and group level studies

PubMed Central

Bakbergenuly, Ilyas; Morgenthaler, Stephan

2016-01-01

We study bias arising as a result of nonlinear transformations of random variables in random or mixed effects models and its effect on inference in group‐level studies or in meta‐analysis. The findings are illustrated on the example of overdispersed binomial distributions, where we demonstrate considerable biases arising from standard log‐odds and arcsine transformations of the estimated probability p^, both for single‐group studies and in combining results from several groups or studies in meta‐analysis. Our simulations confirm that these biases are linear in ρ, for small values of ρ, the intracluster correlation coefficient. These biases do not depend on the sample sizes or the number of studies K in a meta‐analysis and result in abysmal coverage of the combined effect for large K. We also propose bias‐correction for the arcsine transformation. Our simulations demonstrate that this bias‐correction works well for small values of the intraclass correlation. The methods are applied to two examples of meta‐analyses of prevalence. PMID:27192062

A chi-square goodness-of-fit test for non-identically distributed random variables: with application to empirical Bayes

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

Conover, W.J.; Cox, D.D.; Martz, H.F.

1997-12-01

When using parametric empirical Bayes estimation methods for estimating the binomial or Poisson parameter, the validity of the assumed beta or gamma conjugate prior distribution is an important diagnostic consideration. Chi-square goodness-of-fit tests of the beta or gamma prior hypothesis are developed for use when the binomial sample sizes or Poisson exposure times vary. Nine examples illustrate the application of the methods, using real data from such diverse applications as the loss of feedwater flow rates in nuclear power plants, the probability of failure to run on demand and the failure rates of the high pressure coolant injection systems atmore » US commercial boiling water reactors, the probability of failure to run on demand of emergency diesel generators in US commercial nuclear power plants, the rate of failure of aircraft air conditioners, baseball batting averages, the probability of testing positive for toxoplasmosis, and the probability of tumors in rats. The tests are easily applied in practice by means of corresponding Mathematica{reg_sign} computer programs which are provided.« less

Mixture models for estimating the size of a closed population when capture rates vary among individuals

USGS Publications Warehouse

Dorazio, R.M.; Royle, J. Andrew

2003-01-01

We develop a parameterization of the beta-binomial mixture that provides sensible inferences about the size of a closed population when probabilities of capture or detection vary among individuals. Three classes of mixture models (beta-binomial, logistic-normal, and latent-class) are fitted to recaptures of snowshoe hares for estimating abundance and to counts of bird species for estimating species richness. In both sets of data, rates of detection appear to vary more among individuals (animals or species) than among sampling occasions or locations. The estimates of population size and species richness are sensitive to model-specific assumptions about the latent distribution of individual rates of detection. We demonstrate using simulation experiments that conventional diagnostics for assessing model adequacy, such as deviance, cannot be relied on for selecting classes of mixture models that produce valid inferences about population size. Prior knowledge about sources of individual heterogeneity in detection rates, if available, should be used to help select among classes of mixture models that are to be used for inference.

Selecting Tools to Model Integer and Binomial Multiplication

ERIC Educational Resources Information Center

Pratt, Sarah Smitherman; Eddy, Colleen M.

2017-01-01

Mathematics teachers frequently provide concrete manipulatives to students during instruction; however, the rationale for using certain manipulatives in conjunction with concepts may not be explored. This article focuses on area models that are currently used in classrooms to provide concrete examples of integer and binomial multiplication. The…

Patterns of medicinal plant use: an examination of the Ecuadorian Shuar medicinal flora using contingency table and binomial analyses.

PubMed

Bennett, Bradley C; Husby, Chad E

2008-03-28

Botanical pharmacopoeias are non-random subsets of floras, with some taxonomic groups over- or under-represented. Moerman [Moerman, D.E., 1979. Symbols and selectivity: a statistical analysis of Native American medical ethnobotany, Journal of Ethnopharmacology 1, 111-119] introduced linear regression/residual analysis to examine these patterns. However, regression, the commonly-employed analysis, suffers from several statistical flaws. We use contingency table and binomial analyses to examine patterns of Shuar medicinal plant use (from Amazonian Ecuador). We first analyzed the Shuar data using Moerman's approach, modified to better meet requirements of linear regression analysis. Second, we assessed the exact randomization contingency table test for goodness of fit. Third, we developed a binomial model to test for non-random selection of plants in individual families. Modified regression models (which accommodated assumptions of linear regression) reduced R(2) to from 0.59 to 0.38, but did not eliminate all problems associated with regression analyses. Contingency table analyses revealed that the entire flora departs from the null model of equal proportions of medicinal plants in all families. In the binomial analysis, only 10 angiosperm families (of 115) differed significantly from the null model. These 10 families are largely responsible for patterns seen at higher taxonomic levels. Contingency table and binomial analyses offer an easy and statistically valid alternative to the regression approach.

Estimating the Parameters of the Beta-Binomial Distribution.

ERIC Educational Resources Information Center

Wilcox, Rand R.

1979-01-01

For some situations the beta-binomial distribution might be used to describe the marginal distribution of test scores for a particular population of examinees. Several different methods of approximating the maximum likelihood estimate were investigated, and it was found that the Newton-Raphson method should be used when it yields admissable…

Multilevel Models for Binary Data

ERIC Educational Resources Information Center

Powers, Daniel A.

2012-01-01

The methods and models for categorical data analysis cover considerable ground, ranging from regression-type models for binary and binomial data, count data, to ordered and unordered polytomous variables, as well as regression models that mix qualitative and continuous data. This article focuses on methods for binary or binomial data, which are…

Possibility and Challenges of Conversion of Current Virus Species Names to Linnaean Binomials

PubMed Central

Postler, Thomas S.; Clawson, Anna N.; Amarasinghe, Gaya K.; Basler, Christopher F.; Bavari, Sbina; Benkő, Mária; Blasdell, Kim R.; Briese, Thomas; Buchmeier, Michael J.; Bukreyev, Alexander; Calisher, Charles H.; Chandran, Kartik; Charrel, Rémi; Clegg, Christopher S.; Collins, Peter L.; Juan Carlos, De La Torre; Derisi, Joseph L.; Dietzgen, Ralf G.; Dolnik, Olga; Dürrwald, Ralf; Dye, John M.; Easton, Andrew J.; Emonet, Sébastian; Formenty, Pierre; Fouchier, Ron A. M.; Ghedin, Elodie; Gonzalez, Jean-Paul; Harrach, Balázs; Hewson, Roger; Horie, Masayuki; Jiāng, Dàohóng; Kobinger, Gary; Kondo, Hideki; Kropinski, Andrew M.; Krupovic, Mart; Kurath, Gael; Lamb, Robert A.; Leroy, Eric M.; Lukashevich, Igor S.; Maisner, Andrea; Mushegian, Arcady R.; Netesov, Sergey V.; Nowotny, Norbert; Patterson, Jean L.; Payne, Susan L.; PaWeska, Janusz T.; Peters, Clarence J.; Radoshitzky, Sheli R.; Rima, Bertus K.; Romanowski, Victor; Rubbenstroth, Dennis; Sabanadzovic, Sead; Sanfaçon, Hélène; Salvato, Maria S.; Schwemmle, Martin; Smither, Sophie J.; Stenglein, Mark D.; Stone, David M.; Takada, Ayato; Tesh, Robert B.; Tomonaga, Keizo; Tordo, Noël; Towner, Jonathan S.; Vasilakis, Nikos; Volchkov, Viktor E.; Wahl-Jensen, Victoria; Walker, Peter J.; Wang, Lin-Fa; Varsani, Arvind; Whitfield, Anna E.; Zerbini, F. Murilo; Kuhn, Jens H.

2017-01-01

Abstract Botanical, mycological, zoological, and prokaryotic species names follow the Linnaean format, consisting of an italicized Latinized binomen with a capitalized genus name and a lower case species epithet (e.g., Homo sapiens). Virus species names, however, do not follow a uniform format, and, even when binomial, are not Linnaean in style. In this thought exercise, we attempted to convert all currently official names of species included in the virus family Arenaviridae and the virus order Mononegavirales to Linnaean binomials, and to identify and address associated challenges and concerns. Surprisingly, this endeavor was not as complicated or time-consuming as even the authors of this article expected when conceiving the experiment. PMID:27798405

Radial basis function and its application in tourism management

NASA Astrophysics Data System (ADS)

Hu, Shan-Feng; Zhu, Hong-Bin; Zhao, Lei

2018-05-01

In this work, several applications and the performances of the radial basis function (RBF) are briefly reviewed at first. After that, the binomial function combined with three different RBFs including the multiquadric (MQ), inverse quadric (IQ) and inverse multiquadric (IMQ) distributions are adopted to model the tourism data of Huangshan in China. Simulation results showed that all the models match very well with the sample data. It is found that among the three models, the IMQ-RBF model is more suitable for forecasting the tourist flow.

Regular exercise and related factors in patients with Parkinson's disease: Applying zero-inflated negative binomial modeling of exercise count data.

PubMed

Lee, JuHee; Park, Chang Gi; Choi, Moonki

2016-05-01

This study was conducted to identify risk factors that influence regular exercise among patients with Parkinson's disease in Korea. Parkinson's disease is prevalent in the elderly, and may lead to a sedentary lifestyle. Exercise can enhance physical and psychological health. However, patients with Parkinson's disease are less likely to exercise than are other populations due to physical disability. A secondary data analysis and cross-sectional descriptive study were conducted. A convenience sample of 106 patients with Parkinson's disease was recruited at an outpatient neurology clinic of a tertiary hospital in Korea. Demographic characteristics, disease-related characteristics (including disease duration and motor symptoms), self-efficacy for exercise, balance, and exercise level were investigated. Negative binomial regression and zero-inflated negative binomial regression for exercise count data were utilized to determine factors involved in exercise. The mean age of participants was 65.85 ± 8.77 years, and the mean duration of Parkinson's disease was 7.23 ± 6.02 years. Most participants indicated that they engaged in regular exercise (80.19%). Approximately half of participants exercised at least 5 days per week for 30 min, as recommended (51.9%). Motor symptoms were a significant predictor of exercise in the count model, and self-efficacy for exercise was a significant predictor of exercise in the zero model. Severity of motor symptoms was related to frequency of exercise. Self-efficacy contributed to the probability of exercise. Symptom management and improvement of self-efficacy for exercise are important to encourage regular exercise in patients with Parkinson's disease. Copyright © 2015 Elsevier Inc. All rights reserved.

Binomial Coefficients Modulo a Prime--A Visualization Approach to Undergraduate Research

ERIC Educational Resources Information Center

Bardzell, Michael; Poimenidou, Eirini

2011-01-01

In this article we present, as a case study, results of undergraduate research involving binomial coefficients modulo a prime "p." We will discuss how undergraduates were involved in the project, even with a minimal mathematical background beforehand. There are two main avenues of exploration described to discover these binomial…

Using the β-binomial distribution to characterize forest health

Treesearch

S.J. Zarnoch; R.L. Anderson; R.M. Sheffield

1995-01-01

The β-binomial distribution is suggested as a model for describing and analyzing the dichotomous data obtained from programs monitoring the health of forests in the United States. Maximum likelihood estimation of the parameters is given as well as asymptotic likelihood ratio tests. The procedure is illustrated with data on dogwood anthracnose infection (caused...

Integer Solutions of Binomial Coefficients

ERIC Educational Resources Information Center

Gilbertson, Nicholas J.

2016-01-01

A good formula is like a good story, rich in description, powerful in communication, and eye-opening to readers. The formula presented in this article for determining the coefficients of the binomial expansion of (x + y)n is one such "good read." The beauty of this formula is in its simplicity--both describing a quantitative situation…

Confidence Intervals for Weighted Composite Scores under the Compound Binomial Error Model

ERIC Educational Resources Information Center

Kim, Kyung Yong; Lee, Won-Chan

2018-01-01

Reporting confidence intervals with test scores helps test users make important decisions about examinees by providing information about the precision of test scores. Although a variety of estimation procedures based on the binomial error model are available for computing intervals for test scores, these procedures assume that items are randomly…

Macro-level pedestrian and bicycle crash analysis: Incorporating spatial spillover effects in dual state count models.

PubMed

Cai, Qing; Lee, Jaeyoung; Eluru, Naveen; Abdel-Aty, Mohamed

2016-08-01

This study attempts to explore the viability of dual-state models (i.e., zero-inflated and hurdle models) for traffic analysis zones (TAZs) based pedestrian and bicycle crash frequency analysis. Additionally, spatial spillover effects are explored in the models by employing exogenous variables from neighboring zones. The dual-state models such as zero-inflated negative binomial and hurdle negative binomial models (with and without spatial effects) are compared with the conventional single-state model (i.e., negative binomial). The model comparison for pedestrian and bicycle crashes revealed that the models that considered observed spatial effects perform better than the models that did not consider the observed spatial effects. Across the models with spatial spillover effects, the dual-state models especially zero-inflated negative binomial model offered better performance compared to single-state models. Moreover, the model results clearly highlighted the importance of various traffic, roadway, and sociodemographic characteristics of the TAZ as well as neighboring TAZs on pedestrian and bicycle crash frequency. Copyright © 2016 Elsevier Ltd. All rights reserved.

A comparison of different statistical methods analyzing hypoglycemia data using bootstrap simulations.

PubMed

Jiang, Honghua; Ni, Xiao; Huster, William; Heilmann, Cory

2015-01-01

Hypoglycemia has long been recognized as a major barrier to achieving normoglycemia with intensive diabetic therapies. It is a common safety concern for the diabetes patients. Therefore, it is important to apply appropriate statistical methods when analyzing hypoglycemia data. Here, we carried out bootstrap simulations to investigate the performance of the four commonly used statistical models (Poisson, negative binomial, analysis of covariance [ANCOVA], and rank ANCOVA) based on the data from a diabetes clinical trial. Zero-inflated Poisson (ZIP) model and zero-inflated negative binomial (ZINB) model were also evaluated. Simulation results showed that Poisson model inflated type I error, while negative binomial model was overly conservative. However, after adjusting for dispersion, both Poisson and negative binomial models yielded slightly inflated type I errors, which were close to the nominal level and reasonable power. Reasonable control of type I error was associated with ANCOVA model. Rank ANCOVA model was associated with the greatest power and with reasonable control of type I error. Inflated type I error was observed with ZIP and ZINB models.

Pricing American Asian options with higher moments in the underlying distribution

NASA Astrophysics Data System (ADS)

Lo, Keng-Hsin; Wang, Kehluh; Hsu, Ming-Feng

2009-01-01

We develop a modified Edgeworth binomial model with higher moment consideration for pricing American Asian options. With lognormal underlying distribution for benchmark comparison, our algorithm is as precise as that of Chalasani et al. [P. Chalasani, S. Jha, F. Egriboyun, A. Varikooty, A refined binomial lattice for pricing American Asian options, Rev. Derivatives Res. 3 (1) (1999) 85-105] if the number of the time steps increases. If the underlying distribution displays negative skewness and leptokurtosis as often observed for stock index returns, our estimates can work better than those in Chalasani et al. [P. Chalasani, S. Jha, F. Egriboyun, A. Varikooty, A refined binomial lattice for pricing American Asian options, Rev. Derivatives Res. 3 (1) (1999) 85-105] and are very similar to the benchmarks in Hull and White [J. Hull, A. White, Efficient procedures for valuing European and American path-dependent options, J. Derivatives 1 (Fall) (1993) 21-31]. The numerical analysis shows that our modified Edgeworth binomial model can value American Asian options with greater accuracy and speed given higher moments in their underlying distribution.

Discrimination of numerical proportions: A comparison of binomial and Gaussian models.

PubMed

Raidvee, Aire; Lember, Jüri; Allik, Jüri

2017-01-01

Observers discriminated the numerical proportion of two sets of elements (N = 9, 13, 33, and 65) that differed either by color or orientation. According to the standard Thurstonian approach, the accuracy of proportion discrimination is determined by irreducible noise in the nervous system that stochastically transforms the number of presented visual elements onto a continuum of psychological states representing numerosity. As an alternative to this customary approach, we propose a Thurstonian-binomial model, which assumes discrete perceptual states, each of which is associated with a certain visual element. It is shown that the probability β with which each visual element can be noticed and registered by the perceptual system can explain data of numerical proportion discrimination at least as well as the continuous Thurstonian-Gaussian model, and better, if the greater parsimony of the Thurstonian-binomial model is taken into account using AIC model selection. We conclude that Gaussian and binomial models represent two different fundamental principles-internal noise vs. using only a fraction of available information-which are both plausible descriptions of visual perception.

Zero adjusted models with applications to analysing helminths count data.

PubMed

Chipeta, Michael G; Ngwira, Bagrey M; Simoonga, Christopher; Kazembe, Lawrence N

2014-11-27

It is common in public health and epidemiology that the outcome of interest is counts of events occurrence. Analysing these data using classical linear models is mostly inappropriate, even after transformation of outcome variables due to overdispersion. Zero-adjusted mixture count models such as zero-inflated and hurdle count models are applied to count data when over-dispersion and excess zeros exist. Main objective of the current paper is to apply such models to analyse risk factors associated with human helminths (S. haematobium) particularly in a case where there's a high proportion of zero counts. The data were collected during a community-based randomised control trial assessing the impact of mass drug administration (MDA) with praziquantel in Malawi, and a school-based cross sectional epidemiology survey in Zambia. Count data models including traditional (Poisson and negative binomial) models, zero modified models (zero inflated Poisson and zero inflated negative binomial) and hurdle models (Poisson logit hurdle and negative binomial logit hurdle) were fitted and compared. Using Akaike information criteria (AIC), the negative binomial logit hurdle (NBLH) and zero inflated negative binomial (ZINB) showed best performance in both datasets. With regards to zero count capturing, these models performed better than other models. This paper showed that zero modified NBLH and ZINB models are more appropriate methods for the analysis of data with excess zeros. The choice between the hurdle and zero-inflated models should be based on the aim and endpoints of the study.

Evaluation of an operational malaria outbreak identification and response system in Mpumalanga Province, South Africa.

PubMed

Coleman, Marlize; Coleman, Michael; Mabuza, Aaron M; Kok, Gerdalize; Coetzee, Maureen; Durrheim, David N

2008-04-27

To evaluate the performance of a novel malaria outbreak identification system in the epidemic prone rural area of Mpumalanga Province, South Africa, for timely identification of malaria outbreaks and guiding integrated public health responses. Using five years of historical notification data, two binomial thresholds were determined for each primary health care facility in the highest malaria risk area of Mpumalanga province. Whenever the thresholds were exceeded at health facility level (tier 1), primary health care staff notified the malaria control programme, which then confirmed adequate stocks of malaria treatment to manage potential increased cases. The cases were followed up at household level to verify the likely source of infection. The binomial thresholds were reviewed at village/town level (tier 2) to determine whether additional response measures were required. In addition, an automated electronic outbreak identification system at town/village level (tier 2) was integrated into the case notification database (tier 3) to ensure that unexpected increases in case notification were not missed.The performance of these binomial outbreak thresholds was evaluated against other currently recommended thresholds using retrospective data. The acceptability of the system at primary health care level was evaluated through structured interviews with health facility staff. Eighty four percent of health facilities reported outbreaks within 24 hours (n = 95), 92% (n = 104) within 48 hours and 100% (n = 113) within 72 hours. Appropriate response to all malaria outbreaks (n = 113, tier 1, n = 46, tier 2) were achieved within 24 hours. The system was positively viewed by all health facility staff. When compared to other epidemiological systems for a specified 12 month outbreak season (June 2003 to July 2004) the binomial exact thresholds produced one false weekly outbreak, the C-sum 12 weekly outbreaks and the mean + 2 SD nine false weekly outbreaks. Exceeding the binomial level 1 threshold triggered an alert four weeks prior to an outbreak, but exceeding the binomial level 2 threshold identified an outbreak as it occurred. The malaria outbreak surveillance system using binomial thresholds achieved its primary goal of identifying outbreaks early facilitating appropriate local public health responses aimed at averting a possible large-scale epidemic in a low, and unstable, malaria transmission setting.

Smisc - A collection of miscellaneous functions

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

Landon Sego, PNNL

2015-08-31

A collection of functions for statistical computing and data manipulation. These include routines for rapidly aggregating heterogeneous matrices, manipulating file names, loading R objects, sourcing multiple R files, formatting datetimes, multi-core parallel computing, stream editing, specialized plotting, etc. Smisc-package A collection of miscellaneous functions allMissing Identifies missing rows or columns in a data frame or matrix as.numericSilent Silent wrapper for coercing a vector to numeric comboList Produces all possible combinations of a set of linear model predictors cumMax Computes the maximum of the vector up to the current index cumsumNA Computes the cummulative sum of a vector without propogating NAsmore » d2binom Probability functions for the sum of two independent binomials dataIn A flexible way to import data into R. dbb The Beta-Binomial Distribution df2list Row-wise conversion of a data frame to a list dfplapply Parallelized single row processing of a data frame dframeEquiv Examines the equivalence of two dataframes or matrices dkbinom Probability functions for the sum of k independent binomials factor2character Converts all factor variables in a dataframe to character variables findDepMat Identify linearly dependent rows or columns in a matrix formatDT Converts date or datetime strings into alternate formats getExtension Filename manipulations: remove the extension or path, extract the extension or path getPath Filename manipulations: remove the extension or path, extract the extension or path grabLast Filename manipulations: remove the extension or path, extract the extension or path ifelse1 Non-vectorized version of ifelse integ Simple numerical integration routine interactionPlot Two-way Interaction Plot with Error Bar linearMap Linear mapping of a numerical vector or scalar list2df Convert a list to a data frame loadObject Loads and returns the object(s) in an ".Rdata" file more Display the contents of a file to the R terminal movAvg2 Calculate the moving average using a 2-sided window openDevice Opens a graphics device based on the filename extension p2binom Probability functions for the sum of two independent binomials padZero Pad a vector of numbers with zeros parseJob Parses a collection of elements into (almost) equal sized groups pbb The Beta-Binomial Distribution pcbinom A continuous version of the binomial cdf pkbinom Probability functions for the sum of k independent binomials plapply Simple parallelization of lapply plotFun Plot one or more functions on a single plot PowerData An example of power data pvar Prints the name and value of one or more objects qbb The Beta-Binomial Distribution rbb And numerous others (space limits reporting).« less

I Remember You: Independence and the Binomial Model

ERIC Educational Resources Information Center

Levine, Douglas W.; Rockhill, Beverly

2006-01-01

We focus on the problem of ignoring statistical independence. A binomial experiment is used to determine whether judges could match, based on looks alone, dogs to their owners. The experimental design introduces dependencies such that the probability of a given judge correctly matching a dog and an owner changes from trial to trial. We show how…

Possibility and challenges of conversion of current virus species names to Linnaean binomials

USGS Publications Warehouse

Thomas, Postler; Clawson, Anna N.; Amarasinghe, Gaya K.; Basler, Christopher F.; Bavari, Sina; Benko, Maria; Blasdell, Kim R.; Briese, Thomas; Buchmeier, Michael J.; Bukreyev, Alexander; Calisher, Charles H.; Chandran, Kartik; Charrel, Remi; Clegg, Christopher S.; Collins, Peter L.; De la Torre, Juan Carlos; DeRisi, Joseph L.; Dietzgen, Ralf G.; Dolnik, Olga; Durrwald, Ralf; Dye, John M.; Easton, Andrew J.; Emonet, Sebastian; Formenty, Pierre; Fouchier, Ron A. M.; Ghedin, Elodie; Gonzalez, Jean-Paul; Harrach, Balazs; Hewson, Roger; Horie, Masayuki; Jiang, Daohong; Kobinger, Gary P.; Kondo, Hideki; Kropinski, Andrew; Krupovic, Mart; Kurath, Gael; Lamb, Robert A.; Leroy, Eric M.; Lukashevich, Igor S.; Maisner, Andrea; Mushegian, Arcady; Netesov, Sergey V.; Nowotny, Norbert; Patterson, Jean L.; Payne, Susan L.; Paweska, Janusz T.; Peters, C.J.; Radoshitzky, Sheli; Rima, Bertus K.; Romanowski, Victor; Rubbenstroth, Dennis; Sabanadzovic, Sead; Sanfacon, Helene; Salvato , Maria; Schwemmle, Martin; Smither, Sophie J.; Stenglein, Mark; Stone, D.M.; Takada , Ayato; Tesh, Robert B.; Tomonaga, Keizo; Tordo, N.; Towner, Jonathan S.; Vasilakis, Nikos; Volchkov, Victor E.; Jensen, Victoria; Walker, Peter J.; Wang, Lin-Fa; Varsani, Arvind; Whitfield , Anna E.; Zerbini, Francisco Murilo; Kuhn, Jens H.

2017-01-01

Botanical, mycological, zoological, and prokaryotic species names follow the Linnaean format, consisting of an italicized Latinized binomen with a capitalized genus name and a lower case species epithet (e.g., Homo sapiens). Virus species names, however, do not follow a uniform format, and, even when binomial, are not Linnaean in style. In this thought exercise, we attempted to convert all currently official names of species included in the virus family Arenaviridae and the virus order Mononegavirales to Linnaean binomials, and to identify and address associated challenges and concerns. Surprisingly, this endeavor was not as complicated or time-consuming as even the authors of this article expected when conceiving the experiment.

Making sense of the noise: The effect of hydrology on silver carp eDNA detection in the Chicago area waterway system.

PubMed

Song, Jeffery W; Small, Mitchell J; Casman, Elizabeth A

2017-12-15

Environmental DNA (eDNA) sampling is an emerging tool for monitoring the spread of aquatic invasive species. One confounding factor when interpreting eDNA sampling evidence is that eDNA can be present in the water in the absence of living target organisms, originating from excreta, dead tissue, boats, or sewage effluent, etc. In the Chicago Area Waterway System (CAWS), electric fish dispersal barriers were built to prevent non-native Asian carp species from invading Lake Michigan, and yet Asian carp eDNA has been detected above the barriers sporadically since 2009. In this paper the influence of stream flow characteristics in the CAWS on the probability of invasive Asian carp eDNA detection in the CAWS from 2009 to 2012 was examined. In the CAWS, the direction of stream flow is mostly away from Lake Michigan, though there are infrequent reversals in flow direction towards Lake Michigan during dry spells. We find that the flow reversal volume into the Lake has a statistically significant positive relationship with eDNA detection probability, while other covariates, like gage height, precipitation, season, water temperature, dissolved oxygen concentration, pH and chlorophyll concentration do not. This suggests that stream flow direction is highly influential on eDNA detection in the CAWS and should be considered when interpreting eDNA evidence. We also find that the beta-binomial regression model provides a stronger fit for eDNA detection probability compared to a binomial regression model. This paper provides a statistical modeling framework for interpreting eDNA sampling evidence and for evaluating covariates influencing eDNA detection. Copyright © 2017 Elsevier B.V. All rights reserved.

Evaluation of logistic regression models and effect of covariates for case-control study in RNA-Seq analysis.

PubMed

Choi, Seung Hoan; Labadorf, Adam T; Myers, Richard H; Lunetta, Kathryn L; Dupuis, Josée; DeStefano, Anita L

2017-02-06

Next generation sequencing provides a count of RNA molecules in the form of short reads, yielding discrete, often highly non-normally distributed gene expression measurements. Although Negative Binomial (NB) regression has been generally accepted in the analysis of RNA sequencing (RNA-Seq) data, its appropriateness has not been exhaustively evaluated. We explore logistic regression as an alternative method for RNA-Seq studies designed to compare cases and controls, where disease status is modeled as a function of RNA-Seq reads using simulated and Huntington disease data. We evaluate the effect of adjusting for covariates that have an unknown relationship with gene expression. Finally, we incorporate the data adaptive method in order to compare false positive rates. When the sample size is small or the expression levels of a gene are highly dispersed, the NB regression shows inflated Type-I error rates but the Classical logistic and Bayes logistic (BL) regressions are conservative. Firth's logistic (FL) regression performs well or is slightly conservative. Large sample size and low dispersion generally make Type-I error rates of all methods close to nominal alpha levels of 0.05 and 0.01. However, Type-I error rates are controlled after applying the data adaptive method. The NB, BL, and FL regressions gain increased power with large sample size, large log2 fold-change, and low dispersion. The FL regression has comparable power to NB regression. We conclude that implementing the data adaptive method appropriately controls Type-I error rates in RNA-Seq analysis. Firth's logistic regression provides a concise statistical inference process and reduces spurious associations from inaccurately estimated dispersion parameters in the negative binomial framework.

Binomial Test Method for Determining Probability of Detection Capability for Fracture Critical Applications

NASA Technical Reports Server (NTRS)

Generazio, Edward R.

2011-01-01

The capability of an inspection system is established by applications of various methodologies to determine the probability of detection (POD). One accepted metric of an adequate inspection system is that for a minimum flaw size and all greater flaw sizes, there is 0.90 probability of detection with 95% confidence (90/95 POD). Directed design of experiments for probability of detection (DOEPOD) has been developed to provide an efficient and accurate methodology that yields estimates of POD and confidence bounds for both Hit-Miss or signal amplitude testing, where signal amplitudes are reduced to Hit-Miss by using a signal threshold Directed DOEPOD uses a nonparametric approach for the analysis or inspection data that does require any assumptions about the particular functional form of a POD function. The DOEPOD procedure identifies, for a given sample set whether or not the minimum requirement of 0.90 probability of detection with 95% confidence is demonstrated for a minimum flaw size and for all greater flaw sizes (90/95 POD). The DOEPOD procedures are sequentially executed in order to minimize the number of samples needed to demonstrate that there is a 90/95 POD lower confidence bound at a given flaw size and that the POD is monotonic for flaw sizes exceeding that 90/95 POD flaw size. The conservativeness of the DOEPOD methodology results is discussed. Validated guidelines for binomial estimation of POD for fracture critical inspection are established.

Inference for binomial probability based on dependent Bernoulli random variables with applications to meta-analysis and group level studies.

PubMed

Bakbergenuly, Ilyas; Kulinskaya, Elena; Morgenthaler, Stephan

2016-07-01

We study bias arising as a result of nonlinear transformations of random variables in random or mixed effects models and its effect on inference in group-level studies or in meta-analysis. The findings are illustrated on the example of overdispersed binomial distributions, where we demonstrate considerable biases arising from standard log-odds and arcsine transformations of the estimated probability p̂, both for single-group studies and in combining results from several groups or studies in meta-analysis. Our simulations confirm that these biases are linear in ρ, for small values of ρ, the intracluster correlation coefficient. These biases do not depend on the sample sizes or the number of studies K in a meta-analysis and result in abysmal coverage of the combined effect for large K. We also propose bias-correction for the arcsine transformation. Our simulations demonstrate that this bias-correction works well for small values of the intraclass correlation. The methods are applied to two examples of meta-analyses of prevalence. © 2016 The Authors. Biometrical Journal Published by Wiley-VCH Verlag GmbH & Co. KGaA.

The effect of a major cigarette price change on smoking behavior in california: a zero-inflated negative binomial model.

PubMed

Sheu, Mei-Ling; Hu, Teh-Wei; Keeler, Theodore E; Ong, Michael; Sung, Hai-Yen

2004-08-01

The objective of this paper is to determine the price sensitivity of smokers in their consumption of cigarettes, using evidence from a major increase in California cigarette prices due to Proposition 10 and the Tobacco Settlement. The study sample consists of individual survey data from Behavioral Risk Factor Survey (BRFS) and price data from the Bureau of Labor Statistics between 1996 and 1999. A zero-inflated negative binomial (ZINB) regression model was applied for the statistical analysis. The statistical model showed that price did not have an effect on reducing the estimated prevalence of smoking. However, it indicated that among smokers the price elasticity was at the level of -0.46 and statistically significant. Since smoking prevalence is significantly lower than it was a decade ago, price increases are becoming less effective as an inducement for hard-core smokers to quit, although they may respond by decreasing consumption. For those who only smoke occasionally (many of them being young adults) price increases alone may not be an effective inducement to quit smoking. Additional underlying behavioral factors need to be identified so that more effective anti-smoking strategies can be developed.

The Effect of Florida Medicaid's State-Mandated Formulary Provision on Prescription Drug Use and Health Plan Costs in a Medicaid Managed Care Plan.

PubMed

Munshi, Kiraat D; Mager, Douglas; Ward, Krista M; Mischel, Brian; Henderson, Rochelle R

2018-02-01

Formulary or preferred drug list (PDL) management is an effective strategy to ensure clinically efficient prescription drug management by managed care organizations (MCOs). Medicaid MCOs participating in Florida's Medicaid program were required to use a state-mandated PDL between May and August 2014. To examine differences in prescription drug use and plan costs between a single Florida Medicaid managed care (MMC) health plan that implemented a state-mandated PDL policy on July 1, 2014, and a comparable MMC health plan in another state without a state-mandated PDL, controlling for sociodemographic confounders. A retrospective analysis with a pre-post design was conducted using deidentified administrative claims data from a large pharmacy benefit manager. The prepolicy evaluation period was January 1 through June 30, 2014, and the postpolicy period was January 1 through June 30, 2015. Continuously eligible Florida MMC plan members were matched on sociodemographic and health characteristics to their counterparts enrolled in a comparable MMC health plan in another state without a state-mandated formulary. Outcomes were drug use, measured as the number of 30-day adjusted nonspecialty drug prescriptions per member per period, and total drug plan costs per member per period for all drugs, with separate measures for generic and brand drugs. Bivariate comparisons were conducted using t-tests. Employing a difference-in-differences (DID) analytic approach, multivariate negative binomial regression and generalized estimating equation models were used to analyze prescription drug use and costs. The final analytical sample consisted of 18,372 enrollees, evenly divided between the 2 groups. In the postpolicy evaluation period, overall and generic use declined, while brand use increased for members in the Florida health plan. Drug costs, especially for brands, significantly increased for Florida health plan members. No significant changes were observed over the same time period in the control health plan members. DID analyses indicated that the decline in overall drug use was 6% lower (P = 0.020), and the increase in plan costs was 27% higher (P = 0.002) among Florida health plan members compared with control group members. Members in a Florida Medicaid health plan with a state-mandated PDL saw declines in overall and generic drug use and an increase in drug plan costs. States considering a state-mandated PDL should take into account potential effects of decreased generic drug use and increases in prescription drug plan costs. Funding for this study was provided internally by Express Scripts Holding Company. The authors and acknowledged contributors are employees of Express Scripts Holding Company. All authors contributed to the study concept, and study design was provided by Munshi, Mager, and Henderson. Munshi and Mager collected the data, and Munshi provided the statistical analysis. Data interpretation was performed by Munshi, Mager, and Henderson. The manuscript was written by Munshi, Henderson, and Mager and revised by Munshi, Ward, Mischel, and Henderson.

Raw and Central Moments of Binomial Random Variables via Stirling Numbers

ERIC Educational Resources Information Center

Griffiths, Martin

2013-01-01

We consider here the problem of calculating the moments of binomial random variables. It is shown how formulae for both the raw and the central moments of such random variables may be obtained in a recursive manner utilizing Stirling numbers of the first kind. Suggestions are also provided as to how students might be encouraged to explore this…

A Mixed-Effects Heterogeneous Negative Binomial Model for Postfire Conifer Regeneration in Northeastern California, USA

Treesearch

Justin S. Crotteau; Martin W. Ritchie; J. Morgan Varner

2014-01-01

Many western USA fire regimes are typified by mixed-severity fire, which compounds the variability inherent to natural regeneration densities in associated forests. Tree regeneration data are often discrete and nonnegative; accordingly, we fit a series of Poisson and negative binomial variation models to conifer seedling counts across four distinct burn severities and...

Performance of the modified Poisson regression approach for estimating relative risks from clustered prospective data.

PubMed

Yelland, Lisa N; Salter, Amy B; Ryan, Philip

2011-10-15

Modified Poisson regression, which combines a log Poisson regression model with robust variance estimation, is a useful alternative to log binomial regression for estimating relative risks. Previous studies have shown both analytically and by simulation that modified Poisson regression is appropriate for independent prospective data. This method is often applied to clustered prospective data, despite a lack of evidence to support its use in this setting. The purpose of this article is to evaluate the performance of the modified Poisson regression approach for estimating relative risks from clustered prospective data, by using generalized estimating equations to account for clustering. A simulation study is conducted to compare log binomial regression and modified Poisson regression for analyzing clustered data from intervention and observational studies. Both methods generally perform well in terms of bias, type I error, and coverage. Unlike log binomial regression, modified Poisson regression is not prone to convergence problems. The methods are contrasted by using example data sets from 2 large studies. The results presented in this article support the use of modified Poisson regression as an alternative to log binomial regression for analyzing clustered prospective data when clustering is taken into account by using generalized estimating equations.

A recurrent, multistate outbreak of salmonella serotype agona infections associated with dry, unsweetened cereal consumption, United States, 2008.

PubMed

Russo, Elizabeth T; Biggerstaff, Gwen; Hoekstra, R Michael; Meyer, Stephanie; Patel, Nehal; Miller, Benjamin; Quick, Rob

2013-02-01

An outbreak of Salmonella enterica serotype Agona infections associated with nationwide distribution of cereal from Company X was identified in April 2008. This outbreak was detected using PulseNet, the national molecular subtyping network for foodborne disease surveillance, which coincided with Company X's voluntary recall of unsweetened puffed rice and wheat cereals after routine product sampling yielded Salmonella Agona. A case patient was defined as being infected with the outbreak strain of Salmonella Agona, with illness onset from 1 January through 1 July 2008. Case patients were interviewed using a standard questionnaire, and the proportion of ill persons who reported eating Company X puffed rice cereal was compared with Company X's market share data using binomial testing. The Minnesota Department of Agriculture inspected the cereal production facility and collected both product and environmental swab samples. Routine surveillance identified 33 case patients in 17 states. Of 32 patients interviewed, 24 (83%) reported eating Company X puffed rice cereal. Company X puffed rice cereal represented 0.063% of the total ready-to-eat dry cereal market share in the United States at the time of the investigation. Binomial testing suggested that the proportion of exposed case patients would not likely occur by chance (P < 0.0001). Of 17 cereal samples collected from case patient homes for laboratory testing, 2 (12%) yielded Salmonella Agona indistinguishable from the outbreak strain. Twelve environmental swabs and nine product samples from the cereal plant yielded the outbreak strain of Salmonella Agona. Company X cereal was implicated in a similar outbreak of Salmonella Agona infection in 1998 with the same outbreak strain linked to the same production facility. We hypothesize that a recent construction project at this facility created an open wall near the cereal production area allowing reintroduction of Salmonella Agona into the product, highlighting the resilience of Salmonella in dry food production environments.

Temporal Evolution of Non-equilibrium Gamma’ Precipitates in a Rapidly Quenched Nickel Base Superalloy (Preprint)

DTIC Science & Technology

2014-04-01

with the binomial distribution for a particular dataset. This technique is more commonly known as the Langer, Bar-on and Miller ( LBM ) method [22,23...distribution unlimited. Using the LBM method, the frequency distribution plot for a dataset corresponding to a phase separated system, exhibiting a split peak...estimated parameters (namely μ1, μ2, σ, fγ’ and fγ) obtained from the LBM plots in Fig. 5 are summarized in Table 3. The EWQ sample does not exhibit any

Use of the negative binomial-truncated Poisson distribution in thunderstorm prediction

NASA Technical Reports Server (NTRS)

Cohen, A. C.

1971-01-01

A probability model is presented for the distribution of thunderstorms over a small area given that thunderstorm events (1 or more thunderstorms) are occurring over a larger area. The model incorporates the negative binomial and truncated Poisson distributions. Probability tables for Cape Kennedy for spring, summer, and fall months and seasons are presented. The computer program used to compute these probabilities is appended.

Estimating cavity tree and snag abundance using negative binomial regression models and nearest neighbor imputation methods

Treesearch

Bianca N.I. Eskelson; Hailemariam Temesgen; Tara M. Barrett

2009-01-01

Cavity tree and snag abundance data are highly variable and contain many zero observations. We predict cavity tree and snag abundance from variables that are readily available from forest cover maps or remotely sensed data using negative binomial (NB), zero-inflated NB, and zero-altered NB (ZANB) regression models as well as nearest neighbor (NN) imputation methods....

Orchestrating Semiotic Leaps from Tacit to Cultural Quantitative Reasoning--The Case of Anticipating Experimental Outcomes of a Quasi-Binomial Random Generator

ERIC Educational Resources Information Center

Abrahamson, Dor

2009-01-01

This article reports on a case study from a design-based research project that investigated how students make sense of the disciplinary tools they are taught to use, and specifically, what personal, interpersonal, and material resources support this process. The probability topic of binomial distribution was selected due to robust documentation of…

Differential Associations of UPPS-P Impulsivity Traits With Alcohol Problems.

PubMed

McCarty, Kayleigh N; Morris, David H; Hatz, Laura E; McCarthy, Denis M

2017-07-01

The UPPS-P model posits that impulsivity comprises five factors: positive urgency, negative urgency, lack of planning, lack of perseverance, and sensation seeking. Negative and positive urgency are the traits most consistently associated with alcohol problems. However, previous work has examined alcohol problems either individually or in the aggregate, rather than examining multiple problem domains simultaneously. Recent work has also questioned the utility of distinguishing between positive and negative urgency, as this distinction did not meaningfully differ in predicting domains of psychopathology. The aims of this study were to address these issues by (a) testing unique associations of UPPS-P with specific domains of alcohol problems and (b) determining the utility of distinguishing between positive and negative urgency as risk factors for specific alcohol problems. Associations between UPPS-P traits and alcohol problem domains were examined in two cross-sectional data sets using negative binomial regression models. In both samples, negative urgency was associated with social/interpersonal, self-perception, risky behaviors, and blackout drinking problems. Positive urgency was associated with academic/occupational and physiological dependence problems. Both urgency traits were associated with impaired control and self-care problems. Associations for other UPPS-P traits did not replicate across samples. Results indicate that negative and positive urgency have differential associations with alcohol problem domains. Results also suggest a distinction between the type of alcohol problems associated with these traits-negative urgency was associated with problems experienced during a drinking episode, whereas positive urgency was associated with alcohol problems that result from longer-term drinking trends.

Prevalence of polycystic ovary syndrome and its associated complications in Iranian women: A meta-analysis.

PubMed

Jalilian, Anahita; Kiani, Faezeh; Sayehmiri, Fatemeh; Sayehmiri, Kourosh; Khodaee, Zahra; Akbari, Malihe

2015-10-01

Polycystic ovary syndrome (PCOS) is the most common endocrine disorder in women of reproductive age and is the most common cause of infertility due to anovulation. There is no single criterion for the diagnosis of this syndrome. The purpose of this study was to investigate the prevalence of PCOS and its associated complications in Iranian women using meta-analysis method. Prevalence of PCOS was investigated from the SID, Goggle scholar, PubMed, Magiran, Irandoc, and Iranmedex, and weighting of each study was calculated according to sample size and prevalence of the binomial distribution. Data were analyzed using a random-effects model meta-analysis (Random effects model) and the software R and Stata Version 11.2. 30 studies conducted between the years 2006 to 2011 were entered into meta-analysis. The total sample size was 19, 226 women aged between 10-45 years. The prevalence of PCOS based on National institute of child health and human disease of the U.S was, 6.8% (95 % CI: 4.11-8.5), based on Rotterdam was 19.5% (95 % CI: 2.24-8.14), and based on ultrasound was 4.41% (95% CI: 5.68-4.14). Also, the prevalence of hirsutism was estimated to be 13%, acne 26%, androgenic alopecia 9%, menstrual disorders 28%, overweight 21%, obesity 19%, and infertility 8%. The prevalence of PCOS in Iran is not high. However, given the risk of complications such as heart disease - cardiovascular and infertility, prevention of PCOS is important; we suggest that health officials must submit plans for the community in this respect.

Ready or not? School preparedness for California's new personal beliefs exemption law.

PubMed

Wheeler, Marissa; Buttenheim, Alison M

2014-05-07

This paper describes elementary school officials' awareness of and preparedness for the implementation of California's new exemption law that went into effect on January 1, 2014. The new law prescribes stricter requirements for claiming a personal beliefs exemption from mandated school-entry immunizations. We used cross-sectional data collected from a stratified random sample of 315 schools with low, middle, and high rates of personal beliefs exemptions. We described schools' awareness and specific knowledge of the new legislation and tested for differences across school types. We additionally tested for associations between outcome variables and school and respondent characteristics using ordered logit and negative binomial regression. Finally, we described schools' plans and needs for implementing the new legislation. Elementary school staff reported an overall low level of awareness and knowledge about the new legislation and could identify few of its features. We observed, however, that across the exemption-level strata, respondents from high-PBE schools reported significantly higher awareness, knowledge and feature identification compared to respondents from low-PBE schools. Multivariate analyses revealed only one significant association with awareness, knowledge and identification: respondent role. Support staff roles were associated with lower odds of having high self-rated awareness or knowledge compared to health workers, as well as with a reduced log count of features identified. Though most school officials were able to identify a communication plan, schools were still in need of resources and support for successful implementation, in particular, the need for information on the new law. Schools need additional information and support from state and local agencies in order to successfully implement and enforce California's new school immunization law. In particular, our results suggest the need to ensure information on the new law reaches all levels of school staff. Copyright © 2014 Elsevier Ltd. All rights reserved.

Estimating a Logistic Discrimination Functions When One of the Training Samples Is Subject to Misclassification: A Maximum Likelihood Approach.

PubMed

Nagelkerke, Nico; Fidler, Vaclav

2015-01-01

The problem of discrimination and classification is central to much of epidemiology. Here we consider the estimation of a logistic regression/discrimination function from training samples, when one of the training samples is subject to misclassification or mislabeling, e.g. diseased individuals are incorrectly classified/labeled as healthy controls. We show that this leads to zero-inflated binomial model with a defective logistic regression or discrimination function, whose parameters can be estimated using standard statistical methods such as maximum likelihood. These parameters can be used to estimate the probability of true group membership among those, possibly erroneously, classified as controls. Two examples are analyzed and discussed. A simulation study explores properties of the maximum likelihood parameter estimates and the estimates of the number of mislabeled observations.

Indexing the relative abundance of age-0 white sturgeons in an impoundment of the lower Columbia River from highly skewed trawling data

USGS Publications Warehouse

Counihan, T.D.; Miller, Allen I.; Parsley, M.J.

1999-01-01

The development of recruitment monitoring programs for age-0 white sturgeons Acipenser transmontanus is complicated by the statistical properties of catch-per-unit-effort (CPUE) data. We found that age-0 CPUE distributions from bottom trawl surveys violated assumptions of statistical procedures based on normal probability theory. Further, no single data transformation uniformly satisfied these assumptions because CPUE distribution properties varied with the sample mean (??(CPUE)). Given these analytic problems, we propose that an additional index of age-0 white sturgeon relative abundance, the proportion of positive tows (Ep), be used to estimate sample sizes before conducting age-0 recruitment surveys and to evaluate statistical hypothesis tests comparing the relative abundance of age-0 white sturgeons among years. Monte Carlo simulations indicated that Ep was consistently more precise than ??(CPUE), and because Ep is binomially rather than normally distributed, surveys can be planned and analyzed without violating the assumptions of procedures based on normal probability theory. However, we show that Ep may underestimate changes in relative abundance at high levels and confound our ability to quantify responses to management actions if relative abundance is consistently high. If data suggest that most samples will contain age-0 white sturgeons, estimators of relative abundance other than Ep should be considered. Because Ep may also obscure correlations to climatic and hydrologic variables if high abundance levels are present in time series data, we recommend ??(CPUE) be used to describe relations to environmental variables. The use of both Ep and ??(CPUE) will facilitate the evaluation of hypothesis tests comparing relative abundance levels and correlations to variables affecting age-0 recruitment. Estimated sample sizes for surveys should therefore be based on detecting predetermined differences in Ep, but data necessary to calculate ??(CPUE) should also be collected.

Photon Counting Data Analysis: Application of the Maximum Likelihood and Related Methods for the Determination of Lifetimes in Mixtures of Rose Bengal and Rhodamine B

DOE PAGES

Santra, Kalyan; Smith, Emily A.; Petrich, Jacob W.; ...

2016-12-12

It is often convenient to know the minimum amount of data needed in order to obtain a result of desired accuracy and precision. It is a necessity in the case of subdiffraction-limited microscopies, such as stimulated emission depletion (STED) microscopy, owing to the limited sample volumes and the extreme sensitivity of the samples to photobleaching and photodamage. We present a detailed comparison of probability-based techniques (the maximum likelihood method and methods based on the binomial and the Poisson distributions) with residual minimization-based techniques for retrieving the fluorescence decay parameters for various two-fluorophore mixtures, as a function of the total numbermore » of photon counts, in time-correlated, single-photon counting experiments. The probability-based techniques proved to be the most robust (insensitive to initial values) in retrieving the target parameters and, in fact, performed equivalently to 2-3 significant figures. This is to be expected, as we demonstrate that the three methods are fundamentally related. Furthermore, methods based on the Poisson and binomial distributions have the desirable feature of providing a bin-by-bin analysis of a single fluorescence decay trace, which thus permits statistics to be acquired using only the one trace for not only the mean and median values of the fluorescence decay parameters but also for the associated standard deviations. Lastly, these probability-based methods lend themselves well to the analysis of the sparse data sets that are encountered in subdiffraction-limited microscopies.« less

Higher moments of net-proton multiplicity distributions in a heavy-ion event pile-up scenario

NASA Astrophysics Data System (ADS)

Garg, P.; Mishra, D. K.

2017-10-01

High-luminosity modern accelerators, like the Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory (BNL) and Large Hadron Collider (LHC) at European Organization for Nuclear Research (CERN), inherently have event pile-up scenarios which significantly contribute to physics events as a background. While state-of-the-art tracking algorithms and detector concepts take care of these event pile-up scenarios, several offline analytical techniques are used to remove such events from the physics analysis. It is still difficult to identify the remaining pile-up events in an event sample for physics analysis. Since the fraction of these events is significantly small, it may not be as serious of an issue for other analyses as it would be for an event-by-event analysis. Particularly when the characteristics of the multiplicity distribution are observable, one needs to be very careful. In the present work, we demonstrate how a small fraction of residual pile-up events can change the moments and their ratios of an event-by-event net-proton multiplicity distribution, which are sensitive to the dynamical fluctuations due to the QCD critical point. For this study, we assume that the individual event-by-event proton and antiproton multiplicity distributions follow Poisson, negative binomial, or binomial distributions. We observe a significant effect in cumulants and their ratios of net-proton multiplicity distributions due to pile-up events, particularly at lower energies. It might be crucial to estimate the fraction of pile-up events in the data sample while interpreting the experimental observable for the critical point.

Poisson and negative binomial item count techniques for surveys with sensitive question.

PubMed

Tian, Guo-Liang; Tang, Man-Lai; Wu, Qin; Liu, Yin

2017-04-01

Although the item count technique is useful in surveys with sensitive questions, privacy of those respondents who possess the sensitive characteristic of interest may not be well protected due to a defect in its original design. In this article, we propose two new survey designs (namely the Poisson item count technique and negative binomial item count technique) which replace several independent Bernoulli random variables required by the original item count technique with a single Poisson or negative binomial random variable, respectively. The proposed models not only provide closed form variance estimate and confidence interval within [0, 1] for the sensitive proportion, but also simplify the survey design of the original item count technique. Most importantly, the new designs do not leak respondents' privacy. Empirical results show that the proposed techniques perform satisfactorily in the sense that it yields accurate parameter estimate and confidence interval.

Evaluation of the alpha-amylase activity as an indicator of pasteurization efficiency and microbiological quality of liquid whole eggs.

PubMed

Silva, Guilherme Resende da; Menezes, Liliane Denize Miranda; Lanza, Isabela Pereira; Oliveira, Daniela Duarte de; Silva, Carla Aparecida; Klein, Roger Wilker Tavares; Assis, Débora Cristina Sampaio de; Cançado, Silvana de Vasconcelos

2017-09-01

In order to evaluate the efficiency of the pasteurization process in liquid whole eggs, an UV/visible spectrophotometric method was developed and validated for the assessment of alpha-amylase activity. Samples were collected from 30 lots of raw eggs (n = 30) and divided into three groups: one was reserved for analysis of the raw eggs, the second group was pasteurized at 61.1°C for 3.5 minutes (n = 30), and the third group was pasteurized at 64.4°C for 2.5 minutes (n = 30). In addition to assessing alpha-amylase activity, the microbiological quality of the samples was also evaluated by counting total and thermotolerant coliforms, mesophilic aerobic microorganisms, Staphylococcus spp., and Salmonella spp. The validated spectrophotometric method demonstrated linearity, with a coefficient of determination (R2) greater than 0.99, limits of detection (LOD) and quantification (LOQ) of 0.48 mg kg-1 and 1.16 mg kg-1, respectively, and acceptable precision and accuracy with relative standard deviation (RSD) values of less than 10% and recovery rates between 98.81% and 105.40%. The results for alpha-amylase activity in the raw egg samples showed high enzyme activity due to near-complete hydrolysis of the starch, while in the eggs pasteurized at 61.1°C, partial inactivation of the enzyme was observed. In the samples of whole eggs pasteurized at 64.4°C, starch hydrolysis did not occur due to enzyme inactivation. The results of the microbiological analyses showed a decrease (P < 0.0001) in the counts for all the studied microorganisms and in the frequency of Salmonella spp. in the pasteurized egg samples according to the two binomials under investigation, compared to the raw egg samples, which showed high rates of contamination (P < 0.0001). After pasteurization, only one sample (3.33%) was positive for Salmonella spp., indicating failure in the pasteurization process, which was confirmed by the alpha-amylase test. It was concluded that the validated methodology for testing alpha-amylase activity is adequate for assessing the efficiency of the pasteurization process, and that the time-temperature binomial used in this study is suitable to produce pasteurized eggs with high microbiological quality. © 2017 Poultry Science Association Inc.

Oral health of schoolchildren in Western Australia.

PubMed

Arrow, P

2016-09-01

The West Australian School Dental Service (SDS) provides free, statewide, primary dental care to schoolchildren aged 5-17 years. This study reports on an evaluation of the oral health of children examined during the 2014 calendar year. Children were sampled, based on their date of birth, and SDS clinicians collected the clinical information. Weighted mean values of caries experience were presented. Negative binomial regression modelling was undertaken to test for factors of significance in the rate of caries occurrence. Data from children aged 5-15 years were used (girls = 4616, boys = 4900). Mean dmft (5-10-year-olds), 1.42 SE 0.03; mean DMFT (6-15-year-olds), 0.51 SE 0.01. Negative binomial regression model of permanent tooth caries found higher rates of caries in children who were from non-fluoridated areas (RR 2.1); Aboriginal (RR 2.4); had gingival inflammation (RR 1.5); lower ICSEA level (RR 1.4); and recalled at more than 24-month interval (RR 1.8). The study highlighted poor dental health associated with living in non-fluoridated areas, Aboriginal identity, poor oral hygiene, lower socioeconomic level and having extended intervals between dental checkups. Timely assessments and preventive measures targeted at groups, including extending community water fluoridation, may assist in further improving the oral health of children in Western Australia. © 2015 Australian Dental Association.

Negative Binomial Process Count and Mixture Modeling.

PubMed

Zhou, Mingyuan; Carin, Lawrence

2015-02-01

The seemingly disjoint problems of count and mixture modeling are united under the negative binomial (NB) process. A gamma process is employed to model the rate measure of a Poisson process, whose normalization provides a random probability measure for mixture modeling and whose marginalization leads to an NB process for count modeling. A draw from the NB process consists of a Poisson distributed finite number of distinct atoms, each of which is associated with a logarithmic distributed number of data samples. We reveal relationships between various count- and mixture-modeling distributions and construct a Poisson-logarithmic bivariate distribution that connects the NB and Chinese restaurant table distributions. Fundamental properties of the models are developed, and we derive efficient Bayesian inference. It is shown that with augmentation and normalization, the NB process and gamma-NB process can be reduced to the Dirichlet process and hierarchical Dirichlet process, respectively. These relationships highlight theoretical, structural, and computational advantages of the NB process. A variety of NB processes, including the beta-geometric, beta-NB, marked-beta-NB, marked-gamma-NB and zero-inflated-NB processes, with distinct sharing mechanisms, are also constructed. These models are applied to topic modeling, with connections made to existing algorithms under Poisson factor analysis. Example results show the importance of inferring both the NB dispersion and probability parameters.

Goodness-of-fit tests and model diagnostics for negative binomial regression of RNA sequencing data.

PubMed

Mi, Gu; Di, Yanming; Schafer, Daniel W

2015-01-01

This work is about assessing model adequacy for negative binomial (NB) regression, particularly (1) assessing the adequacy of the NB assumption, and (2) assessing the appropriateness of models for NB dispersion parameters. Tools for the first are appropriate for NB regression generally; those for the second are primarily intended for RNA sequencing (RNA-Seq) data analysis. The typically small number of biological samples and large number of genes in RNA-Seq analysis motivate us to address the trade-offs between robustness and statistical power using NB regression models. One widely-used power-saving strategy, for example, is to assume some commonalities of NB dispersion parameters across genes via simple models relating them to mean expression rates, and many such models have been proposed. As RNA-Seq analysis is becoming ever more popular, it is appropriate to make more thorough investigations into power and robustness of the resulting methods, and into practical tools for model assessment. In this article, we propose simulation-based statistical tests and diagnostic graphics to address model adequacy. We provide simulated and real data examples to illustrate that our proposed methods are effective for detecting the misspecification of the NB mean-variance relationship as well as judging the adequacy of fit of several NB dispersion models.

Association between adherence to physical activity guidelines and health-related quality of life among individuals with physician-diagnosed arthritis.

PubMed

Austin, Shamly; Qu, Haiyan; Shewchuk, Richard M

2012-10-01

To examine the association between adherence to physical activity guidelines and health-related quality of life (HRQOL) among individuals with arthritis. A cross-sectional sample with 33,071 US adults, 45 years or older with physician-diagnosed arthritis was obtained from 2007 Behavioral Risk Factor Surveillance System survey. We conducted negative binomial regression analysis to examine HRQOL as a function of adherence to physical activity guidelines controlling for physicians' recommendations for physical activity, age, sex, race, education, marital status, employment, annual income, health insurance, personal physician, emotional support, body mass index, activity limitations, health status, and co-morbidities based on Behavioral Model of Health Services Utilization. Descriptive statistics showed that 60% adults with arthritis did not adhere to physical activity guidelines, mean physically and mentally unhealthy days were 7.7 and 4.4 days, respectively. Results from negative binomial regression indicated that individuals who did not adhere to physical activity guidelines had 1.14 days more physically unhealthy days and 1.12 days more mentally unhealthy days than those who adhered controlling for covariates. Adherence to physical activity is important to improve HRQOL for individuals with arthritis. However, adherence is low among this population. Interventions are required to engage individuals with arthritis in physical activity.

Technical and biological variance structure in mRNA-Seq data: life in the real world

PubMed Central

2012-01-01

Background mRNA expression data from next generation sequencing platforms is obtained in the form of counts per gene or exon. Counts have classically been assumed to follow a Poisson distribution in which the variance is equal to the mean. The Negative Binomial distribution which allows for over-dispersion, i.e., for the variance to be greater than the mean, is commonly used to model count data as well. Results In mRNA-Seq data from 25 subjects, we found technical variation to generally follow a Poisson distribution as has been reported previously and biological variability was over-dispersed relative to the Poisson model. The mean-variance relationship across all genes was quadratic, in keeping with a Negative Binomial (NB) distribution. Over-dispersed Poisson and NB distributional assumptions demonstrated marked improvements in goodness-of-fit (GOF) over the standard Poisson model assumptions, but with evidence of over-fitting in some genes. Modeling of experimental effects improved GOF for high variance genes but increased the over-fitting problem. Conclusions These conclusions will guide development of analytical strategies for accurate modeling of variance structure in these data and sample size determination which in turn will aid in the identification of true biological signals that inform our understanding of biological systems. PMID:22769017

Small area estimation for estimating the number of infant mortality in West Java, Indonesia

NASA Astrophysics Data System (ADS)

Anggreyani, Arie; Indahwati, Kurnia, Anang

2016-02-01

Demographic and Health Survey Indonesia (DHSI) is a national designed survey to provide information regarding birth rate, mortality rate, family planning and health. DHSI was conducted by BPS in cooperation with National Population and Family Planning Institution (BKKBN), Indonesia Ministry of Health (KEMENKES) and USAID. Based on the publication of DHSI 2012, the infant mortality rate for a period of five years before survey conducted is 32 for 1000 birth lives. In this paper, Small Area Estimation (SAE) is used to estimate the number of infant mortality in districts of West Java. SAE is a special model of Generalized Linear Mixed Models (GLMM). In this case, the incidence of infant mortality is a Poisson distribution which has equdispersion assumption. The methods to handle overdispersion are binomial negative and quasi-likelihood model. Based on the results of analysis, quasi-likelihood model is the best model to overcome overdispersion problem. The basic model of the small area estimation used basic area level model. Mean square error (MSE) which based on resampling method is used to measure the accuracy of small area estimates.

On the Relationship between Molecular Hit Rates in High-Throughput Screening and Molecular Descriptors.

PubMed

Hansson, Mari; Pemberton, John; Engkvist, Ola; Feierberg, Isabella; Brive, Lars; Jarvis, Philip; Zander-Balderud, Linda; Chen, Hongming

2014-06-01

High-throughput screening (HTS) is widely used in the pharmaceutical industry to identify novel chemical starting points for drug discovery projects. The current study focuses on the relationship between molecular hit rate in recent in-house HTS and four common molecular descriptors: lipophilicity (ClogP), size (heavy atom count, HEV), fraction of sp(3)-hybridized carbons (Fsp3), and fraction of molecular framework (f(MF)). The molecular hit rate is defined as the fraction of times the molecule has been assigned as active in the HTS campaigns where it has been screened. Beta-binomial statistical models were built to model the molecular hit rate as a function of these descriptors. The advantage of the beta-binomial statistical models is that the correlation between the descriptors is taken into account. Higher degree polynomial terms of the descriptors were also added into the beta-binomial statistic model to improve the model quality. The relative influence of different molecular descriptors on molecular hit rate has been estimated, taking into account that the descriptors are correlated to each other through applying beta-binomial statistical modeling. The results show that ClogP has the largest influence on the molecular hit rate, followed by Fsp3 and HEV. f(MF) has only a minor influence besides its correlation with the other molecular descriptors. © 2013 Society for Laboratory Automation and Screening.

Data mining of tree-based models to analyze freeway accident frequency.

PubMed

Chang, Li-Yen; Chen, Wen-Chieh

2005-01-01

Statistical models, such as Poisson or negative binomial regression models, have been employed to analyze vehicle accident frequency for many years. However, these models have their own model assumptions and pre-defined underlying relationship between dependent and independent variables. If these assumptions are violated, the model could lead to erroneous estimation of accident likelihood. Classification and Regression Tree (CART), one of the most widely applied data mining techniques, has been commonly employed in business administration, industry, and engineering. CART does not require any pre-defined underlying relationship between target (dependent) variable and predictors (independent variables) and has been shown to be a powerful tool, particularly for dealing with prediction and classification problems. This study collected the 2001-2002 accident data of National Freeway 1 in Taiwan. A CART model and a negative binomial regression model were developed to establish the empirical relationship between traffic accidents and highway geometric variables, traffic characteristics, and environmental factors. The CART findings indicated that the average daily traffic volume and precipitation variables were the key determinants for freeway accident frequencies. By comparing the prediction performance between the CART and the negative binomial regression models, this study demonstrates that CART is a good alternative method for analyzing freeway accident frequencies. By comparing the prediction performance between the CART and the negative binomial regression models, this study demonstrates that CART is a good alternative method for analyzing freeway accident frequencies.

The coefficient of determination R2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded.

PubMed

Nakagawa, Shinichi; Johnson, Paul C D; Schielzeth, Holger

2017-09-01

The coefficient of determination R 2 quantifies the proportion of variance explained by a statistical model and is an important summary statistic of biological interest. However, estimating R 2 for generalized linear mixed models (GLMMs) remains challenging. We have previously introduced a version of R 2 that we called [Formula: see text] for Poisson and binomial GLMMs, but not for other distributional families. Similarly, we earlier discussed how to estimate intra-class correlation coefficients (ICCs) using Poisson and binomial GLMMs. In this paper, we generalize our methods to all other non-Gaussian distributions, in particular to negative binomial and gamma distributions that are commonly used for modelling biological data. While expanding our approach, we highlight two useful concepts for biologists, Jensen's inequality and the delta method, both of which help us in understanding the properties of GLMMs. Jensen's inequality has important implications for biologically meaningful interpretation of GLMMs, whereas the delta method allows a general derivation of variance associated with non-Gaussian distributions. We also discuss some special considerations for binomial GLMMs with binary or proportion data. We illustrate the implementation of our extension by worked examples from the field of ecology and evolution in the R environment. However, our method can be used across disciplines and regardless of statistical environments. © 2017 The Author(s).

The effect of clustering on lot quality assurance sampling: a probabilistic model to calculate sample sizes for quality assessments

PubMed Central

2013-01-01

Background Traditional Lot Quality Assurance Sampling (LQAS) designs assume observations are collected using simple random sampling. Alternatively, randomly sampling clusters of observations and then individuals within clusters reduces costs but decreases the precision of the classifications. In this paper, we develop a general framework for designing the cluster(C)-LQAS system and illustrate the method with the design of data quality assessments for the community health worker program in Rwanda. Results To determine sample size and decision rules for C-LQAS, we use the beta-binomial distribution to account for inflated risk of errors introduced by sampling clusters at the first stage. We present general theory and code for sample size calculations. The C-LQAS sample sizes provided in this paper constrain misclassification risks below user-specified limits. Multiple C-LQAS systems meet the specified risk requirements, but numerous considerations, including per-cluster versus per-individual sampling costs, help identify optimal systems for distinct applications. Conclusions We show the utility of C-LQAS for data quality assessments, but the method generalizes to numerous applications. This paper provides the necessary technical detail and supplemental code to support the design of C-LQAS for specific programs. PMID:24160725

The effect of clustering on lot quality assurance sampling: a probabilistic model to calculate sample sizes for quality assessments.

PubMed

Hedt-Gauthier, Bethany L; Mitsunaga, Tisha; Hund, Lauren; Olives, Casey; Pagano, Marcello

2013-10-26

Traditional Lot Quality Assurance Sampling (LQAS) designs assume observations are collected using simple random sampling. Alternatively, randomly sampling clusters of observations and then individuals within clusters reduces costs but decreases the precision of the classifications. In this paper, we develop a general framework for designing the cluster(C)-LQAS system and illustrate the method with the design of data quality assessments for the community health worker program in Rwanda. To determine sample size and decision rules for C-LQAS, we use the beta-binomial distribution to account for inflated risk of errors introduced by sampling clusters at the first stage. We present general theory and code for sample size calculations.The C-LQAS sample sizes provided in this paper constrain misclassification risks below user-specified limits. Multiple C-LQAS systems meet the specified risk requirements, but numerous considerations, including per-cluster versus per-individual sampling costs, help identify optimal systems for distinct applications. We show the utility of C-LQAS for data quality assessments, but the method generalizes to numerous applications. This paper provides the necessary technical detail and supplemental code to support the design of C-LQAS for specific programs.

Comparing Complementary and Alternative Medicine Use with or without Including Prayer as a Modality in a Local and Diverse United States Jurisdiction.

PubMed

Robles, Brenda; Upchurch, Dawn M; Kuo, Tony

2017-01-01

Few studies to date have examined the utilization of complementary and alternative medicine (CAM) in a local, ethnically diverse population in the United States (U.S.). Fewer have addressed the differences in their use based on inclusion or exclusion of prayer as a modality. Variable definitions of CAM are known to affect public health surveillance (i.e., continuous, systematic data collection, analysis, and interpretation) or benchmarking (i.e., identifying and comparing key indicators of health to inform community planning) related to this non-mainstream collection of health and wellness therapies. The present study sought to better understand how including or excluding prayer could affect reporting of CAM use among residents of a large, urban U.S. jurisdiction. Using population-weighted data from a cross-sectional Internet panel survey collected as part of a larger countywide population health survey, the study compared use of CAM based on whether prayer or no prayer was included in its definition. Patterns of CAM use by socio-demographic characteristics were described for the two operationalized definitions. Multivariable binomial regression analyses were performed to control for gender, age, race/ethnicity, education, employment, income, and health insurance status. One of the analyses explored the associations between CAM use and racial/ethnic characteristics in the study sample. Los Angeles County, California. A socio-demographically diverse sample of Los Angeles County residents. CAM use (with prayer) and CAM use (excluding prayer). Blacks were among the highest users of CAM when compared to Whites, especially when prayer was included as a CAM modality. Regardless of prayer inclusion, being a woman predicted higher use of CAM. How CAM is defined matters in gauging the utilization of this non-mainstream collection of therapies. Given that surveillance and/or benchmarking data are often used to inform resource allocation and planning decisions, results from the present study suggest that when prayer is included as part of the CAM definition, utilization/volume estimates of its use increased correspondingly, especially among non-White residents of the region.

Inhomogeneity of the density of Parascaris spp. eggs in faeces of individual foals and the use of hypothesis testing for treatment decision making.

PubMed

Wilkes, E J A; Cowling, A; Woodgate, R G; Hughes, K J

2016-10-15

Faecal egg counts (FEC) are used widely for monitoring of parasite infection in animals, treatment decision-making and estimation of anthelmintic efficacy. When a single count or sample mean is used as a point estimate of the expectation of the egg distribution over some time interval, the variability in the egg density is not accounted for. Although variability, including quantifying sources, of egg count data has been described, the spatiotemporal distribution of nematode eggs in faeces is not well understood. We believe that statistical inference about the mean egg count for treatment decision-making has not been used previously. The aim of this study was to examine the density of Parascaris eggs in solution and faeces and to describe the use of hypothesis testing for decision-making. Faeces from two foals with Parascaris burdens were mixed with magnesium sulphate solution and 30 McMaster chambers were examined to determine the egg distribution in a well-mixed solution. To examine the distribution of eggs in faeces from an individual animal, three faecal piles from a foal with a known Parascaris burden were obtained, from which 81 counts were performed. A single faecal sample was also collected daily from 20 foals on three consecutive days and a FEC was performed on three separate portions of each sample. As appropriate, Poisson or negative binomial confidence intervals for the distribution mean were calculated. Parascaris eggs in a well-mixed solution conformed to a homogeneous Poisson process, while the egg density in faeces was not homogeneous, but aggregated. This study provides an extension from homogeneous to inhomogeneous Poisson processes, leading to an understanding of why Poisson and negative binomial distributions correspondingly provide a good fit for egg count data. The application of one-sided hypothesis tests for decision-making is presented. Copyright © 2016 Elsevier B.V. All rights reserved.

Does the name really matter? The importance of botanical nomenclature and plant taxonomy in biomedical research.

PubMed

Bennett, Bradley C; Balick, Michael J

2014-03-28

Medical research on plant-derived compounds requires a breadth of expertise from field to laboratory and clinical skills. Too often basic botanical skills are evidently lacking, especially with respect to plant taxonomy and botanical nomenclature. Binomial and familial names, synonyms and author citations are often misconstrued. The correct botanical name, linked to a vouchered specimen, is the sine qua non of phytomedical research. Without the unique identifier of a proper binomial, research cannot accurately be linked to the existing literature. Perhaps more significant, is the ambiguity of species determinations that ensues of from poor taxonomic practices. This uncertainty, not surprisingly, obstructs reproducibility of results-the cornerstone of science. Based on our combined six decades of experience with medicinal plants, we discuss the problems of inaccurate taxonomy and botanical nomenclature in biomedical research. This problems appear all too frequently in manuscripts and grant applications that we review and they extend to the published literature. We also review the literature on the importance of taxonomy in other disciplines that relate to medicinal plant research. In most cases, questions regarding orthography, synonymy, author citations, and current family designations of most plant binomials can be resolved using widely-available online databases and other electronic resources. Some complex problems require consultation with a professional plant taxonomist, which also is important for accurate identification of voucher specimens. Researchers should provide the currently accepted binomial and complete author citation, provide relevant synonyms, and employ the Angiosperm Phylogeny Group III family name. Taxonomy is a vital adjunct not only to plant-medicine research but to virtually every field of science. Medicinal plant researchers can increase the precision and utility of their investigations by following sound practices with respect to botanical nomenclature. Correct spellings, accepted binomials, author citations, synonyms, and current family designations can readily be found on reliable online databases. When questions arise, researcher should consult plant taxonomists. © 2013 Published by Elsevier Ireland Ltd.

Exploring the effects of roadway characteristics on the frequency and severity of head-on crashes: case studies from Malaysian federal roads.

PubMed

Hosseinpour, Mehdi; Yahaya, Ahmad Shukri; Sadullah, Ahmad Farhan

2014-01-01

Head-on crashes are among the most severe collision types and of great concern to road safety authorities. Therefore, it justifies more efforts to reduce both the frequency and severity of this collision type. To this end, it is necessary to first identify factors associating with the crash occurrence. This can be done by developing crash prediction models that relate crash outcomes to a set of contributing factors. This study intends to identify the factors affecting both the frequency and severity of head-on crashes that occurred on 448 segments of five federal roads in Malaysia. Data on road characteristics and crash history were collected on the study segments during a 4-year period between 2007 and 2010. The frequency of head-on crashes were fitted by developing and comparing seven count-data models including Poisson, standard negative binomial (NB), random-effect negative binomial, hurdle Poisson, hurdle negative binomial, zero-inflated Poisson, and zero-inflated negative binomial models. To model crash severity, a random-effect generalized ordered probit model (REGOPM) was used given a head-on crash had occurred. With respect to the crash frequency, the random-effect negative binomial (RENB) model was found to outperform the other models according to goodness of fit measures. Based on the results of the model, the variables horizontal curvature, terrain type, heavy-vehicle traffic, and access points were found to be positively related to the frequency of head-on crashes, while posted speed limit and shoulder width decreased the crash frequency. With regard to the crash severity, the results of REGOPM showed that horizontal curvature, paved shoulder width, terrain type, and side friction were associated with more severe crashes, whereas land use, access points, and presence of median reduced the probability of severe crashes. Based on the results of this study, some potential countermeasures were proposed to minimize the risk of head-on crashes. Copyright © 2013 Elsevier Ltd. All rights reserved.

Bayesian sample size calculations in phase II clinical trials using a mixture of informative priors.

PubMed

Gajewski, Byron J; Mayo, Matthew S

2006-08-15

A number of researchers have discussed phase II clinical trials from a Bayesian perspective. A recent article by Mayo and Gajewski focuses on sample size calculations, which they determine by specifying an informative prior distribution and then calculating a posterior probability that the true response will exceed a prespecified target. In this article, we extend these sample size calculations to include a mixture of informative prior distributions. The mixture comes from several sources of information. For example consider information from two (or more) clinicians. The first clinician is pessimistic about the drug and the second clinician is optimistic. We tabulate the results for sample size design using the fact that the simple mixture of Betas is a conjugate family for the Beta- Binomial model. We discuss the theoretical framework for these types of Bayesian designs and show that the Bayesian designs in this paper approximate this theoretical framework. Copyright 2006 John Wiley & Sons, Ltd.

Improved confidence intervals when the sample is counted an integer times longer than the blank.

PubMed

Potter, William Edward; Strzelczyk, Jadwiga Jodi

2011-05-01

Past computer solutions for confidence intervals in paired counting are extended to the case where the ratio of the sample count time to the blank count time is taken to be an integer, IRR. Previously, confidence intervals have been named Neyman-Pearson confidence intervals; more correctly they should have been named Neyman confidence intervals or simply confidence intervals. The technique utilized mimics a technique used by Pearson and Hartley to tabulate confidence intervals for the expected value of the discrete Poisson and Binomial distributions. The blank count and the contribution of the sample to the gross count are assumed to be Poisson distributed. The expected value of the blank count, in the sample count time, is assumed known. The net count, OC, is taken to be the gross count minus the product of IRR with the blank count. The probability density function (PDF) for the net count can be determined in a straightforward manner.

Binomial test statistics using Psi functions

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

Bowman, Kimiko o

2007-01-01

For the negative binomial model (probability generating function (p + 1 - pt){sup -k}) a logarithmic derivative is the Psi function difference {psi}(k + x) - {psi}(k); this and its derivatives lead to a test statistic to decide on the validity of a specified model. The test statistic uses a data base so there exists a comparison available between theory and application. Note that the test function is not dominated by outliers. Applications to (i) Fisher's tick data, (ii) accidents data, (iii) Weldon's dice data are included.

A modified chain binomial model to analyse the ongoing measles epidemic in Greece, July 2017 to February 2018

PubMed Central

Lytras, Theodore; Georgakopoulou, Theano; Tsiodras, Sotirios

2018-01-01

Greece is currently experiencing a large measles outbreak, in the context of multiple similar outbreaks across Europe. We devised and applied a modified chain-binomial epidemic model, requiring very simple data, to estimate the transmission parameters of this outbreak. Model results indicate sustained measles transmission among the Greek Roma population, necessitating a targeted mass vaccination campaign to halt further spread of the epidemic. Our model may be useful for other countries facing similar measles outbreaks. PMID:29717695

A modified chain binomial model to analyse the ongoing measles epidemic in Greece, July 2017 to February 2018.

PubMed

Lytras, Theodore; Georgakopoulou, Theano; Tsiodras, Sotirios

2018-04-01

Greece is currently experiencing a large measles outbreak, in the context of multiple similar outbreaks across Europe. We devised and applied a modified chain-binomial epidemic model, requiring very simple data, to estimate the transmission parameters of this outbreak. Model results indicate sustained measles transmission among the Greek Roma population, necessitating a targeted mass vaccination campaign to halt further spread of the epidemic. Our model may be useful for other countries facing similar measles outbreaks.

[Monitoring microbiological safety of small systems of water distribution. Comparison of two sampling programs in a town in central Italy].

PubMed

Papini, Paolo; Faustini, Annunziata; Manganello, Rosa; Borzacchi, Giancarlo; Spera, Domenico; Perucci, Carlo A

2005-01-01

To determine the frequency of sampling in small water distribution systems (<5,000 inhabitants) and compare the results according to different hypotheses in bacteria distribution. We carried out two sampling programs to monitor the water distribution system in a town in Central Italy between July and September 1992; the Poisson distribution assumption implied 4 water samples, the assumption of negative binomial distribution implied 21 samples. Coliform organisms were used as indicators of water safety. The network consisted of two pipe rings and two wells fed by the same water source. The number of summer customers varied considerably from 3,000 to 20,000. The mean density was 2.33 coliforms/100 ml (sd= 5.29) for 21 samples and 3 coliforms/100 ml (sd= 6) for four samples. However the hypothesis of homogeneity was rejected (p-value <0.001) and the probability of II type error with the assumption of heterogeneity was higher with 4 samples (beta= 0.24) than with 21 (beta= 0.05). For this small network, determining the samples' size according to heterogeneity hypothesis strengthens the statement that water is drinkable compared with homogeneity assumption.

Risk factors related to Toxoplasma gondii seroprevalence in indoor-housed Dutch dairy goats.

PubMed

Deng, Huifang; Dam-Deisz, Cecile; Luttikholt, Saskia; Maas, Miriam; Nielen, Mirjam; Swart, Arno; Vellema, Piet; van der Giessen, Joke; Opsteegh, Marieke

2016-02-01

Toxoplasma gondii can cause disease in goats, but also has impact on human health through food-borne transmission. Our aims were to determine the seroprevalence of T. gondii infection in indoor-housed Dutch dairy goats and to identify the risk factors related to T. gondii seroprevalence. Fifty-two out of ninety approached farmers with indoor-kept goats (58%) participated by answering a standardized questionnaire and contributing 32 goat blood samples each. Serum samples were tested for T. gondii SAG1 antibodies by ELISA and results showed that the frequency distribution of the log10-transformed OD-values fitted well with a binary mixture of a shifted gamma and a shifted reflected gamma distribution. The overall animal seroprevalence was 13.3% (95% CI: 11.7–14.9%), and at least one seropositive animal was found on 61.5% (95% CI: 48.3–74.7%) of the farms. To evaluate potential risk factors on herd level, three modeling strategies (Poisson, negative binomial and zero-inflated) were compared. The negative binomial model fitted the data best with the number of cats (1–4 cats: IR: 2.6, 95% CI: 1.1–6.5; > = 5 cats:IR: 14.2, 95% CI: 3.9–51.1) and mean animal age (IR: 1.5, 95% CI: 1.1–2.1) related to herd positivity. In conclusion, the ELISA test was 100% sensitive and specific based on binary mixture analysis. T. gondii infection is prevalent in indoor housed Dutch dairy goats but at a lower overall animal level seroprevalence than outdoor farmed goats in other European countries, and cat exposure is an important risk factor.

Dental plaque, preventive care, and tooth brushing associated with dental caries in primary teeth in schoolchildren ages 6–9 years of Leon, Nicaragua

PubMed Central

del Socorro Herrera, Miriam; Medina-Solis, Carlo Eduardo; Minaya-Sánchez, Mirna; Pontigo-Loyola, América Patricia; Villalobos-Rodelo, Juan José; Islas-Granillo, Horacio; de la Rosa-Santillana, Rubén; Maupomé, Gerardo

2013-01-01

Background Our study aimed to evaluate the effect of various risk indicators for dental caries on primary teeth of Nicaraguan children (from Leon, Nicaragua) ages 6 to 9, using the negative binomial regression model. Material/Methods A cross-sectional study was carried out to collect clinical, demographic, socioeconomic, and behavioral data from 794 schoolchildren ages 6 to 9 years, randomly selected from 25 schools in the city of León, Nicaragua. Clinical examinations for dental caries (dmft index) were performed by 2 trained and standardized examiners. Socio-demographic, socioeconomic, and behavioral data were self-reported using questionnaires. Multivariate negative binomial regression (NBR) analysis was used. Results Mean age was 7.49±1.12 years. Boys accounted for 50.1% of the sample. Mean dmft was 3.54±3.13 and caries prevalence (dmft >0) was 77.6%. In the NBR multivariate model (p<0.05), for each year of age, the expected mean dmft decreased by 7.5%. Brushing teeth at least once a day and having received preventive dental care in the last year before data collection were associated with declines in the expected mean dmft by 19.5% and 69.6%, respectively. Presence of dental plaque increased the expected mean dmft by 395.5%. Conclusions The proportion of students with caries in this sample was high. We found associations between dental caries in the primary dentition and dental plaque, brushing teeth at least once a day, and having received preventive dental care. To improve oral health, school programs and/or age-appropriate interventions need to be developed based on the specific profile of caries experience and the associated risk indicators. PMID:24247119

Building test data from real outbreaks for evaluating detection algorithms.

PubMed

Texier, Gaetan; Jackson, Michael L; Siwe, Leonel; Meynard, Jean-Baptiste; Deparis, Xavier; Chaudet, Herve

2017-01-01

Benchmarking surveillance systems requires realistic simulations of disease outbreaks. However, obtaining these data in sufficient quantity, with a realistic shape and covering a sufficient range of agents, size and duration, is known to be very difficult. The dataset of outbreak signals generated should reflect the likely distribution of authentic situations faced by the surveillance system, including very unlikely outbreak signals. We propose and evaluate a new approach based on the use of historical outbreak data to simulate tailored outbreak signals. The method relies on a homothetic transformation of the historical distribution followed by resampling processes (Binomial, Inverse Transform Sampling Method-ITSM, Metropolis-Hasting Random Walk, Metropolis-Hasting Independent, Gibbs Sampler, Hybrid Gibbs Sampler). We carried out an analysis to identify the most important input parameters for simulation quality and to evaluate performance for each of the resampling algorithms. Our analysis confirms the influence of the type of algorithm used and simulation parameters (i.e. days, number of cases, outbreak shape, overall scale factor) on the results. We show that, regardless of the outbreaks, algorithms and metrics chosen for the evaluation, simulation quality decreased with the increase in the number of days simulated and increased with the number of cases simulated. Simulating outbreaks with fewer cases than days of duration (i.e. overall scale factor less than 1) resulted in an important loss of information during the simulation. We found that Gibbs sampling with a shrinkage procedure provides a good balance between accuracy and data dependency. If dependency is of little importance, binomial and ITSM methods are accurate. Given the constraint of keeping the simulation within a range of plausible epidemiological curves faced by the surveillance system, our study confirms that our approach can be used to generate a large spectrum of outbreak signals.

Building test data from real outbreaks for evaluating detection algorithms

PubMed Central

Texier, Gaetan; Jackson, Michael L.; Siwe, Leonel; Meynard, Jean-Baptiste; Deparis, Xavier; Chaudet, Herve

2017-01-01

Benchmarking surveillance systems requires realistic simulations of disease outbreaks. However, obtaining these data in sufficient quantity, with a realistic shape and covering a sufficient range of agents, size and duration, is known to be very difficult. The dataset of outbreak signals generated should reflect the likely distribution of authentic situations faced by the surveillance system, including very unlikely outbreak signals. We propose and evaluate a new approach based on the use of historical outbreak data to simulate tailored outbreak signals. The method relies on a homothetic transformation of the historical distribution followed by resampling processes (Binomial, Inverse Transform Sampling Method—ITSM, Metropolis-Hasting Random Walk, Metropolis-Hasting Independent, Gibbs Sampler, Hybrid Gibbs Sampler). We carried out an analysis to identify the most important input parameters for simulation quality and to evaluate performance for each of the resampling algorithms. Our analysis confirms the influence of the type of algorithm used and simulation parameters (i.e. days, number of cases, outbreak shape, overall scale factor) on the results. We show that, regardless of the outbreaks, algorithms and metrics chosen for the evaluation, simulation quality decreased with the increase in the number of days simulated and increased with the number of cases simulated. Simulating outbreaks with fewer cases than days of duration (i.e. overall scale factor less than 1) resulted in an important loss of information during the simulation. We found that Gibbs sampling with a shrinkage procedure provides a good balance between accuracy and data dependency. If dependency is of little importance, binomial and ITSM methods are accurate. Given the constraint of keeping the simulation within a range of plausible epidemiological curves faced by the surveillance system, our study confirms that our approach can be used to generate a large spectrum of outbreak signals. PMID:28863159

Dental plaque, preventive care, and tooth brushing associated with dental caries in primary teeth in schoolchildren ages 6-9 years of Leon, Nicaragua.

PubMed

Herrera, Miriam del Socorro; Medina-Solís, Carlo Eduardo; Minaya-Sánchez, Mirna; Pontigo-Loyola, América Patricia; Villalobos-Rodelo, Juan José; Islas-Granillo, Horacio; de la Rosa-Santillana, Rubén; Maupomé, Gerardo

2013-11-19

Our study aimed to evaluate the effect of various risk indicators for dental caries on primary teeth of Nicaraguan children (from Leon, Nicaragua) ages 6 to 9, using the negative binomial regression model. A cross-sectional study was carried out to collect clinical, demographic, socioeconomic, and behavioral data from 794 schoolchildren ages 6 to 9 years, randomly selected from 25 schools in the city of León, Nicaragua. Clinical examinations for dental caries (dmft index) were performed by 2 trained and standardized examiners. Socio-demographic, socioeconomic, and behavioral data were self-reported using questionnaires. Multivariate negative binomial regression (NBR) analysis was used. Mean age was 7.49 ± 1.12 years. Boys accounted for 50.1% of the sample. Mean dmft was 3.54 ± 3.13 and caries prevalence (dmft >0) was 77.6%. In the NBR multivariate model (p<0.05), for each year of age, the expected mean dmft decreased by 7.5%. Brushing teeth at least once a day and having received preventive dental care in the last year before data collection were associated with declines in the expected mean dmft by 19.5% and 69.6%, respectively. Presence of dental plaque increased the expected mean dmft by 395.5%. The proportion of students with caries in this sample was high. We found associations between dental caries in the primary dentition and dental plaque, brushing teeth at least once a day, and having received preventive dental care. To improve oral health, school programs and/or age-appropriate interventions need to be developed based on the specific profile of caries experience and the associated risk indicators.

Using inquiry-based instruction to meet the standards of No Child Left Behind for middle school earth science

NASA Astrophysics Data System (ADS)

Harris, Michael W.

This study examined the effectiveness of a specific instructional strategy employed to improve performance on the end-of-the-year Criterion-Referenced Competency Test (CRCT) as mandated by the No Child Left Behind (NCLB) Act of 2001. A growing body of evidence suggests that the perceived pressure to produce adequate aggregated scores on the CRCT causes teachers to neglect other relevant aspects of teaching and attend less to individualized instruction. Rooted in constructivist theory, inquiry-based programs provide a o developmental plan of instruction that affords the opportunity for each student to understand their academic needs and strengths. However, the utility of inquiry-based instruction is largely unknown due to the lack of evaluation studies. To address this problem, this quantitative evaluation measured the impact of the Audet and Jordan inquiry-based instructional model on CRCT test scores of 102 students in a sixth-grade science classroom in one north Georgia school. A series of binomial tests of proportions tested differences between CRCT scores of the program participants and those of a matched control sample selected from other district schools that did not adopt the program. The study found no significant differences on CRCT test scores between the treatment and control groups. The study also found no significant performance differences among genders in the sample using inquiry instruction. This implies that the utility of inquiry education might exist outside the domain of test scores. This study can contribute to social change by informing a reevaluation of the instructional strategies that ideally will serve NCLB high-stakes assessment mandates, while also affording students the individual-level skills needed to become productive members of society.

Predictors of the risk of malnutrition among children under the age of 5 years in Somalia.

PubMed

Kinyoki, Damaris K; Berkley, James A; Moloney, Grainne M; Kandala, Ngianga-Bakwin; Noor, Abdisalan M

2015-12-01

To investigate the predictors of wasting, stunting and low mid-upper arm circumference among children aged 6-59 months in Somalia using data from household cross-sectional surveys from 2007 to 2010 in order to help inform better targeting of nutritional interventions. Cross-sectional nutritional assessment surveys using structured interviews were conducted among communities in Somalia each year from 2007 to 2010. A two-stage cluster sampling methodology was used to select children aged 6-59 months from households across three livelihood zones (pastoral, agro-pastoral and riverine). Predictors of three anthropometric measures, weight-for-height (wasting), height-for-age (stunting) and mid-upper arm circumference, were analysed using Bayesian binomial regression, controlling for both spatial and temporal dependence in the data. The study was conducted in randomly sampled villages, representative of three livelihood zones in Somalia. Children between the ages of 6 and 59 months in Somalia. The estimated national prevalence of wasting, stunting and low mid-upper arm circumference in children aged 6-59 months was 21 %, 31 % and 36 %, respectively. Although fever, diarrhoea, sex and age of the child, household size and access to foods were significant predictors of malnutrition, the strongest association was observed between all three indicators of malnutrition and the enhanced vegetation index. A 1-unit increase in enhanced vegetation index was associated with a 38 %, 49 % and 59 % reduction in wasting, stunting and low mid-upper arm circumference, respectively. Infection and climatic variations are likely to be key drivers of malnutrition in Somalia. Better health data and close monitoring and forecasting of droughts may provide valuable information for nutritional intervention planning in Somalia.

Quality of care and contraceptive use in urban Kenya

PubMed Central

Pence, Brian W.; Curtis, Siân L.; Marshall, Stephen W.; Speizer, Ilene S.

2015-01-01

CONTEXT Family planning is highly beneficial to women’s overall health, morbidity, and mortality, particularly in developing countries. Yet, in much of sub-Saharan Africa, contraceptive prevalence remains low while unmet need for family planning remains high. It has been frequently hypothesized that the poor quality of family planning service provision in many low-income settings acts as a barrier to optimal rates of contraceptive use but this association has not been rigorously tested. METHODS Using data collected from 3,990 women in 2010, this study investigates the association between family planning service quality and current modern contraceptive use in five cities in Kenya. In addition to individual-level data, audits of select facilities and service provider interviews were conducted in 260 facilities. Within 126 higher-volume clinics, exit interviews were conducted with family planning clients. Individual and facility-level data are linked based on the source of the woman’s current method or other health service. Adjusted prevalence ratios are estimated using binomial regression and we account for clustering of observations within facilities using robust standard errors. RESULTS Solicitation of client preferences, assistance with method selection, provision of information by providers on side effects, and provider treatment of clients were all associated with a significantly increased likelihood of current modern contraceptive use and effects were often stronger among younger and less educated women. CONCLUSION Efforts to strengthen contraceptive security and improve the content of contraceptive counseling and treatment of clients by providers have the potential to significantly increase contraceptive use in urban Kenya. PMID:26308259

Elective Clinical Target Volumes for Conformal Therapy in Anorectal Cancer: A Radiation Therapy Oncology Group Consensus Panel Contouring Atlas

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

Myerson, Robert J.; Garofalo, Michael C.; El Naqa, Issam

2009-07-01

Purpose: To develop a Radiation Therapy Oncology Group (RTOG) atlas of the elective clinical target volume (CTV) definitions to be used for planning pelvic intensity-modulated radiotherapy (IMRT) for anal and rectal cancers. Methods and Materials: The Gastrointestinal Committee of the RTOG established a task group (the nine physician co-authors) to develop this atlas. They responded to a questionnaire concerning three elective CTVs (CTVA: internal iliac, presacral, and perirectal nodal regions for both anal and rectal case planning; CTVB: external iliac nodal region for anal case planning and for selected rectal cases; CTVC: inguinal nodal region for anal case planning andmore » for select rectal cases), and to outline these areas on individual computed tomographic images. The imaging files were shared via the Advanced Technology Consortium. A program developed by one of the co-authors (I.E.N.) used binomial maximum-likelihood estimates to generate a 95% group consensus contour. The computer-estimated consensus contours were then reviewed by the group and modified to provide a final contouring consensus atlas. Results: The panel achieved consensus CTV definitions to be used as guidelines for the adjuvant therapy of rectal cancer and definitive therapy for anal cancer. The most important difference from similar atlases for gynecologic or genitourinary cancer is mesorectal coverage. Detailed target volume contouring guidelines and images are discussed. Conclusion: This report serves as a template for the definition of the elective CTVs to be used in IMRT planning for anal and rectal cancers, as part of prospective RTOG trials.« less

Change in health care use after coordinated care planning: a quasi-experimental study.

PubMed

Bielska, Iwona A; Cimek, Kelly; Guenter, Dale; O'Halloran, Kelly; Nyitray, Chloe; Hunter, Linda; Wodchis, Walter P

2018-05-31

We sought to determine whether patients with a coordinated care plan developed using the Health Links model of care in the Hamilton Niagara Haldimand Brant Local Health Integration Network differed in their use of health care (no. of emergency department visits, inpatient admissions, length of inpatient stay) when compared with a matched control group of patients with no care plans. We performed a propensity score-matched study of 12 months pre- and 12 months post-health care use. Patients who had a coordinated care plan that started between 2013 and 2015 were propensity score matched to patients in a control group. Patient information was obtained from Client Health and Related Information System, National Ambulatory Care Reporting System and Discharge Abstract Database. Differences in health care use pre- and post-index date were compared using the Wilcoxon signed-rank test. A negative binomial regression model was fit for each health care use outcome at 6 and 12 months post-index date. Six hundred coordinated care plan enrollees and 25 449 potential control patients were included in the matching algorithm, which resulted in 548 matched pairs (91.3%). Both groups showed decreases in health care use post-index date. Matched care plan enrollees had significantly fewer emergency department visits at 6 (incidence rate ratio [IRR] 0.81, 95% confidence interval [CI] 0.72-0.91, p < 0.01) and 12 months post-index date (IRR 0.88, 95% CI 0.79-0.99, p < 0.05) compared with the matched controls. Other use parameters were not significantly different between care plan enrollees and the control group. Care plan enrollees show a decrease in the number of times they visit emergency departments, which may be attributed to integrated and coordinated care planning. This association should be examined to see whether these reductions persist for more than 1 year. Copyright 2018, Joule Inc. or its licensors.

A self-management approach using self-initiated action plans for symptoms with ongoing nurse support in patients with Chronic Obstructive Pulmonary Disease (COPD) and comorbidities: the COPE-III study protocol.

PubMed

Lenferink, Anke; Frith, Peter; van der Valk, Paul; Buckman, Julie; Sladek, Ruth; Cafarella, Paul; van der Palen, Job; Effing, Tanja

2013-09-01

Chronic Obstructive Pulmonary Disease (COPD) frequently coexists with other diseases. Whereas COPD action plans are currently part of usual care, they are less suitable and potentially unsafe for use in the presence of comorbidities. This study evaluates whether an innovative treatment approach directed towards COPD and frequently existing comorbidities can reduce COPD exacerbation days. We hypothesise that this approach, which combines self-initiated action plans and nurse support, will accelerate proper treatment actions and lead to better control of deteriorating symptoms. In this multicenter randomised controlled trial we aim to include 300 patients with COPD (GOLD II-IV), and with at least one comorbidity (cardiovascular disease, diabetes, anxiety and/or depression). Patients will be recruited from hospitals in the Netherlands (n = 150) and Australia (n = 150) and will be assigned to an intervention or control group. All patients will learn to complete daily symptom diaries for 12-months. Intervention group patients will participate in self-management training sessions to learn the use of individualised action plans for COPD and comorbidities, linked to the diary. The primary outcome is the number of COPD exacerbation days. Secondary outcomes include hospitalisations, quality of life, self-efficacy, adherence, patient's satisfaction and confidence, health care use and cost data. Intention-to-treat analyses (random effect negative binomial regression and random effect mixed models) and cost-effectiveness analyses will be performed. Prudence should be employed before extrapolating the use of COPD specific action plans in patients with comorbidities. This study evaluates the efficacy of tailored action plans for both COPD and common comorbidities. Copyright © 2013 Elsevier Inc. All rights reserved.

Analysis of railroad tank car releases using a generalized binomial model.

PubMed

Liu, Xiang; Hong, Yili

2015-11-01

The United States is experiencing an unprecedented boom in shale oil production, leading to a dramatic growth in petroleum crude oil traffic by rail. In 2014, U.S. railroads carried over 500,000 tank carloads of petroleum crude oil, up from 9500 in 2008 (a 5300% increase). In light of continual growth in crude oil by rail, there is an urgent national need to manage this emerging risk. This need has been underscored in the wake of several recent crude oil release incidents. In contrast to highway transport, which usually involves a tank trailer, a crude oil train can carry a large number of tank cars, having the potential for a large, multiple-tank-car release incident. Previous studies exclusively assumed that railroad tank car releases in the same train accident are mutually independent, thereby estimating the number of tank cars releasing given the total number of tank cars derailed based on a binomial model. This paper specifically accounts for dependent tank car releases within a train accident. We estimate the number of tank cars releasing given the number of tank cars derailed based on a generalized binomial model. The generalized binomial model provides a significantly better description for the empirical tank car accident data through our numerical case study. This research aims to provide a new methodology and new insights regarding the further development of risk management strategies for improving railroad crude oil transportation safety. Copyright © 2015 Elsevier Ltd. All rights reserved.

Solar San Diego: The Impact of Binomial Rate Structures on Real PV-Systems

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

Van Geet, O.; Brown, E.; Blair, T.

2008-01-01

There is confusion in the marketplace regarding the impact of solar photovoltaics (PV) on the user's actual electricity bill under California Net Energy Metering, particularly with binomial tariffs (those that include both demand and energy charges) and time-of-use (TOU) rate structures. The City of San Diego has extensive real-time electrical metering on most of its buildings and PV systems, with interval data for overall consumption and PV electrical production available for multiple years. This paper uses 2007 PV-system data from two city facilities to illustrate the impacts of binomial rate designs. The analysis will determine the energy and demand savingsmore » that the PV systems are achieving relative to the absence of systems. A financial analysis of PV-system performance under various rates structures is presented. The data revealed that actual demand and energy use benefits of bionomial tariffs increase in summer months, when solar resources allow for maximized electricity production. In a binomial tariff system, varying on- and semi-peak times can result in approximately $1,100 change in demand charges per month over not having a PV system in place, an approximate 30% cost savings. The PV systems are also shown to have a 30%-50% reduction in facility energy charges in 2007. Future work will include combining demand and electricity charges and increasing the breadth of rate structures tested, including the impacts of non-coincident demand charges.« less

Analysis of multiple tank car releases in train accidents.

PubMed

Liu, Xiang; Liu, Chang; Hong, Yili

2017-10-01

There are annually over two million carloads of hazardous materials transported by rail in the United States. The American railroads use large blocks of tank cars to transport petroleum crude oil and other flammable liquids from production to consumption sites. Being different from roadway transport of hazardous materials, a train accident can potentially result in the derailment and release of multiple tank cars, which may result in significant consequences. The prior literature predominantly assumes that the occurrence of multiple tank car releases in a train accident is a series of independent Bernoulli processes, and thus uses the binomial distribution to estimate the total number of tank car releases given the number of tank cars derailing or damaged. This paper shows that the traditional binomial model can incorrectly estimate multiple tank car release probability by magnitudes in certain circumstances, thereby significantly affecting railroad safety and risk analysis. To bridge this knowledge gap, this paper proposes a novel, alternative Correlated Binomial (CB) model that accounts for the possible correlations of multiple tank car releases in the same train. We test three distinct correlation structures in the CB model, and find that they all outperform the conventional binomial model based on empirical tank car accident data. The analysis shows that considering tank car release correlations would result in a significantly improved fit of the empirical data than otherwise. Consequently, it is prudent to consider alternative modeling techniques when analyzing the probability of multiple tank car releases in railroad accidents. Copyright © 2017 Elsevier Ltd. All rights reserved.

Are autism spectrum conditions more prevalent in an information-technology region? A school-based study of three regions in the Netherlands.

PubMed

Roelfsema, Martine T; Hoekstra, Rosa A; Allison, Carrie; Wheelwright, Sally; Brayne, Carol; Matthews, Fiona E; Baron-Cohen, Simon

2012-05-01

We tested for differences in the prevalence of autism spectrum conditions (ASC) in school-aged children in three geographical regions in the Netherlands. Schools were asked to provide the number of children enrolled, the number having a clinical diagnosis of ASC and/or two control neurodevelopmental conditions. Prevalence was evaluated by negative binomial regression and adjustments were made for non-response and size of the schools. The prevalence estimates of ASC in Eindhoven was 229 per 10,000, significantly higher than in Haarlem (84 per 10,000) and Utrecht (57 per 10,000), whilst the prevalence for the control conditions were similar in all regions. Phase two is planned to validate school-reported cases using standardized diagnostic methods and to explore the possible causes for these differences.

Late winter survival of female mallards in Arkansas

USGS Publications Warehouse

Dugger, B.D.; Reinecke, K.J.; Fredrickson, L.H.

1994-01-01

Determining factors that limit winter survival of waterfowl is necessary to develop effective management plans. We radiomarked immature and adult female mallards (Anas platyrhynchos) after the 1988 and 1989 hunting seasons in eastcentral Arkansas to test whether natural mortality sources and habitat conditions during late winter limit seasonal survival. We used data from 92 females to calculate survival estimates. We observed no mortalities during 2,510 exposure days, despite differences in habitat conditions between years. We used the binomial distribution to calculate daily and 30-day survival estimates plus 95% confidence intervals of 0.9988 ltoreq 0.9997 ltoreq 1.00 and 0.9648 ltoreq 0.9925 ltoreq 1.00, respectively. Our data indirectly support the hypothesis that hunting mortality and habitat conditions during the hunting season are the major determinants of winter survival for female mallards in Arkansas.

Probing the statistics of primordial fluctuations and their evolution

NASA Technical Reports Server (NTRS)

Gaztanaga, Enrique; Yokoyama, Jun'ichi

1993-01-01

The statistical distribution of fluctuations on various scales is analyzed in terms of the counts in cells of smoothed density fields, using volume-limited samples of galaxy redshift catalogs. It is shown that the distribution on large scales, with volume average of the two-point correlation function of the smoothed field less than about 0.05, is consistent with Gaussian. Statistics are shown to agree remarkably well with the negative binomial distribution, which has hierarchial correlations and a Gaussian behavior at large scales. If these observed properties correspond to the matter distribution, they suggest that our universe started with Gaussian fluctuations and evolved keeping hierarchial form.

Definite Integrals, Some Involving Residue Theory Evaluated by Maple Code

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

Bowman, Kimiko o

2010-01-01

The calculus of residue is applied to evaluate certain integrals in the range (-{infinity} to {infinity}) using the Maple symbolic code. These integrals are of the form {integral}{sub -{infinity}}{sup {infinity}} cos(x)/[(x{sup 2} + a{sup 2})(x{sup 2} + b{sup 2}) (x{sup 2} + c{sup 2})]dx and similar extensions. The Maple code is also applied to expressions in maximum likelihood estimator moments when sampling from the negative binomial distribution. In general the Maple code approach to the integrals gives correct answers to specified decimal places, but the symbolic result may be extremely long and complex.

Association between early childhood caries and maternal caries status: A cross-section study in São Luís, Maranhão, Brazil

PubMed Central

de Souza, Pedrita Mara do Espírito Santo; Mello Proença, Mariana Almeida; Franco, Mayra Moura; Rodrigues, Vandilson Pinheiro; Costa, José Ferreira; Costa, Elizabeth Lima

2015-01-01

Objective: This study aims to evaluate the association between early childhood caries (ECC) and maternal caries status, and the maternal perception of ECC risk factors. Materials and Methods: A cross-sectional study was carried out with 77 mother-child pairs, the children ranging from 12 to 36 months of age and their mothers, who were seeking dental care at a health center in São Luís, Maranhão, Brazil. Data collection was conducted using a specific questionnaire for mothers. Oral clinical examination of the mother-child binomial to assess caries incidence, gingival bleeding (GB) and visible plaque was done. Home visits were performed in 10% of the sample in order to observe the environmental conditions, dietary habits and dental hygiene practices. Results: The findings showed that the caries prevalence in children was 22.5 times higher in the mother who had decayed tooth (prevalence ratio [PR] = 22.5, confidence interval [CI] 95% = 3.2–156.6, P < 0.001). GB also was observed in 14 mothers and children, the PR in pair was 12.2 (CI95% = 1.6–88.9, P < 0.001). The variables are related for the mother-child binomial in regression linear analysis. Conclusion: The maternal caries status was associated with ECC. PMID:25713495

Binomial probability distribution model-based protein identification algorithm for tandem mass spectrometry utilizing peak intensity information.

PubMed

Xiao, Chuan-Le; Chen, Xiao-Zhou; Du, Yang-Li; Sun, Xuesong; Zhang, Gong; He, Qing-Yu

2013-01-04

Mass spectrometry has become one of the most important technologies in proteomic analysis. Tandem mass spectrometry (LC-MS/MS) is a major tool for the analysis of peptide mixtures from protein samples. The key step of MS data processing is the identification of peptides from experimental spectra by searching public sequence databases. Although a number of algorithms to identify peptides from MS/MS data have been already proposed, e.g. Sequest, OMSSA, X!Tandem, Mascot, etc., they are mainly based on statistical models considering only peak-matches between experimental and theoretical spectra, but not peak intensity information. Moreover, different algorithms gave different results from the same MS data, implying their probable incompleteness and questionable reproducibility. We developed a novel peptide identification algorithm, ProVerB, based on a binomial probability distribution model of protein tandem mass spectrometry combined with a new scoring function, making full use of peak intensity information and, thus, enhancing the ability of identification. Compared with Mascot, Sequest, and SQID, ProVerB identified significantly more peptides from LC-MS/MS data sets than the current algorithms at 1% False Discovery Rate (FDR) and provided more confident peptide identifications. ProVerB is also compatible with various platforms and experimental data sets, showing its robustness and versatility. The open-source program ProVerB is available at http://bioinformatics.jnu.edu.cn/software/proverb/ .

nbCNV: a multi-constrained optimization model for discovering copy number variants in single-cell sequencing data.

PubMed

Zhang, Changsheng; Cai, Hongmin; Huang, Jingying; Song, Yan

2016-09-17

Variations in DNA copy number have an important contribution to the development of several diseases, including autism, schizophrenia and cancer. Single-cell sequencing technology allows the dissection of genomic heterogeneity at the single-cell level, thereby providing important evolutionary information about cancer cells. In contrast to traditional bulk sequencing, single-cell sequencing requires the amplification of the whole genome of a single cell to accumulate enough samples for sequencing. However, the amplification process inevitably introduces amplification bias, resulting in an over-dispersing portion of the sequencing data. Recent study has manifested that the over-dispersed portion of the single-cell sequencing data could be well modelled by negative binomial distributions. We developed a read-depth based method, nbCNV to detect the copy number variants (CNVs). The nbCNV method uses two constraints-sparsity and smoothness to fit the CNV patterns under the assumption that the read signals are negatively binomially distributed. The problem of CNV detection was formulated as a quadratic optimization problem, and was solved by an efficient numerical solution based on the classical alternating direction minimization method. Extensive experiments to compare nbCNV with existing benchmark models were conducted on both simulated data and empirical single-cell sequencing data. The results of those experiments demonstrate that nbCNV achieves superior performance and high robustness for the detection of CNVs in single-cell sequencing data.

Improving removal-based estimates of abundance by sampling a population of spatially distinct subpopulations

USGS Publications Warehouse

Dorazio, R.M.; Jelks, H.L.; Jordan, F.

2005-01-01

 A statistical modeling framework is described for estimating the abundances of spatially distinct subpopulations of animals surveyed using removal sampling. To illustrate this framework, hierarchical models are developed using the Poisson and negative-binomial distributions to model variation in abundance among subpopulations and using the beta distribution to model variation in capture probabilities. These models are fitted to the removal counts observed in a survey of a federally endangered fish species. The resulting estimates of abundance have similar or better precision than those computed using the conventional approach of analyzing the removal counts of each subpopulation separately. Extension of the hierarchical models to include spatial covariates of abundance is straightforward and may be used to identify important features of an animal's habitat or to predict the abundance of animals at unsampled locations.

A binomial stochastic kinetic approach to the Michaelis-Menten mechanism

NASA Astrophysics Data System (ADS)

Lente, Gábor

2013-05-01

This Letter presents a new method that gives an analytical approximation of the exact solution of the stochastic Michaelis-Menten mechanism without computationally demanding matrix operations. The method is based on solving the deterministic rate equations and then using the results as guiding variables of calculating probability values using binomial distributions. This principle can be generalized to a number of different kinetic schemes and is expected to be very useful in the evaluation of measurements focusing on the catalytic activity of one or a few individual enzyme molecules.

Taxonomy of the order Mononegavirales: update 2017.

PubMed

Amarasinghe, Gaya K; Bào, Yīmíng; Basler, Christopher F; Bavari, Sina; Beer, Martin; Bejerman, Nicolás; Blasdell, Kim R; Bochnowski, Alisa; Briese, Thomas; Bukreyev, Alexander; Calisher, Charles H; Chandran, Kartik; Collins, Peter L; Dietzgen, Ralf G; Dolnik, Olga; Dürrwald, Ralf; Dye, John M; Easton, Andrew J; Ebihara, Hideki; Fang, Qi; Formenty, Pierre; Fouchier, Ron A M; Ghedin, Elodie; Harding, Robert M; Hewson, Roger; Higgins, Colleen M; Hong, Jian; Horie, Masayuki; James, Anthony P; Jiāng, Dàohóng; Kobinger, Gary P; Kondo, Hideki; Kurath, Gael; Lamb, Robert A; Lee, Benhur; Leroy, Eric M; Li, Ming; Maisner, Andrea; Mühlberger, Elke; Netesov, Sergey V; Nowotny, Norbert; Patterson, Jean L; Payne, Susan L; Paweska, Janusz T; Pearson, Michael N; Randall, Rick E; Revill, Peter A; Rima, Bertus K; Rota, Paul; Rubbenstroth, Dennis; Schwemmle, Martin; Smither, Sophie J; Song, Qisheng; Stone, David M; Takada, Ayato; Terregino, Calogero; Tesh, Robert B; Tomonaga, Keizo; Tordo, Noël; Towner, Jonathan S; Vasilakis, Nikos; Volchkov, Viktor E; Wahl-Jensen, Victoria; Walker, Peter J; Wang, Beibei; Wang, David; Wang, Fei; Wang, Lin-Fa; Werren, John H; Whitfield, Anna E; Yan, Zhichao; Ye, Gongyin; Kuhn, Jens H

2017-08-01

In 2017, the order Mononegavirales was expanded by the inclusion of a total of 69 novel species. Five new rhabdovirus genera and one new nyamivirus genus were established to harbor 41 of these species, whereas the remaining new species were assigned to already established genera. Furthermore, non-Latinized binomial species names replaced all paramyxovirus and pneumovirus species names, thereby accomplishing application of binomial species names throughout the entire order. This article presents the updated taxonomy of the order Mononegavirales as now accepted by the International Committee on Taxonomy of Viruses (ICTV).

Categorical Data Analysis Using a Skewed Weibull Regression Model

NASA Astrophysics Data System (ADS)

Caron, Renault; Sinha, Debajyoti; Dey, Dipak; Polpo, Adriano

2018-03-01

In this paper, we present a Weibull link (skewed) model for categorical response data arising from binomial as well as multinomial model. We show that, for such types of categorical data, the most commonly used models (logit, probit and complementary log-log) can be obtained as limiting cases. We further compare the proposed model with some other asymmetrical models. The Bayesian as well as frequentist estimation procedures for binomial and multinomial data responses are presented in details. The analysis of two data sets to show the efficiency of the proposed model is performed.

Sleep Disruption Medical Intervention Forecasting (SDMIF) Module for the Integrated Medical Model

NASA Technical Reports Server (NTRS)

Lewandowski, Beth; Brooker, John; Mallis, Melissa; Hursh, Steve; Caldwell, Lynn; Myers, Jerry

2011-01-01

The NASA Integrated Medical Model (IMM) assesses the risk, including likelihood and impact of occurrence, of all credible in-flight medical conditions. Fatigue due to sleep disruption is a condition that could lead to operational errors, potentially resulting in loss of mission or crew. Pharmacological consumables are mitigation strategies used to manage the risks associated with sleep deficits. The likelihood of medical intervention due to sleep disruption was estimated with a well validated sleep model and a Monte Carlo computer simulation in an effort to optimize the quantity of consumables. METHODS: The key components of the model are the mission parameter program, the calculation of sleep intensity and the diagnosis and decision module. The mission parameter program was used to create simulated daily sleep/wake schedules for an ISS increment. The hypothetical schedules included critical events such as dockings and extravehicular activities and included actual sleep time and sleep quality. The schedules were used as inputs to the Sleep, Activity, Fatigue and Task Effectiveness (SAFTE) Model (IBR Inc., Baltimore MD), which calculated sleep intensity. Sleep data from an ISS study was used to relate calculated sleep intensity to the probability of sleep medication use, using a generalized linear model for binomial regression. A human yes/no decision process using a binomial random number was also factored into sleep medication use probability. RESULTS: These probability calculations were repeated 5000 times resulting in an estimate of the most likely amount of sleep aids used during an ISS mission and a 95% confidence interval. CONCLUSIONS: These results were transferred to the parent IMM for further weighting and integration with other medical conditions, to help inform operational decisions. This model is a potential planning tool for ensuring adequate sleep during sleep disrupted periods of a mission.

Buprenorphine Treatment and Patient Use of Health Services after the Affordable Care Act in an Integrated Health Care System

PubMed Central

Campbell, Cynthia I.; Parthasarathy, Sujaya; Young-Wolff, Kelly C.; Satre, Derek D.

2017-01-01

Introduction The Affordable Care Act (ACA) was expected to benefit patients with substance use disorders, including opioid use disorders (OUDs). This study examined buprenorphine use and health services utilization by patients with OUDs pre- and post-ACA in a large health care system. Methods Using electronic health record data, we examined demographic and clinical characteristics (substance use, psychiatric and medical conditions) of two patient cohorts using buprenorphine: those newly enrolled in 2012 (“pre-ACA”, N=204) and in 2014 (“post-ACA”, N=258). Logistic and negative binomial regressions were used to model persistent buprenorphine use, and to examine whether persistent use was related to health services utilization. Results Buprenorphine patients were largely similar pre- and post-ACA, although more post-ACA patients had a marijuana use disorder (p<.01). Post-ACA patients were more likely to have high deductible benefit plans (p<.01). Use of psychiatry services was lower post-ACA (IRR: 0.56, p<.01), and high deductible plans were also related to lower use of psychiatry services (IRR: 0.30, p<.01). Conclusion The relationship between marijuana use disorder and prescription opioid use is complex, and deserves further study, particularly with increasingly widespread marijuana legalization. Access to psychiatry services may be more challenging for buprenorphine patients post-ACA, especially for patients with deductible plans. PMID:28426332

Using beta binomials to estimate classification uncertainty for ensemble models.

PubMed

Clark, Robert D; Liang, Wenkel; Lee, Adam C; Lawless, Michael S; Fraczkiewicz, Robert; Waldman, Marvin

2014-01-01

Quantitative structure-activity (QSAR) models have enormous potential for reducing drug discovery and development costs as well as the need for animal testing. Great strides have been made in estimating their overall reliability, but to fully realize that potential, researchers and regulators need to know how confident they can be in individual predictions. Submodels in an ensemble model which have been trained on different subsets of a shared training pool represent multiple samples of the model space, and the degree of agreement among them contains information on the reliability of ensemble predictions. For artificial neural network ensembles (ANNEs) using two different methods for determining ensemble classification - one using vote tallies and the other averaging individual network outputs - we have found that the distribution of predictions across positive vote tallies can be reasonably well-modeled as a beta binomial distribution, as can the distribution of errors. Together, these two distributions can be used to estimate the probability that a given predictive classification will be in error. Large data sets comprised of logP, Ames mutagenicity, and CYP2D6 inhibition data are used to illustrate and validate the method. The distributions of predictions and errors for the training pool accurately predicted the distribution of predictions and errors for large external validation sets, even when the number of positive and negative examples in the training pool were not balanced. Moreover, the likelihood of a given compound being prospectively misclassified as a function of the degree of consensus between networks in the ensemble could in most cases be estimated accurately from the fitted beta binomial distributions for the training pool. Confidence in an individual predictive classification by an ensemble model can be accurately assessed by examining the distributions of predictions and errors as a function of the degree of agreement among the constituent submodels. Further, ensemble uncertainty estimation can often be improved by adjusting the voting or classification threshold based on the parameters of the error distribution. Finally, the profiles for models whose predictive uncertainty estimates are not reliable provide clues to that effect without the need for comparison to an external test set.

Fitting statistical distributions to sea duck count data: implications for survey design and abundance estimation

USGS Publications Warehouse

Zipkin, Elise F.; Leirness, Jeffery B.; Kinlan, Brian P.; O'Connell, Allan F.; Silverman, Emily D.

2014-01-01

Determining appropriate statistical distributions for modeling animal count data is important for accurate estimation of abundance, distribution, and trends. In the case of sea ducks along the U.S. Atlantic coast, managers want to estimate local and regional abundance to detect and track population declines, to define areas of high and low use, and to predict the impact of future habitat change on populations. In this paper, we used a modified marked point process to model survey data that recorded flock sizes of Common eiders, Long-tailed ducks, and Black, Surf, and White-winged scoters. The data come from an experimental aerial survey, conducted by the United States Fish & Wildlife Service (USFWS) Division of Migratory Bird Management, during which east-west transects were flown along the Atlantic Coast from Maine to Florida during the winters of 2009–2011. To model the number of flocks per transect (the points), we compared the fit of four statistical distributions (zero-inflated Poisson, zero-inflated geometric, zero-inflated negative binomial and negative binomial) to data on the number of species-specific sea duck flocks that were recorded for each transect flown. To model the flock sizes (the marks), we compared the fit of flock size data for each species to seven statistical distributions: positive Poisson, positive negative binomial, positive geometric, logarithmic, discretized lognormal, zeta and Yule–Simon. Akaike’s Information Criterion and Vuong’s closeness tests indicated that the negative binomial and discretized lognormal were the best distributions for all species for the points and marks, respectively. These findings have important implications for estimating sea duck abundances as the discretized lognormal is a more skewed distribution than the Poisson and negative binomial, which are frequently used to model avian counts; the lognormal is also less heavy-tailed than the power law distributions (e.g., zeta and Yule–Simon), which are becoming increasingly popular for group size modeling. Choosing appropriate statistical distributions for modeling flock size data is fundamental to accurately estimating population summaries, determining required survey effort, and assessing and propagating uncertainty through decision-making processes.

Selecting the right statistical model for analysis of insect count data by using information theoretic measures.

PubMed

Sileshi, G

2006-10-01

Researchers and regulatory agencies often make statistical inferences from insect count data using modelling approaches that assume homogeneous variance. Such models do not allow for formal appraisal of variability which in its different forms is the subject of interest in ecology. Therefore, the objectives of this paper were to (i) compare models suitable for handling variance heterogeneity and (ii) select optimal models to ensure valid statistical inferences from insect count data. The log-normal, standard Poisson, Poisson corrected for overdispersion, zero-inflated Poisson, the negative binomial distribution and zero-inflated negative binomial models were compared using six count datasets on foliage-dwelling insects and five families of soil-dwelling insects. Akaike's and Schwarz Bayesian information criteria were used for comparing the various models. Over 50% of the counts were zeros even in locally abundant species such as Ootheca bennigseni Weise, Mesoplatys ochroptera Stål and Diaecoderus spp. The Poisson model after correction for overdispersion and the standard negative binomial distribution model provided better description of the probability distribution of seven out of the 11 insects than the log-normal, standard Poisson, zero-inflated Poisson or zero-inflated negative binomial models. It is concluded that excess zeros and variance heterogeneity are common data phenomena in insect counts. If not properly modelled, these properties can invalidate the normal distribution assumptions resulting in biased estimation of ecological effects and jeopardizing the integrity of the scientific inferences. Therefore, it is recommended that statistical models appropriate for handling these data properties be selected using objective criteria to ensure efficient statistical inference.

Golay Complementary Waveforms in Reed–Müller Sequences for Radar Detection of Nonzero Doppler Targets

PubMed Central

Wang, Xuezhi; Huang, Xiaotao; Suvorova, Sofia; Moran, Bill

2018-01-01

Golay complementary waveforms can, in theory, yield radar returns of high range resolution with essentially zero sidelobes. In practice, when deployed conventionally, while high signal-to-noise ratios can be achieved for static target detection, significant range sidelobes are generated by target returns of nonzero Doppler causing unreliable detection. We consider signal processing techniques using Golay complementary waveforms to improve radar detection performance in scenarios involving multiple nonzero Doppler targets. A signal processing procedure based on an existing, so called, Binomial Design algorithm that alters the transmission order of Golay complementary waveforms and weights the returns is proposed in an attempt to achieve an enhanced illumination performance. The procedure applies one of three proposed waveform transmission ordering algorithms, followed by a pointwise nonlinear processor combining the outputs of the Binomial Design algorithm and one of the ordering algorithms. The computational complexity of the Binomial Design algorithm and the three ordering algorithms are compared, and a statistical analysis of the performance of the pointwise nonlinear processing is given. Estimation of the areas in the Delay–Doppler map occupied by significant range sidelobes for given targets are also discussed. Numerical simulations for the comparison of the performances of the Binomial Design algorithm and the three ordering algorithms are presented for both fixed and randomized target locations. The simulation results demonstrate that the proposed signal processing procedure has a better detection performance in terms of lower sidelobes and higher Doppler resolution in the presence of multiple nonzero Doppler targets compared to existing methods. PMID:29324708

Some considerations for excess zeroes in substance abuse research.

PubMed

Bandyopadhyay, Dipankar; DeSantis, Stacia M; Korte, Jeffrey E; Brady, Kathleen T

2011-09-01

Count data collected in substance abuse research often come with an excess of "zeroes," which are typically handled using zero-inflated regression models. However, there is a need to consider the design aspects of those studies before using such a statistical model to ascertain the sources of zeroes. We sought to illustrate hurdle models as alternatives to zero-inflated models to validate a two-stage decision-making process in situations of "excess zeroes." We use data from a study of 45 cocaine-dependent subjects where the primary scientific question was to evaluate whether study participation influences drug-seeking behavior. The outcome, "the frequency (count) of cocaine use days per week," is bounded (ranging from 0 to 7). We fit and compare binomial, Poisson, negative binomial, and the hurdle version of these models to study the effect of gender, age, time, and study participation on cocaine use. The hurdle binomial model provides the best fit. Gender and time are not predictive of use. Higher odds of use versus no use are associated with age; however once use is experienced, odds of further use decrease with increase in age. Participation was associated with higher odds of no-cocaine use; once there is use, participation reduced the odds of further use. Age and study participation are significantly predictive of cocaine-use behavior. The two-stage decision process as modeled by a hurdle binomial model (appropriate for bounded count data with excess zeroes) provides interesting insights into the study of covariate effects on count responses of substance use, when all enrolled subjects are believed to be "at-risk" of use.

Metaprop: a Stata command to perform meta-analysis of binomial data.

PubMed

Nyaga, Victoria N; Arbyn, Marc; Aerts, Marc

2014-01-01

Meta-analyses have become an essential tool in synthesizing evidence on clinical and epidemiological questions derived from a multitude of similar studies assessing the particular issue. Appropriate and accessible statistical software is needed to produce the summary statistic of interest. Metaprop is a statistical program implemented to perform meta-analyses of proportions in Stata. It builds further on the existing Stata procedure metan which is typically used to pool effects (risk ratios, odds ratios, differences of risks or means) but which is also used to pool proportions. Metaprop implements procedures which are specific to binomial data and allows computation of exact binomial and score test-based confidence intervals. It provides appropriate methods for dealing with proportions close to or at the margins where the normal approximation procedures often break down, by use of the binomial distribution to model the within-study variability or by allowing Freeman-Tukey double arcsine transformation to stabilize the variances. Metaprop was applied on two published meta-analyses: 1) prevalence of HPV-infection in women with a Pap smear showing ASC-US; 2) cure rate after treatment for cervical precancer using cold coagulation. The first meta-analysis showed a pooled HPV-prevalence of 43% (95% CI: 38%-48%). In the second meta-analysis, the pooled percentage of cured women was 94% (95% CI: 86%-97%). By using metaprop, no studies with 0% or 100% proportions were excluded from the meta-analysis. Furthermore, study specific and pooled confidence intervals always were within admissible values, contrary to the original publication, where metan was used.

CAN'T MISS--conquer any number task by making important statistics simple. Part 1. Types of variables, mean, median, variance, and standard deviation.

PubMed

Hansen, John P

2003-01-01

Healthcare quality improvement professionals need to understand and use inferential statistics to interpret sample data from their organizations. In quality improvement and healthcare research studies all the data from a population often are not available, so investigators take samples and make inferences about the population by using inferential statistics. This three-part series will give readers an understanding of the concepts of inferential statistics as well as the specific tools for calculating confidence intervals for samples of data. This article, Part 1, presents basic information about data including a classification system that describes the four major types of variables: continuous quantitative variable, discrete quantitative variable, ordinal categorical variable (including the binomial variable), and nominal categorical variable. A histogram is a graph that displays the frequency distribution for a continuous variable. The article also demonstrates how to calculate the mean, median, standard deviation, and variance for a continuous variable.

Distribution pattern of public transport passenger in Yogyakarta, Indonesia

NASA Astrophysics Data System (ADS)

Narendra, Alfa; Malkhamah, Siti; Sopha, Bertha Maya

2018-03-01

The arrival and departure distribution pattern of Trans Jogja bus passenger is one of the fundamental model for simulation. The purpose of this paper is to build models of passengers flows. This research used passengers data from January to May 2014. There is no policy that change the operation system affecting the nature of this pattern nowadays. The roads, buses, land uses, schedule, and people are relatively still the same. The data then categorized based on the direction, days, and location. Moreover, each category was fitted into some well-known discrete distributions. Those distributions are compared based on its AIC value and BIC. The chosen distribution model has the smallest AIC and BIC value and the negative binomial distribution found has the smallest AIC and BIC value. Probability mass function (PMF) plots of those models were compared to draw generic model from each categorical negative binomial distribution models. The value of accepted generic negative binomial distribution is 0.7064 and 1.4504 of mu. The minimum and maximum passenger vector value of distribution are is 0 and 41.

Temporal acceleration of spatially distributed kinetic Monte Carlo simulations

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

Chatterjee, Abhijit; Vlachos, Dionisios G.

The computational intensity of kinetic Monte Carlo (KMC) simulation is a major impediment in simulating large length and time scales. In recent work, an approximate method for KMC simulation of spatially uniform systems, termed the binomial {tau}-leap method, was introduced [A. Chatterjee, D.G. Vlachos, M.A. Katsoulakis, Binomial distribution based {tau}-leap accelerated stochastic simulation, J. Chem. Phys. 122 (2005) 024112], where molecular bundles instead of individual processes are executed over coarse-grained time increments. This temporal coarse-graining can lead to significant computational savings but its generalization to spatially lattice KMC simulation has not been realized yet. Here we extend the binomial {tau}-leapmore » method to lattice KMC simulations by combining it with spatially adaptive coarse-graining. Absolute stability and computational speed-up analyses for spatial systems along with simulations provide insights into the conditions where accuracy and substantial acceleration of the new spatio-temporal coarse-graining method are ensured. Model systems demonstrate that the r-time increment criterion of Chatterjee et al. obeys the absolute stability limit for values of r up to near 1.« less

Modeling number of claims and prediction of total claim amount

NASA Astrophysics Data System (ADS)

Acar, Aslıhan Şentürk; Karabey, Uǧur

2017-07-01

In this study we focus on annual number of claims of a private health insurance data set which belongs to a local insurance company in Turkey. In addition to Poisson model and negative binomial model, zero-inflated Poisson model and zero-inflated negative binomial model are used to model the number of claims in order to take into account excess zeros. To investigate the impact of different distributional assumptions for the number of claims on the prediction of total claim amount, predictive performances of candidate models are compared by using root mean square error (RMSE) and mean absolute error (MAE) criteria.

Binomial tree method for pricing a regime-switching volatility stock loans

NASA Astrophysics Data System (ADS)

Putri, Endah R. M.; Zamani, Muhammad S.; Utomo, Daryono B.

2018-03-01

Binomial model with regime switching may represents the price of stock loan which follows the stochastic process. Stock loan is one of alternative that appeal investors to get the liquidity without selling the stock. The stock loan mechanism resembles that of American call option when someone can exercise any time during the contract period. From the resembles both of mechanism, determination price of stock loan can be interpreted from the model of American call option. The simulation result shows the behavior of the price of stock loan under a regime-switching with respect to various interest rate and maturity.

Umbral Calculus and Holonomic Modules in Positive Characteristic

NASA Astrophysics Data System (ADS)

Kochubei, Anatoly N.

2006-03-01

In the framework of analysis over local fields of positive characteristic, we develop algebraic tools for introducing and investigating various polynomial systems. In this survey paper we describe a function field version of umbral calculus developed on the basis of a relation of binomial type satisfied by the Carlitz polynomials. We consider modules over the Weyl-Carlitz ring, a function field counterpart of the Weyl algebra. It is shown that some basic objects of function field arithmetic, like the Carlitz module, Thakur's hypergeometric polynomials, and analogs of binomial coefficients arising in the positive characteristic version of umbral calculus, generate holonomic modules.

Modelling parasite aggregation: disentangling statistical and ecological approaches.

PubMed

Yakob, Laith; Soares Magalhães, Ricardo J; Gray, Darren J; Milinovich, Gabriel; Wardrop, Nicola; Dunning, Rebecca; Barendregt, Jan; Bieri, Franziska; Williams, Gail M; Clements, Archie C A

2014-05-01

The overdispersion in macroparasite infection intensity among host populations is commonly simulated using a constant negative binomial aggregation parameter. We describe an alternative to utilising the negative binomial approach and demonstrate important disparities in intervention efficacy projections that can come about from opting for pattern-fitting models that are not process-explicit. We present model output in the context of the epidemiology and control of soil-transmitted helminths due to the significant public health burden imposed by these parasites, but our methods are applicable to other infections with demonstrable aggregation in parasite numbers among hosts. Copyright © 2014. Published by Elsevier Ltd.

FluBreaks: early epidemic detection from Google flu trends.

PubMed

Pervaiz, Fahad; Pervaiz, Mansoor; Abdur Rehman, Nabeel; Saif, Umar

2012-10-04

The Google Flu Trends service was launched in 2008 to track changes in the volume of online search queries related to flu-like symptoms. Over the last few years, the trend data produced by this service has shown a consistent relationship with the actual number of flu reports collected by the US Centers for Disease Control and Prevention (CDC), often identifying increases in flu cases weeks in advance of CDC records. However, contrary to popular belief, Google Flu Trends is not an early epidemic detection system. Instead, it is designed as a baseline indicator of the trend, or changes, in the number of disease cases. To evaluate whether these trends can be used as a basis for an early warning system for epidemics. We present the first detailed algorithmic analysis of how Google Flu Trends can be used as a basis for building a fully automated system for early warning of epidemics in advance of methods used by the CDC. Based on our work, we present a novel early epidemic detection system, called FluBreaks (dritte.org/flubreaks), based on Google Flu Trends data. We compared the accuracy and practicality of three types of algorithms: normal distribution algorithms, Poisson distribution algorithms, and negative binomial distribution algorithms. We explored the relative merits of these methods, and related our findings to changes in Internet penetration and population size for the regions in Google Flu Trends providing data. Across our performance metrics of percentage true-positives (RTP), percentage false-positives (RFP), percentage overlap (OT), and percentage early alarms (EA), Poisson- and negative binomial-based algorithms performed better in all except RFP. Poisson-based algorithms had average values of 99%, 28%, 71%, and 76% for RTP, RFP, OT, and EA, respectively, whereas negative binomial-based algorithms had average values of 97.8%, 17.8%, 60%, and 55% for RTP, RFP, OT, and EA, respectively. Moreover, the EA was also affected by the region's population size. Regions with larger populations (regions 4 and 6) had higher values of EA than region 10 (which had the smallest population) for negative binomial- and Poisson-based algorithms. The difference was 12.5% and 13.5% on average in negative binomial- and Poisson-based algorithms, respectively. We present the first detailed comparative analysis of popular early epidemic detection algorithms on Google Flu Trends data. We note that realizing this opportunity requires moving beyond the cumulative sum and historical limits method-based normal distribution approaches, traditionally employed by the CDC, to negative binomial- and Poisson-based algorithms to deal with potentially noisy search query data from regions with varying population and Internet penetrations. Based on our work, we have developed FluBreaks, an early warning system for flu epidemics using Google Flu Trends.

Investigation of a supplementary tool to assist in the prioritization of emphasis areas in North American strategic highway safety plans.

PubMed

Park, Peter Y; Young, Jason

2012-03-01

An important potential benefit of a jurisdiction developing an upper-level traffic safety policy statement, such as a strategic highway safety plan (SHSP) or a traffic safety action plan, is the creation of a manageable number of focus areas, known as emphasis areas. The responsible agencies in the jurisdiction can then direct their finite resources in a systematic and strategic way designed to maximize the effort to reduce the number and severity of roadway collisions. In the United States, the federal government through AASHTO has suggested 22 potential emphasis areas. In Canada, CCMTA's 10 potential emphasis areas have been listed for consideration. This study reviewed the SHSP and traffic safety action plan of 53 jurisdictions in North America, and conducted descriptive data analyses to clarify the issues that currently affect the selection and prioritization process of jurisdiction-specific emphasis areas. We found that the current process relies heavily on high-level collision data analysis and communication among the SHSP stakeholders, but may not be the most efficient and effective way of selecting and prioritizing the emphasis areas and allocating safety improvement resources. This study then formulated a formal collision diagnosis test, known as the beta-binomial test, to clarify and illuminate the selection and the prioritization of jurisdiction-specific emphasis areas. We developed numerical examples to demonstrate how engineers can apply the proposed diagnosis test to improve the selection and prioritization of individual jurisdictions' emphasis areas. Copyright © 2011 Elsevier Ltd. All rights reserved.

Assessment of DSM-5 Section II Personality Disorders With the MMPI-2-RF in a Nonclinical Sample.

PubMed

Sellbom, Martin; Smith, Alexander

2017-01-01

The Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF; Ben-Porath & Tellegen, 2008 / 2011 ) is frequently used in clinical practice. However, there has been a dearth of literature on how well this instrument can assess symptoms associated with personality disorders (PDs). This investigation examined a range of hypothesized MMPI-2-RF scales in predicting PD symptoms. We evaluated these associations in a sample of 397 university students who had been administered the MMPI-2-RF and the Structured Clinical Interview for DSM-IV Axis II Disorders-Personality Questionnaire (First, Gibbon, Spitzer, Williams, & Benjamin, 1997 ). Zero-order correlation analyses and negative binomial regression models indicated that a wide range of MMPI-2-RF scale hypotheses were supported; however, the least support was available for predicting schizoid and obsessive-compulsive PDs. Implications for MMPI-2-RF interpretation and PD diagnosis are discussed.

[Parenting styles and their relationship with hyperactivity].

PubMed

Raya Trenas, Antonio Félix; Herreruzo Cabrera, Javier; Pino Osuna, María José

2008-11-01

The present study aims to determine the relationship among factors that make up the parenting styles according to the PCRI (Parent-Child Relationship Inventory) and hyperactivity reported by parents through the BASC (Behaviour Assessment System for Children). We selected a sample of 32 children between 3 and 14 years old (23 male and 9 female) with risk scores in hyperactivity and another similar group with low scores in hyperactivity. After administering both instruments to the parents, we carried out a binomial logistic regression analysis which resulted in a prediction model for 84.4% of the sample, made up of the PCRI factors: fathers' involvement, communication and role orientation, mothers' parental support, and both parents' limit-setting and autonomy. Moreover, our analysis of the variance produced significant differences in the support perceived by the fathers and mothers of both groups. Lastly, the utility of results to propose intervention strategies within the family based on an authoritative style is discussed.

Gastrointestinal parasite egg excretion in young calves in periurban livestock production in Mali.

PubMed

Wymann, Monica Natalie; Traore, Koniba; Bonfoh, Bassirou; Tembely, Saïdou; Tembely, Sékouba; Zinsstag, Jakob

2008-04-01

To acquire the information needed to improve parasite control in periurban cattle production in Mali, repeated sampling of faeces of 694 calves kept around Bamako was done in 2003/2004. The effects of season, age, breed, management type, parasite control and presence of sheep on egg and oocyst counts were determined. A Bayesian model was used with a negative binomial distribution and herd and individual effects, to account for the clustering of calves in herds and the repeated sampling. Interviews were conducted to report the current control strategies. We found eggs of Strongyloides papillosus (Age class 0-1 month: prevalence 39%, 2-3 months: 59%, 5-6 months: 42%), strongyles (14%, 24%, 36%), coccidian oocysts (37%, 68%, 64%) and at low prevalence eggs of Toxocara vitulorum, Moniezia sp., Trichuris sp. and Paramphistomum sp. Season and age effects occurred. Reported utilisation of parasite control was high (92%) but monthly recorded use was significantly lower (61%).

A Nationwide Study of Discrimination and Chronic Health Conditions Among Asian Americans

PubMed Central

Gee, Gilbert C.; Spencer, Michael S.; Chen, Juan; Takeuchi, David

2007-01-01

Objectives. We examined whether self-reported everyday discrimination was associated with chronic health conditions among a nationally representative sample of Asian Americans. Methods. Data were from the Asian American subsample (n = 2095) of the National Latino and Asian American Study conducted in 2002 and 2003. Regression techniques (negative binomial and logistic) were used to examine the association between discrimination and chronic health conditions. Analyses were conducted for the entire sample and 3 Asian subgroups (Chinese, Vietnamese, and Filipino). Results. Reports of everyday discrimination were associated with many chronic conditions, after we controlled for age, gender, region, per capita income, education, employment, and social desirability bias. Discrimination was also associated with indicators of heart disease, pain, and respiratory illnesses. There were some differences by Asian subgroup. Conclusions. Everyday discrimination may contribute to stress experienced by racial/ethnic minorities and could lead to chronic illness. PMID:17538055

Void probability as a function of the void's shape and scale-invariant models

NASA Technical Reports Server (NTRS)

Elizalde, E.; Gaztanaga, E.

1991-01-01

The dependence of counts in cells on the shape of the cell for the large scale galaxy distribution is studied. A very concrete prediction can be done concerning the void distribution for scale invariant models. The prediction is tested on a sample of the CfA catalog, and good agreement is found. It is observed that the probability of a cell to be occupied is bigger for some elongated cells. A phenomenological scale invariant model for the observed distribution of the counts in cells, an extension of the negative binomial distribution, is presented in order to illustrate how this dependence can be quantitatively determined. An original, intuitive derivation of this model is presented.

Traumatic Brain Injury among US Active Duty Military Personnel and Negative Drinking-Related Consequences

PubMed Central

Adams, Rachel Sayko; Larson, Mary Jo; Corrigan, John D.; Ritter, Grant A.; Williams, Thomas V.

2013-01-01

This study used the 2008 Department of Defense Survey of Health Related Behaviors among Active Duty Military Personnel to determine whether traumatic brain injury (TBI) is associated with past year drinking-related consequences. The study sample included currently-drinking personnel who had a combat deployment in the past year and were home for ≥6 months (N = 3,350). Negative binomial regression models were used to assess the incidence rate ratios of consequences, by TBI-level. Experiencing a TBI with a loss of consciousness >20 minutes was significantly associated with consequences independent of demographics, combat exposure, posttraumatic stress disorder, and binge drinking. The study’s limitations are noted. PMID:23869456

An examination of sources of sensitivity of consumer surplus estimates in travel cost models.

PubMed

Blaine, Thomas W; Lichtkoppler, Frank R; Bader, Timothy J; Hartman, Travis J; Lucente, Joseph E

2015-03-15

We examine sensitivity of estimates of recreation demand using the Travel Cost Method (TCM) to four factors. Three of the four have been routinely and widely discussed in the TCM literature: a) Poisson verses negative binomial regression; b) application of Englin correction to account for endogenous stratification; c) truncation of the data set to eliminate outliers. A fourth issue we address has not been widely modeled: the potential effect on recreation demand of the interaction between income and travel cost. We provide a straightforward comparison of all four factors, analyzing the impact of each on regression parameters and consumer surplus estimates. Truncation has a modest effect on estimates obtained from the Poisson models but a radical effect on the estimates obtained by way of the negative binomial. Inclusion of an income-travel cost interaction term generally produces a more conservative but not a statistically significantly different estimate of consumer surplus in both Poisson and negative binomial models. It also generates broader confidence intervals. Application of truncation, the Englin correction and the income-travel cost interaction produced the most conservative estimates of consumer surplus and eliminated the statistical difference between the Poisson and the negative binomial. Use of the income-travel cost interaction term reveals that for visitors who face relatively low travel costs, the relationship between income and travel demand is negative, while it is positive for those who face high travel costs. This provides an explanation of the ambiguities on the findings regarding the role of income widely observed in the TCM literature. Our results suggest that policies that reduce access to publicly owned resources inordinately impact local low income recreationists and are contrary to environmental justice. Copyright © 2014 Elsevier Ltd. All rights reserved.

A big data approach to the development of mixed-effects models for seizure count data.

PubMed

Tharayil, Joseph J; Chiang, Sharon; Moss, Robert; Stern, John M; Theodore, William H; Goldenholz, Daniel M

2017-05-01

Our objective was to develop a generalized linear mixed model for predicting seizure count that is useful in the design and analysis of clinical trials. This model also may benefit the design and interpretation of seizure-recording paradigms. Most existing seizure count models do not include children, and there is currently no consensus regarding the most suitable model that can be applied to children and adults. Therefore, an additional objective was to develop a model that accounts for both adult and pediatric epilepsy. Using data from SeizureTracker.com, a patient-reported seizure diary tool with >1.2 million recorded seizures across 8 years, we evaluated the appropriateness of Poisson, negative binomial, zero-inflated negative binomial, and modified negative binomial models for seizure count data based on minimization of the Bayesian information criterion. Generalized linear mixed-effects models were used to account for demographic and etiologic covariates and for autocorrelation structure. Holdout cross-validation was used to evaluate predictive accuracy in simulating seizure frequencies. For both adults and children, we found that a negative binomial model with autocorrelation over 1 day was optimal. Using holdout cross-validation, the proposed model was found to provide accurate simulation of seizure counts for patients with up to four seizures per day. The optimal model can be used to generate more realistic simulated patient data with very few input parameters. The availability of a parsimonious, realistic virtual patient model can be of great utility in simulations of phase II/III clinical trials, epilepsy monitoring units, outpatient biosensors, and mobile Health (mHealth) applications. Wiley Periodicals, Inc. © 2017 International League Against Epilepsy.

Impact of formal training on agreement of videofluoroscopic swallowing study interpretation across and within disciplines.

PubMed

Silbergleit, Alice K; Cook, Diana; Kienzle, Scott; Boettcher, Erica; Myers, Daniel; Collins, Denise; Peterson, Edward; Silbergleit, Matthew A; Silbergleit, Richard

2018-04-04

Formal agreement studies on interpretation of the videofluoroscopic swallowing study (VFSS) procedure among speech-language pathologists, radiology house officers, and staff radiologists have not been pursued. Each of these professions participates in the procedure, interprets the examination, and writes separate reports on the findings. The aim of this study was to determine reliability of interpretation between and within the disciplines and to determine if structured training improved reliability. Thirteen speech-language pathologists (SLPs), ten diagnostic radiologists (RADs) and twenty-one diagnostic radiology house officers (HOs) participated in this study. Each group viewed 24 VFSS samples and rated the presence or absence of seven aberrant swallowing features as well as the presence of dysphagia and identification of oral dysphagia, pharyngeal dysphagia, or both. During part two, the groups were provided with a training session on normal and abnormal swallowing, using different VFSS samples from those in part one, followed by re-rating of the original 24 VFSS samples. A generalized estimating equations (GEE) approach with a binomial link function was used to examine each question separately. For each cluster of tests, as example, all pairwise comparisons between the three groups in the pretraining period, a Hochberg's correction for multiple testing was used to determine significance. A GEE approach with a binomial link function was used to compare the premeasure to postmeasure for each of the three groups of raters stratified by experience. The primary result revealed that the HO group scored significantly lower than the SLP and RAD group on identification of the presence of dysphagia (p = 0.008; p = 0.001, respectively), identification of oral phase dysphagia (p = 0.003; p = 0.001, respectively), and identification of both oral and pharyngeal phase dysphagia, (p = 0.014, p = 0.001, respectively) pretraining. Post training there was no statistically significant difference between the three groups on identification of dysphagia and identification of combined oral and pharyngeal dysphagia. Formal training to identify oropharyngeal dysphagia characteristics appears to improve accuracy of interpretation of the VFSS procedure for radiology house officers. Consideration to include formal training in this area for radiology residency training programs is recommended.

A fast least-squares algorithm for population inference

PubMed Central

2013-01-01

Background Population inference is an important problem in genetics used to remove population stratification in genome-wide association studies and to detect migration patterns or shared ancestry. An individual’s genotype can be modeled as a probabilistic function of ancestral population memberships, Q, and the allele frequencies in those populations, P. The parameters, P and Q, of this binomial likelihood model can be inferred using slow sampling methods such as Markov Chain Monte Carlo methods or faster gradient based approaches such as sequential quadratic programming. This paper proposes a least-squares simplification of the binomial likelihood model motivated by a Euclidean interpretation of the genotype feature space. This results in a faster algorithm that easily incorporates the degree of admixture within the sample of individuals and improves estimates without requiring trial-and-error tuning. Results We show that the expected value of the least-squares solution across all possible genotype datasets is equal to the true solution when part of the problem has been solved, and that the variance of the solution approaches zero as its size increases. The Least-squares algorithm performs nearly as well as Admixture for these theoretical scenarios. We compare least-squares, Admixture, and FRAPPE for a variety of problem sizes and difficulties. For particularly hard problems with a large number of populations, small number of samples, or greater degree of admixture, least-squares performs better than the other methods. On simulated mixtures of real population allele frequencies from the HapMap project, Admixture estimates sparsely mixed individuals better than Least-squares. The least-squares approach, however, performs within 1.5% of the Admixture error. On individual genotypes from the HapMap project, Admixture and least-squares perform qualitatively similarly and within 1.2% of each other. Significantly, the least-squares approach nearly always converges 1.5- to 6-times faster. Conclusions The computational advantage of the least-squares approach along with its good estimation performance warrants further research, especially for very large datasets. As problem sizes increase, the difference in estimation performance between all algorithms decreases. In addition, when prior information is known, the least-squares approach easily incorporates the expected degree of admixture to improve the estimate. PMID:23343408

A fast least-squares algorithm for population inference.

PubMed

Parry, R Mitchell; Wang, May D

2013-01-23

Population inference is an important problem in genetics used to remove population stratification in genome-wide association studies and to detect migration patterns or shared ancestry. An individual's genotype can be modeled as a probabilistic function of ancestral population memberships, Q, and the allele frequencies in those populations, P. The parameters, P and Q, of this binomial likelihood model can be inferred using slow sampling methods such as Markov Chain Monte Carlo methods or faster gradient based approaches such as sequential quadratic programming. This paper proposes a least-squares simplification of the binomial likelihood model motivated by a Euclidean interpretation of the genotype feature space. This results in a faster algorithm that easily incorporates the degree of admixture within the sample of individuals and improves estimates without requiring trial-and-error tuning. We show that the expected value of the least-squares solution across all possible genotype datasets is equal to the true solution when part of the problem has been solved, and that the variance of the solution approaches zero as its size increases. The Least-squares algorithm performs nearly as well as Admixture for these theoretical scenarios. We compare least-squares, Admixture, and FRAPPE for a variety of problem sizes and difficulties. For particularly hard problems with a large number of populations, small number of samples, or greater degree of admixture, least-squares performs better than the other methods. On simulated mixtures of real population allele frequencies from the HapMap project, Admixture estimates sparsely mixed individuals better than Least-squares. The least-squares approach, however, performs within 1.5% of the Admixture error. On individual genotypes from the HapMap project, Admixture and least-squares perform qualitatively similarly and within 1.2% of each other. Significantly, the least-squares approach nearly always converges 1.5- to 6-times faster. The computational advantage of the least-squares approach along with its good estimation performance warrants further research, especially for very large datasets. As problem sizes increase, the difference in estimation performance between all algorithms decreases. In addition, when prior information is known, the least-squares approach easily incorporates the expected degree of admixture to improve the estimate.

GENE-Counter: A Computational Pipeline for the Analysis of RNA-Seq Data for Gene Expression Differences

PubMed Central

Di, Yanming; Schafer, Daniel W.; Wilhelm, Larry J.; Fox, Samuel E.; Sullivan, Christopher M.; Curzon, Aron D.; Carrington, James C.; Mockler, Todd C.; Chang, Jeff H.

2011-01-01

GENE-counter is a complete Perl-based computational pipeline for analyzing RNA-Sequencing (RNA-Seq) data for differential gene expression. In addition to its use in studying transcriptomes of eukaryotic model organisms, GENE-counter is applicable for prokaryotes and non-model organisms without an available genome reference sequence. For alignments, GENE-counter is configured for CASHX, Bowtie, and BWA, but an end user can use any Sequence Alignment/Map (SAM)-compliant program of preference. To analyze data for differential gene expression, GENE-counter can be run with any one of three statistics packages that are based on variations of the negative binomial distribution. The default method is a new and simple statistical test we developed based on an over-parameterized version of the negative binomial distribution. GENE-counter also includes three different methods for assessing differentially expressed features for enriched gene ontology (GO) terms. Results are transparent and data are systematically stored in a MySQL relational database to facilitate additional analyses as well as quality assessment. We used next generation sequencing to generate a small-scale RNA-Seq dataset derived from the heavily studied defense response of Arabidopsis thaliana and used GENE-counter to process the data. Collectively, the support from analysis of microarrays as well as the observed and substantial overlap in results from each of the three statistics packages demonstrates that GENE-counter is well suited for handling the unique characteristics of small sample sizes and high variability in gene counts. PMID:21998647

Sampling Error in Relation to Cyst Nematode Population Density Estimation in Small Field Plots.

PubMed

Župunski, Vesna; Jevtić, Radivoje; Jokić, Vesna Spasić; Župunski, Ljubica; Lalošević, Mirjana; Ćirić, Mihajlo; Ćurčić, Živko

2017-06-01

Cyst nematodes are serious plant-parasitic pests which could cause severe yield losses and extensive damage. Since there is still very little information about error of population density estimation in small field plots, this study contributes to the broad issue of population density assessment. It was shown that there was no significant difference between cyst counts of five or seven bulk samples taken per each 1-m 2 plot, if average cyst count per examined plot exceeds 75 cysts per 100 g of soil. Goodness of fit of data to probability distribution tested with χ 2 test confirmed a negative binomial distribution of cyst counts for 21 out of 23 plots. The recommended measure of sampling precision of 17% expressed through coefficient of variation ( cv ) was achieved if the plots of 1 m 2 contaminated with more than 90 cysts per 100 g of soil were sampled with 10-core bulk samples taken in five repetitions. If plots were contaminated with less than 75 cysts per 100 g of soil, 10-core bulk samples taken in seven repetitions gave cv higher than 23%. This study indicates that more attention should be paid on estimation of sampling error in experimental field plots to ensure more reliable estimation of population density of cyst nematodes.

Distributional assumptions in food and feed commodities- development of fit-for-purpose sampling protocols.

PubMed

Paoletti, Claudia; Esbensen, Kim H

2015-01-01

Material heterogeneity influences the effectiveness of sampling procedures. Most sampling guidelines used for assessment of food and/or feed commodities are based on classical statistical distribution requirements, the normal, binomial, and Poisson distributions-and almost universally rely on the assumption of randomness. However, this is unrealistic. The scientific food and feed community recognizes a strong preponderance of non random distribution within commodity lots, which should be a more realistic prerequisite for definition of effective sampling protocols. Nevertheless, these heterogeneity issues are overlooked as the prime focus is often placed only on financial, time, equipment, and personnel constraints instead of mandating acquisition of documented representative samples under realistic heterogeneity conditions. This study shows how the principles promulgated in the Theory of Sampling (TOS) and practically tested over 60 years provide an effective framework for dealing with the complete set of adverse aspects of both compositional and distributional heterogeneity (material sampling errors), as well as with the errors incurred by the sampling process itself. The results of an empirical European Union study on genetically modified soybean heterogeneity, Kernel Lot Distribution Assessment are summarized, as they have a strong bearing on the issue of proper sampling protocol development. TOS principles apply universally in the food and feed realm and must therefore be considered the only basis for development of valid sampling protocols free from distributional constraints.

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

Sigeti, David E.; Pelak, Robert A.

We present a Bayesian statistical methodology for identifying improvement in predictive simulations, including an analysis of the number of (presumably expensive) simulations that will need to be made in order to establish with a given level of confidence that an improvement has been observed. Our analysis assumes the ability to predict (or postdict) the same experiments with legacy and new simulation codes and uses a simple binomial model for the probability, {theta}, that, in an experiment chosen at random, the new code will provide a better prediction than the old. This model makes it possible to do statistical analysis withmore » an absolute minimum of assumptions about the statistics of the quantities involved, at the price of discarding some potentially important information in the data. In particular, the analysis depends only on whether or not the new code predicts better than the old in any given experiment, and not on the magnitude of the improvement. We show how the posterior distribution for {theta} may be used, in a kind of Bayesian hypothesis testing, both to decide if an improvement has been observed and to quantify our confidence in that decision. We quantify the predictive probability that should be assigned, prior to taking any data, to the possibility of achieving a given level of confidence, as a function of sample size. We show how this predictive probability depends on the true value of {theta} and, in particular, how there will always be a region around {theta} = 1/2 where it is highly improbable that we will be able to identify an improvement in predictive capability, although the width of this region will shrink to zero as the sample size goes to infinity. We show how the posterior standard deviation may be used, as a kind of 'plan B metric' in the case that the analysis shows that {theta} is close to 1/2 and argue that such a plan B should generally be part of hypothesis testing. All the analysis presented in the paper is done with a general beta-function prior for {theta}, enabling sequential analysis in which a small number of new simulations may be done and the resulting posterior for {theta} used as a prior to inform the next stage of power analysis.« less

Use of negative binomial distribution to describe the presence of Anisakis in Thyrsites atun.

PubMed

Peña-Rehbein, Patricio; De los Ríos-Escalante, Patricio

2012-01-01

Nematodes of the genus Anisakis have marine fishes as intermediate hosts. One of these hosts is Thyrsites atun, an important fishery resource in Chile between 38 and 41° S. This paper describes the frequency and number of Anisakis nematodes in the internal organs of Thyrsites atun. An analysis based on spatial distribution models showed that the parasites tend to be clustered. The variation in the number of parasites per host could be described by the negative binomial distribution. The maximum observed number of parasites was nine parasites per host. The environmental and zoonotic aspects of the study are also discussed.

Solving the problem of negative populations in approximate accelerated stochastic simulations using the representative reaction approach.

PubMed

Kadam, Shantanu; Vanka, Kumar

2013-02-15

Methods based on the stochastic formulation of chemical kinetics have the potential to accurately reproduce the dynamical behavior of various biochemical systems of interest. However, the computational expense makes them impractical for the study of real systems. Attempts to render these methods practical have led to the development of accelerated methods, where the reaction numbers are modeled by Poisson random numbers. However, for certain systems, such methods give rise to physically unrealistic negative numbers for species populations. The methods which make use of binomial variables, in place of Poisson random numbers, have since become popular, and have been partially successful in addressing this problem. In this manuscript, the development of two new computational methods, based on the representative reaction approach (RRA), has been discussed. The new methods endeavor to solve the problem of negative numbers, by making use of tools like the stochastic simulation algorithm and the binomial method, in conjunction with the RRA. It is found that these newly developed methods perform better than other binomial methods used for stochastic simulations, in resolving the problem of negative populations. Copyright © 2012 Wiley Periodicals, Inc.

Estimating abundance while accounting for rarity, correlated behavior, and other sources of variation in counts

USGS Publications Warehouse

Dorazio, Robert M.; Martin, Juulien; Edwards, Holly H.

2013-01-01

The class of N-mixture models allows abundance to be estimated from repeated, point count surveys while adjusting for imperfect detection of individuals. We developed an extension of N-mixture models to account for two commonly observed phenomena in point count surveys: rarity and lack of independence induced by unmeasurable sources of variation in the detectability of individuals. Rarity increases the number of locations with zero detections in excess of those expected under simple models of abundance (e.g., Poisson or negative binomial). Correlated behavior of individuals and other phenomena, though difficult to measure, increases the variation in detection probabilities among surveys. Our extension of N-mixture models includes a hurdle model of abundance and a beta-binomial model of detectability that accounts for additional (extra-binomial) sources of variation in detections among surveys. As an illustration, we fit this model to repeated point counts of the West Indian manatee, which was observed in a pilot study using aerial surveys. Our extension of N-mixture models provides increased flexibility. The effects of different sets of covariates may be estimated for the probability of occurrence of a species, for its mean abundance at occupied locations, and for its detectability.

Estimating abundance while accounting for rarity, correlated behavior, and other sources of variation in counts.

PubMed

Dorazio, Robert M; Martin, Julien; Edwards, Holly H

2013-07-01

The class of N-mixture models allows abundance to be estimated from repeated, point count surveys while adjusting for imperfect detection of individuals. We developed an extension of N-mixture models to account for two commonly observed phenomena in point count surveys: rarity and lack of independence induced by unmeasurable sources of variation in the detectability of individuals. Rarity increases the number of locations with zero detections in excess of those expected under simple models of abundance (e.g., Poisson or negative binomial). Correlated behavior of individuals and other phenomena, though difficult to measure, increases the variation in detection probabilities among surveys. Our extension of N-mixture models includes a hurdle model of abundance and a beta-binomial model of detectability that accounts for additional (extra-binomial) sources of variation in detections among surveys. As an illustration, we fit this model to repeated point counts of the West Indian manatee, which was observed in a pilot study using aerial surveys. Our extension of N-mixture models provides increased flexibility. The effects of different sets of covariates may be estimated for the probability of occurrence of a species, for its mean abundance at occupied locations, and for its detectability.

Mutational Analysis of the Adaptor Protein 2 Sigma Subunit (AP2S1) Gene: Search for Autosomal Dominant Hypocalcemia Type 3 (ADH3)

PubMed Central

Rogers, Angela; Nesbit, M. Andrew; Hannan, Fadil M.; Howles, Sarah A.; Gorvin, Caroline M.; Cranston, Treena; Allgrove, Jeremy; Bevan, John S.; Bano, Gul; Brain, Caroline; Datta, Vipan; Grossman, Ashley B.; Hodgson, Shirley V.; Izatt, Louise; Millar-Jones, Lynne; Pearce, Simon H.; Robertson, Lisa; Selby, Peter L.; Shine, Brian; Snape, Katie; Warner, Justin

2014-01-01

Context: Autosomal dominant hypocalcemia (ADH) types 1 and 2 are due to calcium-sensing receptor (CASR) and G-protein subunit-α11 (GNA11) gain-of-function mutations, respectively, whereas CASR and GNA11 loss-of-function mutations result in familial hypocalciuric hypercalcemia (FHH) types 1 and 2, respectively. Loss-of-function mutations of adaptor protein-2 sigma subunit (AP2σ 2), encoded by AP2S1, cause FHH3, and we therefore sought for gain-of-function AP2S1 mutations that may cause an additional form of ADH, which we designated ADH3. Objective: The objective of the study was to investigate the hypothesis that gain-of-function AP2S1 mutations may cause ADH3. Design: The sample size required for the detection of at least one mutation with a greater than 95% likelihood was determined by binomial probability analysis. Nineteen patients (including six familial cases) with hypocalcemia in association with low or normal serum PTH concentrations, consistent with ADH, but who did not have CASR or GNA11 mutations, were ascertained. Leukocyte DNA was used for sequence and copy number variation analysis of AP2S1. Results: Binomial probability analysis, using the assumption that AP2S1 mutations would occur in hypocalcemic patients at a prevalence of 20%, which is observed in FHH patients without CASR or GNA11 mutations, indicated that the likelihood of detecting at least one AP2S1 mutation was greater than 95% and greater than 98% in sample sizes of 14 and 19 hypocalcemic patients, respectively. AP2S1 mutations and copy number variations were not detected in the 19 hypocalcemic patients. Conclusion: The absence of AP2S1 abnormalities in hypocalcemic patients, suggests that ADH3 may not occur or otherwise represents a rare hypocalcemic disorder. PMID:24708097

The Predisposing Factors between Dental Caries and Deviations from Normal Weight.

PubMed

Chopra, Amandeep; Rao, Nanak Chand; Gupta, Nidhi; Vashisth, Shelja; Lakhanpal, Manav

2015-04-01

Dental caries and deviations from normal weight are two conditions which share several broadly predisposing factors. So it's important to understand any relationship between dental state and body weight if either is to be managed appropriately. The study was done to find out the correlation between body mass index (BMI), diet, and dental caries among 12-15-year-old schoolgoing children in Panchkula District. A multistage sample of 12-15-year-old school children (n = 810) in Panchkula district, Haryana was considered. Child demographic details and diet history for 5 days was recorded. Data regarding dental caries status was collected using World Health Organization (1997) format. BMI was calculated and categorized according to the World Health Organization classification system for BMI. The data were subjected to statistical analysis using chi-square test and binomial regression developed using the Statistical Package for Social Sciences (SPSS) 20.0. The mean Decayed Missing Filled Teeth (DMFT) score was found to be 1.72 with decayed, missing, and filled teeth to be 1.22, 0.04, and 0.44, respectively. When the sample was assessed based on type of diet, it was found that vegetarians had higher mean DMFT (1.72) as compared to children having mixed diet. Overweight children had highest DMFT (3.21) which was followed by underweight (2.31) and obese children (2.23). Binomial regression revealed that females were 1.293 times at risk of developing caries as compared to males. Fair and poor Simplified-Oral Hygiene Index (OHI-S) showed 3.920 and 4.297 times risk of developing caries as compared to good oral hygiene, respectively. Upper high socioeconomic status (SES) is at most risk of developing caries. Underweight, overweight, and obese are at 2.7, 2.5, and 3 times risk of developing caries as compared to children with normal BMI, respectively. Dental caries and deviations from normal weight are two conditions which share several broadly predisposing factors such as diet, SES, lifestyle and other environmental factors.

7 CFR 43.104 - Master table of single and double sampling plans.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 2 2012-01-01 2012-01-01 false Master table of single and double sampling plans. 43... STANDARD CONTAINER REGULATIONS STANDARDS FOR SAMPLING PLANS Sampling Plans § 43.104 Master table of single and double sampling plans. (a) In the master table, a sampling plan is selected by first determining...

7 CFR 43.104 - Master table of single and double sampling plans.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 2 2013-01-01 2013-01-01 false Master table of single and double sampling plans. 43... STANDARD CONTAINER REGULATIONS STANDARDS FOR SAMPLING PLANS Sampling Plans § 43.104 Master table of single and double sampling plans. (a) In the master table, a sampling plan is selected by first determining...

7 CFR 43.104 - Master table of single and double sampling plans.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 2 2014-01-01 2014-01-01 false Master table of single and double sampling plans. 43... STANDARD CONTAINER REGULATIONS STANDARDS FOR SAMPLING PLANS Sampling Plans § 43.104 Master table of single and double sampling plans. (a) In the master table, a sampling plan is selected by first determining...

7 CFR 43.104 - Master table of single and double sampling plans.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Master table of single and double sampling plans. 43... STANDARD CONTAINER REGULATIONS STANDARDS FOR SAMPLING PLANS Sampling Plans § 43.104 Master table of single and double sampling plans. (a) In the master table, a sampling plan is selected by first determining...

Differential expression analysis for RNAseq using Poisson mixed models

PubMed Central

Sun, Shiquan; Hood, Michelle; Scott, Laura; Peng, Qinke; Mukherjee, Sayan; Tung, Jenny

2017-01-01

Abstract Identifying differentially expressed (DE) genes from RNA sequencing (RNAseq) studies is among the most common analyses in genomics. However, RNAseq DE analysis presents several statistical and computational challenges, including over-dispersed read counts and, in some settings, sample non-independence. Previous count-based methods rely on simple hierarchical Poisson models (e.g. negative binomial) to model independent over-dispersion, but do not account for sample non-independence due to relatedness, population structure and/or hidden confounders. Here, we present a Poisson mixed model with two random effects terms that account for both independent over-dispersion and sample non-independence. We also develop a scalable sampling-based inference algorithm using a latent variable representation of the Poisson distribution. With simulations, we show that our method properly controls for type I error and is generally more powerful than other widely used approaches, except in small samples (n <15) with other unfavorable properties (e.g. small effect sizes). We also apply our method to three real datasets that contain related individuals, population stratification or hidden confounders. Our results show that our method increases power in all three data compared to other approaches, though the power gain is smallest in the smallest sample (n = 6). Our method is implemented in MACAU, freely available at www.xzlab.org/software.html. PMID:28369632

MSeq-CNV: accurate detection of Copy Number Variation from Sequencing of Multiple samples.

PubMed

Malekpour, Seyed Amir; Pezeshk, Hamid; Sadeghi, Mehdi

2018-03-05

Currently a few tools are capable of detecting genome-wide Copy Number Variations (CNVs) based on sequencing of multiple samples. Although aberrations in mate pair insertion sizes provide additional hints for the CNV detection based on multiple samples, the majority of the current tools rely only on the depth of coverage. Here, we propose a new algorithm (MSeq-CNV) which allows detecting common CNVs across multiple samples. MSeq-CNV applies a mixture density for modeling aberrations in depth of coverage and abnormalities in the mate pair insertion sizes. Each component in this mixture density applies a Binomial distribution for modeling the number of mate pairs with aberration in the insertion size and also a Poisson distribution for emitting the read counts, in each genomic position. MSeq-CNV is applied on simulated data and also on real data of six HapMap individuals with high-coverage sequencing, in 1000 Genomes Project. These individuals include a CEU trio of European ancestry and a YRI trio of Nigerian ethnicity. Ancestry of these individuals is studied by clustering the identified CNVs. MSeq-CNV is also applied for detecting CNVs in two samples with low-coverage sequencing in 1000 Genomes Project and six samples form the Simons Genome Diversity Project.

Outpatient Utilization by Infants Auto-assigned to Medicaid Managed Care Plans

PubMed Central

Cohn, Lisa M.; Clark, Sarah J.

2013-01-01

To test the hypothesis that infants auto-assigned to a Medicaid managed care plan would have lower primary care and higher emergency department (ED) utilization compared to infants with a chosen plan. Retrospective cohort study. Medicaid administrative data were used to identify all children 0–3 months of age at enrollment in Michigan Medicaid managed care in 2005–2008 with 18-months of subsequent enrollment. Medicaid encounter and state immunization registry data were then acquired. Auto-assigned infants were compared versus chosen plan infants on: (1) well-child visits (WCVs); (2) immunizations; (3) acute office visits; and (4) ED visits. Chi squared and rank-sum tests and logistic and negative binomial regression were used in bivariate and multivariable analyses for dichotomous and count data, respectively. 18 % of infants were auto-assigned. Auto-assigned infants were less likely to meet goal number of WCVs in 18-months of managed care enrollment (32 vs. 53 %, p < 0.001) and to be up-to-date on immunizations at 12 months of age (75 vs. 85 %, p < 0.001). Auto-assigned infants had fewer acute office visits (median: 4 vs. 5, p < 0.001) but were only slightly more likely to have 2 or more ED visits (51 vs. 46 %, p < 0.001) in 18-months of enrollment. All results were significant in multivariable analyses. Auto-assigned infants were less likely to use preventive and acute primary care but only slightly more likely to use emergency care. Future work is needed to understand mechanisms of differences in utilization, but auto-assigned children may represent a target group for efforts to promote pediatric preventive care in Medicaid. PMID:23775252

Outpatient utilization by infants auto-assigned to Medicaid managed care plans.

PubMed

Zickafoose, Joseph S; Cohn, Lisa M; Clark, Sarah J

2014-04-01

To test the hypothesis that infants auto-assigned to a Medicaid managed care plan would have lower primary care and higher emergency department (ED) utilization compared to infants with a chosen plan. Retrospective cohort study. Medicaid administrative data were used to identify all children 0-3 months of age at enrollment in Michigan Medicaid managed care in 2005-2008 with 18-months of subsequent enrollment. Medicaid encounter and state immunization registry data were then acquired. Auto-assigned infants were compared versus chosen plan infants on: (1) well-child visits (WCVs); (2) immunizations; (3) acute office visits; and (4) ED visits. Chi squared and rank-sum tests and logistic and negative binomial regression were used in bivariate and multivariable analyses for dichotomous and count data, respectively. 18% of infants were auto-assigned. Auto-assigned infants were less likely to meet goal number of WCVs in 18-months of managed care enrollment (32 vs. 53%, p < 0.001) and to be up-to-date on immunizations at 12 months of age (75 vs. 85%, p < 0.001). Auto-assigned infants had fewer acute office visits (median: 4 vs. 5, p < 0.001) but were only slightly more likely to have 2 or more ED visits (51 vs. 46%, p < 0.001) in 18-months of enrollment. All results were significant in multivariable analyses. Auto-assigned infants were less likely to use preventive and acute primary care but only slightly more likely to use emergency care. Future work is needed to understand mechanisms of differences in utilization, but auto-assigned children may represent a target group for efforts to promote pediatric preventive care in Medicaid.

Targeting a high-risk group for fall prevention: strategies for health plans.

PubMed

Jennings, Lee A; Reuben, David B; Kim, Sung-Bou; Keeler, Emmett; Roth, Carol P; Zingmond, David S; Wenger, Neil S; Ganz, David A

2015-09-01

Although Medicare has implemented incentives for health plans to reduce fall risk, the best way to identify older people at high risk of falling and to use screening results to target fall prevention services remains unknown. We evaluated 4 different strategies using a combination of administrative data and patient-reported information that health plans could easily obtain. Observational study. We used data from 1776 patients 75 years or older in 4 community-based primary care practices who screened positive for a fear of falling and/or a history of falls. For these patients, we predicted fall-related injuries in the 24 months after the date of screening using claims/encounter data. After controlling for age and gender, we predicted the number of fall-related injuries by adding Elixhauser comorbidity count, any claim for a fall-related injury during the 12 months prior to screening, and falls screening question responses in a sequential fashion using negative binomial regression models. Basic patient characteristics, including age and Elixhauser comorbidity count, were strong predictors of fall-related injury. Among falls screening questions, a positive response to, "Have you fallen 2 or more times in the past year?" was the most predictive of a fall-related injury (incidence rate ratio [IRR], 1.56; 95% CI, 1.25-1.94). Prior claim for a fall-related injury also independently predicted this type of injury (IRR, 1.41; 95% CI, 1.05-1.89). The best model for predicting fall-related injuries combined all of these approaches. The combination of administrative data and a simple screening item can be used by health plans to target patients at high risk for future fall-related injuries.

The impact of parental and peer social support on dating violence perpetration and victimization among female adolescents: a longitudinal study.

PubMed

Richards, Tara N; Branch, Kathryn A; Ray, Katherine

2014-01-01

Little is known about the role social support may play in reducing the risk of adolescent dating violence perpetration and victimization. This study is a longitudinal analysis of the independent impact of social support from friends and parents on the risk of emotional and physical dating violence perpetration and victimization among a large sample of female youth (n = 346). Findings indicate that 22% of the sample indicated perpetrating physical dating violence against a partner, whereas almost 16% revealed being the victim of physical dating violence; 34% of the sample indicated perpetrating emotional dating violence against a partner, whereas almost 39% revealed being the victim of emotional dating violence. Negative binomial regression models indicated that increased levels of support from friends at Time 1 was associated with significantly less physical and emotional dating violence perpetration and emotional (but not physical) dating violence victimization at Time 2. Parental support was not significantly related to dating violence in any model. Implications for dating violence curriculum and future research are addressed.

Alternative sample sizes for verification dose experiments and dose audits

NASA Astrophysics Data System (ADS)

Taylor, W. A.; Hansen, J. M.

1999-01-01

ISO 11137 (1995), "Sterilization of Health Care Products—Requirements for Validation and Routine Control—Radiation Sterilization", provides sampling plans for performing initial verification dose experiments and quarterly dose audits. Alternative sampling plans are presented which provide equivalent protection. These sampling plans can significantly reduce the cost of testing. These alternative sampling plans have been included in a draft ISO Technical Report (type 2). This paper examines the rational behind the proposed alternative sampling plans. The protection provided by the current verification and audit sampling plans is first examined. Then methods for identifying equivalent plans are highlighted. Finally, methods for comparing the cost associated with the different plans are provided. This paper includes additional guidance for selecting between the original and alternative sampling plans not included in the technical report.

The Association between Romantic Relationships and Delinquency in Adolescence and Young Adulthood

PubMed Central

Cui, Ming; Ueno, Koji; Fincham, Frank D.; Donnellan, M. Brent; Wickrama, K. A. S.

2011-01-01

This study examined the association between romantic relationships and delinquency in adolescence and young adulthood. Using a large, longitudinal, and nationally representative sample, results from negative binomial regressions showed a positive association between romantic involvement and delinquency in adolescence. Further, the cumulative number of romantic relationships from adolescence to young adulthood was positively related to delinquency in young adulthood even controlling for earlier delinquency in adolescence. These analyses also controlled for the effects of participant gender, age at initial assessment, puberty, race/ethnicity, and other demographic characteristics (e.g., family structure and parents’ education). Findings are discussed in terms of their implications for understanding the role of romantic relationships in the development of young people and for stimulating future research questions. PMID:22984343

Void probability as a function of the void's shape and scale-invariant models. [in studies of spacial galactic distribution

NASA Technical Reports Server (NTRS)

Elizalde, E.; Gaztanaga, E.

1992-01-01

The dependence of counts in cells on the shape of the cell for the large scale galaxy distribution is studied. A very concrete prediction can be done concerning the void distribution for scale invariant models. The prediction is tested on a sample of the CfA catalog, and good agreement is found. It is observed that the probability of a cell to be occupied is bigger for some elongated cells. A phenomenological scale invariant model for the observed distribution of the counts in cells, an extension of the negative binomial distribution, is presented in order to illustrate how this dependence can be quantitatively determined. An original, intuitive derivation of this model is presented.

Pollution, Poverty, and Potentially Preventable Childhood Morbidity in Central California.

PubMed

Lessard, Lauren N; Alcala, Emanuel; Capitman, John A

2016-01-01

To measure ecological relationships between neighborhood pollution burden, poverty, race/ethnicity, and pediatric preventable disease hospitalization rates. Preventable disease hospitalization rates were obtained from the 2012 California Office of Statewide Health Planning and Development database, for 8 Central Valley counties. US Census Data was used to incorporate zip code level factors including racial diversity and poverty rates. The pollution burden score was calculated by the California Office of Environmental Health Hazard Assessment using 11 indicators. Poisson-based negative binomial regression was used for final analysis. Stratification of sample by age, race/ethnicity, and insurance coverage was also incorporated. Children experiencing potentially preventable hospitalizations are disproportionately low income and under the age of 4 years. With every unit increase in pollution burden, preventable disease hospitalizations rates increase between 21% and 32%, depending on racial and age subgroups. Although living in a poor neighborhood was not associated with potentially avoidable hospitalizations, children enrolled in Medi-Cal who live in neighborhoods with lower pollution burden and lower levels of poverty, face 32% lower risk for ambulatory care sensitive condition hospitalization. Children living in primary care shortage areas are at increased risk of preventable hospitalizations. Preventable disease hospitalizations increase for all subgroups, except white/non-Hispanic children, as neighborhoods became more racially diverse. Understanding the geographic distribution of disease and impact of individual and community level factors is essential to expanding access to care and preventive resources to improve the health of children in California's most polluted and underserved region. Copyright © 2016 Elsevier Inc. All rights reserved.

Generalization of multifractal theory within quantum calculus

NASA Astrophysics Data System (ADS)

Olemskoi, A.; Shuda, I.; Borisyuk, V.

2010-03-01

On the basis of the deformed series in quantum calculus, we generalize the partition function and the mass exponent of a multifractal, as well as the average of a random variable distributed over a self-similar set. For the partition function, such expansion is shown to be determined by binomial-type combinations of the Tsallis entropies related to manifold deformations, while the mass exponent expansion generalizes the known relation τq=Dq(q-1). We find the equation for the set of averages related to ordinary, escort, and generalized probabilities in terms of the deformed expansion as well. Multifractals related to the Cantor binomial set, exchange currency series, and porous-surface condensates are considered as examples.

Using real options analysis to support strategic management decisions

NASA Astrophysics Data System (ADS)

Kabaivanov, Stanimir; Markovska, Veneta; Milev, Mariyan

2013-12-01

Decision making is a complex process that requires taking into consideration multiple heterogeneous sources of uncertainty. Standard valuation and financial analysis techniques often fail to properly account for all these sources of risk as well as for all sources of additional flexibility. In this paper we explore applications of a modified binomial tree method for real options analysis (ROA) in an effort to improve decision making process. Usual cases of use of real options are analyzed with elaborate study on the applications and advantages that company management can derive from their application. A numeric results based on extending simple binomial tree approach for multiple sources of uncertainty are provided to demonstrate the improvement effects on management decisions.

RnaSeqSampleSize: real data based sample size estimation for RNA sequencing.

PubMed

Zhao, Shilin; Li, Chung-I; Guo, Yan; Sheng, Quanhu; Shyr, Yu

2018-05-30

One of the most important and often neglected components of a successful RNA sequencing (RNA-Seq) experiment is sample size estimation. A few negative binomial model-based methods have been developed to estimate sample size based on the parameters of a single gene. However, thousands of genes are quantified and tested for differential expression simultaneously in RNA-Seq experiments. Thus, additional issues should be carefully addressed, including the false discovery rate for multiple statistic tests, widely distributed read counts and dispersions for different genes. To solve these issues, we developed a sample size and power estimation method named RnaSeqSampleSize, based on the distributions of gene average read counts and dispersions estimated from real RNA-seq data. Datasets from previous, similar experiments such as the Cancer Genome Atlas (TCGA) can be used as a point of reference. Read counts and their dispersions were estimated from the reference's distribution; using that information, we estimated and summarized the power and sample size. RnaSeqSampleSize is implemented in R language and can be installed from Bioconductor website. A user friendly web graphic interface is provided at http://cqs.mc.vanderbilt.edu/shiny/RnaSeqSampleSize/ . RnaSeqSampleSize provides a convenient and powerful way for power and sample size estimation for an RNAseq experiment. It is also equipped with several unique features, including estimation for interested genes or pathway, power curve visualization, and parameter optimization.

Comparison of chain sampling plans with single and double sampling plans

NASA Technical Reports Server (NTRS)

Stephens, K. S.; Dodge, H. F.

1976-01-01

The efficiency of chain sampling is examined through matching of operating characteristics (OC) curves of chain sampling plans (ChSP) with single and double sampling plans. In particular, the operating characteristics of some ChSP-0, 3 and 1, 3 as well as ChSP-0, 4 and 1, 4 are presented, where the number pairs represent the first and the second cumulative acceptance numbers. The fact that the ChSP procedure uses cumulative results from two or more samples and that the parameters can be varied to produce a wide variety of operating characteristics raises the question whether it may be possible for such plans to provide a given protection with less inspection than with single or double sampling plans. The operating ratio values reported illustrate the possibilities of matching single and double sampling plans with ChSP. It is shown that chain sampling plans provide improved efficiency over single and double sampling plans having substantially the same operating characteristics.

P-Hacking in Orthopaedic Literature: A Twist to the Tail.

PubMed

Bin Abd Razak, Hamid Rahmatullah; Ang, Jin-Guang Ernest; Attal, Hersh; Howe, Tet-Sen; Allen, John Carson

2016-10-19

"P-hacking" occurs when researchers preferentially select data or statistical analyses until nonsignificant results become significant. We wanted to evaluate if the phenomenon of p-hacking was evident in orthopaedic literature. We text-mined through all articles published in three top orthopaedic journals in 2015. For anonymity, we cipher-coded the three journals. We included all studies that reported a single p value to answer their main hypothesis. These p values were then charted and frequency graphs were generated to illustrate any evidence of p-hacking. Binomial tests were employed to look for evidence of evidential value and significance of p-hacking. Frequency plots for all three journals revealed evidence of p-hacking. Binomial tests for all three journals were significant for evidence of evidential value (p < 0.0001 for all). However, the binomial test for p-hacking was significant only for one journal (p = 0.0092). P-hacking is an evolving phenomenon that threatens to jeopardize the evidence-based practice of medicine. Although our results show that there is good evidential value for orthopaedic literature published in our top journals, there is some evidence of p-hacking of which authors and readers should be wary. Copyright © 2016 by The Journal of Bone and Joint Surgery, Incorporated.

The analysis of incontinence episodes and other count data in patients with overactive bladder by Poisson and negative binomial regression.

PubMed

Martina, R; Kay, R; van Maanen, R; Ridder, A

2015-01-01

Clinical studies in overactive bladder have traditionally used analysis of covariance or nonparametric methods to analyse the number of incontinence episodes and other count data. It is known that if the underlying distributional assumptions of a particular parametric method do not hold, an alternative parametric method may be more efficient than a nonparametric one, which makes no assumptions regarding the underlying distribution of the data. Therefore, there are advantages in using methods based on the Poisson distribution or extensions of that method, which incorporate specific features that provide a modelling framework for count data. One challenge with count data is overdispersion, but methods are available that can account for this through the introduction of random effect terms in the modelling, and it is this modelling framework that leads to the negative binomial distribution. These models can also provide clinicians with a clearer and more appropriate interpretation of treatment effects in terms of rate ratios. In this paper, the previously used parametric and non-parametric approaches are contrasted with those based on Poisson regression and various extensions in trials evaluating solifenacin and mirabegron in patients with overactive bladder. In these applications, negative binomial models are seen to fit the data well. Copyright © 2014 John Wiley & Sons, Ltd.

Statistical tests to compare motif count exceptionalities

PubMed Central

Robin, Stéphane; Schbath, Sophie; Vandewalle, Vincent

2007-01-01

Background Finding over- or under-represented motifs in biological sequences is now a common task in genomics. Thanks to p-value calculation for motif counts, exceptional motifs are identified and represent candidate functional motifs. The present work addresses the related question of comparing the exceptionality of one motif in two different sequences. Just comparing the motif count p-values in each sequence is indeed not sufficient to decide if this motif is significantly more exceptional in one sequence compared to the other one. A statistical test is required. Results We develop and analyze two statistical tests, an exact binomial one and an asymptotic likelihood ratio test, to decide whether the exceptionality of a given motif is equivalent or significantly different in two sequences of interest. For that purpose, motif occurrences are modeled by Poisson processes, with a special care for overlapping motifs. Both tests can take the sequence compositions into account. As an illustration, we compare the octamer exceptionalities in the Escherichia coli K-12 backbone versus variable strain-specific loops. Conclusion The exact binomial test is particularly adapted for small counts. For large counts, we advise to use the likelihood ratio test which is asymptotic but strongly correlated with the exact binomial test and very simple to use. PMID:17346349

Interrelationships Between Receiver/Relative Operating Characteristics Display, Binomial, Logit, and Bayes' Rule Probability of Detection Methodologies

NASA Technical Reports Server (NTRS)

Generazio, Edward R.

2014-01-01

Unknown risks are introduced into failure critical systems when probability of detection (POD) capabilities are accepted without a complete understanding of the statistical method applied and the interpretation of the statistical results. The presence of this risk in the nondestructive evaluation (NDE) community is revealed in common statements about POD. These statements are often interpreted in a variety of ways and therefore, the very existence of the statements identifies the need for a more comprehensive understanding of POD methodologies. Statistical methodologies have data requirements to be met, procedures to be followed, and requirements for validation or demonstration of adequacy of the POD estimates. Risks are further enhanced due to the wide range of statistical methodologies used for determining the POD capability. Receiver/Relative Operating Characteristics (ROC) Display, simple binomial, logistic regression, and Bayes' rule POD methodologies are widely used in determining POD capability. This work focuses on Hit-Miss data to reveal the framework of the interrelationships between Receiver/Relative Operating Characteristics Display, simple binomial, logistic regression, and Bayes' Rule methodologies as they are applied to POD. Knowledge of these interrelationships leads to an intuitive and global understanding of the statistical data, procedural and validation requirements for establishing credible POD estimates.

Impact of cigarette smoking on utilization of nursing home services.

PubMed

Warner, Kenneth E; McCammon, Ryan J; Fries, Brant E; Langa, Kenneth M

2013-11-01

Few studies have examined the effects of smoking on nursing home utilization, generally using poor data on smoking status. No previous study has distinguished utilization for recent from long-term quitters. Using the Health and Retirement Study, we assessed nursing home utilization by never-smokers, long-term quitters (quit >3 years), recent quitters (quit ≤3 years), and current smokers. We used logistic regression to evaluate the likelihood of a nursing home admission. For those with an admission, we used negative binomial regression on the number of nursing home nights. Finally, we employed zero-inflated negative binomial regression to estimate nights for the full sample. Controlling for other variables, compared with never-smokers, long-term quitters have an odds ratio (OR) for nursing home admission of 1.18 (95% CI: 1.07-1.2), current smokers 1.39 (1.23-1.57), and recent quitters 1.55 (1.29-1.87). The probability of admission rises rapidly with age and is lower for African Americans and Hispanics, more affluent respondents, respondents with a spouse present in the home, and respondents with a living child. Given admission, smoking status is not associated with length of stay (LOS). LOS is longer for older respondents and women and shorter for more affluent respondents and those with spouses present. Compared with otherwise identical never-smokers, former and current smokers have a significantly increased risk of nursing home admission. That recent quitters are at greatest risk of admission is consistent with evidence that many stop smoking because they are sick, often due to smoking.

Dental Caries and Enamel Defects in Very Low Birth Weight Adolescents

PubMed Central

Nelson, S.; Albert, J.M.; Lombardi, G.; Wishnek, S.; Asaad, G.; Kirchner, H.L.; Singer, L.T.

2011-01-01

Objectives The purpose of this study was to examine developmental enamel defects and dental caries in very low birth weight adolescents with high risk (HR-VLBW) and low risk (LR-VLBW) compared to full-term (term) adolescents. Methods The sample consisted of 224 subjects (80 HR-VLBW, 59 LR-VLBW, 85 term adolescents) recruited from an ongoing longitudinal study. Sociodemographic and medical information was available from birth. Dental examination of the adolescent at the 14-year visit included: enamel defects (opacity and hypoplasia); decayed, missing, filled teeth of incisors and molars (DMFT-IM) and of overall permanent teeth (DMFT); Simplified Oral Hygiene Index for debris/calculus on teeth, and sealant presence. A caregiver questionnaire completed simultaneously assessed dental behavior, access, insurance status and prevention factors. Hierarchical analysis utilized the zero-inflated negative binomial model and zero-inflated Poisson model. Results The zero-inflated negative binomial model controlling for sociodemographic variables indicated that the LR-VLBW group had an estimated 75% increase (p < 0.05) in number of demarcated opacities in the incisors and first molar teeth compared to the term group. Hierarchical modeling indicated that demarcated opacities were a significant predictor of DMFT-IM after control for relevant covariates. The term adolescents had significantly increased DMFT-IM and DMFT scores compared to the LR-VLBW adolescents. Conclusion LR-VLBW was a significant risk factor for increased enamel defects in the permanent incisors and first molars. Term children had increased caries compared to the LR-VLBW group. The effect of birth group and enamel defects on caries has to be investigated longitudinally from birth. PMID:20975268

Hopelessness as a Predictor of Suicide Ideation in Depressed Male and Female Adolescent Youth.

PubMed

Wolfe, Kristin L; Nakonezny, Paul A; Owen, Victoria J; Rial, Katherine V; Moorehead, Alexandra P; Kennard, Beth D; Emslie, Graham J

2017-12-21

We examined hopelessness as a predictor of suicide ideation in depressed youth after acute medication treatment. A total of 158 depressed adolescents were administered the Children's Depression Rating Scale-Revised (CDRS-R) and Columbia Suicide Severity Rating Scale (C-SSRS) as part of a larger battery at baseline and at weekly visits across 6 weeks of acute fluoxetine treatment. The Beck Hopelessness Scale (BHS) was administered at baseline and week 6. A negative binomial regression model via a generalized estimating equation analysis of repeated measures was used to estimate suicide ideation over the 6 weeks of acute treatment from baseline measure of hopelessness. Depression severity and gender were included as covariates in the model. The negative binomial analysis was also conducted separately for the sample of males and females (in a gender-stratified analysis). Mean CDRS-R total scores were 60.30 ± 8.93 at baseline and 34.65 ± 10.41 at week 6. Mean baseline and week 6 BHS scores were 9.57 ± 5.51 and 5.59 ± 5.38, respectively. Per the C-SSRS, 43.04% and 83.54% reported having no suicide ideation at baseline and at week 6, respectively. The analyses revealed that baseline hopelessness was positively related to suicide ideation over treatment (p = .0027), independent of changes in depression severity. This significant finding persisted only for females (p = .0024). These results indicate the importance of early identification of hopelessness. © 2017 The American Association of Suicidology.

Drivers of multidimensional eco-innovation: empirical evidence from the Brazilian industry.

PubMed

da Silva Rabêlo, Olivan; de Azevedo Melo, Andrea Sales Soares

2018-03-08

The study analyses the relationships between the main drivers of eco-innovation introduced by innovative industries, focused on cooperation strategy. Eco-innovation is analysed by means of a multidimensional identification strategy, showing the relationships between the independent variables and the variable of interest. The literature discussing environmental innovation is different from the one discussing other types of innovation inasmuch as it seeks to grasp its determinants and to mostly highlight the relevance of environmental regulation. The key feature of this paper is that it ascribes special relevance to cooperation strategy with external partners and to the propensity of innovative industry introducing eco-innovation. A sample of 35,060 Brazilian industries were analysed, between 2003 and 2011, by means of Binomial, Multinomial and Ordinal logistic regressions with microdata collected with the research and innovation department (PINTEC) from the Brazilian Institute of Geography and Statistics (Instituto Brasileiro de Geografia e Estatística). The econometric results estimated by the Logit Multinomial method suggest that the cooperation with external partners practiced by innovative industries facilitates the adoption of eco-innovation in dimension 01 with probability of 64.59%, 57.63% in dimension 02 and 81.02% in dimension 03. The data reveal that the higher the degree of eco-innovation complexity, the harder industries seek to obtain cooperation with external partners. When calculating with the Logit Ordinal and Binomial models, cooperation increases the probability that the industry is eco-innovative in 65.09% and 89.34%, respectively. Environmental regulation and innovation in product and information management were also positively correlated as drivers of eco-innovation.

Impact of early childhood caries on oral health-related quality of life of preschool children.

PubMed

Li, M Y; Zhi, Q H; Zhou, Y; Qiu, R M; Lin, H C

2015-03-01

Child oral health-related quality of life (COHRQoL) has been assessed in developed areas; however, it remains unstudied in mainland China. Studies on COHRQoL would benefit a large number of children in China suffering from oral health problems such as dental caries. This study explored the relationship between COHRQoL and early childhood caries, adjusted by socioeconomic factors, in 3- to 4-year-old children in a region of southern China. In this study, 1062 children aged 3-4 years were recruited by cluster sampling and their oral health statuses were examined by a trained dentist. The Chinese version of the Early Childhood Oral Health Impact Scale (ECOHIS) and questions about the children's socioeconomic conditions were completed by the children's parents. A negative binomial regression analysis was used to assess the prevalence of early childhood caries among the children and its influence on COHRQoL. The total ECOHIS scores of the returned scale sets ranged from 0 to 31, and their average scores was 3.1±5.1. The negative binomial analysis showed that the dmfs indices were significantly associated with the ECOHIS score and subscale scores (P<0.05). The multivariate adjusted model showed that a higher dmft index was associated with greater negative impact on COHRQoL (RR = 1.10; 95% CI = 1.07, 1.13; P < 0.05). However, demographic and socioeconomic factors were not associated with COHRQoL (P>0.05). The severity of early childhood caries has a negative impact on the oral health-related quality of life of preschool children and their parents.

Estimating the effectiveness of further sampling in species inventories

USGS Publications Warehouse

Keating, K.A.; Quinn, J.F.; Ivie, M.A.; Ivie, L.L.

1998-01-01

Estimators of the number of additional species expected in the next ??n samples offer a potentially important tool for improving cost-effectiveness of species inventories but are largely untested. We used Monte Carlo methods to compare 11 such estimators, across a range of community structures and sampling regimes, and validated our results, where possible, using empirical data from vascular plant and beetle inventories from Glacier National Park, Montana, USA. We found that B. Efron and R. Thisted's 1976 negative binomial estimator was most robust to differences in community structure and that it was among the most accurate estimators when sampling was from model communities with structures resembling the large, heterogeneous communities that are the likely targets of major inventory efforts. Other estimators may be preferred under specific conditions, however. For example, when sampling was from model communities with highly even species-abundance distributions, estimates based on the Michaelis-Menten model were most accurate; when sampling was from moderately even model communities with S=10 species or communities with highly uneven species-abundance distributions, estimates based on Gleason's (1922) species-area model were most accurate. We suggest that use of such methods in species inventories can help improve cost-effectiveness by providing an objective basis for redirecting sampling to more-productive sites, methods, or time periods as the expectation of detecting additional species becomes unacceptably low.

Sampling Outdoor, Resting Anopheles gambiae and Other Mosquitoes (Diptera: Culicidae) in Western Kenya with Clay Pots

PubMed Central

Odiere, M.; Bayoh, M. N.; Gimnig, J.; Vulule, J.; Irungu, L.; Walker, E.

2014-01-01

Clay pots were analyzed as devices for sampling the outdoor resting fraction of Anopheles gambiae Giles (Diptera: Culicidae) and other mosquito species in a rural, western Kenya. Clay pots (Anopheles gambiae resting pots, herein AgREPOTs), outdoor pit shelters, indoor pyrethrum spray collections (PSC), and Colombian curtain exit traps were compared in collections done biweekly for nine intervals from April to June 2005 in 20 housing compounds. Of 10,517 mosquitoes sampled, 4,668 An. gambiae s.l. were sampled in total of which 63% were An. gambiae s.s. (46% female) and 37% were An. arabiensis (66% female). The clay pots were useful and practical for sampling both sexes of An. gambiae s.l. Additionally, 617 An. funestus (58% female) and 5,232 Culex spp. (males and females together) were collected. Temporal changes in abundance of An. gambiae s.l. were similarly revealed by all four sampling methods, indicating that the clay pots could be used as devices to quantify variation in mosquito population density. Dispersion patterns of the different species and sexes fit well the negative binomial distribution, indicating that the mosquitoes were aggregated in distribution. Aside from providing a useful sampling tool, the AgREPOT also may be useful as a delivery vehicle for insecticides or pathogens to males and females that enter and rest in them. PMID:17294916

Univariate and bivariate likelihood-based meta-analysis methods performed comparably when marginal sensitivity and specificity were the targets of inference.

PubMed

Dahabreh, Issa J; Trikalinos, Thomas A; Lau, Joseph; Schmid, Christopher H

2017-03-01

To compare statistical methods for meta-analysis of sensitivity and specificity of medical tests (e.g., diagnostic or screening tests). We constructed a database of PubMed-indexed meta-analyses of test performance from which 2 × 2 tables for each included study could be extracted. We reanalyzed the data using univariate and bivariate random effects models fit with inverse variance and maximum likelihood methods. Analyses were performed using both normal and binomial likelihoods to describe within-study variability. The bivariate model using the binomial likelihood was also fit using a fully Bayesian approach. We use two worked examples-thoracic computerized tomography to detect aortic injury and rapid prescreening of Papanicolaou smears to detect cytological abnormalities-to highlight that different meta-analysis approaches can produce different results. We also present results from reanalysis of 308 meta-analyses of sensitivity and specificity. Models using the normal approximation produced sensitivity and specificity estimates closer to 50% and smaller standard errors compared to models using the binomial likelihood; absolute differences of 5% or greater were observed in 12% and 5% of meta-analyses for sensitivity and specificity, respectively. Results from univariate and bivariate random effects models were similar, regardless of estimation method. Maximum likelihood and Bayesian methods produced almost identical summary estimates under the bivariate model; however, Bayesian analyses indicated greater uncertainty around those estimates. Bivariate models produced imprecise estimates of the between-study correlation of sensitivity and specificity. Differences between methods were larger with increasing proportion of studies that were small or required a continuity correction. The binomial likelihood should be used to model within-study variability. Univariate and bivariate models give similar estimates of the marginal distributions for sensitivity and specificity. Bayesian methods fully quantify uncertainty and their ability to incorporate external evidence may be useful for imprecisely estimated parameters. Copyright © 2017 Elsevier Inc. All rights reserved.

A methodology to design heuristics for model selection based on the characteristics of data: Application to investigate when the Negative Binomial Lindley (NB-L) is preferred over the Negative Binomial (NB).

PubMed

Shirazi, Mohammadali; Dhavala, Soma Sekhar; Lord, Dominique; Geedipally, Srinivas Reddy

2017-10-01

Safety analysts usually use post-modeling methods, such as the Goodness-of-Fit statistics or the Likelihood Ratio Test, to decide between two or more competitive distributions or models. Such metrics require all competitive distributions to be fitted to the data before any comparisons can be accomplished. Given the continuous growth in introducing new statistical distributions, choosing the best one using such post-modeling methods is not a trivial task, in addition to all theoretical or numerical issues the analyst may face during the analysis. Furthermore, and most importantly, these measures or tests do not provide any intuitions into why a specific distribution (or model) is preferred over another (Goodness-of-Logic). This paper ponders into these issues by proposing a methodology to design heuristics for Model Selection based on the characteristics of data, in terms of descriptive summary statistics, before fitting the models. The proposed methodology employs two analytic tools: (1) Monte-Carlo Simulations and (2) Machine Learning Classifiers, to design easy heuristics to predict the label of the 'most-likely-true' distribution for analyzing data. The proposed methodology was applied to investigate when the recently introduced Negative Binomial Lindley (NB-L) distribution is preferred over the Negative Binomial (NB) distribution. Heuristics were designed to select the 'most-likely-true' distribution between these two distributions, given a set of prescribed summary statistics of data. The proposed heuristics were successfully compared against classical tests for several real or observed datasets. Not only they are easy to use and do not need any post-modeling inputs, but also, using these heuristics, the analyst can attain useful information about why the NB-L is preferred over the NB - or vice versa- when modeling data. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Binomial Model in Fluctuation Analysis of Quantal Neurotransmitter Release

PubMed Central

Quastel, D. M. J.

1997-01-01

The mathematics of the binomial model for quantal neurotransmitter release is considered in general terms, to explore what information might be extractable from statistical aspects of data. For an array of N statistically independent release sites, each with a release probability p, the compound binomial always pertains, with = N

, p′ ≡ 1 - var(m)/ =

(1 + cvp2) and n′ ≡ /p′ = N/(1 + cvp2), where m is the output/stimulus and cvp2 is var(p)/

2. Unless n′ is invariant with ambient conditions or stimulation paradigms, the simple binomial (cvp = 0) is untenable and n′ is neither N nor the number of “active” sites or sites with a quantum available. At each site p = popA, where po is the output probability if a site is “eligible” or “filled” despite previous quantal discharge, and pA (eligibility probability) depends at least on the replenishment rate, po, and interstimulus time. Assuming stochastic replenishment, a simple algorithm allows calculation of the full statistical composition of outputs for any hypothetical combinations of po's and refill rates, for any stimulation paradigm and spontaneous release. A rise in n′ (reduced cvp) tends to occur whenever po varies widely between sites, with a raised stimulation frequency or factors tending to increase po's. Unlike and var(m) at equilibrium, output changes early in trains of stimuli, and covariances, potentially provide information about whether changes in reflect change in or in . Formulae are derived for variance and third moments of postsynaptic responses, which depend on the quantal mix in the signals. A new, easily computed function, the area product, gives noise-unbiased variance of a series of synaptic signals and its peristimulus time distribution, which is modified by the unit channel composition of quantal responses and if the signals reflect mixed responses from synapses with different quantal time course. PMID:9017200

Finite-key analysis for quantum key distribution with weak coherent pulses based on Bernoulli sampling

NASA Astrophysics Data System (ADS)

Kawakami, Shun; Sasaki, Toshihiko; Koashi, Masato

2017-07-01

An essential step in quantum key distribution is the estimation of parameters related to the leaked amount of information, which is usually done by sampling of the communication data. When the data size is finite, the final key rate depends on how the estimation process handles statistical fluctuations. Many of the present security analyses are based on the method with simple random sampling, where hypergeometric distribution or its known bounds are used for the estimation. Here we propose a concise method based on Bernoulli sampling, which is related to binomial distribution. Our method is suitable for the Bennett-Brassard 1984 (BB84) protocol with weak coherent pulses [C. H. Bennett and G. Brassard, Proceedings of the IEEE Conference on Computers, Systems and Signal Processing (IEEE, New York, 1984), Vol. 175], reducing the number of estimated parameters to achieve a higher key generation rate compared to the method with simple random sampling. We also apply the method to prove the security of the differential-quadrature-phase-shift (DQPS) protocol in the finite-key regime. The result indicates that the advantage of the DQPS protocol over the phase-encoding BB84 protocol in terms of the key rate, which was previously confirmed in the asymptotic regime, persists in the finite-key regime.

Quasi-equilibrium theory for the distribution of rare alleles in a subdivided population: justification and implications.

PubMed

Burr, T L

2000-05-01

This paper examines a quasi-equilibrium theory of rare alleles for subdivided populations that follow an island-model version of the Wright-Fisher model of evolution. All mutations are assumed to create new alleles. We present four results: (1) conditions for the theory to apply are formally established using properties of the moments of the binomial distribution; (2) approximations currently in the literature can be replaced with exact results that are in better agreement with our simulations; (3) a modified maximum likelihood estimator of migration rate exhibits the same good performance on island-model data or on data simulated from the multinomial mixed with the Dirichlet distribution, and (4) a connection between the rare-allele method and the Ewens Sampling Formula for the infinite-allele mutation model is made. This introduces a new and simpler proof for the expected number of alleles implied by the Ewens Sampling Formula. Copyright 2000 Academic Press.

The relationship between social support and adolescent dating violence: a comparison across genders.

PubMed

Richards, Tara N; Branch, Kathryn A

2012-05-01

Although much research has focused on the function of social support in adult intimate partner violence, little is known about the role of social support in adolescent dating violence. This study is an exploratory analysis of the independent impact of social support from friends and family on the risk of adolescent dating violence perpetration and victimization among a large sample of youth (n = 970). Approximately, 21% of the sample reported experiencing victimization in a dating relationship whereas 23% indicated perpetrating dating violence. Male youth reported significantly more involvement in dating violence as both perpetrators and victims. Negative binomial regression modeling indicated that increased levels of support from friends was associated with significantly less dating violence perpetration and victimization; however, when gendered models were explored, the protective role of social support was only maintained for female youth. Family support was not significantly related to dating violence in any model. Implications for dating violence curriculum and future research are addressed.

Error simulation of paired-comparison-based scaling methods

NASA Astrophysics Data System (ADS)

Cui, Chengwu

2000-12-01

Subjective image quality measurement usually resorts to psycho physical scaling. However, it is difficult to evaluate the inherent precision of these scaling methods. Without knowing the potential errors of the measurement, subsequent use of the data can be misleading. In this paper, the errors on scaled values derived form paired comparison based scaling methods are simulated with randomly introduced proportion of choice errors that follow the binomial distribution. Simulation results are given for various combinations of the number of stimuli and the sampling size. The errors are presented in the form of average standard deviation of the scaled values and can be fitted reasonably well with an empirical equation that can be sued for scaling error estimation and measurement design. The simulation proves paired comparison based scaling methods can have large errors on the derived scaled values when the sampling size and the number of stimuli are small. Examples are also given to show the potential errors on actually scaled values of color image prints as measured by the method of paired comparison.

Automatic variance analysis of multistage care pathways.

PubMed

Li, Xiang; Liu, Haifeng; Zhang, Shilei; Mei, Jing; Xie, Guotong; Yu, Yiqin; Li, Jing; Lakshmanan, Geetika T

2014-01-01

A care pathway (CP) is a standardized process that consists of multiple care stages, clinical activities and their relations, aimed at ensuring and enhancing the quality of care. However, actual care may deviate from the planned CP, and analysis of these deviations can help clinicians refine the CP and reduce medical errors. In this paper, we propose a CP variance analysis method to automatically identify the deviations between actual patient traces in electronic medical records (EMR) and a multistage CP. As the care stage information is usually unavailable in EMR, we first align every trace with the CP using a hidden Markov model. From the aligned traces, we report three types of deviations for every care stage: additional activities, absent activities and violated constraints, which are identified by using the techniques of temporal logic and binomial tests. The method has been applied to a CP for the management of congestive heart failure and real world EMR, providing meaningful evidence for the further improvement of care quality.

Predicting Binge Drinking in College Students: Rational Beliefs, Stress, or Loneliness?

PubMed

Chen, Yixin; Feeley, Thomas Hugh

2015-01-01

We proposed a conceptual model to predict binge-drinking behavior among college students, based on the theory of planned behavior and the stress-coping hypothesis. A two-wave online survey was conducted with predictors and drinking behavior measured separately over 2 weeks' time. In the Wave 1 survey, 279 students at a public university in the United States answered questions assessing key predictors and individual characteristics. In the Wave 2 survey, 179 participants returned and reported their drinking behavior over 2 weeks' time. After conducting a negative binomial regression, we found that more favorable attitude toward drinking and less perceived control of drinking at Wave 1 were associated with more binge drinking at Wave 2; subjective norm at Wave 1 was not a significant predictor of binge drinking at Wave 2; students with higher stress at Wave 1 engaged in more binge drinking at Wave 2, but those with higher loneliness did not. Implications of findings are discussed. © The Author(s) 2016.

Healthcare use and cost in dementia caregivers: Longitudinal results from the Predictors Caregiver Study

PubMed Central

Zhu, Carolyn W.; Scarmeas, Nikolaos; Ornstein, Katherine; Albert, Marilyn; Brandt, Jason; Blacker, Deborah; Sano, Mary; Stern, Yaakov

2014-01-01

OBJECTIVE: To examine the effects of caregiver and patient characteristics on caregivers’ medical care use and cost. METHODS: 147 caregiver/patient dyads were followed annually for 6 years in 3 academic AD centers in the US. Logistic, negative binomial, and generalized linear mixed models were used to examine overall effects of caregiver/patient characteristics on caregivers’ hospitalizations, doctor visits, outpatient tests and procedures, and prescription and over-the-counter medications. RESULTS: Patients’ comorbid conditions and dependence were associated with increased healthcare use and costs of caregivers. Increases in caregiver depressive symptoms are associated with increases in multiple domains of caregivers’ healthcare use and costs. DISCUSSION: Findings suggest that we should expand our focus on dementia patients to include family caregivers to obtain a fuller picture of effects of caregiving. Primary care providers should integrate caregivers’ needs in healthcare planning and delivery. Clinical interventions that treat patients and caregivers as a whole will likely achieve the greatest beneficial effects. PMID:24637299

Regional Differences in the Growing Incidence of Dengue Fever in Vietnam Explained by Weather Variability

PubMed Central

Vu, Ha Hai; Okumura, Junko; Hashizume, Masahiro; Tran, Duong Nhu; Yamamoto, Taro

2014-01-01

Dengue fever is a major health problem in Vietnam, but its incidence differs from province to province. To understand this at the local level, we assessed the effect of four weather components (humidity, rainfall, temperature and sunshine) on the number of dengue cases in nine provinces of Vietnam. Monthly data from 1999 to 2009 were analysed by time-series regression using negative binomial models. A test for heterogeneity was applied to assess the weather-dengue association in the provinces. Those associations were significantly heterogeneous (for temperature, humidity, and sunshine: P < 0.001 heterogeneity test; for rainfall: P = 0.018 heterogeneity test). This confirms that weather components strongly affect dengue transmission at a lag time of 0 to 3 months, with considerable variation in their influence among different areas in Vietnam. This finding may promote the strategic prevention of dengue disease by suggesting specific plans at the local level, rather than a nationally unified approach. PMID:24808744

Alone on the Inside: The Impact of Social Isolation and Helping Others on AOD Use and Criminal Activity

PubMed Central

Johnson, Byron R.; Pagano, Maria E.; Lee, Matthew T.; Post, Stephen G.

2015-01-01

Because addiction is a socially isolating disease, social support for recovery is an important element of treatment planning. This study examines the relationship between social isolation, giving and receiving social support in Alcoholics Anonymous during treatment, and post-treatment outcomes among juvenile offenders court-referred to addiction treatment. Adolescents (N = 195) aged 14 to 18 years were prospectively assessed at treatment admission, treatment discharge, 6 months, and 12 months after treatment discharge. The influence of social isolation variables on relapse and severe criminal activity in the 12-months post-treatment was examined using negative binomial logistic regressions and event history methods. Juveniles entering treatment with social estrangement were significantly more likely to relapse, be incarcerated, and commit a violent crime in the 12-months post-treatment. Giving help to others in Alcoholics Anonymous during treatment significantly reduced the risk of relapse, incarceration, and violent crime in the 12-months post-treatment whereas receiving help did not. PMID:29628533

A new framework of statistical inferences based on the valid joint sampling distribution of the observed counts in an incomplete contingency table.

PubMed

Tian, Guo-Liang; Li, Hui-Qiong

2017-08-01

Some existing confidence interval methods and hypothesis testing methods in the analysis of a contingency table with incomplete observations in both margins entirely depend on an underlying assumption that the sampling distribution of the observed counts is a product of independent multinomial/binomial distributions for complete and incomplete counts. However, it can be shown that this independency assumption is incorrect and can result in unreliable conclusions because of the under-estimation of the uncertainty. Therefore, the first objective of this paper is to derive the valid joint sampling distribution of the observed counts in a contingency table with incomplete observations in both margins. The second objective is to provide a new framework for analyzing incomplete contingency tables based on the derived joint sampling distribution of the observed counts by developing a Fisher scoring algorithm to calculate maximum likelihood estimates of parameters of interest, the bootstrap confidence interval methods, and the bootstrap testing hypothesis methods. We compare the differences between the valid sampling distribution and the sampling distribution under the independency assumption. Simulation studies showed that average/expected confidence-interval widths of parameters based on the sampling distribution under the independency assumption are shorter than those based on the new sampling distribution, yielding unrealistic results. A real data set is analyzed to illustrate the application of the new sampling distribution for incomplete contingency tables and the analysis results again confirm the conclusions obtained from the simulation studies.

40 CFR 141.802 - Coliform sampling plan.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 23 2011-07-01 2011-07-01 false Coliform sampling plan. 141.802... sampling plan. (a) Each air carrier under this subpart must develop a coliform sampling plan covering each... required actions, including repeat and follow-up sampling, corrective action, and notification of...

40 CFR 141.802 - Coliform sampling plan.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 22 2010-07-01 2010-07-01 false Coliform sampling plan. 141.802... sampling plan. (a) Each air carrier under this subpart must develop a coliform sampling plan covering each... required actions, including repeat and follow-up sampling, corrective action, and notification of...

A Random Variable Transformation Process.

ERIC Educational Resources Information Center

Scheuermann, Larry

1989-01-01

Provides a short BASIC program, RANVAR, which generates random variates for various theoretical probability distributions. The seven variates include: uniform, exponential, normal, binomial, Poisson, Pascal, and triangular. (MVL)

The Social Acceptance of Community Solar: A Portland Case Study

NASA Astrophysics Data System (ADS)

Weaver, Anne

Community solar is a renewable energy practice that's been adopted by multiple U.S. states and is being considered by many more, including the state of Oregon. A recent senate bill in Oregon, called the "Clean Electricity and Coal Transition Plan", includes a provision that directs the Oregon Public Utility Commission to establish a community solar program for investor-owned utilities by late 2017. Thus, energy consumers in Portland will be offered participation in community solar projects in the near future. Community solar is a mechanism that allows ratepayers to experience both the costs and benefits of solar energy while also helping to offset the proportion of fossil-fuel generated electricity in utility grids, thus aiding climate change mitigation. For community solar to achieve market success in the residential sector of Portland, ratepayers of investor-owned utilities must socially accept this energy practice. The aim of this study was to forecast the potential social acceptance of community solar among Portland residents by measuring willingness to participate in these projects. Additionally, consumer characteristics, attitudes, awareness, and knowledge were captured to assess the influence of these factors on intent to enroll in community solar. The theory of planned behavior, as well as the social acceptance, diffusion of innovation, and dual-interest theories were frameworks used to inform the analysis of community solar adoption. These research objectives were addressed through a mixed-mode survey of Portland residents, using a stratified random sample of Portland neighborhoods to acquire a gradient of demographics. 330 questionnaires were completed, yielding a 34.2% response rate. Descriptive statistics, binomial logistic regression models, and mean willingness to pay were the analyses conducted to measure the influence of project factors and demographic characteristics on likelihood of community solar participation. Roughly 60% of respondents exhibited interest in community solar enrollment. The logistic regression model revealed the percent change in utility bill (essentially the rate of return on the community solar investment) as a dramatically influential variable predicting willingness to participate. Community solar project scenarios also had a strong influence on willingness to participate: larger, cheaper, and distant projects were preferred over small and expensive local projects. Results indicate that community solar project features that accentuate affordability are most important to energy consumers. Additionally, demographic characteristics that were strongly correlated with willingness to enroll were politically liberal ideologies, higher incomes, current enrollment in green utility programs, and membership in an environmental organization. Thus, the market acceptance of community solar in Portland will potentially be broadened by emphasizing affordability over other features, such as community and locality. Additionally, I explored attitudinal influences on interest in community solar by conducting exploratory factor analysis on attitudes towards energy, climate change, and solar barriers and subsequently conducting binomial logistic regression models. Results found that perceiving renewable energy as environmentally beneficial was positively correlated with intent to enroll in community solar, which supported the notion that environmental attitudes will lead to environmental behaviors. The logistic regression model also revealed a negative correlation between community solar interest and negative attitudes towards renewable energy. Perceptions of solar barriers were mild, indicating that lack of an enabling mechanism may be the reason solar continues to be underutilized in this region.

Differential expression analysis for RNAseq using Poisson mixed models.

PubMed

Sun, Shiquan; Hood, Michelle; Scott, Laura; Peng, Qinke; Mukherjee, Sayan; Tung, Jenny; Zhou, Xiang

2017-06-20

Identifying differentially expressed (DE) genes from RNA sequencing (RNAseq) studies is among the most common analyses in genomics. However, RNAseq DE analysis presents several statistical and computational challenges, including over-dispersed read counts and, in some settings, sample non-independence. Previous count-based methods rely on simple hierarchical Poisson models (e.g. negative binomial) to model independent over-dispersion, but do not account for sample non-independence due to relatedness, population structure and/or hidden confounders. Here, we present a Poisson mixed model with two random effects terms that account for both independent over-dispersion and sample non-independence. We also develop a scalable sampling-based inference algorithm using a latent variable representation of the Poisson distribution. With simulations, we show that our method properly controls for type I error and is generally more powerful than other widely used approaches, except in small samples (n <15) with other unfavorable properties (e.g. small effect sizes). We also apply our method to three real datasets that contain related individuals, population stratification or hidden confounders. Our results show that our method increases power in all three data compared to other approaches, though the power gain is smallest in the smallest sample (n = 6). Our method is implemented in MACAU, freely available at www.xzlab.org/software.html. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Designing a multiple dependent state sampling plan based on the coefficient of variation.

PubMed

Yan, Aijun; Liu, Sanyang; Dong, Xiaojuan

2016-01-01

A multiple dependent state (MDS) sampling plan is developed based on the coefficient of variation of the quality characteristic which follows a normal distribution with unknown mean and variance. The optimal plan parameters of the proposed plan are solved by a nonlinear optimization model, which satisfies the given producer's risk and consumer's risk at the same time and minimizes the sample size required for inspection. The advantages of the proposed MDS sampling plan over the existing single sampling plan are discussed. Finally an example is given to illustrate the proposed plan.

The impact of texting bans on motor vehicle crash-related hospitalizations.

PubMed

Ferdinand, Alva O; Menachemi, Nir; Blackburn, Justin L; Sen, Bisakha; Nelson, Leonard; Morrisey, Michael

2015-05-01

We used a panel design and the Nationwide Inpatient Sample from 19 states between 2003 and 2010 to examine the impact of texting bans on crash-related hospitalizations. We conducted conditional negative binomial regressions with state, year, and month fixed effects to examine changes in crash-related hospitalizations in states after the enactment of a texting ban relative to those in states without such bans. Results indicate that texting bans were associated with a 7% reduction in crash-related hospitalizations among all age groups. Texting bans were significantly associated with reductions in hospitalizations among those aged 22 to 64 years and those aged 65 years or older. Marginal reductions were seen among adolescents. States that have not passed strict texting bans should consider doing so.

The Impact of Texting Bans on Motor Vehicle Crash–Related Hospitalizations

PubMed Central

Menachemi, Nir; Blackburn, Justin L.; Sen, Bisakha; Nelson, Leonard; Morrisey, Michael

2015-01-01

We used a panel design and the Nationwide Inpatient Sample from 19 states between 2003 and 2010 to examine the impact of texting bans on crash-related hospitalizations. We conducted conditional negative binomial regressions with state, year, and month fixed effects to examine changes in crash-related hospitalizations in states after the enactment of a texting ban relative to those in states without such bans. Results indicate that texting bans were associated with a 7% reduction in crash-related hospitalizations among all age groups. Texting bans were significantly associated with reductions in hospitalizations among those aged 22 to 64 years and those aged 65 years or older. Marginal reductions were seen among adolescents. States that have not passed strict texting bans should consider doing so. PMID:25790409

Willingness to pay for non angler recreation at the lower Snake River reservoirs

USGS Publications Warehouse

McKean, J.R.; Johnson, D.; Taylor, R.G.; Johnson, Richard L.

2005-01-01

This study applied the travel cost method to estimate demand for non angler recreation at the impounded Snake River in eastern Washington. Net value per person per recreation trip is estimated for the full non angler sample and separately for camping, boating, water-skiing, and swimming/picnicking. Certain recreation activities would be reduced or eliminated and new activities would be added if the dams were breached to protect endangered salmon and steelhead. The effect of breaching on non angling benefits was found by subtracting our benefits estimate from the projected non angling benefits with breaching. Major issues in demand model specification and definition of the price variables are discussed. The estimation method selected was truncated negative binomial regression with adjustment for self selection bias.

7 CFR 42.104 - Sampling plans and defects.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Sampling plans and defects. 42.104 Section 42.104... REGULATIONS STANDARDS FOR CONDITION OF FOOD CONTAINERS Procedures for Stationary Lot Sampling and Inspection § 42.104 Sampling plans and defects. (a) Sampling plans. Sections 42.109 through 42.111 show the number...

7 CFR 42.104 - Sampling plans and defects.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 2 2011-01-01 2011-01-01 false Sampling plans and defects. 42.104 Section 42.104... REGULATIONS STANDARDS FOR CONDITION OF FOOD CONTAINERS Procedures for Stationary Lot Sampling and Inspection § 42.104 Sampling plans and defects. (a) Sampling plans. Sections 42.109 through 42.111 show the number...

7 CFR 275.11 - Sampling.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 4 2010-01-01 2010-01-01 false Sampling. 275.11 Section 275.11 Agriculture... § 275.11 Sampling. (a) Sampling plan. Each State agency shall develop a quality control sampling plan which demonstrates the integrity of its sampling procedures. (1) Content. The sampling plan shall...

7 CFR 275.11 - Sampling.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 4 2011-01-01 2011-01-01 false Sampling. 275.11 Section 275.11 Agriculture... § 275.11 Sampling. (a) Sampling plan. Each State agency shall develop a quality control sampling plan which demonstrates the integrity of its sampling procedures. (1) Content. The sampling plan shall...

A comparison of different ways of including baseline counts in negative binomial models for data from falls prevention trials.

PubMed

Zheng, Han; Kimber, Alan; Goodwin, Victoria A; Pickering, Ruth M

2018-01-01

A common design for a falls prevention trial is to assess falling at baseline, randomize participants into an intervention or control group, and ask them to record the number of falls they experience during a follow-up period of time. This paper addresses how best to include the baseline count in the analysis of the follow-up count of falls in negative binomial (NB) regression. We examine the performance of various approaches in simulated datasets where both counts are generated from a mixed Poisson distribution with shared random subject effect. Including the baseline count after log-transformation as a regressor in NB regression (NB-logged) or as an offset (NB-offset) resulted in greater power than including the untransformed baseline count (NB-unlogged). Cook and Wei's conditional negative binomial (CNB) model replicates the underlying process generating the data. In our motivating dataset, a statistically significant intervention effect resulted from the NB-logged, NB-offset, and CNB models, but not from NB-unlogged, and large, outlying baseline counts were overly influential in NB-unlogged but not in NB-logged. We conclude that there is little to lose by including the log-transformed baseline count in standard NB regression compared to CNB for moderate to larger sized datasets. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Fixed-Precision Sequential Sampling Plans for Estimating Alfalfa Caterpillar, Colias lesbia, Egg Density in Alfalfa, Medicago sativa, Fields in Córdoba, Argentina

PubMed Central

Serra, Gerardo V.; Porta, Norma C. La; Avalos, Susana; Mazzuferi, Vilma

2013-01-01

The alfalfa caterpillar, Colias lesbia (Fabricius) (Lepidoptera: Pieridae), is a major pest of alfalfa, Medicago sativa L. (Fabales: Fabaceae), crops in Argentina. Its management is based mainly on chemical control of larvae whenever the larvae exceed the action threshold. To develop and validate fixed-precision sequential sampling plans, an intensive sampling programme for C. lesbia eggs was carried out in two alfalfa plots located in the Province of Córdoba, Argentina, from 1999 to 2002. Using Resampling for Validation of Sampling Plans software, 12 additional independent data sets were used to validate the sequential sampling plan with precision levels of 0.10 and 0.25 (SE/mean), respectively. For a range of mean densities of 0.10 to 8.35 eggs/sample, an average sample size of only 27 and 26 sample units was required to achieve a desired precision level of 0.25 for the sampling plans of Green and Kuno, respectively. As the precision level was increased to 0.10, average sample size increased to 161 and 157 sample units for the sampling plans of Green and Kuno, respectively. We recommend using Green's sequential sampling plan because it is less sensitive to changes in egg density. These sampling plans are a valuable tool for researchers to study population dynamics and to evaluate integrated pest management strategies. PMID:23909840

Two-sample discrimination of Poisson means

NASA Technical Reports Server (NTRS)

Lampton, M.

1994-01-01

This paper presents a statistical test for detecting significant differences between two random count accumulations. The null hypothesis is that the two samples share a common random arrival process with a mean count proportional to each sample's exposure. The model represents the partition of N total events into two counts, A and B, as a sequence of N independent Bernoulli trials whose partition fraction, f, is determined by the ratio of the exposures of A and B. The detection of a significant difference is claimed when the background (null) hypothesis is rejected, which occurs when the observed sample falls in a critical region of (A, B) space. The critical region depends on f and the desired significance level, alpha. The model correctly takes into account the fluctuations in both the signals and the background data, including the important case of small numbers of counts in the signal, the background, or both. The significance can be exactly determined from the cumulative binomial distribution, which in turn can be inverted to determine the critical A(B) or B(A) contour. This paper gives efficient implementations of these tests, based on lookup tables. Applications include the detection of clustering of astronomical objects, the detection of faint emission or absorption lines in photon-limited spectroscopy, the detection of faint emitters or absorbers in photon-limited imaging, and dosimetry.

Football goal distributions and extremal statistics

NASA Astrophysics Data System (ADS)

Greenhough, J.; Birch, P. C.; Chapman, S. C.; Rowlands, G.

2002-12-01

We analyse the distributions of the number of goals scored by home teams, away teams, and the total scored in the match, in domestic football games from 169 countries between 1999 and 2001. The probability density functions (PDFs) of goals scored are too heavy-tailed to be fitted over their entire ranges by Poisson or negative binomial distributions which would be expected for uncorrelated processes. Log-normal distributions cannot include zero scores and here we find that the PDFs are consistent with those arising from extremal statistics. In addition, we show that it is sufficient to model English top division and FA Cup matches in the seasons of 1970/71-2000/01 on Poisson or negative binomial distributions, as reported in analyses of earlier seasons, and that these are not consistent with extremal statistics.

A comparison of two gears for quantifying abundance of lotic-dwelling crayfish

USGS Publications Warehouse

Williams, Kristi; Brewer, Shannon K.; Ellersieck, Mark R.

2014-01-01

Crayfish (saddlebacked crayfish, Orconectes medius) catch was compared using a kick seine applied two different ways with a 1-m2 quadrat sampler (with known efficiency and bias in riffles) from three small streams in the Missouri Ozarks. Triplicate samples (one of each technique) were taken from two creeks and one headwater stream (n=69 sites) over a two-year period. General linear mixed models showed the number of crayfish collected using the quadrat sampler was greater than the number collected using either of the two seine techniques. However, there was no significant interaction with gear suggesting year, stream size, and channel unit type did not relate to different catches of crayfish by gear type. Variation in catch among gears was similar, as was the proportion of young-of-year individuals across samples taken with different gears or techniques. Negative binomial linear regression provided the appropriate relation between the gears which allows correction factors to be applied, if necessary, to relate catches by the kick seine to those of the quadrat sampler. The kick seine appears to be a reasonable substitute to the quadrat sampler in these shallow streams, with the advantage of ease of use and shorter time required per sample.

EM Adaptive LASSO—A Multilocus Modeling Strategy for Detecting SNPs Associated with Zero-inflated Count Phenotypes

PubMed Central

Mallick, Himel; Tiwari, Hemant K.

2016-01-01

Count data are increasingly ubiquitous in genetic association studies, where it is possible to observe excess zero counts as compared to what is expected based on standard assumptions. For instance, in rheumatology, data are usually collected in multiple joints within a person or multiple sub-regions of a joint, and it is not uncommon that the phenotypes contain enormous number of zeroes due to the presence of excessive zero counts in majority of patients. Most existing statistical methods assume that the count phenotypes follow one of these four distributions with appropriate dispersion-handling mechanisms: Poisson, Zero-inflated Poisson (ZIP), Negative Binomial, and Zero-inflated Negative Binomial (ZINB). However, little is known about their implications in genetic association studies. Also, there is a relative paucity of literature on their usefulness with respect to model misspecification and variable selection. In this article, we have investigated the performance of several state-of-the-art approaches for handling zero-inflated count data along with a novel penalized regression approach with an adaptive LASSO penalty, by simulating data under a variety of disease models and linkage disequilibrium patterns. By taking into account data-adaptive weights in the estimation procedure, the proposed method provides greater flexibility in multi-SNP modeling of zero-inflated count phenotypes. A fast coordinate descent algorithm nested within an EM (expectation-maximization) algorithm is implemented for estimating the model parameters and conducting variable selection simultaneously. Results show that the proposed method has optimal performance in the presence of multicollinearity, as measured by both prediction accuracy and empirical power, which is especially apparent as the sample size increases. Moreover, the Type I error rates become more or less uncontrollable for the competing methods when a model is misspecified, a phenomenon routinely encountered in practice. PMID:27066062

EM Adaptive LASSO-A Multilocus Modeling Strategy for Detecting SNPs Associated with Zero-inflated Count Phenotypes.

PubMed

Mallick, Himel; Tiwari, Hemant K

2016-01-01

Count data are increasingly ubiquitous in genetic association studies, where it is possible to observe excess zero counts as compared to what is expected based on standard assumptions. For instance, in rheumatology, data are usually collected in multiple joints within a person or multiple sub-regions of a joint, and it is not uncommon that the phenotypes contain enormous number of zeroes due to the presence of excessive zero counts in majority of patients. Most existing statistical methods assume that the count phenotypes follow one of these four distributions with appropriate dispersion-handling mechanisms: Poisson, Zero-inflated Poisson (ZIP), Negative Binomial, and Zero-inflated Negative Binomial (ZINB). However, little is known about their implications in genetic association studies. Also, there is a relative paucity of literature on their usefulness with respect to model misspecification and variable selection. In this article, we have investigated the performance of several state-of-the-art approaches for handling zero-inflated count data along with a novel penalized regression approach with an adaptive LASSO penalty, by simulating data under a variety of disease models and linkage disequilibrium patterns. By taking into account data-adaptive weights in the estimation procedure, the proposed method provides greater flexibility in multi-SNP modeling of zero-inflated count phenotypes. A fast coordinate descent algorithm nested within an EM (expectation-maximization) algorithm is implemented for estimating the model parameters and conducting variable selection simultaneously. Results show that the proposed method has optimal performance in the presence of multicollinearity, as measured by both prediction accuracy and empirical power, which is especially apparent as the sample size increases. Moreover, the Type I error rates become more or less uncontrollable for the competing methods when a model is misspecified, a phenomenon routinely encountered in practice.

Mycophenolic Acid Pharmacokinetics and Relapse in Children with Steroid–Dependent Idiopathic Nephrotic Syndrome

PubMed Central

Tellier, Stéphanie; Dallocchio, Aymeric; Guigonis, Vincent; Saint-Marcoux, Frank; Llanas, Brigitte; Ichay, Lydia; Bandin, Flavio; Godron, Astrid; Morin, Denis; Brochard, Karine; Gandia, Peggy; Bouchet, Stéphane; Marquet, Pierre; Decramer, Stéphane

2016-01-01

Background and objectives Therapeutic drug monitoring of mycophenolic acid can improve clinical outcome in organ transplantation and lupus, but data are scarce in idiopathic nephrotic syndrome. The aim of our study was to investigate whether mycophenolic acid pharmacokinetics are associated with disease control in children receiving mycophenolate mofetil for the treatment of steroid–dependent nephrotic syndrome. Design, setting, participants, & measurements This was a retrospective multicenter study including 95 children with steroid–dependent nephrotic syndrome treated with mycophenolate mofetil with or without steroids. Area under the concentration-time curve of mycophenolic acid was determined in all children on the basis of sampling times at 20, 60, and 180 minutes postdose, using Bayesian estimation. The association between a threshold value of the area under the concentration-time curve of mycophenolic acid and the relapse rate was assessed using a negative binomial model. Results In total, 140 areas under the concentration-time curve of mycophenolic acid were analyzed. The findings indicate individual dose adaptation in 53 patients (38%) to achieve an area under the concentration-time curve target of 30–60 mg·h/L. In a multivariable negative binomial model including sex, age at disease onset, time to start of mycophenolate mofetil, previous immunomodulatory treatment, and concomitant prednisone dose, a level of area under the concentration-time curve of mycophenolic acid >45 mg·h/L was significantly associated with a lower relapse rate (rate ratio, 0.65; 95% confidence interval, 0.46 to 0.89; P=0.01). Conclusions Therapeutic drug monitoring leading to individualized dosing may improve the efficacy of mycophenolate mofetil in steroid–dependent nephrotic syndrome. Additional prospective studies are warranted to determine the optimal target for area under the concentration-time curve of mycophenolic acid in this population. PMID:27445161

Mycophenolic Acid Pharmacokinetics and Relapse in Children with Steroid-Dependent Idiopathic Nephrotic Syndrome.

PubMed

Tellier, Stéphanie; Dallocchio, Aymeric; Guigonis, Vincent; Saint-Marcoux, Frank; Llanas, Brigitte; Ichay, Lydia; Bandin, Flavio; Godron, Astrid; Morin, Denis; Brochard, Karine; Gandia, Peggy; Bouchet, Stéphane; Marquet, Pierre; Decramer, Stéphane; Harambat, Jérôme

2016-10-07

Therapeutic drug monitoring of mycophenolic acid can improve clinical outcome in organ transplantation and lupus, but data are scarce in idiopathic nephrotic syndrome. The aim of our study was to investigate whether mycophenolic acid pharmacokinetics are associated with disease control in children receiving mycophenolate mofetil for the treatment of steroid-dependent nephrotic syndrome. This was a retrospective multicenter study including 95 children with steroid-dependent nephrotic syndrome treated with mycophenolate mofetil with or without steroids. Area under the concentration-time curve of mycophenolic acid was determined in all children on the basis of sampling times at 20, 60, and 180 minutes postdose, using Bayesian estimation. The association between a threshold value of the area under the concentration-time curve of mycophenolic acid and the relapse rate was assessed using a negative binomial model. In total, 140 areas under the concentration-time curve of mycophenolic acid were analyzed. The findings indicate individual dose adaptation in 53 patients (38%) to achieve an area under the concentration-time curve target of 30-60 mg·h/L. In a multivariable negative binomial model including sex, age at disease onset, time to start of mycophenolate mofetil, previous immunomodulatory treatment, and concomitant prednisone dose, a level of area under the concentration-time curve of mycophenolic acid >45 mg·h/L was significantly associated with a lower relapse rate (rate ratio, 0.65; 95% confidence interval, 0.46 to 0.89; P =0.01). Therapeutic drug monitoring leading to individualized dosing may improve the efficacy of mycophenolate mofetil in steroid-dependent nephrotic syndrome. Additional prospective studies are warranted to determine the optimal target for area under the concentration-time curve of mycophenolic acid in this population. Copyright © 2016 by the American Society of Nephrology.

Multivariate random-parameters zero-inflated negative binomial regression model: an application to estimate crash frequencies at intersections.

PubMed

Dong, Chunjiao; Clarke, David B; Yan, Xuedong; Khattak, Asad; Huang, Baoshan

2014-09-01

Crash data are collected through police reports and integrated with road inventory data for further analysis. Integrated police reports and inventory data yield correlated multivariate data for roadway entities (e.g., segments or intersections). Analysis of such data reveals important relationships that can help focus on high-risk situations and coming up with safety countermeasures. To understand relationships between crash frequencies and associated variables, while taking full advantage of the available data, multivariate random-parameters models are appropriate since they can simultaneously consider the correlation among the specific crash types and account for unobserved heterogeneity. However, a key issue that arises with correlated multivariate data is the number of crash-free samples increases, as crash counts have many categories. In this paper, we describe a multivariate random-parameters zero-inflated negative binomial (MRZINB) regression model for jointly modeling crash counts. The full Bayesian method is employed to estimate the model parameters. Crash frequencies at urban signalized intersections in Tennessee are analyzed. The paper investigates the performance of MZINB and MRZINB regression models in establishing the relationship between crash frequencies, pavement conditions, traffic factors, and geometric design features of roadway intersections. Compared to the MZINB model, the MRZINB model identifies additional statistically significant factors and provides better goodness of fit in developing the relationships. The empirical results show that MRZINB model possesses most of the desirable statistical properties in terms of its ability to accommodate unobserved heterogeneity and excess zero counts in correlated data. Notably, in the random-parameters MZINB model, the estimated parameters vary significantly across intersections for different crash types. Copyright © 2014 Elsevier Ltd. All rights reserved.

[Association between cesarean birth and the risk of obesity in 6-17 year-olds].

PubMed

Wang, Z H; Xu, R B; Dong, Y H; Yang, Y D; Wang, S; Wang, X J; Yang, Z G; Zou, Z Y; Ma, J

2017-12-10

Objective: To explore the association between cesarean section and obesity in child and adolescent. Methods: In this study, a total number of 42 758 primary and middle school students aged between 6 and 17 were selected, using the stratified cluster sampling method in 93 primary and middle schools in Hunan, Ningxia, Tianjin, Chongqing, Liaoning, Shanghai and Guangdong provinces and autonomous regions. Log-Binomial regression model was used to analyze the association between cesarean section and obesity in childhood or adolescent. Results: Mean age of the subjects was (10.5±3.2) years. The overall rate of cesarean section among subjects attending primary or secondary schools was 42.3%, with 55.9% in boys and, 40.6% in girls respectively and with difference statistically significant ( P <0.001). The rate on obesity among those that received cesarean section (17.6%) was significantly higher than those who experienced vaginal delivery (10.2%) ( P <0.001). Results from the log-binomial regression model showed that cesarean section significantly increased the risk of obesity in child and adolescent ( OR =1.72, 95% CI : 1.63-1.82; P <0.001). After adjusting for factors as sex, residential areas (urban or rural), feeding patterns, frequencies of milk-feeding, eating high-energy foods, eating fried foods and the levels of parental education, family income, parental obesity, physical activity levels, gestational age and birth weight etc ., the differences were still statistically significant ( OR =1.48, 95% CI : 1.39-1.57; P <0.001). Conclusion: The rate of cesarean section among pregnant women in China appeared high which may significantly increase the risk of obesity in child or adolescent.

Recurrent suicide attempts in patients with depressive and anxiety disorders: the role of borderline personality traits.

PubMed

Stringer, Barbara; van Meijel, Berno; Eikelenboom, Merijn; Koekkoek, Bauke; Licht, Carmilla M M; Kerkhof, Ad J F M; Penninx, Brenda W J H; Beekman, Aartjan T F

2013-10-01

The presence of a comorbid borderline personality disorder (BPD) may be associated with an increase of suicidal behaviors in patients with depressive and anxiety disorders. The aim of this study is to examine the role of borderline personality traits on recurrent suicide attempts. The Netherlands Study on Depression and Anxiety included 1838 respondents with lifetime depressive and/or anxiety disorders, of whom 309 reported at least one previous suicide attempt. A univariable negative binomial regression analysis was performed to examine the association between comorbid borderline personality traits and suicide attempts. Univariable and multivariable negative binomial regression analyses were performed to identify risk factors for the number of recurrent suicide attempts in four clusters (type and severity of axis-I disorders, BPD traits, determinants of suicide attempts and socio-demographics). In the total sample the suicide attempt rate ratio increased with 33% for every unit increase in BPD traits. A lifetime diagnosis of dysthymia and comorbid BPD traits, especially the symptoms anger and fights, were independently and significantly associated with recurrent suicide attempts in the final model (n=309). The screening of personality disorders was added to the NESDA assessments at the 4-year follow-up for the first time. Therefore we were not able to examine the influence of comorbid BPD traits on suicide attempts over time. Persons with a lifetime diagnosis of dysthymia combined with borderline personality traits especially difficulties in coping with anger seemed to be at high risk for recurrent suicide attempts. For clinical practice, it is recommended to screen for comorbid borderline personality traits and to strengthen the patient's coping skills with regard to anger. © 2013 Elsevier B.V. All rights reserved.

Mapping CHU9D Utility Scores from the PedsQLTM 4.0 SF-15.

PubMed

Mpundu-Kaambwa, Christine; Chen, Gang; Russo, Remo; Stevens, Katherine; Petersen, Karin Dam; Ratcliffe, Julie

2017-04-01

The Pediatric Quality of Life Inventory™ 4.0 Short Form 15 Generic Core Scales (hereafter the PedsQL) and the Child Health Utility-9 Dimensions (CHU9D) are two generic instruments designed to measure health-related quality of life in children and adolescents in the general population and paediatric patient groups living with specific health conditions. Although the PedsQL is widely used among paediatric patient populations, presently it is not possible to directly use the scores from the instrument to calculate quality-adjusted life-years (QALYs) for application in economic evaluation because it produces summary scores which are not preference-based. This paper examines different econometric mapping techniques for estimating CHU9D utility scores from the PedsQL for the purpose of calculating QALYs for cost-utility analysis. The PedsQL and the CHU9D were completed by a community sample of 755 Australian adolescents aged 15-17 years. Seven regression models were estimated: ordinary least squares estimator, generalised linear model, robust MM estimator, multivariate factorial polynomial estimator, beta-binomial estimator, finite mixture model and multinomial logistic model. The mean absolute error (MAE) and the mean squared error (MSE) were used to assess predictive ability of the models. The MM estimator with stepwise-selected PedsQL dimension scores as explanatory variables had the best predictive accuracy using MAE and the equivalent beta-binomial model had the best predictive accuracy using MSE. Our mapping algorithm facilitates the estimation of health-state utilities for use within economic evaluations where only PedsQL data is available and is suitable for use in community-based adolescents aged 15-17 years. Applicability of the algorithm in younger populations should be assessed in further research.

Household expenditure on leprosy outpatient services in the Indian health system: A comparative study

PubMed Central

Suryawanshi, Pramilesh; Raikwar, Akash; Arif, Mohammad; Richardus, Jan Hendrik

2018-01-01

Background Leprosy is a major public health problem in many low and middle income countries, especially in India, and contributes considerably to the global burden of the disease. Leprosy and poverty are closely associated, and therefore the economic burden of leprosy is a concern. However, evidence on patient’s expenditure is scarce. In this study, we estimate the expenditure in primary care (outpatient) by leprosy households in two different public health settings. Methodology/Principal findings We performed a cross-sectional study, comparing the Union Territory of Dadra and Nagar Haveli with the Umbergaon block of Valsad, Gujrat, India. A household (HH) survey was conducted between May and October, 2016. We calculated direct and indirect expenditure by zero inflated negative binomial and negative binomial regression. The sampled households were comparable on socioeconomic indicators. The mean direct expenditure was USD 6.5 (95% CI: 2.4–17.9) in Dadra and Nagar Haveli and USD 5.4 (95% CI: 3.8–7.9) per visit in Umbergaon. The mean indirect expenditure was USD 8.7 (95% CI: 7.2–10.6) in Dadra and Nagar Haveli and USD 12.4 (95% CI: 7.0–21.9) in Umbergaon. The age of the leprosy patients and type of health facilities were the major predictors of total expenditure on leprosy primary care. The higher the age, the higher the expenditure at both sites. The private facilities are more expensive than the government facilities at both sites. If the public health system is enhanced, government facilities are the first preference for patients. Conclusions/Significance An enhanced public health system reduces the patient’s expenditure and improves the health seeking behaviour. We recommend investing in health system strengthening to reduce the economic burden of leprosy. PMID:29300747

Monitoring the impact of a national school based deworming programme on soil-transmitted helminths in Kenya: the first three years, 2012 - 2014.

PubMed

Okoyo, Collins; Nikolay, Birgit; Kihara, Jimmy; Simiyu, Elses; Garn, Joshua V; Freeman, Mathew C; Mwanje, Mariam T; Mukoko, Dunstan A; Brooker, Simon J; Pullan, Rachel L; Njenga, Sammy M; Mwandawiro, Charles S

2016-07-25

In 2012, the Kenyan Ministries of Health and of Education began a programme to deworm all school-age children living in areas at high risk of soil-transmitted helminths (STH) and schistosome infections. The impact of this school-based mass drug administration (MDA) programme in Kenya is monitored by the Kenya Medical Research Institute (KEMRI) as part of a five-year (2012-2017) study. This article focuses on the impact of MDA on STH infections and presents the overall achieved reductions from baseline to mid-term, as well as yearly patterns of reductions and subsequent re-infections per school community. The study involved a series of pre- and post-intervention, repeat cross-sectional surveys in a representative, stratified, two-stage sample of schools across Kenya. The programme contained two tiers of monitoring; a national baseline and mid-term survey including 200 schools, and surveys conducted among 60 schools pre- and post-intervention. Stool samples were collected from randomly selected school children and tested for helminth infections using Kato-Katz technique. The prevalence and mean intensity of each helminth species were calculated at the school and county levels and 95 % confidence intervals (CIs) were obtained by binomial and negative binomial regression, respectively, taking into account clustering by schools. The overall prevalence of STH infection at baseline was 32.3 % (hookworms: 15.4 %; Ascaris lumbricoides: 18.1 %; and Trichuris trichiura: 6.7 %). After two rounds of MDA, the overall prevalence of STH had reduced to 16.4 % (hookworms: 2.3 %; A. lumbricoides: 11.9 %; and T. trichiura: 4.5 %). The relative reductions of moderate to heavy intensity of infections were 33.7 % (STH combined), 77.3 % (hookworms) and 33.9 % (A. lumbricoides). For T. trichiura, however, moderate to heavy intensity of infections increased non-significantly by 18.0 % from baseline to mid-term survey. The school-based deworming programme has substantially reduced STH infections, but because of ongoing transmission additional strategies may be required to achieve a sustained interruption of transmission.

Effects of interactive metronome therapy on cognitive functioning after blast-related brain injury: a randomized controlled pilot trial.

PubMed

Nelson, Lonnie A; Macdonald, Margaret; Stall, Christina; Pazdan, Renee

2013-11-01

We report preliminary findings on the efficacy of interactive metronome (IM) therapy for the remediation of cognitive difficulties in soldiers with persisting cognitive complaints following blast-related mild-to-moderate traumatic brain injury (TBI). Forty-six of a planned sample of 50 active duty soldiers with persistent cognitive complaints following a documented history of blast-related TBI of mild-to-moderate severity were randomly assigned to receive either standard rehabilitation care (SRC) or SRC plus a 15-session standardized course of IM therapy. Primary outcome measures were Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) Index Scores. Secondary outcome measures included selected subtests from the Delis-Kaplan Executive Functioning System (Trail Making Test and Color-Word Interference) and the Wechsler Adult Intelligence Scale-Fourth Edition (Symbol Search, Digit-Symbol Coding, Digit Span, and Letter-Number Sequencing) as well as the Integrated Visual and Auditory Continuous Performance Test. Significant group differences (SRC vs. IM) were observed for RBANS Attention (p = .044), Immediate Memory (p = .019), and Delayed Memory (p = .031) indices in unadjusted analyses, with the IM group showing significantly greater improvement at Time 2 than the SRC group, with effect sizes in the medium-to-large range in the adjusted analyses for each outcome (Cohen's d = 0.511, 0.768, and 0.527, respectively). Though not all were statistically significant, effects in 21 of 26 cognitive outcome measures were consistently in favor of the IM treatment group (binomial probability = .00098). The addition of IM therapy to SRC appears to have a positive effect on neuropsychological outcomes for soldiers who have sustained mild-to-moderate TBI and have persistent cognitive complaints after the period for expected recovery has passed. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Cross-cultural analysis of the motor development of Brazilian, Greek and Canadian infants assessed with the Alberta Infant Motor Scale

PubMed Central

Saccani, Raquel; Valentini, Nadia Cristina

2013-01-01

OBJECTIVE: To compare the motor development of infants from three population samples (Brazil, Canada and Greece), to investigate differences in the percentile curves of motor development in these samples, and to investigate the prevalence of motor delays in Brazilian children. METHODS: Observational, descriptive and cross-sectional study with 795 Brazilian infants from zero to 18 months of age, assessed by the Alberta Infant Motor Scale (AIMS) at day care centers, nurseries, basic health units and at home. The Brazilian infants' motor scores were compared to the results of two population samples from Greece (424 infants) and Canada (2,400 infants). Descriptive statistics was used, with one-sample t-test and binomial tests, being significant p≤0.05. RESULTS: 65.4% of Brazilian children showed typical motor development, although with lower mean scores. In the beginning of the second year of life, the differences in the motor development among Brazilian, Canadian and Greek infants were milder; at 15 months of age, the motor development became similar in the three groups. A non-linear motor development trend was observed. CONCLUSIONS: The lowest motor percentiles of the Brazilian sample emphasized the need for national norms in order to correctly categorize the infant motor development. The different ways of motor development may be a consequence of cultural differences in infant care. PMID:24142318

Cross-cultural analysis of the motor development of Brazilian, Greek and Canadian infants assessed with the Alberta Infant Motor Scale.

PubMed

Saccani, Raquel; Valentini, Nadia Cristina

2013-09-01

To compare the motor development of infants from three population samples (Brazil, Canada and Greece), to investigate differences in the percentile curves of motor development in these samples, and to investigate the prevalence of motor delays in Brazilian children. Observational, descriptive and cross-sectional study with 795 Brazilian infants from zero to 18 months of age, assessed by the Alberta Infant Motor Scale (AIMS) at day care centers, nurseries, basic health units and at home. The Brazilian infants' motor scores were compared to the results of two population samples from Greece (424 infants) and Canada (2,400 infants). Descriptive statistics was used, with one-sample t-test and binomial tests, being significant p ≤ 0.05. 65.4% of Brazilian children showed typical motor development, although with lower mean scores. In the beginning of the second year of life, the differences in the motor development among Brazilian, Canadian and Greek infants were milder; at 15 months of age, the motor development became similar in the three groups. A non-linear motor development trend was observed. The lowest motor percentiles of the Brazilian sample emphasized the need for national norms in order to correctly categorize the infant motor development. The different ways of motor development may be a consequence of cultural differences in infant care.

The accuracy of selected land use and land cover maps at scales of 1:250,000 and 1:100,000

USGS Publications Warehouse

Fitzpatrick-Lins, Katherine

1980-01-01

Land use and land cover maps produced by the U.S. Geological Survey are found to meet or exceed the established standard of accuracy. When analyzed using a point sampling technique and binomial probability theory, several maps, illustrative of those produced for different parts of the country, were found to meet or exceed accuracies of 85 percent. Those maps tested were Tampa, Fla., Portland, Me., Charleston, W. Va., and Greeley, Colo., published at a scale of 1:250,000, and Atlanta, Ga., and Seattle and Tacoma, Wash., published at a scale of 1:100,000. For each map, the values were determined by calculating the ratio of the total number of points correctly interpreted to the total number of points sampled. Six of the seven maps tested have accuracies of 85 percent or better at the 95-percent lower confidence limit. When the sample data for predominant categories (those sampled with a significant number of points) were grouped together for all maps, accuracies of those predominant categories met the 85-percent accuracy criterion, with one exception. One category, Residential, had less than 85-percent accuracy at the 95-percent lower confidence limit. Nearly all residential land sampled was mapped correctly, but some areas of other land uses were mapped incorrectly as Residential.

Testing the non-unity of rate ratio under inverse sampling.

PubMed

Tang, Man-Lai; Liao, Yi Jie; Ng, Hong Keung Tony; Chan, Ping Shing

2007-08-01

Inverse sampling is considered to be a more appropriate sampling scheme than the usual binomial sampling scheme when subjects arrive sequentially, when the underlying response of interest is acute, and when maximum likelihood estimators of some epidemiologic indices are undefined. In this article, we study various statistics for testing non-unity rate ratios in case-control studies under inverse sampling. These include the Wald, unconditional score, likelihood ratio and conditional score statistics. Three methods (the asymptotic, conditional exact, and Mid-P methods) are adopted for P-value calculation. We evaluate the performance of different combinations of test statistics and P-value calculation methods in terms of their empirical sizes and powers via Monte Carlo simulation. In general, asymptotic score and conditional score tests are preferable for their actual type I error rates are well controlled around the pre-chosen nominal level, and their powers are comparatively the largest. The exact version of Wald test is recommended if one wants to control the actual type I error rate at or below the pre-chosen nominal level. If larger power is expected and fluctuation of sizes around the pre-chosen nominal level are allowed, then the Mid-P version of Wald test is a desirable alternative. We illustrate the methodologies with a real example from a heart disease study. (c) 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Relative humidity and activity patterns of Ixodes scapularis (Acari: Ixodidae)

USGS Publications Warehouse

Berger, K.A.; Ginsberg, Howard S.; Gonzalez, L.; Mather, T.N.

2014-01-01

Laboratory studies have shown clear relationships between relative humidity (RH) and the activity and survival of Ixodes scapularis Say (blacklegged tick). However, field studies have produced conflicting results. We examined this relationship using weekly tick count totals and hourly RH observations at three field sites, stratified by latitude, within the state of Rhode Island. Records of nymphal tick abundance were compared with several RH-related variables (e.g., RH at time of sampling and mean weekly daytime RH). In total, 825 nymphs were sampled in 2009, a year of greater precipitation, with a weighted average leaf litter RH recorded at time of sampling of 85.22%. Alternatively, 649 nymphs were collected in 2010, a year of relatively low precipitation, and a weighted average RH recorded at time of sampling was 75.51%. Negative binomial regression analysis of tick count totals identified cumulative hours <82% RH threshold as a significant factor observed in both years (2009: P = 0.0037; 2010: P < 0.0001). Mean weekly daytime RH did not significantly predict tick activity in either year. However, mean weekly daytime RH recorded with 1-wk lag before sample date was a significant variable (P = 0.0016) in 2010. These results suggest a lag effect between moisture availability and patterns of tick activity and abundance. Differences in the relative importance of each RH variable between years may have been due to abnormally wet summer conditions in 2009.

Development of enhanced pavement deterioration curves.

DOT National Transportation Integrated Search

2016-10-01

This report describes the research performed by the Center for Sustainable Transportation Infrastructure (CSTI) at the Virginia Tech Transportation Institute (VTTI) to develop a pavement condition prediction model, using (negative binomial) regressio...

Long-Term Ecological Monitoring Field Sampling Plan for 2007

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

T. Haney

2007-07-31

This field sampling plan describes the field investigations planned for the Long-Term Ecological Monitoring Project at the Idaho National Laboratory Site in 2007. This plan and the Quality Assurance Project Plan for Waste Area Groups 1, 2, 3, 4, 5, 6, 7, 10, and Removal Actions constitute the sampling and analysis plan supporting long-term ecological monitoring sampling in 2007. The data collected under this plan will become part of the long-term ecological monitoring data set that is being collected annually. The data will be used t determine the requirements for the subsequent long-term ecological monitoring. This plan guides the 2007more » investigations, including sampling, quality assurance, quality control, analytical procedures, and data management. As such, this plan will help to ensure that the resulting monitoring data will be scientifically valid, defensible, and of known and acceptable quality.« less

Indicators of Terrorism Vulnerability in Africa

DTIC Science & Technology

2015-03-26

the terror threat and vulnerabilities across Africa. Key words: Terrorism, Africa, Negative Binomial Regression, Classification Tree iv I would like...31 Metrics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 Log -likelihood...70 viii Page 5.3 Classification Tree Description

Points on the Path to Probability.

ERIC Educational Resources Information Center

Kiernan, James F.

2001-01-01

Presents the problem of points and the development of the binomial triangle, or Pascal's triangle. Examines various attempts to solve this problem to give students insight into the nature of mathematical discovery. (KHR)

Conditional analysis of mixed Poisson processes with baseline counts: implications for trial design and analysis.

PubMed

Cook, Richard J; Wei, Wei

2003-07-01

The design of clinical trials is typically based on marginal comparisons of a primary response under two or more treatments. The considerable gains in efficiency afforded by models conditional on one or more baseline responses has been extensively studied for Gaussian models. The purpose of this article is to present methods for the design and analysis of clinical trials in which the response is a count or a point process, and a corresponding baseline count is available prior to randomization. The methods are based on a conditional negative binomial model for the response given the baseline count and can be used to examine the effect of introducing selection criteria on power and sample size requirements. We show that designs based on this approach are more efficient than those proposed by McMahon et al. (1994).

Child Schooling in Ethiopia: The Role of Maternal Autonomy.

PubMed

Gebremedhin, Tesfaye Alemayehu; Mohanty, Itismita

2016-01-01

This paper examines the effects of maternal autonomy on child schooling outcomes in Ethiopia using a nationally representative Ethiopian Demographic and Health survey for 2011. The empirical strategy uses a Hurdle Negative Binomial Regression model to estimate years of schooling. An ordered probit model is also estimated to examine age grade distortion using a trichotomous dependent variable that captures three states of child schooling. The large sample size and the range of questions available in this dataset allow us to explore the influence of individual and household level social, economic and cultural factors on child schooling. The analysis finds statistically significant effects of maternal autonomy variables on child schooling in Ethiopia. The roles of maternal autonomy and other household-level factors on child schooling are important issues in Ethiopia, where health and education outcomes are poor for large segments of the population.

Comparison of the efficiency between two sampling plans for aflatoxins analysis in maize

PubMed Central

Mallmann, Adriano Olnei; Marchioro, Alexandro; Oliveira, Maurício Schneider; Rauber, Ricardo Hummes; Dilkin, Paulo; Mallmann, Carlos Augusto

2014-01-01

Variance and performance of two sampling plans for aflatoxins quantification in maize were evaluated. Eight lots of maize were sampled using two plans: manual, using sampling spear for kernels; and automatic, using a continuous flow to collect milled maize. Total variance and sampling, preparation, and analysis variance were determined and compared between plans through multifactor analysis of variance. Four theoretical distribution models were used to compare aflatoxins quantification distributions in eight maize lots. The acceptance and rejection probabilities for a lot under certain aflatoxin concentration were determined using variance and the information on the selected distribution model to build the operational characteristic curves (OC). Sampling and total variance were lower at the automatic plan. The OC curve from the automatic plan reduced both consumer and producer risks in comparison to the manual plan. The automatic plan is more efficient than the manual one because it expresses more accurately the real aflatoxin contamination in maize. PMID:24948911

Matching the Statistical Model to the Research Question for Dental Caries Indices with Many Zero Counts.

PubMed

Preisser, John S; Long, D Leann; Stamm, John W

2017-01-01

Marginalized zero-inflated count regression models have recently been introduced for the statistical analysis of dental caries indices and other zero-inflated count data as alternatives to traditional zero-inflated and hurdle models. Unlike the standard approaches, the marginalized models directly estimate overall exposure or treatment effects by relating covariates to the marginal mean count. This article discusses model interpretation and model class choice according to the research question being addressed in caries research. Two data sets, one consisting of fictional dmft counts in 2 groups and the other on DMFS among schoolchildren from a randomized clinical trial comparing 3 toothpaste formulations to prevent incident dental caries, are analyzed with negative binomial hurdle, zero-inflated negative binomial, and marginalized zero-inflated negative binomial models. In the first example, estimates of treatment effects vary according to the type of incidence rate ratio (IRR) estimated by the model. Estimates of IRRs in the analysis of the randomized clinical trial were similar despite their distinctive interpretations. The choice of statistical model class should match the study's purpose, while accounting for the broad decline in children's caries experience, such that dmft and DMFS indices more frequently generate zero counts. Marginalized (marginal mean) models for zero-inflated count data should be considered for direct assessment of exposure effects on the marginal mean dental caries count in the presence of high frequencies of zero counts. © 2017 S. Karger AG, Basel.

Matching the Statistical Model to the Research Question for Dental Caries Indices with Many Zero Counts

PubMed Central

Preisser, John S.; Long, D. Leann; Stamm, John W.

2017-01-01

Marginalized zero-inflated count regression models have recently been introduced for the statistical analysis of dental caries indices and other zero-inflated count data as alternatives to traditional zero-inflated and hurdle models. Unlike the standard approaches, the marginalized models directly estimate overall exposure or treatment effects by relating covariates to the marginal mean count. This article discusses model interpretation and model class choice according to the research question being addressed in caries research. Two datasets, one consisting of fictional dmft counts in two groups and the other on DMFS among schoolchildren from a randomized clinical trial (RCT) comparing three toothpaste formulations to prevent incident dental caries, are analysed with negative binomial hurdle (NBH), zero-inflated negative binomial (ZINB), and marginalized zero-inflated negative binomial (MZINB) models. In the first example, estimates of treatment effects vary according to the type of incidence rate ratio (IRR) estimated by the model. Estimates of IRRs in the analysis of the RCT were similar despite their distinctive interpretations. Choice of statistical model class should match the study’s purpose, while accounting for the broad decline in children’s caries experience, such that dmft and DMFS indices more frequently generate zero counts. Marginalized (marginal mean) models for zero-inflated count data should be considered for direct assessment of exposure effects on the marginal mean dental caries count in the presence of high frequencies of zero counts. PMID:28291962

Linnaean sources and concepts of orchids.

PubMed

Jarvis, Charlie; Cribb, Phillip

2009-08-01

Linnaeus developed a robust system for naming plants and a useful, if mechanical, system for classifying them. His binomial nomenclature proved the catalyst for the rapid development of our knowledge of orchids, with his work on the family dating back to 1737 in the first edition of his Genera Plantarum. His first work devoted to orchids, indeed the first monograph of the family, was published in 1740 and formed the basis for his account in Species Plantarum, published in 1753, in which he gave a binomial name to each species. Given the overwhelming number of orchids, he included surprisingly few - only 62 mostly European species - in Species Plantarum, his seminal work on the plants of the world. This reflects the European origin of modern botany and the concentration of extra-European exploration on other matters, such as conquest, gold and useful plants. Nevertheless, the scope of Linnaeus' work is broad, including plants from as far afield as India, Japan, China and the Philippines to the east, and eastern Canada, the West Indies and northern South America to the west. In his later publications he described and named a further 45 orchids, mostly from Europe, South Africa and the tropical Americas. The philosophical basis of Linnaeus' work on orchids is discussed and his contribution to our knowledge of the family assessed. His generic and species concepts are considered in the light of current systematic ideas, but his adoption of binomial nomenclature for all plants is his lasting legacy.

Time-dependent summary receiver operating characteristics for meta-analysis of prognostic studies.

PubMed

Hattori, Satoshi; Zhou, Xiao-Hua

2016-11-20

Prognostic studies are widely conducted to examine whether biomarkers are associated with patient's prognoses and play important roles in medical decisions. Because findings from one prognostic study may be very limited, meta-analyses may be useful to obtain sound evidence. However, prognostic studies are often analyzed by relying on a study-specific cut-off value, which can lead to difficulty in applying the standard meta-analysis techniques. In this paper, we propose two methods to estimate a time-dependent version of the summary receiver operating characteristics curve for meta-analyses of prognostic studies with a right-censored time-to-event outcome. We introduce a bivariate normal model for the pair of time-dependent sensitivity and specificity and propose a method to form inferences based on summary statistics reported in published papers. This method provides a valid inference asymptotically. In addition, we consider a bivariate binomial model. To draw inferences from this bivariate binomial model, we introduce a multiple imputation method. The multiple imputation is found to be approximately proper multiple imputation, and thus the standard Rubin's variance formula is justified from a Bayesian view point. Our simulation study and application to a real dataset revealed that both methods work well with a moderate or large number of studies and the bivariate binomial model coupled with the multiple imputation outperforms the bivariate normal model with a small number of studies. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

CROSSER - CUMULATIVE BINOMIAL PROGRAMS

NASA Technical Reports Server (NTRS)

Bowerman, P. N.

1994-01-01

The cumulative binomial program, CROSSER, is one of a set of three programs which calculate cumulative binomial probability distributions for arbitrary inputs. The three programs, CROSSER, CUMBIN (NPO-17555), and NEWTONP (NPO-17556), can be used independently of one another. CROSSER can be used by statisticians and users of statistical procedures, test planners, designers, and numerical analysts. The program has been used for reliability/availability calculations. CROSSER calculates the point at which the reliability of a k-out-of-n system equals the common reliability of the n components. It is designed to work well with all integer values 0 < k <= n. To run the program, the user simply runs the executable version and inputs the information requested by the program. The program is not designed to weed out incorrect inputs, so the user must take care to make sure the inputs are correct. Once all input has been entered, the program calculates and lists the result. It also lists the number of iterations of Newton's method required to calculate the answer within the given error. The CROSSER program is written in C. It was developed on an IBM AT with a numeric co-processor using Microsoft C 5.0. Because the source code is written using standard C structures and functions, it should compile correctly with most C compilers. The program format is interactive. It has been implemented under DOS 3.2 and has a memory requirement of 26K. CROSSER was developed in 1988.

Linnaean sources and concepts of orchids

PubMed Central

Jarvis, Charlie; Cribb, Phillip

2009-01-01

Background Linnaeus developed a robust system for naming plants and a useful, if mechanical, system for classifying them. His binomial nomenclature proved the catalyst for the rapid development of our knowledge of orchids, with his work on the family dating back to 1737 in the first edition of his Genera Plantarum. His first work devoted to orchids, indeed the first monograph of the family, was published in 1740 and formed the basis for his account in Species Plantarum, published in 1753, in which he gave a binomial name to each species. Given the overwhelming number of orchids, he included surprisingly few – only 62 mostly European species – in Species Plantarum, his seminal work on the plants of the world. This reflects the European origin of modern botany and the concentration of extra-European exploration on other matters, such as conquest, gold and useful plants. Nevertheless, the scope of Linnaeus' work is broad, including plants from as far afield as India, Japan, China and the Philippines to the east, and eastern Canada, the West Indies and northern South America to the west. In his later publications he described and named a further 45 orchids, mostly from Europe, South Africa and the tropical Americas. Scope The philosophical basis of Linnaeus' work on orchids is discussed and his contribution to our knowledge of the family assessed. His generic and species concepts are considered in the light of current systematic ideas, but his adoption of binomial nomenclature for all plants is his lasting legacy. PMID:19182221

7 CFR 43.103 - Purpose and scope.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing... SAMPLING PLANS Sampling Plans § 43.103 Purpose and scope. (a) This subpart contains selected single and double sampling plans for inspection by attributes. They are to serve as a source of plans for developing...

A time series model: First-order integer-valued autoregressive (INAR(1))

NASA Astrophysics Data System (ADS)

Simarmata, D. M.; Novkaniza, F.; Widyaningsih, Y.

2017-07-01

Nonnegative integer-valued time series arises in many applications. A time series model: first-order Integer-valued AutoRegressive (INAR(1)) is constructed by binomial thinning operator to model nonnegative integer-valued time series. INAR (1) depends on one period from the process before. The parameter of the model can be estimated by Conditional Least Squares (CLS). Specification of INAR(1) is following the specification of (AR(1)). Forecasting in INAR(1) uses median or Bayesian forecasting methodology. Median forecasting methodology obtains integer s, which is cumulative density function (CDF) until s, is more than or equal to 0.5. Bayesian forecasting methodology forecasts h-step-ahead of generating the parameter of the model and parameter of innovation term using Adaptive Rejection Metropolis Sampling within Gibbs sampling (ARMS), then finding the least integer s, where CDF until s is more than or equal to u . u is a value taken from the Uniform(0,1) distribution. INAR(1) is applied on pneumonia case in Penjaringan, Jakarta Utara, January 2008 until April 2016 monthly.

Construction of CASCI-type wave functions for very large active spaces.

PubMed

Boguslawski, Katharina; Marti, Konrad H; Reiher, Markus

2011-06-14

We present a procedure to construct a configuration-interaction expansion containing arbitrary excitations from an underlying full-configuration-interaction-type wave function defined for a very large active space. Our procedure is based on the density-matrix renormalization group (DMRG) algorithm that provides the necessary information in terms of the eigenstates of the reduced density matrices to calculate the coefficient of any basis state in the many-particle Hilbert space. Since the dimension of the Hilbert space scales binomially with the size of the active space, a sophisticated Monte Carlo sampling routine is employed. This sampling algorithm can also construct such configuration-interaction-type wave functions from any other type of tensor network states. The configuration-interaction information obtained serves several purposes. It yields a qualitatively correct description of the molecule's electronic structure, it allows us to analyze DMRG wave functions converged for the same molecular system but with different parameter sets (e.g., different numbers of active-system (block) states), and it can be considered a balanced reference for the application of a subsequent standard multi-reference configuration-interaction method.

Computational Aspects of N-Mixture Models

PubMed Central

Dennis, Emily B; Morgan, Byron JT; Ridout, Martin S

2015-01-01

The N-mixture model is widely used to estimate the abundance of a population in the presence of unknown detection probability from only a set of counts subject to spatial and temporal replication (Royle, 2004, Biometrics 60, 105–115). We explain and exploit the equivalence of N-mixture and multivariate Poisson and negative-binomial models, which provides powerful new approaches for fitting these models. We show that particularly when detection probability and the number of sampling occasions are small, infinite estimates of abundance can arise. We propose a sample covariance as a diagnostic for this event, and demonstrate its good performance in the Poisson case. Infinite estimates may be missed in practice, due to numerical optimization procedures terminating at arbitrarily large values. It is shown that the use of a bound, K, for an infinite summation in the N-mixture likelihood can result in underestimation of abundance, so that default values of K in computer packages should be avoided. Instead we propose a simple automatic way to choose K. The methods are illustrated by analysis of data on Hermann's tortoise Testudo hermanni. PMID:25314629

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

Marutzky, Sam; Farnham, Irene

The purpose of the Nevada National Security Site (NNSS) Integrated Sampling Plan (referred to herein as the Plan) is to provide a comprehensive, integrated approach for collecting and analyzing groundwater samples to meet the needs and objectives of the U.S. Department of Energy (DOE), National Nuclear Security Administration Nevada Field Office (NNSA/NFO) Underground Test Area (UGTA) Activity. Implementation of this Plan will provide high-quality data required by the UGTA Activity for ensuring public protection in an efficient and cost-effective manner. The Plan is designed to ensure compliance with the UGTA Quality Assurance Plan (QAP). The Plan’s scope comprises sample collectionmore » and analysis requirements relevant to assessing the extent of groundwater contamination from underground nuclear testing. This Plan identifies locations to be sampled by corrective action unit (CAU) and location type, sampling frequencies, sample collection methodologies, and the constituents to be analyzed. In addition, the Plan defines data collection criteria such as well-purging requirements, detection levels, and accuracy requirements; identifies reporting and data management requirements; and provides a process to ensure coordination between NNSS groundwater sampling programs for sampling of interest to UGTA. This Plan does not address compliance with requirements for wells that supply the NNSS public water system or wells involved in a permitted activity.« less

Chain sampling plan (ChSP-1) for desired acceptable quality level (AQL) and limiting quality level (LQL)

NASA Astrophysics Data System (ADS)

Raju, C.; Vidya, R.

2017-11-01

Chain Sampling Plan is widely used whenever a small sample attributes plan is required to be used for situations involving destructive products coming out of continuous production process [1, 2]. This paper presents a procedure for the construction and selection of a ChSP-1 by attributes inspection based on membership functions [3]. A procedure using search technique is developed for obtaining the parameters of single sampling plan for a given set of AQL and LQL values. A sample of tables providing ChSP-1 plans for various combinations of AQL and LQL values are presented [4].

The Use of Informative Priors in Bayesian Modeling Age-at-death; a Quick Look at Chronological and Biological Age Changes in the Sacroiliac Joint in American Males.

PubMed

Godde, Kanya

2017-01-01

The aim of this study is to examine how well different informative priors model age-at-death in Bayesian statistics, which will shed light on how the skeleton ages, particularly at the sacroiliac joint. Data from four samples were compared for their performance as informative priors for auricular surface age-at-death estimation: (1) American population from US Census data; (2) county data from the US Census data; (3) a local cemetery; and (4) a skeletal collection. The skeletal collection and cemetery are located within the county that was sampled. A Gompertz model was applied to compare survivorship across the four samples. Transition analysis parameters, coupled with the generated Gompertz parameters, were input into Bayes' theorem to generate highest posterior density ranges from posterior density functions. Transition analysis describes the age at which an individual transitions from one age phase to another. The result is age ranges that should describe the chronological age of 90% of the individuals who fall in a particular phase. Cumulative binomial tests indicate the method performed lower than 90% at capturing chronological age as assigned to a biological phase, despite wide age ranges at older ages. The samples performed similarly overall, despite small differences in survivorship. Collectively, these results show that as we age, the senescence pattern becomes more variable. More local samples performed better at describing the aging process than more general samples, which implies practitioners need to consider sample selection when using the literature to diagnose and work with patients with sacroiliac joint pain.

Comparing ELISA test-positive prevalence, risk factors and management recommendations for Johne's disease prevention between organic and conventional dairy farms in Ontario, Canada.

PubMed

Pieper, Laura; Sorge, Ulrike S; DeVries, Trevor; Godkin, Ann; Lissemore, Kerry; Kelton, David

2015-11-01

Johne's disease (JD) is a chronic, infectious disease in cattle. Between 2010 and 2013, a voluntary JD control program was successfully launched in Ontario, Canada, including a Risk Assessment and Management Plan (RAMP) and JD ELISA testing of the entire milking herd. Over the last decade, the organic dairy sector has been growing. However, organic farming regulations and philosophies may influence the risk for JD transmission on Ontario organic dairy farms. The aim of this cross-sectional study was to investigate differences in JD ELISA test positive prevalence, risk factors for JD and recommendations for JD prevention between organic and conventional dairy herds in Ontario. RAMP results (i.e. RAMP scores and recommendations) and ELISA results were available for 2103 dairy herds, including 42 organic herds. If available, additional data on milk production, milk quality, and herd characteristics were gathered. Organic and conventional herds had a similar herd-level JD ELISA test-positive prevalence (26.2% and 27.2%, respectively). Organic herds (4.2%) had a higher within-herd JD ELISA test-positive prevalence compared to conventional herds (2.3%) if they had at least one JD test-positive animal on the farm. Organic farms had lower risk scores for biosecurity (9 points lower), and higher scores in the calving (7 points higher) and the calf-rearing management areas (4 points higher). After accounting for RAMP score, organic farms received fewer recommendations for the calving management area (Odds Ratio=0.41) and more recommendations in the adult cow management area (Odds Ratio=2.70). A zero-inflated negative binomial model was built with purchase of animals and the herd size included in the logistic portion of the model. Herd type (organic or conventional), colostrum and milk feeding practices, average bulk tank somatic cell count, and presence of non-Holstein breeds were included in the negative binomial portion of the model. Organic farms had a higher number of test positive animals (Count Ratio=2.02). Further research is necessary to investigate the apparent disconnect between risk factors and recommendations on organic dairy farms. Copyright © 2015 Elsevier B.V. All rights reserved.

Introductory Statistics in the Garden

ERIC Educational Resources Information Center

Wagaman, John C.

2017-01-01

This article describes four semesters of introductory statistics courses that incorporate service learning and gardening into the curriculum with applications of the binomial distribution, least squares regression and hypothesis testing. The activities span multiple semesters and are iterative in nature.

Covering Resilience: A Recent Development for Binomial Checkpointing

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

Walther, Andrea; Narayanan, Sri Hari Krishna

In terms of computing time, adjoint methods offer a very attractive alternative to compute gradient information, required, e.g., for optimization purposes. However, together with this very favorable temporal complexity result comes a memory requirement that is in essence proportional with the operation count of the underlying function, e.g., if algorithmic differentiation is used to provide the adjoints. For this reason, checkpointing approaches in many variants have become popular. This paper analyzes an extension of the so-called binomial approach to cover also possible failures of the computing systems. Such a measure of precaution is of special interest for massive parallel simulationsmore » and adjoint calculations where the mean time between failure of the large scale computing system is smaller than the time needed to complete the calculation of the adjoint information. We describe the extensions of standard checkpointing approaches required for such resilience, provide a corresponding implementation and discuss first numerical results.« less

Gamma Oscillations of Spiking Neural Populations Enhance Signal Discrimination

PubMed Central

Masuda, Naoki; Doiron, Brent

2007-01-01

Selective attention is an important filter for complex environments where distractions compete with signals. Attention increases both the gamma-band power of cortical local field potentials and the spike-field coherence within the receptive field of an attended object. However, the mechanisms by which gamma-band activity enhances, if at all, the encoding of input signals are not well understood. We propose that gamma oscillations induce binomial-like spike-count statistics across noisy neural populations. Using simplified models of spiking neurons, we show how the discrimination of static signals based on the population spike-count response is improved with gamma induced binomial statistics. These results give an important mechanistic link between the neural correlates of attention and the discrimination tasks where attention is known to enhance performance. Further, they show how a rhythmicity of spike responses can enhance coding schemes that are not temporally sensitive. PMID:18052541

Application of a hurdle negative binomial count data model to demand for bass fishing in the southeastern United States.

PubMed

Bilgic, Abdulbaki; Florkowski, Wojciech J

2007-06-01

This paper identifies factors that influence the demand for a bass fishing trip taken in the southeastern United States using a hurdle negative binomial count data model. The probability of fishing for a bass is estimated in the first stage and the fishing trip frequency is estimated in the second stage for individuals reporting bass fishing trips in the Southeast. The applied approach allows the decomposition of the effects of factors responsible for the decision to take a trip and the trip number. Calculated partial and total elasticities indicate a highly inelastic demand for the number of fishing trips as trip costs increase. However, the demand can be expected to increase if anglers experience a success measured by the number of caught fish or their size. Benefit estimates based on alternative estimation methods differ substantially, suggesting the need for testing each modeling approach applied in empirical studies.

Joint multifractal analysis based on the partition function approach: analytical analysis, numerical simulation and empirical application

NASA Astrophysics Data System (ADS)

Xie, Wen-Jie; Jiang, Zhi-Qiang; Gu, Gao-Feng; Xiong, Xiong; Zhou, Wei-Xing

2015-10-01

Many complex systems generate multifractal time series which are long-range cross-correlated. Numerous methods have been proposed to characterize the multifractal nature of these long-range cross correlations. However, several important issues about these methods are not well understood and most methods consider only one moment order. We study the joint multifractal analysis based on partition function with two moment orders, which was initially invented to investigate fluid fields, and derive analytically several important properties. We apply the method numerically to binomial measures with multifractal cross correlations and bivariate fractional Brownian motions without multifractal cross correlations. For binomial multifractal measures, the explicit expressions of mass function, singularity strength and multifractal spectrum of the cross correlations are derived, which agree excellently with the numerical results. We also apply the method to stock market indexes and unveil intriguing multifractality in the cross correlations of index volatilities.

Spatiotemporal and random parameter panel data models of traffic crash fatalities in Vietnam.

PubMed

Truong, Long T; Kieu, Le-Minh; Vu, Tuan A

2016-09-01

This paper investigates factors associated with traffic crash fatalities in 63 provinces of Vietnam during the period from 2012 to 2014. Random effect negative binomial (RENB) and random parameter negative binomial (RPNB) panel data models are adopted to consider spatial heterogeneity across provinces. In addition, a spatiotemporal model with conditional autoregressive priors (ST-CAR) is utilised to account for spatiotemporal autocorrelation in the data. The statistical comparison indicates the ST-CAR model outperforms the RENB and RPNB models. Estimation results provide several significant findings. For example, traffic crash fatalities tend to be higher in provinces with greater numbers of level crossings. Passenger distance travelled and road lengths are also positively associated with fatalities. However, hospital densities are negatively associated with fatalities. The safety impact of the national highway 1A, the main transport corridor of the country, is also highlighted. Copyright © 2016 Elsevier Ltd. All rights reserved.

A comparison of LMC and SDL complexity measures on binomial distributions

NASA Astrophysics Data System (ADS)

Piqueira, José Roberto C.

2016-02-01

The concept of complexity has been widely discussed in the last forty years, with a lot of thinking contributions coming from all areas of the human knowledge, including Philosophy, Linguistics, History, Biology, Physics, Chemistry and many others, with mathematicians trying to give a rigorous view of it. In this sense, thermodynamics meets information theory and, by using the entropy definition, López-Ruiz, Mancini and Calbet proposed a definition for complexity that is referred as LMC measure. Shiner, Davison and Landsberg, by slightly changing the LMC definition, proposed the SDL measure and the both, LMC and SDL, are satisfactory to measure complexity for a lot of problems. Here, SDL and LMC measures are applied to the case of a binomial probability distribution, trying to clarify how the length of the data set implies complexity and how the success probability of the repeated trials determines how complex the whole set is.

Extended Poisson process modelling and analysis of grouped binary data.

PubMed

Faddy, Malcolm J; Smith, David M

2012-05-01

A simple extension of the Poisson process results in binomially distributed counts of events in a time interval. A further extension generalises this to probability distributions under- or over-dispersed relative to the binomial distribution. Substantial levels of under-dispersion are possible with this modelling, but only modest levels of over-dispersion - up to Poisson-like variation. Although simple analytical expressions for the moments of these probability distributions are not available, approximate expressions for the mean and variance are derived, and used to re-parameterise the models. The modelling is applied in the analysis of two published data sets, one showing under-dispersion and the other over-dispersion. More appropriate assessment of the precision of estimated parameters and reliable model checking diagnostics follow from this more general modelling of these data sets. © 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

A comparative study of count models: application to pedestrian-vehicle crashes along Malaysia federal roads.

PubMed

Hosseinpour, Mehdi; Pour, Mehdi Hossein; Prasetijo, Joewono; Yahaya, Ahmad Shukri; Ghadiri, Seyed Mohammad Reza

2013-01-01

The objective of this study was to examine the effects of various roadway characteristics on the incidence of pedestrian-vehicle crashes by developing a set of crash prediction models on 543 km of Malaysia federal roads over a 4-year time span between 2007 and 2010. Four count models including the Poisson, negative binomial (NB), hurdle Poisson (HP), and hurdle negative binomial (HNB) models were developed and compared to model the number of pedestrian crashes. The results indicated the presence of overdispersion in the pedestrian crashes (PCs) and showed that it is due to excess zero rather than variability in the crash data. To handle the issue, the hurdle Poisson model was found to be the best model among the considered models in terms of comparative measures. Moreover, the variables average daily traffic, heavy vehicle traffic, speed limit, land use, and area type were significantly associated with PCs.

Inferring subunit stoichiometry from single molecule photobleaching

PubMed Central

2013-01-01

Single molecule photobleaching is a powerful tool for determining the stoichiometry of protein complexes. By attaching fluorophores to proteins of interest, the number of associated subunits in a complex can be deduced by imaging single molecules and counting fluorophore photobleaching steps. Because some bleaching steps might be unobserved, the ensemble of steps will be binomially distributed. In this work, it is shown that inferring the true composition of a complex from such data is nontrivial because binomially distributed observations present an ill-posed inference problem. That is, a unique and optimal estimate of the relevant parameters cannot be extracted from the observations. Because of this, a method has not been firmly established to quantify confidence when using this technique. This paper presents a general inference model for interpreting such data and provides methods for accurately estimating parameter confidence. The formalization and methods presented here provide a rigorous analytical basis for this pervasive experimental tool. PMID:23712552

WHAMII - An enumeration and insertion procedure with binomial bounds for the stochastic time-constrained traveling salesman problem

NASA Technical Reports Server (NTRS)

Dahl, Roy W.; Keating, Karen; Salamone, Daryl J.; Levy, Laurence; Nag, Barindra; Sanborn, Joan A.

1987-01-01

This paper presents an algorithm (WHAMII) designed to solve the Artificial Intelligence Design Challenge at the 1987 AIAA Guidance, Navigation and Control Conference. The problem under consideration is a stochastic generalization of the traveling salesman problem in which travel costs can incur a penalty with a given probability. The variability in travel costs leads to a probability constraint with respect to violating the budget allocation. Given the small size of the problem (eleven cities), an approach is considered that combines partial tour enumeration with a heuristic city insertion procedure. For computational efficiency during both the enumeration and insertion procedures, precalculated binomial probabilities are used to determine an upper bound on the actual probability of violating the budget constraint for each tour. The actual probability is calculated for the final best tour, and additional insertions are attempted until the actual probability exceeds the bound.

Is “Hit and Run” a Single Word? The Processing of Irreversible Binomials in Neglect Dyslexia

PubMed Central

Arcara, Giorgio; Lacaita, Graziano; Mattaloni, Elisa; Passarini, Laura; Mondini, Sara; Benincà, Paola; Semenza, Carlo

2012-01-01

The present study is the first neuropsychological investigation into the problem of the mental representation and processing of irreversible binomials (IBs), i.e., word pairs linked by a conjunction (e.g., “hit and run,” “dead or alive”). In order to test their lexical status, the phenomenon of neglect dyslexia is explored. People with left-sided neglect dyslexia show a clear lexical effect: they can read IBs better (i.e., by dropping the leftmost words less frequently) when their components are presented in their correct order. This may be taken as an indication that they treat these constructions as lexical, not decomposable, elements. This finding therefore constitutes strong evidence that IBs tend to be stored in the mental lexicon as a whole and that this whole form is preferably addressed in the retrieval process. PMID:22347199

Safety models incorporating graph theory based transit indicators.

PubMed

Quintero, Liliana; Sayed, Tarek; Wahba, Mohamed M

2013-01-01

There is a considerable need for tools to enable the evaluation of the safety of transit networks at the planning stage. One interesting approach for the planning of public transportation systems is the study of networks. Network techniques involve the analysis of systems by viewing them as a graph composed of a set of vertices (nodes) and edges (links). Once the transport system is visualized as a graph, various network properties can be evaluated based on the relationships between the network elements. Several indicators can be calculated including connectivity, coverage, directness and complexity, among others. The main objective of this study is to investigate the relationship between network-based transit indicators and safety. The study develops macro-level collision prediction models that explicitly incorporate transit physical and operational elements and transit network indicators as explanatory variables. Several macro-level (zonal) collision prediction models were developed using a generalized linear regression technique, assuming a negative binomial error structure. The models were grouped into four main themes: transit infrastructure, transit network topology, transit route design, and transit performance and operations. The safety models showed that collisions were significantly associated with transit network properties such as: connectivity, coverage, overlapping degree and the Local Index of Transit Availability. As well, the models showed a significant relationship between collisions and some transit physical and operational attributes such as the number of routes, frequency of routes, bus density, length of bus and 3+ priority lanes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Reductions in Diagnostic Imaging With High Deductible Health Plans.

PubMed

Zheng, Sarah; Ren, Zhong Justin; Heineke, Janelle; Geissler, Kimberley H

2016-02-01

Diagnostic imaging utilization grew rapidly over the past 2 decades. It remains unclear whether patient cost-sharing is an effective policy lever to reduce imaging utilization and spending. Using 2010 commercial insurance claims data of >21 million individuals, we compared diagnostic imaging utilization and standardized payments between High Deductible Health Plan (HDHP) and non-HDHP enrollees. Negative binomial models were used to estimate associations between HDHP enrollment and utilization, and were repeated for standardized payments. A Hurdle model were used to estimate associations between HDHP enrollment and whether an enrollee had diagnostic imaging, and then the magnitude of associations for enrollees with imaging. Models with interaction terms were used to estimate associations between HDHP enrollment and imaging by risk score tercile. All models included controls for patient age, sex, geographic location, and health status. HDHP enrollment was associated with a 7.5% decrease in the number of imaging studies and a 10.2% decrease in standardized imaging payments. HDHP enrollees were 1.8% points less likely to use imaging; once an enrollee had at least 1 imaging study, differences in utilization and associated payments were small. Associations between HDHP and utilization were largest in the lowest (least sick) risk score tercile. Increased patient cost-sharing may contribute to reductions in diagnostic imaging utilization and spending. However, increased cost-sharing may not encourage patients to differentiate between high-value and low-value diagnostic imaging services; better patient awareness and education may be a crucial part of any reductions in diagnostic imaging utilization.

Sampling and Analysis Plan for U.S. Department of Energy Office of Legacy Management Sites

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

None

2012-10-24

This plan incorporates U.S. Department of Energy (DOE) Office of Legacy Management (LM) standard operating procedures (SOPs) into environmental monitoring activities and will be implemented at all sites managed by LM. This document provides detailed procedures for the field sampling teams so that samples are collected in a consistent and technically defensible manner. Site-specific plans (e.g., long-term surveillance and maintenance plans, environmental monitoring plans) document background information and establish the basis for sampling and monitoring activities. Information will be included in site-specific tabbed sections to this plan, which identify sample locations, sample frequencies, types of samples, field measurements, and associatedmore » analytes for each site. Additionally, within each tabbed section, program directives will be included, when developed, to establish additional site-specific requirements to modify or clarify requirements in this plan as they apply to the corresponding site. A flowchart detailing project tasks required to accomplish routine sampling is displayed in Figure 1. LM environmental procedures are contained in the Environmental Procedures Catalog (LMS/PRO/S04325), which incorporates American Society for Testing and Materials (ASTM), DOE, and U.S. Environmental Protection Agency (EPA) guidance. Specific procedures used for groundwater and surface water monitoring are included in Appendix A. If other environmental media are monitored, SOPs used for air, soil/sediment, and biota monitoring can be found in the site-specific tabbed sections in Appendix D or in site-specific documents. The procedures in the Environmental Procedures Catalog are intended as general guidance and require additional detail from planning documents in order to be complete; the following sections fulfill that function and specify additional procedural requirements to form SOPs. Routine revision of this Sampling and Analysis Plan will be conducted annually at the beginning of each fiscal year when attachments in Appendix D, including program directives and sampling location/analytical tables, will be reviewed by project personnel and updated. The sampling location/analytical tables in Appendix D, however, may have interim updates according to project direction that are not reflected in this plan. Deviations from location/analytical tables in Appendix D prior to sampling will be documented in project correspondence (e.g., startup letters). If significant changes to other aspects of this plan are required before the annual update, then the plan will be revised as needed.« less

40 CFR 265.92 - Sampling and analysis.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 25 2010-07-01 2010-07-01 false Sampling and analysis. 265.92 Section... FACILITIES Ground-Water Monitoring § 265.92 Sampling and analysis. (a) The owner or operator must obtain and... follow a ground-water sampling and analysis plan. He must keep this plan at the facility. The plan must...

40 CFR 265.92 - Sampling and analysis.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 40 Protection of Environment 26 2011-07-01 2011-07-01 false Sampling and analysis. 265.92 Section... FACILITIES Ground-Water Monitoring § 265.92 Sampling and analysis. (a) The owner or operator must obtain and... follow a ground-water sampling and analysis plan. He must keep this plan at the facility. The plan must...

Are Podcasts Effective at Educating African-American Men about Diabetes?

PubMed Central

Ross, Levi; Iwanenko, Walter; Schiffert, Judith; Sen, Arup

2013-01-01

Education is a critical component of the National Blueprint to eliminate racial disparities in diabetes. Research indicates that traditional methods of diabetes education has had limited effectiveness with minority populations and suggest that different educational approaches be explored. The purpose of the research was to explore the effectiveness of an emergent technology (podcast) for use in educating inner-city, African-American men about diabetes prevention. Thirty African-American men participated in self-administered, pretest-posttest surveys in August 2009. Surveys collected information on demographic characteristics, perceptions of diabetes and diabetes knowledge. Paired samples t-test was computed to evaluate pretest-posttest changes in overall knowledge. McNemar or binomial tests were computed to evaluate pretest-posttest knowledge changes on each of the 15 individual knowledge items. Diabetes knowledge scores for the sample increased from 8.27 at pretest to 10.47 at posttest (p = .001). Posttest knowledge scores increased for 77% of men, stayed the same for 13%, and decreased for 10%. Men who listened to the podcast correctly answered 40% more knowledge questions on their posttest assessments. Results from this exploratory study suggest that podcasts are useful for helping inner-city, African-American men recall diabetes prevention information. Additional research is recommended with larger randomly selected samples using more rigorous research designs. PMID:22516566

Are podcasts effective at educating African American men about diabetes?

PubMed

Johnson, Jarrett; Ross, Levi; Iwanenko, Walter; Schiffert, Judith; Sen, Arup

2012-09-01

Education is a critical component of the National Blueprint to eliminate racial disparities in diabetes. Research indicates that traditional methods of diabetes education has had limited effectiveness with minority populations and suggests that different educational approaches be explored. The purpose of the research was to explore the effectiveness of an emergent technology (podcast) for use in educating inner-city, African American men about diabetes prevention. Thirty African American men participated in self-administered, pretest-posttest surveys in August 2009. Surveys collected information on demographic characteristics, perceptions of diabetes, and diabetes knowledge. Paired samples t test was computed to evaluate pretest-posttest changes in overall knowledge. McNemar or binomial tests were computed to evaluate pretest-posttest knowledge changes on each of the 15 individual knowledge items. Diabetes knowledge scores for the sample increased from 8.27 at pretest to 10.47 at posttest (p = .001). Posttest knowledge scores increased for 77% of men, stayed the same for 13%, and decreased for 10%. Men who listened to the podcast correctly answered 40% more knowledge questions on their posttest assessments. Results from this exploratory study suggest that podcasts are useful for helping inner-city, African American men recall diabetes prevention information. Additional research is recommended with larger randomly selected samples using more rigorous research designs.

How do high cost-sharing policies for physician care affect inpatient care use and costs among people with chronic disease?

PubMed

Xin, Haichang

2015-01-01

Rapidly rising health care costs continue to be a significant concern in the United States. High cost-sharing strategies thus have been widely used to address rising health care costs. Since high cost-sharing policies can reduce needed care as well as unneeded care use, it raises the concern whether these policies for physician care are a good strategy for controlling costs among chronically ill patients, especially whether utilization and costs in inpatient care will increase in response. This study examined whether high cost sharing in physician care affects inpatient care utilization and costs differently between individuals with and without chronic conditions. Findings from this study will contribute to the insurance benefit design that can control care utilization and save costs of chronically ill individuals. Prior studies suffered from gaps that limit both internal validity and external validity of their findings. This study has its unique contributions by filling these gaps jointly. The study used data from the 2007 Medical Expenditure Panel Survey, a nationally representative sample, with a cross-sectional study design. Instrumental variable technique was used to address the endogeneity between health care utilization and cost-sharing levels. We used negative binomial regression to analyze the count data and generalized linear models for costs data. To account for national survey sampling design, weight and variance were adjusted. The study compared the effects of high cost-sharing policies on inpatient care utilization and costs between individuals with and without chronic conditions to answer the research question. The final study sample consisted of 4523 individuals; among them, 752 had hospitalizations. The multivariate analysis demonstrated consistent patterns. Compared with low cost-sharing policies, high cost-sharing policies for physician care were not associated with a greater increase in inpatient care utilization (P = .86 for chronically ill people and P = .67 for healthy people, respectively) and costs (P = .38 for chronically ill people and P = .68 for healthy people, respectively). The sensitivity analysis with a 10% cost-sharing level also generated consistent insignificant results for both chronically ill and healthy groups. Relative to nonchronically ill individuals, chronically ill individuals may increase their utilization and expenditures of inpatient care to a similar extent in response to increased physician care cost sharing. This may be due to cost pressure from inpatient care and short observation window. Although this study did not find evidence that high cost-sharing policies for physician care increase inpatient care differently for individuals with and without chronic conditions, interpretation of this finding should be cautious. It is possible that in the long run, these sick people would demonstrate substantial demands for medical care and there could be a total cost increase for health plans ultimately. Health plans need to be cautious of policies for chronically ill enrollees.

Choosing a Cluster Sampling Design for Lot Quality Assurance Sampling Surveys

PubMed Central

Hund, Lauren; Bedrick, Edward J.; Pagano, Marcello

2015-01-01

Lot quality assurance sampling (LQAS) surveys are commonly used for monitoring and evaluation in resource-limited settings. Recently several methods have been proposed to combine LQAS with cluster sampling for more timely and cost-effective data collection. For some of these methods, the standard binomial model can be used for constructing decision rules as the clustering can be ignored. For other designs, considered here, clustering is accommodated in the design phase. In this paper, we compare these latter cluster LQAS methodologies and provide recommendations for choosing a cluster LQAS design. We compare technical differences in the three methods and determine situations in which the choice of method results in a substantively different design. We consider two different aspects of the methods: the distributional assumptions and the clustering parameterization. Further, we provide software tools for implementing each method and clarify misconceptions about these designs in the literature. We illustrate the differences in these methods using vaccination and nutrition cluster LQAS surveys as example designs. The cluster methods are not sensitive to the distributional assumptions but can result in substantially different designs (sample sizes) depending on the clustering parameterization. However, none of the clustering parameterizations used in the existing methods appears to be consistent with the observed data, and, consequently, choice between the cluster LQAS methods is not straightforward. Further research should attempt to characterize clustering patterns in specific applications and provide suggestions for best-practice cluster LQAS designs on a setting-specific basis. PMID:26125967

Choosing a Cluster Sampling Design for Lot Quality Assurance Sampling Surveys.

PubMed

Hund, Lauren; Bedrick, Edward J; Pagano, Marcello

2015-01-01

Lot quality assurance sampling (LQAS) surveys are commonly used for monitoring and evaluation in resource-limited settings. Recently several methods have been proposed to combine LQAS with cluster sampling for more timely and cost-effective data collection. For some of these methods, the standard binomial model can be used for constructing decision rules as the clustering can be ignored. For other designs, considered here, clustering is accommodated in the design phase. In this paper, we compare these latter cluster LQAS methodologies and provide recommendations for choosing a cluster LQAS design. We compare technical differences in the three methods and determine situations in which the choice of method results in a substantively different design. We consider two different aspects of the methods: the distributional assumptions and the clustering parameterization. Further, we provide software tools for implementing each method and clarify misconceptions about these designs in the literature. We illustrate the differences in these methods using vaccination and nutrition cluster LQAS surveys as example designs. The cluster methods are not sensitive to the distributional assumptions but can result in substantially different designs (sample sizes) depending on the clustering parameterization. However, none of the clustering parameterizations used in the existing methods appears to be consistent with the observed data, and, consequently, choice between the cluster LQAS methods is not straightforward. Further research should attempt to characterize clustering patterns in specific applications and provide suggestions for best-practice cluster LQAS designs on a setting-specific basis.

Generalized binomial τ-leap method for biochemical kinetics incorporating both delay and intrinsic noise

NASA Astrophysics Data System (ADS)

Leier, André; Marquez-Lago, Tatiana T.; Burrage, Kevin

2008-05-01

The delay stochastic simulation algorithm (DSSA) by Barrio et al. [Plos Comput. Biol. 2, 117(E) (2006)] was developed to simulate delayed processes in cell biology in the presence of intrinsic noise, that is, when there are small-to-moderate numbers of certain key molecules present in a chemical reaction system. These delayed processes can faithfully represent complex interactions and mechanisms that imply a number of spatiotemporal processes often not explicitly modeled such as transcription and translation, basic in the modeling of cell signaling pathways. However, for systems with widely varying reaction rate constants or large numbers of molecules, the simulation time steps of both the stochastic simulation algorithm (SSA) and the DSSA can become very small causing considerable computational overheads. In order to overcome the limit of small step sizes, various τ-leap strategies have been suggested for improving computational performance of the SSA. In this paper, we present a binomial τ-DSSA method that extends the τ-leap idea to the delay setting and avoids drawing insufficient numbers of reactions, a common shortcoming of existing binomial τ-leap methods that becomes evident when dealing with complex chemical interactions. The resulting inaccuracies are most evident in the delayed case, even when considering reaction products as potential reactants within the same time step in which they are produced. Moreover, we extend the framework to account for multicellular systems with different degrees of intercellular communication. We apply these ideas to two important genetic regulatory models, namely, the hes1 gene, implicated as a molecular clock, and a Her1/Her 7 model for coupled oscillating cells.

Modeling left-turn crash occurrence at signalized intersections by conflicting patterns.

PubMed

Wang, Xuesong; Abdel-Aty, Mohamed

2008-01-01

In order to better understand the underlying crash mechanisms, left-turn crashes occurring at 197 four-legged signalized intersections over 6 years were classified into nine patterns based on vehicle maneuvers and then were assigned to intersection approaches. Crash frequency of each pattern was modeled at the approach level by mainly using Generalized Estimating Equations (GEE) with the Negative Binomial as the link function to account for the correlation among the crash data. GEE with a binomial logit link function was also applied for patterns with fewer crashes. The Cumulative Residuals test shows that, for correlated left-turn crashes, GEE models usually outperformed basic Negative Binomial models. The estimation results show that there are obvious differences in the factors that cause the occurrence of different left-turn collision patterns. For example, for each pattern, the traffic flows to which the colliding vehicles belong are identified to be significant. The width of the crossing distance (represented by the number of through lanes on the opposing approach of the left-turning traffic) is associated with more left-turn traffic colliding with opposing through traffic (Pattern 5), but with less left-turning traffic colliding with near-side crossing through traffic (Pattern 8). The safety effectiveness of the left-turning signal is not consistent for different crash patterns; "protected" phasing is correlated with fewer Pattern 5 crashes, but with more Pattern 8 crashes. The study indicates that in order to develop efficient countermeasures for left-turn crashes and improve safety at signalized intersections, left-turn crashes should be considered in different patterns.

Analyzing crash frequency in freeway tunnels: A correlated random parameters approach.

PubMed

Hou, Qinzhong; Tarko, Andrew P; Meng, Xianghai

2018-02-01

The majority of past road safety studies focused on open road segments while only a few focused on tunnels. Moreover, the past tunnel studies produced some inconsistent results about the safety effects of the traffic patterns, the tunnel design, and the pavement conditions. The effects of these conditions therefore remain unknown, especially for freeway tunnels in China. The study presented in this paper investigated the safety effects of these various factors utilizing a four-year period (2009-2012) of data as well as three models: 1) a random effects negative binomial model (RENB), 2) an uncorrelated random parameters negative binomial model (URPNB), and 3) a correlated random parameters negative binomial model (CRPNB). Of these three, the results showed that the CRPNB model provided better goodness-of-fit and offered more insights into the factors that contribute to tunnel safety. The CRPNB was not only able to allocate the part of the otherwise unobserved heterogeneity to the individual model parameters but also was able to estimate the cross-correlations between these parameters. Furthermore, the study results showed that traffic volume, tunnel length, proportion of heavy trucks, curvature, and pavement rutting were associated with higher frequencies of traffic crashes, while the distance to the tunnel wall, distance to the adjacent tunnel, distress ratio, International Roughness Index (IRI), and friction coefficient were associated with lower crash frequencies. In addition, the effects of the heterogeneity of the proportion of heavy trucks, the curvature, the rutting depth, and the friction coefficient were identified and their inter-correlations were analyzed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimation of the cure rate in Iranian breast cancer patients.

PubMed

Rahimzadeh, Mitra; Baghestani, Ahmad Reza; Gohari, Mahmood Reza; Pourhoseingholi, Mohamad Amin

2014-01-01

Although the Cox's proportional hazard model is the popular approach for survival analysis to investigate significant risk factors of cancer patient survival, it is not appropriate in the case of log-term disease free survival. Recently, cure rate models have been introduced to distinguish between clinical determinants of cure and variables associated with the time to event of interest. The aim of this study was to use a cure rate model to determine the clinical associated factors for cure rates of patients with breast cancer (BC). This prospective cohort study covered 305 patients with BC, admitted at Shahid Faiazbakhsh Hospital, Tehran, during 2006 to 2008 and followed until April 2012. Cases of patient death were confirmed by telephone contact. For data analysis, a non-mixed cure rate model with Poisson distribution and negative binomial distribution were employed. All analyses were carried out using a developed Macro in WinBugs. Deviance information criteria (DIC) were employed to find the best model. The overall 1-year, 3-year and 5-year relative survival rates were 97%, 89% and 74%. Metastasis and stage of BC were the significant factors, but age was significant only in negative binomial model. The DIC also showed that the negative binomial model had a better fit. This study indicated that, metastasis and stage of BC were identified as the clinical criteria for cure rates. There are limited studies on BC survival which employed these cure rate models to identify the clinical factors associated with cure. These models are better than Cox, in the case of long-term survival.

Taxonomic minimalism.

PubMed

Beattle, A J; Oliver, I

1994-12-01

Biological surveys are in increasing demand while taxonomic resources continue to decline. How much formal taxonomy is required to get the job done? The answer depends on the kind of job but it is possible that taxonomic minimalism, especially (1) the use of higher taxonomic ranks, (2) the use of morphospecies rather than species (as identified by Latin binomials), and (3) the involvement of taxonomic specialists only for training and verification, may offer advantages for biodiversity assessment, environmental monitoring and ecological research. As such, formal taxonomy remains central to the process of biological inventory and survey but resources may be allocated more efficiently. For example, if formal Identification is not required, resources may be concentrated on replication and increasing sample sizes. Taxonomic minimalism may also facilitate the inclusion in these activities of important but neglected groups, especially among the invertebrates, and perhaps even microorganisms. Copyright © 1994. Published by Elsevier Ltd.

[Bus drivers' biomechanical risk assessment in two different contexts].

PubMed

Baracco, A; Coggiola, M; Perrelli, F; Banchio, M; Martignone, S; Gullino, A; Romano, C

2012-01-01

The application of standardize methods for the biomechanical risk assessment in non-industrial cycled activity is not always possible. A typical case is the public transport sector, where workers complain of suffering for shoulder more than elbow and wrist pains. The Authors present the results of two studies involving two public transport companies and the risk of biomechanical overload of upper limbs for bus and tram drivers. The analysis has been made using three different approaches: focus groups; static analysis by using anthropometric manikins; work sampling technique by monitoring worker's activity and posture at each minute, for two hours and for each binomial vehicle-route, considering P5F e P95M drivers and assessing the perceived efforts thorough the Borg's CR10 Scale. The conclusive results show that the ergonomic analysis managed by multiple non-standardized techniques may reach consistent and repeatable results according to the epidemiological evidences.

Changes in the labour market and health inequalities during the years of the recent economic downturn in Italy.

PubMed

Sarti, Simone; Zella, Sara

2016-05-01

There is widespread concern that episodes of unemployment and unstable working conditions adversely affect health. We add to the debate by focusing on the relationship between work trajectory and the self-reported health of Italian men and women during the present economic downturn. Relying on Italian data in the EU-SILC project (from 2007 to 2010), our sample includes all individuals aged 30 to 60 in 2010, and uses multivariate binomial regression models for preliminary analyses and the Structural Equations modelling (SEM) to observe the cumulative effects of health status according to different job trajectories. Our main findings show similar pictures for men and women. Individuals who are unemployed, ejected or in precarious occupational positions have a higher risk of worsening their health status during these years. Copyright © 2016 Elsevier Inc. All rights reserved.

On Statistical Modeling of Sequencing Noise in High Depth Data to Assess Tumor Evolution

NASA Astrophysics Data System (ADS)

Rabadan, Raul; Bhanot, Gyan; Marsilio, Sonia; Chiorazzi, Nicholas; Pasqualucci, Laura; Khiabanian, Hossein

2018-07-01

One cause of cancer mortality is tumor evolution to therapy-resistant disease. First line therapy often targets the dominant clone, and drug resistance can emerge from preexisting clones that gain fitness through therapy-induced natural selection. Such mutations may be identified using targeted sequencing assays by analysis of noise in high-depth data. Here, we develop a comprehensive, unbiased model for sequencing error background. We find that noise in sufficiently deep DNA sequencing data can be approximated by aggregating negative binomial distributions. Mutations with frequencies above noise may have prognostic value. We evaluate our model with simulated exponentially expanded populations as well as data from cell line and patient sample dilution experiments, demonstrating its utility in prognosticating tumor progression. Our results may have the potential to identify significant mutations that can cause recurrence. These results are relevant in the pretreatment clinical setting to determine appropriate therapy and prepare for potential recurrence pretreatment.

Motorcycle dependency index at household level: case of Yogyakarta urbanized area

NASA Astrophysics Data System (ADS)

Herwangi, Y.; Putri, S. P.; Ronita, P. S.

2018-05-01

Dependency on private vehicles has become a prevalent phenomenon in big cities experiencing urban sprawl. Related to that, there are still many unknown factors affecting the dependence on motorcycles. Various factors are suspected to influence this, ranging from spatial factors to aspatial factors. This research was conducted in Yogyakarta Urbanized Area (YUA) by taking 175 samples. Binomial Logistic Regression is used in order to find the factors that affect motorcycle dependency. The results showed that the index of dependency in YUA can be quite high. Motorcycle usage, bicycle ownership, and perception about the increase of fuel price are the factors that have a significant influence on motorcycle dependence in YUA. Even though the correlation between spatial factors and motorcycle dependency was weak, it cannot be said to have no effect. These factors are most likely to be influential if other indicators are included with more suitable proxies.

Optimal estimation for discrete time jump processes

NASA Technical Reports Server (NTRS)

Vaca, M. V.; Tretter, S. A.

1978-01-01

Optimum estimates of nonobservable random variables or random processes which influence the rate functions of a discrete time jump process (DTJP) are derived. The approach used is based on the a posteriori probability of a nonobservable event expressed in terms of the a priori probability of that event and of the sample function probability of the DTJP. Thus a general representation is obtained for optimum estimates, and recursive equations are derived for minimum mean-squared error (MMSE) estimates. In general, MMSE estimates are nonlinear functions of the observations. The problem is considered of estimating the rate of a DTJP when the rate is a random variable with a beta probability density function and the jump amplitudes are binomially distributed. It is shown that the MMSE estimates are linear. The class of beta density functions is rather rich and explains why there are insignificant differences between optimum unconstrained and linear MMSE estimates in a variety of problems.

Child Schooling in Ethiopia: The Role of Maternal Autonomy

PubMed Central

Mohanty, Itismita

2016-01-01

This paper examines the effects of maternal autonomy on child schooling outcomes in Ethiopia using a nationally representative Ethiopian Demographic and Health survey for 2011. The empirical strategy uses a Hurdle Negative Binomial Regression model to estimate years of schooling. An ordered probit model is also estimated to examine age grade distortion using a trichotomous dependent variable that captures three states of child schooling. The large sample size and the range of questions available in this dataset allow us to explore the influence of individual and household level social, economic and cultural factors on child schooling. The analysis finds statistically significant effects of maternal autonomy variables on child schooling in Ethiopia. The roles of maternal autonomy and other household-level factors on child schooling are important issues in Ethiopia, where health and education outcomes are poor for large segments of the population. PMID:27942039

Work performance decrements are associated with Australian working conditions, particularly the demand to work longer hours.

PubMed

Holden, Libby; Scuffham, Paul A; Hilton, Michael F; Vecchio, Nerina N; Whiteford, Harvey A

2010-03-01

To demonstrate the importance of including a range of working conditions in models exploring the association between health- and work-related performance. The Australian Work Outcomes Research Cost-benefit study cross-sectional screening data set was used to explore health-related absenteeism and work performance losses on a sample of approximately 78,000 working Australians, including available demographic and working condition factors. Data collected using the World Health Organization Health and Productivity Questionnaire were analyzed with negative binomial logistic regression and multinomial logistic regressions for absenteeism and work performance, respectively. Hours expected to work, annual wage, and job insecurity play a vital role in the association between health- and work-related performance for both work attendance and self-reported work performance. Australian working conditions are contributing to both absenteeism and low work performance, regardless of health status.

Prevalence and risk factors of musculoskeletal disorders among Sri Lankan rubber tappers

PubMed Central

de Silva, Vijitha; Tharindra, Hemajith; Ostbye, Truls

2016-01-01

Background Rubber tapping exposes workers to risk factors for musculoskeletal disorders (MSDs). Objectives This cross-sectional study assessed the prevalence and factors associated with MSDs among Sri Lankan rubber tappers. Methods Questionnaires were administered to 300 rubber tappers to measure MSDs and potential associated factors. Ergonomic exposure levels were measured for 90 tappers using the Quick Exposure Check instrument. MSD prevalence and prevalence ratios were calculated using log-binomial regression. Results In the past 12 months, 66% of rubber tappers in our sample experienced an MSD. Ergonomic exposure levels were high or very high in the back (94.4%), shoulders (96.7%), and neck (83.3%). Being female, older, Tamil, working two jobs, alternating tapping hands, and depression were significantly associated with increased risk of MSDs. Conclusions MSDs are common among rubber tappers in Sri Lanka. These results suggest a need for work process modifications to prevent MSDs. PMID:27092589

Does the Organized Sexual Murderer Better Delay and Avoid Detection?

PubMed

Beauregard, Eric; Martineau, Melissa

2016-01-01

According to the organized-disorganized model, organized sexual murderers adopt specific behaviors during the commission of their crimes that contribute to avoiding police detection. The current study examines the effect of sexual murderers' organized behaviors on their ability to both delay and/or avoid police detection. Using a combination of negative binomial and logistic regression analyses on a sample of 350 sexual murder cases, findings showed that although both measures of delaying and avoiding detection are positively correlated, different behavioral patterns were observed. For instance, offenders who moved the victim's body were more likely to avoid detection but the victim's body was likely to be recovered faster. Moreover, victim characteristics have an impact on both measures; however, this effect disappears for the measure of delaying detection once the organized behaviors are introduced. Implications of the findings are discussed. © The Author(s) 2014.

On Statistical Modeling of Sequencing Noise in High Depth Data to Assess Tumor Evolution

NASA Astrophysics Data System (ADS)

Rabadan, Raul; Bhanot, Gyan; Marsilio, Sonia; Chiorazzi, Nicholas; Pasqualucci, Laura; Khiabanian, Hossein

2017-12-01

One cause of cancer mortality is tumor evolution to therapy-resistant disease. First line therapy often targets the dominant clone, and drug resistance can emerge from preexisting clones that gain fitness through therapy-induced natural selection. Such mutations may be identified using targeted sequencing assays by analysis of noise in high-depth data. Here, we develop a comprehensive, unbiased model for sequencing error background. We find that noise in sufficiently deep DNA sequencing data can be approximated by aggregating negative binomial distributions. Mutations with frequencies above noise may have prognostic value. We evaluate our model with simulated exponentially expanded populations as well as data from cell line and patient sample dilution experiments, demonstrating its utility in prognosticating tumor progression. Our results may have the potential to identify significant mutations that can cause recurrence. These results are relevant in the pretreatment clinical setting to determine appropriate therapy and prepare for potential recurrence pretreatment.

ICP Corporate Customer Assessment - Sampling Plan

DTIC Science & Technology

1995-07-01

CORPORATE CUSTOMER ASSESSMENT - SAMPLING PLAN JULY 1995 Lead Analyst: Lieutenant Commander William J. Wilkinson, USN Associate Analyst: Mr. Henry J...project developed a plan for conducting recurring surveys of Defense Logistics Agency customers , in support of the DLA Corporate Customer Assessment...Team. The primary product was a sampling plan, including stratification of customers by Military Service or Federal Agency and by commodity purchased

Fixed precision sampling plans for white apple leafhopper (Homoptera: Cicadellidae) on apple.

PubMed

Beers, Elizabeth H; Jones, Vincent P

2004-10-01

Constant precision sampling plans for the white apple leafhopper, Typhlocyba pomaria McAtee, were developed so that it could be used as an indicator species for system stability as new integrated pest management programs without broad-spectrum pesticides are developed. Taylor's power law was used to model the relationship between the mean and the variance, and Green's constant precision sequential sample equation was used to develop sampling plans. Bootstrap simulations of the sampling plans showed greater precision (D = 0.25) than the desired precision (Do = 0.3), particularly at low mean population densities. We found that by adjusting the Do value in Green's equation to 0.4, we were able to reduce the average sample number by 25% and provided an average D = 0.31. The sampling plan described allows T. pomaria to be used as reasonable indicator species of agroecosystem stability in Washington apple orchards.

Addendum to Sampling and Analysis Plan (SAP) for Assessment of LANL-Derived Residual Radionuclides in Soils within Tract A-16-d for Land Conveyance and Transfer for Sewage Treatment Facility Area

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

Whicker, Jeffrey Jay; Gillis, Jessica Mcdonnel; Ruedig, Elizabeth

This report summarizes the sampling design used, associated statistical assumptions, as well as general guidelines for conducting post-sampling data analysis. Sampling plan components presented here include how many sampling locations to choose and where within the sampling area to collect those samples. The type of medium to sample (i.e., soil, groundwater, etc.) and how to analyze the samples (in-situ, fixed laboratory, etc.) are addressed in other sections of the sampling plan.

S-SPatt: simple statistics for patterns on Markov chains.

PubMed

Nuel, Grégory

2005-07-01

S-SPatt allows the counting of patterns occurrences in text files and, assuming these texts are generated from a random Markovian source, the computation of the P-value of a given observation using a simple binomial approximation.

Evaluation of surrogate measures for pedestrian safety in various road and roadside environments.

DOT National Transportation Integrated Search

2012-10-01

This report presents an investigation of pedestrian conflicts and crash count models to learn which exposure measures and roadway or roadside characteristics significantly influence pedestrian safety at road crossings. Negative binomial models were e...

Spatial Distribution and Sampling Plans for Grapevine Plant Canopy-Inhabiting Scaphoideus titanus (Hemiptera: Cicadellidae) Nymphs.

PubMed

Rigamonti, Ivo E; Brambilla, Carla; Colleoni, Emanuele; Jermini, Mauro; Trivellone, Valeria; Baumgärtner, Johann

2016-04-01

The paper deals with the study of the spatial distribution and the design of sampling plans for estimating nymph densities of the grape leafhopper Scaphoideus titanus Ball in vine plant canopies. In a reference vineyard sampled for model parameterization, leaf samples were repeatedly taken according to a multistage, stratified, random sampling procedure, and data were subjected to an ANOVA. There were no significant differences in density neither among the strata within the vineyard nor between the two strata with basal and apical leaves. The significant differences between densities on trunk and productive shoots led to the adoption of two-stage (leaves and plants) and three-stage (leaves, shoots, and plants) sampling plans for trunk shoots- and productive shoots-inhabiting individuals, respectively. The mean crowding to mean relationship used to analyze the nymphs spatial distribution revealed aggregated distributions. In both the enumerative and the sequential enumerative sampling plans, the number of leaves of trunk shoots, and of leaves and shoots of productive shoots, was kept constant while the number of plants varied. In additional vineyards data were collected and used to test the applicability of the distribution model and the sampling plans. The tests confirmed the applicability 1) of the mean crowding to mean regression model on the plant and leaf stages for representing trunk shoot-inhabiting distributions, and on the plant, shoot, and leaf stages for productive shoot-inhabiting nymphs, 2) of the enumerative sampling plan, and 3) of the sequential enumerative sampling plan. In general, sequential enumerative sampling was more cost efficient than enumerative sampling.

Designing a two-rank acceptance sampling plan for quality inspection of geospatial data products

NASA Astrophysics Data System (ADS)

Tong, Xiaohua; Wang, Zhenhua; Xie, Huan; Liang, Dan; Jiang, Zuoqin; Li, Jinchao; Li, Jun

2011-10-01

To address the disadvantages of classical sampling plans designed for traditional industrial products, we originally propose a two-rank acceptance sampling plan (TRASP) for the inspection of geospatial data outputs based on the acceptance quality level (AQL). The first rank sampling plan is to inspect the lot consisting of map sheets, and the second is to inspect the lot consisting of features in an individual map sheet. The TRASP design is formulated as an optimization problem with respect to sample size and acceptance number, which covers two lot size cases. The first case is for a small lot size with nonconformities being modeled by a hypergeometric distribution function, and the second is for a larger lot size with nonconformities being modeled by a Poisson distribution function. The proposed TRASP is illustrated through two empirical case studies. Our analysis demonstrates that: (1) the proposed TRASP provides a general approach for quality inspection of geospatial data outputs consisting of non-uniform items and (2) the proposed acceptance sampling plan based on TRASP performs better than other classical sampling plans. It overcomes the drawbacks of percent sampling, i.e., "strictness for large lot size, toleration for small lot size," and those of a national standard used specifically for industrial outputs, i.e., "lots with different sizes corresponding to the same sampling plan."

Using known populations of pronghorn to evaluate sampling plans and estimators

USGS Publications Warehouse

Kraft, K.M.; Johnson, D.H.; Samuelson, J.M.; Allen, S.H.

1995-01-01

Although sampling plans and estimators of abundance have good theoretical properties, their performance in real situations is rarely assessed because true population sizes are unknown. We evaluated widely used sampling plans and estimators of population size on 3 known clustered distributions of pronghorn (Antilocapra americana). Our criteria were accuracy of the estimate, coverage of 95% confidence intervals, and cost. Sampling plans were combinations of sampling intensities (16, 33, and 50%), sample selection (simple random sampling without replacement, systematic sampling, and probability proportional to size sampling with replacement), and stratification. We paired sampling plans with suitable estimators (simple, ratio, and probability proportional to size). We used area of the sampling unit as the auxiliary variable for the ratio and probability proportional to size estimators. All estimators were nearly unbiased, but precision was generally low (overall mean coefficient of variation [CV] = 29). Coverage of 95% confidence intervals was only 89% because of the highly skewed distribution of the pronghorn counts and small sample sizes, especially with stratification. Stratification combined with accurate estimates of optimal stratum sample sizes increased precision, reducing the mean CV from 33 without stratification to 25 with stratification; costs increased 23%. Precise results (mean CV = 13) but poor confidence interval coverage (83%) were obtained with simple and ratio estimators when the allocation scheme included all sampling units in the stratum containing most pronghorn. Although areas of the sampling units varied, ratio estimators and probability proportional to size sampling did not increase precision, possibly because of the clumped distribution of pronghorn. Managers should be cautious in using sampling plans and estimators to estimate abundance of aggregated populations.

Effect of Sampling Plans on the Risk of Escherichia coli O157 Illness.

PubMed

Kiermeier, Andreas; Sumner, John; Jenson, Ian

2015-07-01

Australia exports about 150,000 to 200,000 tons of manufacturing beef to the United States annually. Each lot is tested for Escherichia coli O157 using the N-60 sampling protocol, where 60 small pieces of surface meat from each lot of production are tested. A risk assessment of E. coli O157 illness from the consumption of hamburgers made from Australian manufacturing meat formed the basis to evaluate the effect of sample size and amount on the number of illnesses predicted. The sampling plans evaluated included no sampling (resulting in an estimated 55.2 illnesses per annum), the current N-60 plan (50.2 illnesses), N-90 (49.6 illnesses), N-120 (48.4 illnesses), and a more stringent N-60 sampling plan taking five 25-g samples from each of 12 cartons (47.4 illnesses per annum). While sampling may detect some highly contaminated lots, it does not guarantee that all such lots are removed from commerce. It is concluded that increasing the sample size or sample amount from the current N-60 plan would have a very small public health effect.

Final report : sampling plan for pavement condition ratings of secondary roads.

DOT National Transportation Integrated Search

1984-01-01

The purpose of this project was to develop a random sampling plan for use in selecting segments of the secondary highway system for evaluation under the Department's PMS. The plan developed is described here. It is a simple, workable, random sampling...

Nevada National Security Site Integrated Groundwater Sampling Plan, Revision 1

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

Wilborn, Bill R.; Boehlecke, Robert F.

The purpose is to provide a comprehensive, integrated approach for collecting and analyzing groundwater samples to meet the needs and objectives of the DOE/EM Nevada Program’s UGTA Activity. Implementation of this Plan will provide high-quality data required by the UGTA Activity for ensuring public protection in an efficient and cost-effective manner. The Plan is designed to ensure compliance with the UGTA Quality Assurance Plan (QAP) (NNSA/NFO, 2015); Federal Facility Agreement and Consent Order (FFACO) (1996, as amended); and DOE Order 458.1, Radiation Protection of the Public and the Environment (DOE, 2013). The Plan’s scope comprises sample collection and analysis requirementsmore » relevant to assessing both the extent of groundwater contamination from underground nuclear testing and impact of testing on water quality in downgradient communities. This Plan identifies locations to be sampled by CAU and location type, sampling frequencies, sample collection methodologies, and the constituents to be analyzed. In addition, the Plan defines data collection criteria such as well purging, detection levels, and accuracy requirements/recommendations; identifies reporting and data management requirements; and provides a process to ensure coordination between NNSS groundwater sampling programs for sampling analytes of interest to UGTA. Information used in the Plan development—including the rationale for selection of wells, sampling frequency, and the analytical suite—is discussed under separate cover (N-I, 2014) and is not reproduced herein. This Plan does not address compliance for those wells involved in a permitted activity. Sampling and analysis requirements associated with these wells are described in their respective permits and are discussed in NNSS environmental reports (see Section 5.2). In addition, sampling for UGTA CAUs that are in the Closure Report (CR) stage are not included in this Plan. Sampling requirements for these CAUs are described in the CR. Frenchman Flat is currently the only UGTA CAU in the CR stage. Sampling requirements for this CAU are described in Underground Test Area (UGTA) Closure Report for Corrective Action Unit 98: Frenchman Flat Nevada National Security Site, Nevada (NNSA/NFO, 2016).« less

Lotka's Law and Institutional Productivity.

ERIC Educational Resources Information Center

Kumar, Suresh; Sharma, Praveen; Garg, K. C.

1998-01-01

Examines the applicability of Lotka's Law, negative binomial distribution, and lognormal distribution for institutional productivity in the same way as it is to authors and their productivity. Results indicate that none of the distributions are applicable for institutional productivity in engineering sciences. (Author/LRW)

Surveillance plan for the early detection of H5N1 highly pathogenic avian influenza virus in migratory birds in the United States: surveillance year 2009

USGS Publications Warehouse

Brand, Christopher J.

2009-01-01

Executive Summary: This Surveillance Plan (Plan) describes plans for conducting surveillance of wild birds in the United States and its Territories and Freely-Associated States to provide for early detection of the introduction of the H5N1 Highly Pathogenic Avian Influenza (HPAI) subtype of the influenza A virus by migratory birds during the 2009 surveillance year, spanning the period of April 1, 2009 - March 31, 2010. The Plan represents a continuation of surveillance efforts begun in 2006 under the Interagency Strategic Plan for the Early Detection of H5N1 Highly Pathogenic Avian Influenza in Wild Migratory Birds (U.S. Department of Agriculture and U.S. Department of the Interior, 2006). The Plan sets forth sampling plans by: region, target species or species groups to be sampled, locations of sampling, sample sizes, and sampling approaches and methods. This Plan will be reviewed annually and modified as appropriate for subsequent surveillance years based on evaluation of information from previous years of surveillance, changing patterns and threats of H5N1 HPAI, and changes in funding availability for avian influenza surveillance. Specific sampling strategies will be developed accordingly within each of six regions, defined here as Alaska, Hawaiian/Pacific Islands, Lower Pacific Flyway (Washington, Oregon, California, Idaho, Nevada, Arizona), Central Flyway, Mississippi Flyway, and Atlantic Flyway.

7 CFR 43.106 - Choosing AQL's and sampling plans.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 2 2010-01-01 2010-01-01 false Choosing AQL's and sampling plans. 43.106 Section 43.106 Agriculture Regulations of the Department of Agriculture AGRICULTURAL MARKETING SERVICE (Standards, Inspections, Marketing Practices), DEPARTMENT OF AGRICULTURE COMMODITY STANDARDS AND STANDARD CONTAINER REGULATIONS STANDARDS FOR SAMPLING PLANS...

PCB Analysis Plan for Tank Archive Samples

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

NGUYEN, D.M.

2001-03-22

This analysis plan specifies laboratory analysis, quality assurance/quality control (QA/QC), and data reporting requirements for analyzing polychlorinated biphenyls (PCB) concentrations in archive samples. Tank waste archive samples that are planned for PCB analysis are identified in Nguyen 2001. The tanks and samples are summarized in Table 1-1. The analytical data will be used to establish a PCB baseline inventory in Hanford tanks.

Coosa River Storage Annex, Talladega, Alabama Environmental Investigation, Final Management and Resources Utilization Plan

DTIC Science & Technology

1991-02-01

to adequately assess the health and environmental risks associated with the closure and transfer of the Annex forI other use; and 3) identification of...1990); Draft Final Technical Plan, Draft Final Sampling Design Plan and Draft Final Health and Safety Plan, USATHAMA, June 1990. 2.1.2 Draft Final...Final Technical Plan, Sampling Design Plan and Health and Safety Plan) supplied by USATHAMA. The estimate may be revised, with USATHAMA approval, as

The Use of Informative Priors in Bayesian Modeling Age-at-death; a Quick Look at Chronological and Biological Age Changes in the Sacroiliac Joint in American Males

PubMed Central

Godde, Kanya

2017-01-01

The aim of this study is to examine how well different informative priors model age-at-death in Bayesian statistics, which will shed light on how the skeleton ages, particularly at the sacroiliac joint. Data from four samples were compared for their performance as informative priors for auricular surface age-at-death estimation: (1) American population from US Census data; (2) county data from the US Census data; (3) a local cemetery; and (4) a skeletal collection. The skeletal collection and cemetery are located within the county that was sampled. A Gompertz model was applied to compare survivorship across the four samples. Transition analysis parameters, coupled with the generated Gompertz parameters, were input into Bayes' theorem to generate highest posterior density ranges from posterior density functions. Transition analysis describes the age at which an individual transitions from one age phase to another. The result is age ranges that should describe the chronological age of 90% of the individuals who fall in a particular phase. Cumulative binomial tests indicate the method performed lower than 90% at capturing chronological age as assigned to a biological phase, despite wide age ranges at older ages. The samples performed similarly overall, despite small differences in survivorship. Collectively, these results show that as we age, the senescence pattern becomes more variable. More local samples performed better at describing the aging process than more general samples, which implies practitioners need to consider sample selection when using the literature to diagnose and work with patients with sacroiliac joint pain. PMID:29546217

Seroprevalence of HCV and HIV infection among clients of the nation's longest-standing statewide syringe exchange program: A cross-sectional study of Community Health Outreach Work to Prevent AIDS (CHOW).

PubMed

Salek, Thomas P; Katz, Alan R; Lenze, Stacy M; Lusk, Heather M; Li, Dongmei; Des Jarlais, Don C

2017-10-01

The Community Health Outreach Work to Prevent AIDS (CHOW) Project is the first and longest-standing statewide integrated and funded needle and syringe exchange program (SEP) in the US. Initiated on O'ahu in 1990, CHOW expanded statewide in 1993. The purpose of this study is to estimate the prevalences of hepatitis C virus (HCV) and human immunodeficiency virus (HIV) infection, and to characterize risk behaviors associated with infection among clients of a long-standing SEP through the analysis of the 2012 CHOW evaluation data. A cross-sectional sample of 130 CHOW Project clients was selected from January 1, 2012 through December 31, 2012. Questionnaires captured self-reported exposure information. HIV and HCV antibodies were detected via rapid, point-of-care FDA-approved tests. Log-binomial regressions were used to estimate prevalence proportion ratios (PPRs). A piecewise linear log-binomial regression model containing 1 spline knot was used to fit the age-HCV relationship. The estimated seroprevalence of HCV was 67.7% (95% confidence interval [CI]=59.5-75.8%). HIV seroprevalence was 2.3% (95% CI=0-4.9%). Anti-HCV prevalence demonstrated age-specific patterns, ranging from 31.6% through 90.9% in people who inject drugs (PWID) <30 to ≥60 years respectively. Age (continuous/year) prior to spline knot at 51.5 years (adjusted PPR [APPR]=1.03; 95% CI=1.02-1.05) and months exchanging syringes (quartiles) (APPR=1.92; 95% CI=1.3-3.29) were independently associated with anti-HCV prevalence. In Hawai'i, HCV prevalence among PWID is hyperendemic demonstrating age- and SEP duration-specific trends. Relatively low HIV prevalence compared with HCV prevalence reflects differences in transmissibility of these 2 blood-borne pathogens and suggests much greater efficacy of SEP for HIV prevention. Copyright © 2017 Elsevier B.V. All rights reserved.

Quantifying the safety effects of horizontal curves on two-way, two-lane rural roads.

PubMed

Gooch, Jeffrey P; Gayah, Vikash V; Donnell, Eric T

2016-07-01

The objective of this study is to quantify the safety performance of horizontal curves on two-way, two-lane rural roads relative to tangent segments. Past research is limited by small samples sizes, outdated statistical evaluation methods, and unreported standard errors. This study overcomes these drawbacks by using the propensity scores-potential outcomes framework. The impact of adjacent curves on horizontal curve safety is also explored using a cross-sectional regression model of only horizontal curves. The models estimated in the present study used eight years of crash data (2005-2012) obtained from over 10,000 miles of state-owned two-lane rural roads in Pennsylvania. These data included information on roadway geometry (e.g., horizontal curvature, lane width, and shoulder width), traffic volume, roadside hazard rating, and the presence of various low-cost safety countermeasures (e.g., centerline and shoulder rumble strips, curve and intersection warning pavement markings, and aggressive driving pavement dots). Crash prediction is performed by means of mixed effects negative binomial regression using the explanatory variables noted previously, as well as attributes of adjacent horizontal curves. The results indicate that both the presence of a horizontal curve and its degree of curvature must be considered when predicting the frequency of total crashes on horizontal curves. Both are associated with an increase in crash frequency, which is consistent with previous findings in the literature. Mixed effects negative binomial regression models for total crash frequency on horizontal curves indicate that the distance to adjacent curves is not statistically significant. However, the degree of curvature of adjacent curves in close proximity (within 0.75 miles) was found to be statistically significant and negatively correlated with crash frequency on the subject curve. This is logical, as drivers exiting a sharp curve are likely to be driving slower and with more awareness as they approach the next horizontal curve. Copyright © 2016 Elsevier Ltd. All rights reserved.

The 6-min push test is reliable and predicts low fitness in spinal cord injury.

PubMed

Cowan, Rachel E; Callahan, Morgan K; Nash, Mark S

2012-10-01

The objective of this study is to assess 6-min push test (6MPT) reliability, determine whether the 6MPT is sensitive to fitness differences, and assess if 6MPT distance predicts fitness level in persons with spinal cord injury (SCI) or disease. Forty individuals with SCI who could self-propel a manual wheelchair completed an incremental arm crank peak oxygen consumption assessment and two 6MPTs across 3 d (37% tetraplegia (TP), 63% paraplegia (PP), 85% men, 70% white, 63% Hispanic, mean age = 34 ± 10 yr, mean duration of injury = 13 ± 10 yr, and mean body mass index = 24 ± 5 kg.m). Intraclass correlation and Bland-Altman plots assessed 6MPT distance (m) reliability. Mann-Whitney U test compared 6MPT distance (m) of high and low fitness groups for TP and PP. The fitness status prediction was developed using N = 30 and validated in N = 10 (validation group (VG)). A nonstatistical prediction approach, below or above a threshold distance (TP = 445 m and PP = 604 m), was validated statistically by binomial logistic regression. Accuracy, sensitivity, and specificity were computed to evaluate the threshold approach. Intraclass correlation coefficients exceeded 0.90 for the whole sample and the TP/PP subsets. High fitness persons propelled farther than low fitness persons for both TP/PP (both P < 0.05). Binomial logistic regression (P < 0.008) predicted the same fitness levels in the VG as the threshold approach. In the VG, overall accuracy was 70%. Eighty-six percent of low fitness persons were correctly identified (sensitivity), and 33% of high fitness persons were correctly identified (specificity). The 6MPT may be a useful tool for SCI clinicians and researchers. 6MPT distance demonstrates excellent reliability and is sensitive to differences in fitness level. 6MPT distances less than a threshold distance may be an effective approach to identify low fitness in person with SCI.

Factors associated with stigma attitude towards people living with HIV among general individuals in Heilongjiang, Northeast China.

PubMed

Li, Xin; Yuan, Lili; Li, Xiaoxia; Shi, Jingli; Jiang, Liying; Zhang, Chundi; Yang, Xiujing; Zhang, Yeli; Zhao, Donghui; Zhao, Yashuang

2017-02-17

HIV-related stigma always is major obstacles to an effective HIV response worldwide. The effect of HIV-related stigma on HIV prevention and treatment is particularly serious in China. This study was to examine stigma attitude towards people living with HIV/AIDS (PLWHA) among general individuals in Heilongjiang Province, Northeast China and the factors associated with stigma attitude, including socio-demographic factors and HIV/AIDS Knowledge. A cross-sectional survey was carried out in Heilongjiang Province, China. A total of 4050 general individuals with age 15-69 years in four villages in rural areas and two communities in urban areas were drawn using stratified cluster sampling. Standardized questionnaire interviews were administered. Univariate and multivariate log-binomial regression were performed to assess factors affecting stigma attitude towards PLWHA. The proportions of participants holding stigma attitude towards PLWHA were 49.6% among rural respondents and 37.0% among urban respondents (P < 0.001). Multivariate log binomial regression analysis among both rural participants (RR = 0.89, 95% CI: 0.87-0.91, P < 0.001) and urban participants (RR = 0.89, 95% CI: 0.87-0.91, P < 0.001) showed that greater knowledge of HIV transmission misconceptions was significantly associated with lower stigma attitude towards people living with HIV. And among urban participants, higher education level (high school vs. primary school or less: RR = 0.73, 95%CI: 0.62-0.87, P < 0.001; middle school vs. primary school or less: RR = 0.83, 95%CI: 0.71-0.97, P = 0.018) were also significantly associated with lower stigma attitude towards PLWHA. The level of stigma attitude towards PLWHA is higher in rural areas than in urban areas in Heilongjiang. Meanwhile, individuals who better were aware of HIV/AIDS transmission misconceptions may hold lower stigma attitude toward PLWHA whether among rural or urban residents.

Association between Parental Access to Paid Sick Leave and Children's Access to and Use of Healthcare Services

PubMed Central

Asfaw, Abay; Colopy, Maria

2017-01-01

Background We examined the association between parental access to paid sick leave (PPSL) and children's use of preventive care and reduced likelihood of delayed medical care and emergency room (ER) visits. Methods We used the child sample of the National Health Interview Survey data (linked to the adult and family samples) from 2011 through 2015 and logistic and negative binomial regression models. Results Controlling for covariates, the odds of children with PPSL receiving flu vaccination were 12.5% [95%CI: 1.06–1.19] higher and receiving annual medical checkups were 13.2% [95%CI: 1.04–1.23] higher than those of children without PPSL. With PPSL, the odds of children receiving delayed medical care because of time mismatch were 13.3% [95%CI: 0.76–0.98] lower, and being taken to ER were 53.6% [95%CI: 0.27–0.81] lower than those of children without PPSL. PPSL was associated with 11% [95%CI: 0.82–0.97] fewer ER visits per year. Conclusion PPSL may improve children's access and use of healthcare services and reduce the number of ER visits. PMID:28169438

Psychosocial factor exposures in the workplace: differences between immigrants and Spaniards.

PubMed

Font, Ariadna; Moncada, Salvador; Llorens, Clara; Benavides, Fernando G

2012-10-01

The purpose of this study was to analyse psychosocial factor exposures in the workplace for immigrant workers in Spain and identify differences in exposure at work between immigrants and Spaniards. A multi-stage sample was taken by conglomerates (final sample size: 7555 workers). The information was obtained in 2004 and 2005 using a standardized questionnaire administered by interviewing participants in their homes. The analysis focused on eight psychosocial factors. For quantitative demands and insecurity, the exposure was defined according to the higher third, and for the others, the exposure was defined according to the lower third. The prevalence ratio (PR) and confidence interval (CI) for unfavourable psychosocial factor, both crude and adjusted, were calculated using log binomial models. Those with highest prevalence of unfavourable psychosocial factor were immigrant manual workers, particularly in low possibilities for development (PR=2.87; 95% CI 2.44-3.73), and immigrant women, particularly in low control over working times (PR=1.72; 95% CI 1.55-1.91). Immigrant workers with manual jobs and immigrant women are the groups most exposed to psychosocial factor. In efforts to prevent these exposures, these inequalities should be taken into account.

The association between subclinical mastitis around calving and reproductive performance in grazing dairy cows.

PubMed

Villa-Arcila, N A; Sanchez, J; Ratto, M H; Rodriguez-Lecompte, J C; Duque-Madrid, P C; Sanchez-Arias, S; Ceballos-Marquez, A

2017-10-01

The objective of this study was to evaluate the effect of subclinical mastitis (SCM) on calving-to-first-service interval (CFS), calving-to-conception interval (CC), and on the number of services per conception (S/C) in grazing Holstein and Normande cows. Primiparous (n=43) and multiparous (n=165) cows were selected from five dairy herds. Two composite milk samples were aseptically collected from each cow at drying-off, and then every week during the first postpartum month. One sample was used for somatic cell count (SCC), and the other one for bacteriological analysis. Cows were followed up to 300 d after calving. Non-parametric and parametric survival models, and negative binomial regression were used to assess the association between SCM, evaluated by SCC and milk culture, and reproductive indices. Staphylococcus aureus, CNS, and Streptococcus uberis were the most frequent isolated pathogens. Subclinical mastitis in the first month of lactation was not associated with CFS; however, the CC interval was longer in cows with SCM compared to healthy cows, the former also had a higher number of S/C. Copyright © 2017 Elsevier B.V. All rights reserved.

Serological survey of Neospora caninum infection in cattle herds from Western Romania.

PubMed

Imre, Kálmán; Morariu, Sorin; Ilie, Marius S; Imre, Mirela; Ferrari, Nicola; Genchi, Claudio; Dărăbuş, Gheorghe

2012-06-01

Serum samples from 376 randomly selected adult cattle, from 25 farms located in 3 counties (Arad, Bihor, and Timiş) from western Romania, were sampled for Neospora caninum antibodies using a commercial ELISA-kit. Seroprevalence values and risk factors for neosporosis (cow age, breed, herd size, farming system, previous abortion, and number of farm dogs) were examined using a generalized linear mixed model with a binomial distribution. Overall, the seroprevalence of N. caninum was 27.7% (104/376) with a prevalence of 27.9% (24/86) in Arad, 26.9% (25/93) in Bihor, and 27.9% (55/197) in Timiş. Of 25 cattle herds, 23 were seropositive with a prevalence ranging from 10.0 to 52.2%. No correlation was found between N. caninum seropositivity and age, breed, herd size, breeding system, and previous abortion. The number of farm dogs was the only factor (P(Wald)  =  0.03) positively associated with seroprevalence in cows and can be considered the risk factor in the acquiring of infection. The present work is the first regarding serological evidence of N. caninum infection in cattle from western Romania.

Formal Home Care Utilization Patterns by Rural–Urban Community Residence

PubMed Central

Spector, William; Van Nostrand, Joan

2009-01-01

Background We examined formal home care utilization among civilian adults across metro and nonmetro residential categories before and after adjustment for predisposing, enabling, and need variables. Methods Two years of the Medical Expenditure Panel Survey (MEPS) were combined to produce a nationally representative sample of adults who resided in the community for a calendar year. We established 6 rural–urban categories based upon Urban Influence Codes and examined 2 dependent variables: (a) likelihood of using any formal home care and (b) number of provider days received by users. The Area Resource File provided county-level information. Logistic and negative binomial regression analyses were employed, with adjustments for the MEPS complex sampling design and the combined years. Results Under controls for predisposing, enabling, and need variables, differences in likelihood of any formal home care use disappear, but differences in number of provider days received by users emerged, with fewer provider days in remote areas than in metro and several other nonmetro types. Conclusions It is important to fully account for predisposing, enabling, and need factors when assessing rural and urban home care utilization patterns. The limited provider days in remote counties under controls suggest a possible access problem for adults in these areas. PMID:19196690

The protective effect of neighborhood social cohesion in child abuse and neglect.

PubMed

Maguire-Jack, Kathryn; Showalter, Kathryn

2016-02-01

Relations between parents within a neighborhood have the potential to provide a supportive environment for healthy and positive parenting. Neighborhood social cohesion, or the mutual trust and support among neighbors, is one process through which parenting may be improved. The current study investigates the association between neighborhood social cohesion and abuse and neglect, as well as specific types of abuse and neglect. The sample for the study is comprised of 896 parents in one urban Midwestern County in the United States. Participants were recruited from Women, Infants, and Children clinics. Negative binomial regression is used to examine the association between neighborhood social cohesion and child maltreatment behaviors, as measured by the Conflict Tactics Scale, Parent-to-Child Version (Straus et al., 1998). In this sample of families, neighborhood social cohesion is associated with child neglect, but not abuse. In examining the relationship with specific types of abuse and neglect, it was found that neighborhood social cohesion may have a protective role in some acts of neglect, such as meeting a child's basic needs, but not potentially more complex needs like parental substance abuse. Copyright © 2015 Elsevier Ltd. All rights reserved.

Mapping the Personality Psychopathology Five domains onto DSM-IV personality disorders in Dutch clinical and forensic samples: implications for DSM-5.

PubMed

Sellbom, Martin; Smid, Wineke; de Saeger, Hilde; Smit, Naomi; Kamphuis, Jan H

2014-01-01

The Personality Psychopathology Five (PSY-5) model represents 5 broadband dimensional personality domains that align with the originally proposed DSM-5 personality trait system, which was eventually placed in Section III for further study. The main objective of this study was to examine the associations between the PSY-5 model and personality disorder criteria. More specifically, we aimed to determine if the PSY-5 domain scales converged with the alternative DSM-5 Section III model for personality disorders, with a particular emphasis on the personality trait profiles proposed for each of the specific personality disorder types. Two samples from The Netherlands consisting of clinical patients from a personality disorder treatment program (n = 190) and forensic psychiatric hospital (n = 162) were used. All patients had been administered the MMPI-2 (from which MMPI-2-RF PSY-5 scales were scored) and structured clinical interviews to assess personality disorder criteria. Results based on Poisson or negative binomial regression models showed statistically significant and meaningful associations for the hypothesized PSY-5 domains for each of the 6 personality disorders, with a few minor exceptions that are discussed in detail. Implications for these findings are also discussed.

Various methods of determining the natural frequencies and damping of composite cantilever plates. 1. Exact solution for the binomial model of deformation

NASA Astrophysics Data System (ADS)

Skel'chik, V. S.; Ryabov, V. M.

1996-11-01

On the basis of the classical theory of thin anisotropic laminated plates the article analyzes the free vibrations of rectangular cantilever plates made of fibrous composites. The application of Kantorovich's method for the binomial representation of the shape of the elastic surface of a plate yielded for two unknown functions a system of two connected differential equations and the corresponding boundary conditions at the place of constraint and at the free edge. The exact solution for the frequencies and forms of the free vibrations was found with the use of Laplace transformation with respect to the space variable. The magnitudes of several first dimensionless frequencies of the bending and torsional vibrations of the plate were calculated for a wide range of change of two dimensionless complexes, with the dimensions of the plate and the anisotropy of the elastic properties of the material taken into account. The article shows that with torsional vibrations the warping constraint at the fixed end explains the apparent dependence of the shear modulus of the composite on the length of the specimen that had been discovered earlier on in experiments with a torsional pendulum. It examines the interaction and transformation of the second bending mode and of the first torsional mode of the vibrations. It analyzes the asymptotics of the dimensionless frequencies when the length of the plate is increased, and it shows that taking into account the bending-torsion interaction in strongly anisotropic materials type unidirectional carbon reinforced plastic can reduce substantially the frequencies of the bending vibrations but has no effect (within the framework of the binomial model) on the frequencies of the torsional vibrations.

Zero-state Markov switching count-data models: an empirical assessment.

PubMed

Malyshkina, Nataliya V; Mannering, Fred L

2010-01-01

In this study, a two-state Markov switching count-data model is proposed as an alternative to zero-inflated models to account for the preponderance of zeros sometimes observed in transportation count data, such as the number of accidents occurring on a roadway segment over some period of time. For this accident-frequency case, zero-inflated models assume the existence of two states: one of the states is a zero-accident count state, which has accident probabilities that are so low that they cannot be statistically distinguished from zero, and the other state is a normal-count state, in which counts can be non-negative integers that are generated by some counting process, for example, a Poisson or negative binomial. While zero-inflated models have come under some criticism with regard to accident-frequency applications - one fact is undeniable - in many applications they provide a statistically superior fit to the data. The Markov switching approach we propose seeks to overcome some of the criticism associated with the zero-accident state of the zero-inflated model by allowing individual roadway segments to switch between zero and normal-count states over time. An important advantage of this Markov switching approach is that it allows for the direct statistical estimation of the specific roadway-segment state (i.e., zero-accident or normal-count state) whereas traditional zero-inflated models do not. To demonstrate the applicability of this approach, a two-state Markov switching negative binomial model (estimated with Bayesian inference) and standard zero-inflated negative binomial models are estimated using five-year accident frequencies on Indiana interstate highway segments. It is shown that the Markov switching model is a viable alternative and results in a superior statistical fit relative to the zero-inflated models.

Neighborhood educational disparities in active commuting among women: the effect of distance between the place of residence and the place of work/study (an ACTI-Cités study).

PubMed

Perchoux, Camille; Nazare, Julie-Anne; Benmarhnia, Tarik; Salze, Paul; Feuillet, Thierry; Hercberg, Serge; Hess, Franck; Menai, Mehdi; Weber, Christiane; Charreire, Hélène; Enaux, Christophe; Oppert, Jean-Michel; Simon, Chantal

2017-06-12

Active transportation has been associated with favorable health outcomes. Previous research highlighted the influence of neighborhood educational level on active transportation. However, little is known regarding the effect of commuting distance on social disparities in active commuting. In this regard, women have been poorly studied. The objective of this paper was to evaluate the relationship between neighborhood educational level and active commuting, and to assess whether the commuting distance modifies this relationship in adult women. This cross-sectional study is based on a subsample of women from the Nutrinet-Santé web-cohort (N = 1169). Binomial, log-binomial and negative binomial regressions were used to assess the associations between neighborhood education level and (i) the likelihood of reporting any active commuting time, and (ii) the share of commuting time made by active transportation modes. Potential effect measure modification of distance to work on the previous associations was assessed both on the additive and the multiplicative scales. Neighborhood education level was positively associated with the probability of reporting any active commuting time (relative risk = 1.774; p < 0.05) and the share of commuting time spent active (relative risk = 1.423; p < 0.05). The impact of neighborhood education was greater at long distances to work for both outcomes. Our results suggest that neighborhood educational disparities in active commuting tend to increase with commuting distance among women. Further research is needed to provide geographically driven guidance for health promotion intervention aiming at reducing disparities in active transportation among socioeconomic groups.

Comparative assessment of analytical approaches to quantify the risk for introduction of rare animal diseases: the example of avian influenza in Spain.

PubMed

Sánchez-Vizcaíno, Fernando; Perez, Andrés; Martínez-López, Beatriz; Sánchez-Vizcaíno, José Manuel

2012-08-01

Trade of animals and animal products imposes an uncertain and variable risk for exotic animal diseases introduction into importing countries. Risk analysis provides importing countries with an objective, transparent, and internationally accepted method for assessing that risk. Over the last decades, European Union countries have conducted probabilistic risk assessments quite frequently to quantify the risk for rare animal diseases introduction into their territories. Most probabilistic animal health risk assessments have been typically classified into one-level and multilevel binomial models. One-level models are more simple than multilevel models because they assume that animals or products originate from one single population. However, it is unknown whether such simplification may result in substantially different results compared to those obtained through the use of multilevel models. Here, data used on a probabilistic multilevel binomial model formulated to assess the risk for highly pathogenic avian influenza introduction into Spain were reanalyzed using a one-level binomial model and their outcomes were compared. An alternative ordinal model is also proposed here, which makes use of simpler assumptions and less information compared to those required by traditional one-level and multilevel approaches. Results suggest that, at least under certain circumstances, results of the one-level and ordinal approaches are similar to those obtained using multilevel models. Consequently, we argue that, when data are insufficient to run traditional probabilistic models, the ordinal approach presented here may be a suitable alternative to rank exporting countries in terms of the risk that they impose for the spread of rare animal diseases into disease-free countries. © 2012 Society for Risk Analysis.

Appendix E - Sample Production Facility Plan

EPA Pesticide Factsheets

This sample Spill Prevention, Control and Countermeasure (SPCC) Plan in Appendix E is intended to provide examples and illustrations of how a production facility could address a variety of scenarios in its SPCC Plan.

Transportation Demand Management Planning At Multi-Tenant Buildings, An Example Of Tdm Planning During Project

DOT National Transportation Integrated Search

1988-09-01

THIS GUIDE FOR DEVELOPERS, BUILDING OWNERS AND BUILDING MANAGERS IS ONE IN A SERIES OF SAMPLES OF TDM PLANS THAT ILLUSTRATE THE DESIGN AND PROPOSED APPLICATION OF TDM STRATEGIES. THIS SAMPLE PLAN WAS PREPARED FOR A FICTITIOUS BUILDING MANAGER NEAR DO...

Development of sampling plans for cotton bolls injured by stink bugs (Hemiptera: Pentatomidae).

PubMed

Reay-Jones, F P F; Toews, M D; Greene, J K; Reeves, R B

2010-04-01

Cotton, Gossypium hirsutum L., bolls were sampled in commercial fields for stink bug (Hemiptera: Pentatomidae) injury during 2007 and 2008 in South Carolina and Georgia. Across both years of this study, boll-injury percentages averaged 14.8 +/- 0.3 (SEM). At average boll injury treatment levels of 10, 20, 30, and 50%, the percentage of samples with at least one injured boll was 82, 97, 100, and 100%, respectively. Percentage of field-sampling date combinations with average injury < 10, 20, 30, and 50% was 35, 80, 95, and 99%, respectively. At the average of 14.8% boll injury or 2.9 injured bolls per 20-boll sample, 112 samples at Dx = 0.1 (within 10% of the mean) were required for population estimation, compared with only 15 samples at Dx = 0.3. Using a sample size of 20 bolls, our study indicated that, at the 10% threshold and alpha = beta = 0.2 (with 80% confidence), control was not needed when <1.03 bolls were injured. The sampling plan required continued sampling for a range of 1.03-3.8 injured bolls per 20-boll sample. Only when injury was > 3.8 injured bolls per 20-boll sample was a control measure needed. Sequential sampling plans were also determined for thresholds of 20, 30, and 50% injured bolls. Sample sizes for sequential sampling plans were significantly reduced when compared with a fixed sampling plan (n=10) for all thresholds and error rates.

Introducing Perception and Modelling of Spatial Randomness in Classroom

ERIC Educational Resources Information Center

De Nóbrega, José Renato

2017-01-01

A strategy to facilitate understanding of spatial randomness is described, using student activities developed in sequence: looking at spatial patterns, simulating approximate spatial randomness using a grid of equally-likely squares, using binomial probabilities for approximations and predictions and then comparing with given Poisson…

Appendix F - Sample Contingency Plan

EPA Pesticide Factsheets

This sample Contingency Plan in Appendix F is intended to provide examples of contingency planning as a reference when a facility determines that the required secondary containment is impracticable, pursuant to 40 CFR §112.7(d).

Appendix D - Sample Bulk Storage Facility Plan

EPA Pesticide Factsheets

This sample Spill Prevention, Control and Countermeasure (SPCC) Plan in Appendix D is intended to provide examples and illustrations of how a bulk storage facility could address a variety of scenarios in its SPCC Plan.

SERE: single-parameter quality control and sample comparison for RNA-Seq.

PubMed

Schulze, Stefan K; Kanwar, Rahul; Gölzenleuchter, Meike; Therneau, Terry M; Beutler, Andreas S

2012-10-03

Assessing the reliability of experimental replicates (or global alterations corresponding to different experimental conditions) is a critical step in analyzing RNA-Seq data. Pearson's correlation coefficient r has been widely used in the RNA-Seq field even though its statistical characteristics may be poorly suited to the task. Here we present a single-parameter test procedure for count data, the Simple Error Ratio Estimate (SERE), that can determine whether two RNA-Seq libraries are faithful replicates or globally different. Benchmarking shows that the interpretation of SERE is unambiguous regardless of the total read count or the range of expression differences among bins (exons or genes), a score of 1 indicating faithful replication (i.e., samples are affected only by Poisson variation of individual counts), a score of 0 indicating data duplication, and scores >1 corresponding to true global differences between RNA-Seq libraries. On the contrary the interpretation of Pearson's r is generally ambiguous and highly dependent on sequencing depth and the range of expression levels inherent to the sample (difference between lowest and highest bin count). Cohen's simple Kappa results are also ambiguous and are highly dependent on the choice of bins. For quantifying global sample differences SERE performs similarly to a measure based on the negative binomial distribution yet is simpler to compute. SERE can therefore serve as a straightforward and reliable statistical procedure for the global assessment of pairs or large groups of RNA-Seq datasets by a single statistical parameter.

SERE: Single-parameter quality control and sample comparison for RNA-Seq

PubMed Central

2012-01-01

Background Assessing the reliability of experimental replicates (or global alterations corresponding to different experimental conditions) is a critical step in analyzing RNA-Seq data. Pearson’s correlation coefficient r has been widely used in the RNA-Seq field even though its statistical characteristics may be poorly suited to the task. Results Here we present a single-parameter test procedure for count data, the Simple Error Ratio Estimate (SERE), that can determine whether two RNA-Seq libraries are faithful replicates or globally different. Benchmarking shows that the interpretation of SERE is unambiguous regardless of the total read count or the range of expression differences among bins (exons or genes), a score of 1 indicating faithful replication (i.e., samples are affected only by Poisson variation of individual counts), a score of 0 indicating data duplication, and scores >1 corresponding to true global differences between RNA-Seq libraries. On the contrary the interpretation of Pearson’s r is generally ambiguous and highly dependent on sequencing depth and the range of expression levels inherent to the sample (difference between lowest and highest bin count). Cohen’s simple Kappa results are also ambiguous and are highly dependent on the choice of bins. For quantifying global sample differences SERE performs similarly to a measure based on the negative binomial distribution yet is simpler to compute. Conclusions SERE can therefore serve as a straightforward and reliable statistical procedure for the global assessment of pairs or large groups of RNA-Seq datasets by a single statistical parameter. PMID:23033915

Population size and stopover duration estimation using mark–resight data and Bayesian analysis of a superpopulation model

USGS Publications Warehouse

Lyons, James E.; Kendall, William L.; Royle, J. Andrew; Converse, Sarah J.; Andres, Brad A.; Buchanan, Joseph B.

2016-01-01

We present a novel formulation of a mark–recapture–resight model that allows estimation of population size, stopover duration, and arrival and departure schedules at migration areas. Estimation is based on encounter histories of uniquely marked individuals and relative counts of marked and unmarked animals. We use a Bayesian analysis of a state–space formulation of the Jolly–Seber mark–recapture model, integrated with a binomial model for counts of unmarked animals, to derive estimates of population size and arrival and departure probabilities. We also provide a novel estimator for stopover duration that is derived from the latent state variable representing the interim between arrival and departure in the state–space model. We conduct a simulation study of field sampling protocols to understand the impact of superpopulation size, proportion marked, and number of animals sampled on bias and precision of estimates. Simulation results indicate that relative bias of estimates of the proportion of the population with marks was low for all sampling scenarios and never exceeded 2%. Our approach does not require enumeration of all unmarked animals detected or direct knowledge of the number of marked animals in the population at the time of the study. This provides flexibility and potential application in a variety of sampling situations (e.g., migratory birds, breeding seabirds, sea turtles, fish, pinnipeds, etc.). Application of the methods is demonstrated with data from a study of migratory sandpipers.

Finding consistent patterns: A nonparametric approach for identifying differential expression in RNA-Seq data

PubMed Central

Li, Jun; Tibshirani, Robert

2015-01-01

We discuss the identification of features that are associated with an outcome in RNA-Sequencing (RNA-Seq) and other sequencing-based comparative genomic experiments. RNA-Seq data takes the form of counts, so models based on the normal distribution are generally unsuitable. The problem is especially challenging because different sequencing experiments may generate quite different total numbers of reads, or ‘sequencing depths’. Existing methods for this problem are based on Poisson or negative binomial models: they are useful but can be heavily influenced by ‘outliers’ in the data. We introduce a simple, nonparametric method with resampling to account for the different sequencing depths. The new method is more robust than parametric methods. It can be applied to data with quantitative, survival, two-class or multiple-class outcomes. We compare our proposed method to Poisson and negative binomial-based methods in simulated and real data sets, and find that our method discovers more consistent patterns than competing methods. PMID:22127579

Extending the Binomial Checkpointing Technique for Resilience

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

Walther, Andrea; Narayanan, Sri Hari Krishna

In terms of computing time, adjoint methods offer a very attractive alternative to compute gradient information, re- quired, e.g., for optimization purposes. However, together with this very favorable temporal complexity result comes a memory requirement that is in essence proportional with the operation count of the underlying function, e.g., if algo- rithmic differentiation is used to provide the adjoints. For this reason, checkpointing approaches in many variants have become popular. This paper analyzes an extension of the so-called binomial approach to cover also possible failures of the computing systems. Such a measure of precaution is of special interest for massivemore » parallel simulations and adjoint calculations where the mean time between failure of the large scale computing system is smaller than the time needed to complete the calculation of the adjoint information. We de- scribe the extensions of standard checkpointing approaches required for such resilience, provide a corresponding imple- mentation and discuss numerical results.« less

On measures of association among genetic variables

PubMed Central

Gianola, Daniel; Manfredi, Eduardo; Simianer, Henner

2012-01-01

Summary Systems involving many variables are important in population and quantitative genetics, for example, in multi-trait prediction of breeding values and in exploration of multi-locus associations. We studied departures of the joint distribution of sets of genetic variables from independence. New measures of association based on notions of statistical distance between distributions are presented. These are more general than correlations, which are pairwise measures, and lack a clear interpretation beyond the bivariate normal distribution. Our measures are based on logarithmic (Kullback-Leibler) and on relative ‘distances’ between distributions. Indexes of association are developed and illustrated for quantitative genetics settings in which the joint distribution of the variables is either multivariate normal or multivariate-t, and we show how the indexes can be used to study linkage disequilibrium in a two-locus system with multiple alleles and present applications to systems of correlated beta distributions. Two multivariate beta and multivariate beta-binomial processes are examined, and new distributions are introduced: the GMS-Sarmanov multivariate beta and its beta-binomial counterpart. PMID:22742500

Multifractal Cross Wavelet Analysis

NASA Astrophysics Data System (ADS)

Jiang, Zhi-Qiang; Gao, Xing-Lu; Zhou, Wei-Xing; Stanley, H. Eugene

Complex systems are composed of mutually interacting components and the output values of these components usually exhibit long-range cross-correlations. Using wavelet analysis, we propose a method of characterizing the joint multifractal nature of these long-range cross correlations, a method we call multifractal cross wavelet analysis (MFXWT). We assess the performance of the MFXWT method by performing extensive numerical experiments on the dual binomial measures with multifractal cross correlations and the bivariate fractional Brownian motions (bFBMs) with monofractal cross correlations. For binomial multifractal measures, we find the empirical joint multifractality of MFXWT to be in approximate agreement with the theoretical formula. For bFBMs, MFXWT may provide spurious multifractality because of the wide spanning range of the multifractal spectrum. We also apply the MFXWT method to stock market indices, and in pairs of index returns and volatilities we find an intriguing joint multifractal behavior. The tests on surrogate series also reveal that the cross correlation behavior, particularly the cross correlation with zero lag, is the main origin of cross multifractality.

Distribution of apparent activation energy counterparts during thermo - And thermo-oxidative degradation of Aronia melanocarpa (black chokeberry).

PubMed

Janković, Bojan; Marinović-Cincović, Milena; Janković, Marija

2017-09-01

Kinetics of degradation for Aronia melanocarpa fresh fruits in argon and air atmospheres were investigated. The investigation was based on probability distributions of apparent activation energy of counterparts (ε a ). Isoconversional analysis results indicated that the degradation process in an inert atmosphere was governed by decomposition reactions of esterified compounds. Also, based on same kinetics approach, it was assumed that in an air atmosphere, the primary compound in degradation pathways could be anthocyanins, which undergo rapid chemical reactions. A new model of reactivity demonstrated that, under inert atmospheres, expectation values for ε a occured at levels of statistical probability. These values corresponded to decomposition processes in which polyphenolic compounds might be involved. ε a values obeyed laws of binomial distribution. It was established that, for thermo-oxidative degradation, Poisson distribution represented a very successful approximation for ε a values where there was additional mechanistic complexity and the binomial distribution was no longer valid. Copyright © 2017 Elsevier Ltd. All rights reserved.

34 CFR Appendix A to Subpart N of... - Sample Default Prevention Plan

Code of Federal Regulations, 2011 CFR

2011-07-01

... 34 Education 3 2011-07-01 2011-07-01 false Sample Default Prevention Plan A Appendix A to Subpart N of Part 668 Education Regulations of the Offices of the Department of Education (Continued) OFFICE... Default Rates Appendix A to Subpart N of Part 668—Sample Default Prevention Plan This appendix is provided...

40 CFR Appendix Xi to Part 86 - Sampling Plans for Selective Enforcement Auditing of Light-Duty Vehicles

Code of Federal Regulations, 2010 CFR

2010-07-01

... 40 Protection of Environment 19 2010-07-01 2010-07-01 false Sampling Plans for Selective Enforcement Auditing of Light-Duty Vehicles XI Appendix XI to Part 86 Protection of Environment ENVIRONMENTAL... Enforcement Auditing of Light-Duty Vehicles 40% AQL Table 1—Sampling Plan Code Letter Annual sales of...

Microbiological sampling plan based on risk classification to verify supplier selection and production of served meals in food service operation.

PubMed

Lahou, Evy; Jacxsens, Liesbeth; Van Landeghem, Filip; Uyttendaele, Mieke

2014-08-01

Food service operations are confronted with a diverse range of raw materials and served meals. The implementation of a microbial sampling plan in the framework of verification of suppliers and their own production process (functionality of their prerequisite and HACCP program), demands selection of food products and sampling frequencies. However, these are often selected without a well described scientifically underpinned sampling plan. Therefore, an approach on how to set-up a focused sampling plan, enabled by a microbial risk categorization of food products, for both incoming raw materials and meals served to the consumers is presented. The sampling plan was implemented as a case study during a one-year period in an institutional food service operation to test the feasibility of the chosen approach. This resulted in 123 samples of raw materials and 87 samples of meal servings (focused on high risk categorized food products) which were analyzed for spoilage bacteria, hygiene indicators and food borne pathogens. Although sampling plans are intrinsically limited in assessing the quality and safety of sampled foods, it was shown to be useful to reveal major non-compliances and opportunities to improve the food safety management system in place. Points of attention deduced in the case study were control of Listeria monocytogenes in raw meat spread and raw fish as well as overall microbial quality of served sandwiches and salads. Copyright © 2014 Elsevier Ltd. All rights reserved.

Data Validation Package August 2015 Groundwater Sampling at the Grand Junction, Colorado, Disposal Site October 2015

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

Frazier, William; Baur, Gary

2015-11-03

The 1998 Interim Long-Term Surveillance Plan for the Cheney Disposal Site Near Grand Junction, Colorado, requires annual monitoring to assess the performance of the disposal cell. Monitoring wells 0731, 0732 and 0733 were sampled as specified in the plan. Sampling and analyses were conducted in accordance with Sampling and Analysis Plan for the U.S. Department of Energy Office of Legacy Management Sites.

Health services utilization of people having and not having a regular doctor in Canada.

PubMed

Thanh, Nguyen Xuan; Rapoport, John

2017-04-01

Canada having a universal health insurance plan that provides hospital and physician benefits offers a natural experiment of whether continuity of care actually provides lower or higher utilization of services. The question we are evaluating is whether Canadians, who have a regular physician, use more health resources than those who do not have one? Using two statistical methods, including propensity score matching and zero-inflated negative binomial regression, we analyzed data from the 2010 and 2007/2008 Canadian Community Health Surveys separately to document differences between people self-reportedly having and not having a regular doctor in the utilization of general practitioner, specialist, and hospital services. The results showed, consistently for all two statistical methods and two datasets used, that people reportedly having a regular doctor used more healthcare services than a matched group of people who was self-reportedly not having a regular doctor. For specialist and hospital utilization, the statistically significant differences were in the likelihood if the service was used but not in the number of specialist visits or hospital nights among users. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Land cover and air pollution are associated with asthma hospitalisations: A cross-sectional study.

PubMed

Alcock, Ian; White, Mathew; Cherrie, Mark; Wheeler, Benedict; Taylor, Jonathon; McInnes, Rachel; Otte Im Kampe, Eveline; Vardoulakis, Sotiris; Sarran, Christophe; Soyiri, Ireneous; Fleming, Lora

2017-12-01

There is increasing policy interest in the potential for vegetation in urban areas to mitigate harmful effects of air pollution on respiratory health. We aimed to quantify relationships between tree and green space density and asthma-related hospitalisations, and explore how these varied with exposure to background air pollution concentrations. Population standardised asthma hospitalisation rates (1997-2012) for 26,455 urban residential areas of England were merged with area-level data on vegetation and background air pollutant concentrations. We fitted negative binomial regression models using maximum likelihood estimation to obtain estimates of asthma-vegetation relationships at different levels of pollutant exposure. Green space and gardens were associated with reductions in asthma hospitalisation when pollutant exposures were lower but had no significant association when pollutant exposures were higher. In contrast, tree density was associated with reduced asthma hospitalisation when pollutant exposures were higher but had no significant association when pollutant exposures were lower. We found differential effects of natural environments at high and low background pollutant concentrations. These findings can provide evidence for urban planning decisions which aim to leverage health co-benefits from environmental improvements. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effect of asthma and PTSD on persistence and onset of gastroesophageal reflux symptoms among adults exposed to the September 11, 2001, terrorist attacks.

PubMed

Li, Jiehui; Brackbill, Robert M; Jordan, Hannah T; Cone, James E; Farfel, Mark R; Stellman, Steven D

2016-09-01

Little is known about the direction of causality among asthma, posttraumatic stress disorder (PTSD), and onset of gastroesophageal reflux symptoms (GERS) after exposure to the 9/11/2001 World Trade Center (WTC) disaster. Using data from the WTC Health Registry, we investigated the effects of early diagnosed post-9/11 asthma and PTSD on the late onset and persistence of GERS using log-binomial regression, and examined whether PTSD mediated the asthma-GERS association using structural equation modeling. Of 29,406 enrollees, 23% reported GERS at follow-up in 2011-2012. Early post-9/11 asthma and PTSD were each independently associated with both the persistence of GERS that was present at baseline and the development of GERS in persons without a prior history. PTSD mediated the association between early post-9/11 asthma and late-onset GERS. Clinicians should assess patients with post-9/11 GERS for comorbid asthma and PTSD, and plan medical care for these conditions in an integrated fashion. Am. J. Ind. Med. 59:805-814, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Flood return level analysis of Peaks over Threshold series under changing climate

NASA Astrophysics Data System (ADS)

Li, L.; Xiong, L.; Hu, T.; Xu, C. Y.; Guo, S.

2016-12-01

Obtaining insights into future flood estimation is of great significance for water planning and management. Traditional flood return level analysis with the stationarity assumption has been challenged by changing environments. A method that takes into consideration the nonstationarity context has been extended to derive flood return levels for Peaks over Threshold (POT) series. With application to POT series, a Poisson distribution is normally assumed to describe the arrival rate of exceedance events, but this distribution assumption has at times been reported as invalid. The Negative Binomial (NB) distribution is therefore proposed as an alternative to the Poisson distribution assumption. Flood return levels were extrapolated in nonstationarity context for the POT series of the Weihe basin, China under future climate scenarios. The results show that the flood return levels estimated under nonstationarity can be different with an assumption of Poisson and NB distribution, respectively. The difference is found to be related to the threshold value of POT series. The study indicates the importance of distribution selection in flood return level analysis under nonstationarity and provides a reference on the impact of climate change on flood estimation in the Weihe basin for the future.

Exploring Audiologists' Language and Hearing Aid Uptake in Initial Rehabilitation Appointments.

PubMed

Sciacca, Anna; Meyer, Carly; Ekberg, Katie; Barr, Caitlin; Hickson, Louise

2017-06-13

The study aimed (a) to profile audiologists' language during the diagnosis and management planning phase of hearing assessment appointments and (b) to explore associations between audiologists' language and patients' decisions to obtain hearing aids. Sixty-two audiologist-patient dyads participated. Patient participants were aged 55 years or older. Hearing assessment appointments were audiovisually recorded and transcribed for analysis. Audiologists' language was profiled using two measures: general language complexity and use of jargon. A binomial, multivariate logistic regression analysis was conducted to investigate the associations between these language measures and hearing aid uptake. The logistic regression model revealed that the Flesch-Kincaid reading grade level of audiologists' language was significantly associated with hearing aid uptake. Patients were less likely to obtain hearing aids when audiologists' language was at a higher reading grade level. No associations were found between audiologists' use of jargon and hearing aid uptake. Audiologists' use of complex language may present a barrier for patients to understand hearing rehabilitation recommendations. Reduced understanding may limit patient participation in the decision-making process and result in patients being less willing to trial hearing aids. Clear, concise language is recommended to facilitate shared decision making.

Underground Test Area Calendar Year 2014 Annual Sampling Analysis Report Nevada National Security Site, Nevada, Revision 0

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

Farnham, Irene

2016-12-01

This report presents the analytical data for the 2014 fiscal year (FY) and calendar year (CY) (October 1, 2013, through December 31, 2014), and an evaluation of the data to ensure that the Sampling Plan’s objectives are met. In addition to samples collected and analyzed for the Sampling Plan, some NNSS wells are monitored by NNSA/NFO to demonstrate compliance with State-issued water discharge permits; with protection of groundwater from ongoing radiological waste disposal activities (compliance wells); and to demonstrate that the onsite drinking water supply is below SDWA maximum contaminant levels (MCLs) (public water system [PWS] wells). While not allmore » sampled locations are required by the Sampling Plan, these samples are relevant to its objectives and are therefore presented herein for completeness purposes. Special investigations that took place in 2014 that are relevant to the Sampling Plan are also presented. This is the first annual report released to support Sampling Plan implementation.« less

SAMPLING OF CONTAMINATED SITES

EPA Science Inventory

A critical aspect of characterization of the amount and species of contamination of a hazardous waste site is the sampling plan developed for that site. f the sampling plan is not thoroughly conceptualized before sampling takes place, then certain critical aspects of the limits o...

Assessment of Alcohol and Tobacco Use Disorders Among Religious Users of Ayahuasca

PubMed Central

Barbosa, Paulo Cesar Ribeiro; Tófoli, Luís F.; Bogenschutz, Michael P.; Hoy, Robert; Berro, Lais F.; Marinho, Eduardo A. V.; Areco, Kelsy N.; Winkelman, Michael J.

2018-01-01

The aims of this study were to assess the impact of ceremonial use of ayahuasca—a psychedelic brew containing N,N-dimethyltryptamine (DMT) and β-carboline —and attendance at União do Vegetal (UDV) meetings on substance abuse; here we report the findings related to alcohol and tobacco use disorder. A total of 1,947 members of UDV 18+ years old were evaluated in terms of years of membership and ceremonial attendance during the previous 12 months. Participants were recruited from 10 states from all major regions of Brazil. Alcohol and tobacco use was evaluated through questionnaires first developed by the World Health Organization and the Substance Abuse and Mental Health Services Administration. Analyses compared levels of alcohol and tobacco use disorder between the UDV and a national normative sample (n = 7,939). Binomial tests for proportions indicated that lifetime use of alcohol and tobacco was higher in UDV sample compared to the Brazilian norms for age ranges of 25–34 and over 34 years old, but not for the age range of 18–24 years old. However, current use disorders for alcohol and tobacco were significantly lower in the UDV sample than the Brazilian norms. Regression analyses revealed a significant impact of attendance at ayahuasca ceremonies during the previous 12 months and years of UDV membership on the reduction of alcohol and tobacco use disorder. PMID:29740355

A robust design mark-resight abundance estimator allowing heterogeneity in resighting probabilities

USGS Publications Warehouse

McClintock, B.T.; White, Gary C.; Burnham, K.P.

2006-01-01

This article introduces the beta-binomial estimator (BBE), a closed-population abundance mark-resight model combining the favorable qualities of maximum likelihood theory and the allowance of individual heterogeneity in sighting probability (p). The model may be parameterized for a robust sampling design consisting of multiple primary sampling occasions where closure need not be met between primary occasions. We applied the model to brown bear data from three study areas in Alaska and compared its performance to the joint hypergeometric estimator (JHE) and Bowden's estimator (BOWE). BBE estimates suggest heterogeneity levels were non-negligible and discourage the use of JHE for these data. Compared to JHE and BOWE, confidence intervals were considerably shorter for the AICc model-averaged BBE. To evaluate the properties of BBE relative to JHE and BOWE when sample sizes are small, simulations were performed with data from three primary occasions generated under both individual heterogeneity and temporal variation in p. All models remained consistent regardless of levels of variation in p. In terms of precision, the AICc model-averaged BBE showed advantages over JHE and BOWE when heterogeneity was present and mean sighting probabilities were similar between primary occasions. Based on the conditions examined, BBE is a reliable alternative to JHE or BOWE and provides a framework for further advances in mark-resight abundance estimation. ?? 2006 American Statistical Association and the International Biometric Society.

A Binomial Test of Group Differences with Correlated Outcome Measures

ERIC Educational Resources Information Center

Onwuegbuzie, Anthony J.; Levin, Joel R.; Ferron, John M.

2011-01-01

Building on previous arguments for why educational researchers should not provide effect-size estimates in the face of statistically nonsignificant outcomes (Robinson & Levin, 1997), Onwuegbuzie and Levin (2005) proposed a 3-step statistical approach for assessing group differences when multiple outcome measures are individually analyzed…

Comparing Environmental Influences on Coral Bleaching Across and within Species using Clustered Binomial Regression

EPA Science Inventory

Differential susceptibility among reef-building coral species can lead to community shifts and loss of diversity as a result of temperature-induced mass bleaching events. However, the influence of the local environment on species-specific bleaching susceptibilities has not been ...

Yes, the GIGP Really Does Work--And Is Workable!

ERIC Educational Resources Information Center

Burrell, Quentin L.; Fenton, Michael R.

1993-01-01

Discusses the generalized inverse Gaussian-Poisson (GIGP) process for informetric modeling. Negative binomial distribution is discussed, construction of the GIGP process is explained, zero-truncated GIGP is considered, and applications of the process with journals, library circulation statistics, and database index terms are described. (50…

Sequence Factorial and Its Applications

ERIC Educational Resources Information Center

Asiru, Muniru A.

2012-01-01

In this note, we introduce sequence factorial and use this to study generalized M-bonomial coefficients. For the sequence of natural numbers, the twin concepts of sequence factorial and generalized M-bonomial coefficients, respectively, extend the corresponding concepts of factorial of an integer and binomial coefficients. Some latent properties…

Estimating species - area relationships by modeling abundance and frequency subject to incomplete sampling.

PubMed

Yamaura, Yuichi; Connor, Edward F; Royle, J Andrew; Itoh, Katsuo; Sato, Kiyoshi; Taki, Hisatomo; Mishima, Yoshio

2016-07-01

Models and data used to describe species-area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species-area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species-area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density-area relationships and occurrence probability-area relationships can alter the form of species-area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied to a variety of study designs and allows the inclusion of additional environmental covariates.

Estimating species – area relationships by modeling abundance and frequency subject to incomplete sampling

USGS Publications Warehouse

Yamaura, Yuichi; Connor, Edward F.; Royle, Andy; Itoh, Katsuo; Sato, Kiyoshi; Taki, Hisatomo; Mishima, Yoshio

2016-01-01

Models and data used to describe species–area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species–area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species-level Poisson processes and estimate patch-level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early-successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species–area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density–area relationships and occurrence probability–area relationships can alter the form of species–area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied to a variety of study designs and allows the inclusion of additional environmental covariates.

Stratification of American hearing aid users by age and audiometric characteristics: a method for representative sampling.

PubMed

Aronoff, Justin M; Yoon, Yang-soo; Soli, Sigfrid D

2010-06-01

Stratified sampling plans can increase the accuracy and facilitate the interpretation of a dataset characterizing a large population. However, such sampling plans have found minimal use in hearing aid (HA) research, in part because of a paucity of quantitative data on the characteristics of HA users. The goal of this study was to devise a quantitatively derived stratified sampling plan for HA research, so that such studies will be more representative and generalizable, and the results obtained using this method are more easily reinterpreted as the population changes. Pure-tone average (PTA) and age information were collected for 84,200 HAs acquired in 2006 and 2007. The distribution of PTA and age was quantified for each HA type and for a composite of all HA users. Based on their respective distributions, PTA and age were each divided into three groups, the combination of which defined the stratification plan. The most populous PTA and age group was also subdivided, allowing greater homogeneity within strata. Finally, the percentage of users in each stratum was calculated. This article provides a stratified sampling plan for HA research, based on a quantitative analysis of the distribution of PTA and age for HA users. Adopting such a sampling plan will make HA research results more representative and generalizable. In addition, data acquired using such plans can be reinterpreted as the HA population changes.

Science: Curriculum Guide for Teaching Gifted Children Science in Grades One Through Three: A Sample Ecology Unit.

ERIC Educational Resources Information Center

California State Dept. of Education, Sacramento. Office of Curriculum Services.

The natural science curriculum guide for gifted primary students includes a sample teaching-learning plan for an ecology unit and eight sample lesson plans. Chapter One provides an overview of the unit, a review of behavioral objectives, and a list of concepts and generalizations. The second chapter cites a teaching-learning plan dealing with such…

40 CFR Appendix X to Part 86 - Sampling Plans for Selective Enforcement Auditing of Heavy-Duty Engines and Light-Duty Trucks

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 19 2014-07-01 2014-07-01 false Sampling Plans for Selective Enforcement Auditing of Heavy-Duty Engines and Light-Duty Trucks X Appendix X to Part 86 Protection of... AND IN-USE HIGHWAY VEHICLES AND ENGINES Pt. 86, App. X Appendix X to Part 86—Sampling Plans for...

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

Tyrrell, Evan; Denny, Angelita

Fifty-two groundwater samples and one surface water sample were collected at the Monument Valley, Arizona, Processing Site to monitor groundwater contaminants for evaluating the effectiveness of the proposed compliance strategy as specified in the 1999 Final Site Observational Work Plan for the UMTRA Project Site at Monument Valley, Arizona. Sampling and analyses were conducted as specified in the Sampling and Analysis Plan for U.S. Department of Energy Office of Legacy Management Sites (LMS/PRO/S04351, continually updated, http://energy.gov/lm/downloads/sampling-and-analysis-plan-us-department- energy-office-legacy-management-sites). Samples were collected for metals, anions, nitrate + nitrite as N, and ammonia as N analyses at all locations.

Customized sampling plans : a guide to alternative sampling techniques for National Transit Database reporting

DOT National Transportation Integrated Search

2004-05-01

For estimating the system total unlinked passenger trips and passenger miles of a fixed-route bus system for the National Transit Database (NTD), the FTA approved sampling plans may either over-sample or do not yield FTAs required confidence and p...

IAEA Sampling Plan

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

Geist, William H.

2017-09-15

The objectives for this presentation are to describe the method that the IAEA uses to determine a sampling plan for nuclear material measurements; describe the terms detection probability and significant quantity; list the three nuclear materials measurement types; describe the sampling method applied to an item facility; and describe multiple method sampling.

Statistical Methods in Assembly Quality Management of Multi-Element Products on Automatic Rotor Lines

NASA Astrophysics Data System (ADS)

Pries, V. V.; Proskuriakov, N. E.

2018-04-01

To control the assembly quality of multi-element mass-produced products on automatic rotor lines, control methods with operational feedback are required. However, due to possible failures in the operation of the devices and systems of automatic rotor line, there is always a real probability of getting defective (incomplete) products into the output process stream. Therefore, a continuous sampling control of the products completeness, based on the use of statistical methods, remains an important element in managing the quality of assembly of multi-element mass products on automatic rotor lines. The feature of continuous sampling control of the multi-element products completeness in the assembly process is its breaking sort, which excludes the possibility of returning component parts after sampling control to the process stream and leads to a decrease in the actual productivity of the assembly equipment. Therefore, the use of statistical procedures for continuous sampling control of the multi-element products completeness when assembled on automatic rotor lines requires the use of such sampling plans that ensure a minimum size of control samples. Comparison of the values of the limit of the average output defect level for the continuous sampling plan (CSP) and for the automated continuous sampling plan (ACSP) shows the possibility of providing lower limit values for the average output defects level using the ACSP-1. Also, the average sample size when using the ACSP-1 plan is less than when using the CSP-1 plan. Thus, the application of statistical methods in the assembly quality management of multi-element products on automatic rotor lines, involving the use of proposed plans and methods for continuous selective control, will allow to automating sampling control procedures and the required level of quality of assembled products while minimizing sample size.

Critical Values for Lawshe's Content Validity Ratio: Revisiting the Original Methods of Calculation

ERIC Educational Resources Information Center

Ayre, Colin; Scally, Andrew John

2014-01-01

The content validity ratio originally proposed by Lawshe is widely used to quantify content validity and yet methods used to calculate the original critical values were never reported. Methods for original calculation of critical values are suggested along with tables of exact binomial probabilities.

School Violence: The Role of Parental and Community Involvement

ERIC Educational Resources Information Center

Lesneskie, Eric; Block, Steven

2017-01-01

This study utilizes the School Survey on Crime and Safety to identify variables that predict lower levels of violence from four domains: school security, school climate, parental involvement, and community involvement. Negative binomial regression was performed and the findings indicate that statistically significant results come from all four…

Predicting Children's Asthma Hospitalizations: Rural and Urban Differences in Texas

ERIC Educational Resources Information Center

Grineski, Sara E.

2009-01-01

Asthma is the number one chronic health condition facing children today; however, little is known about rural-urban inequalities in asthma. This "area effects on health" study examines rural-urban differences in childhood asthma hospitalizations within the state of Texas using negative binomial regression models. Effects associated with…

Comments Regarding the Binary Power Law for Heterogeneity of Disease Incidence

USDA-ARS?s Scientific Manuscript database

The binary power law (BPL) has been successfully used to characterize heterogeneity (over dispersion or small-scale aggregation) of disease incidence for many plant pathosystems. With the BPL, the log of the observed variance is a linear function of the log of the theoretical variance for a binomial...

The Grammar of Fantasy.

ERIC Educational Resources Information Center

Rodari, Gianni

1998-01-01

Depicts how any word chosen by chance can function as a magical word to exhume fields of memory and excite imagination. Details several word games of invention for children (such as the "fantastic binomial," using creative errors, and "Little Red Riding Hood in a Helicopter") that juxtapose normally unrelated words and that can…

An Alternate Approach to Alternating Sums: A Method to DIE for

ERIC Educational Resources Information Center

Benjamin, Arthur T.; Quinn, Jennifer J.

2008-01-01

Positive sums count. Alternating sums match. Alternating sums of binomial coefficients, Fibonacci numbers, and other combinatorial quantities are analyzed using sign-reversing involutions. In particular, we describe the quantity being considered, match positive and negative terms through an Involution, and count the Exceptions to the matching rule…

Transportation safety data and analysis : Volume 2, Calibration of the highway safety manual and development of new safety performance functions.

DOT National Transportation Integrated Search

2011-03-01

This report documents the calibration of the Highway Safety Manual (HSM) safety performance function (SPF) : for rural two-lane two-way roadway segments in Utah and the development of new models using negative : binomial and hierarchical Bayesian mod...

Teaching Pascal's Triangle from a Computer Science Perspective

ERIC Educational Resources Information Center

Skurnick, Ronald

2004-01-01

Pascal's Triangle is named for the seventeenth-century French philosopher and mathematician Blaise Pascal (the same person for whom the computer programming language is named). Students are generally introduced to Pascal's Triangle in an algebra or precalculus class in which the Binomial Theorem is presented. This article, presents a new method…

A Unifying Probability Example.

ERIC Educational Resources Information Center

Maruszewski, Richard F., Jr.

2002-01-01

Presents an example from probability and statistics that ties together several topics including the mean and variance of a discrete random variable, the binomial distribution and its particular mean and variance, the sum of independent random variables, the mean and variance of the sum, and the central limit theorem. Uses Excel to illustrate these…

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

Buchstaber, V M; Ustinov, A V

We describe the coefficient rings of universal formal group laws which arise in algebraic geometry, algebraic topology and their application to mathematical physics. We also describe the homomorphisms of these coefficient rings coming from reductions of one formal group law to another. The proofs are based on the number-theoretic properties of binomial coefficients. Bibliography: 37 titles.

Visualizing and Understanding Probability and Statistics: Graphical Simulations Using Excel

ERIC Educational Resources Information Center

Gordon, Sheldon P.; Gordon, Florence S.

2009-01-01

The authors describe a collection of dynamic interactive simulations for teaching and learning most of the important ideas and techniques of introductory statistics and probability. The modules cover such topics as randomness, simulations of probability experiments such as coin flipping, dice rolling and general binomial experiments, a simulation…

An Exercise to Introduce Power

ERIC Educational Resources Information Center

Seier, Edith; Liu, Yali

2013-01-01

In introductory statistics courses, the concept of power is usually presented in the context of testing hypotheses about the population mean. We instead propose an exercise that uses a binomial probability table to introduce the idea of power in the context of testing a population proportion. (Contains 2 tables, and 2 figures.)

Data Validation Package, June 2016 Groundwater Sampling at the Hallam, Nebraska, Decommissioned Reactor Site, August 2016

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

Surovchak, Scott; Miller, Michele

The 2008 Long-Term Surveillance Plan [LTSP] for the Decommissioned Hallam Nuclear Power Facility, Hallam, Nebraska (http://www.lm.doe.gov/Hallam/Documents.aspx) requires groundwater monitoring once every 2 years. Seventeen monitoring wells at the Hallam site were sampled during this event as specified in the plan. Planned monitoring locations are shown in Attachment 1, Sampling and Analysis Work Order. Water levels were measured at all sampled wells and at two additional wells (6A and 6B) prior to the start of sampling. Additionally, water levels of each sampled well were measured at the beginning of sampling. See Attachment 2, Trip Report, for additional details. Sampling and analysismore » were conducted as specified in Sampling and Analysis Plan for U.S. Department of Energy Office of Legacy Management Sites (LMS/PRO/S04351, continually updated, http://energy.gov/lm/downloads/sampling-and-analysis-plan-us-department- energy-office-legacy-management-sites). Gross alpha and gross beta are the only parameters that were detected at statistically significant concentrations. Time/concentration graphs of the gross alpha and gross beta data are included in Attachment 3, Data Presentation. The gross alpha and gross beta activity concentrations observed are consistent with values previously observed and are attributed to naturally occurring radionuclides (e.g., uranium and uranium decay chain products) in the groundwater.« less

UMTRA Project water sampling and analysis plan, Durango, Colorado. Revision 1

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

NONE

1995-09-01

Planned, routine ground water sampling activities at the US Department of Energy (DOE) Uranium Mill Tailings Remedial Action (UMTRA) Project site in Durango, Colorado, are described in this water sampling and analysis plan. The plan identifies and justifies the sampling locations, analytical parameters, detection limits, and sampling frequency for the routine monitoring stations at the site. The ground water data are used to characterize the site ground water compliance strategies and to monitor contaminants of potential concern identified in the baseline risk assessment (DOE, 1995a). Regulatory basis for routine ground water monitoring at UMTRA Project sites is derived from themore » US EPA regulations in 40 CFR Part 192 (1994) and EPA standards of 1995 (60 FR 2854). Sampling procedures are guided by the UMTRA Project standard operating procedures (SOP) (JEG, n.d.), the Technical Approach Document (TAD) (DOE, 1989), and the most effective technical approach for the site.« less

Data Validation Package - July 2016 Groundwater Sampling at the Gunnison, Colorado, Disposal Site

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

Linard, Joshua; Campbell, Sam

Groundwater sampling at the Gunnison, Colorado, Disposal Site is conducted every 5 years to monitor disposal cell performance. During this event, samples were collected from eight monitoring wells as specified in the 1997 Long-Term Surveillance Plan for the Gunnison, Colorado, Disposal Site. Sampling and analyses were conducted as specified in the Sampling and Analysis Plan for US Department of Energy Office of Legacy Management Sites (LMS/PRO/S04351, continually updated, http://energy.gov/lm/downloads/sampling-and­ analysis-plan-us-department-energy-office-legacy-management-sites). Planned monitoring locations are shown in Attachment 1, Sampling and Analysis Work Order. A duplicate sample was collected from location 0723. Water levels were measured at all monitoring wells thatmore » were sampled and seven additional wells. The analytical data and associated qualifiers can be viewed in environmental database reports and are also available for viewing with dynamic mapping via the GEMS (Geospatial Environmental Mapping System) website at http://gems.lm.doe.gov/#. No issues were identified during the data validation process that require additional action or follow-up.« less

Development of an automated pre-sampling plan for construction projects : final report.

DOT National Transportation Integrated Search

1983-03-01

The development of an automated pre-sampling plan was undertaken to free the district construction personnel from the cumbersome and time-consuming task of preparing such plans manually. A computer program was written and linked to a data file which ...

Impact of a passive social marketing intervention in community pharmacies on oral contraceptive and condom sales: a quasi-experimental study.

PubMed

Farris, Karen B; Aquilino, Mary L; Batra, Peter; Marshall, Vince; Losch, Mary E

2015-02-13

Almost 50% of pregnancies in the United States are unwanted or mistimed. Notably, just over one-half of unintended pregnancies occurred when birth control was being used, suggesting inappropriate or poor use or contraceptive failure. About two-thirds of all women who are of reproductive age use contraceptives, and oral hormonal contraceptives remain the most common contraceptive method. Often, contraceptive products are obtained in community pharmacies. The purpose of this study was to determine whether a pharmacy-based intervention would impact sales of contraceptive products in pharmacies. This study was conducted in Iowa and used a quasi-experimental design including 55 community pharmacies (independent and grocery) in 12 counties as the intervention and 32 grocery pharmacies in 10 counties as a comparison group. The passive intervention was focused towards 18-30 year old women who visited community pharmacies and prompted those of childbearing age to "plan your pregnancy" and "consider using birth control". The intervention was delivered via educational tri-fold brochures, posters and 'shelf talkers.' Data sources for evaluation were contraceptive sales from intervention and comparison pharmacies, and a mixed negative binomial regression was used with study group*time interactions to examine the impact of the intervention on oral contraceptive and condom sales. Data from 2009 were considered baseline sales. From 2009 to 2011, condom sales decreased over time and oral contraceptives sales showed no change. Overall, the units sold were significantly higher in grocery pharmacies than in independent pharmacies for both contraceptive types. In the negative binomial regression for condoms, there was an overall significant interaction between the study group and time variables (p = 0.003), indicating an effect of the intervention, and there was a significant slowing in the drop of sales at time 3 in comparison with time 1 (p < 0.001). There was a statistically significant association between pharmacy type and study group, where the independent intervention pharmacies had a higher proportion of stores with increases in condom sales compared to grocery pharmacies in the intervention or comparison group. A passive community pharmacy-based public health intervention appeared to reduce the decrease in condom sales from baseline, particularly in independent pharmacies, but it did not impact oral contraceptive sales.

Present and foreseeable future of metabolomics in forensic analysis.

PubMed

Castillo-Peinado, L S; Luque de Castro, M D

2016-06-21

The revulsive publications during the last years on the precariousness of forensic sciences worldwide have promoted the move of major steps towards improvement of this science. One of the steps (viz. a higher involvement of metabolomics in the new era of forensic analysis) deserves to be discussed under different angles. Thus, the characteristics of metabolomics that make it a useful tool in forensic analysis, the aspects in which this omics is so far implicit, but not mentioned in forensic analyses, and how typical forensic parameters such as the post-mortem interval or fingerprints take benefits from metabolomics are critically discussed in this review. The way in which the metabolomics-forensic binomial succeeds when either conventional or less frequent samples are used is highlighted here. Finally, the pillars that should support future developments involving metabolomics and forensic analysis, and the research required for a fruitful in-depth involvement of metabolomics in forensic analysis are critically discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

Maternal employment and Mexican school-age children overweight in 2012: the importance of households features.

PubMed

Espinosa, Alejandro Martínez

2018-01-01

International evidence regarding the relationship between maternal employment and school-age children overweight and obesity shows divergent results. In Mexico, this relationship has not been confirmed by national data sets analysis. Consequently, the objective of this article was to evaluate the role of the mothers' participation in labor force related to excess body weight in Mexican school-age children (aged 5-11 years). A cross-sectional study was conducted on a sample of 17,418 individuals from the National Health and Nutrition Survey 2012, applying binomial logistic regression models. After controlling for individual, maternal and contextual features, the mothers' participation in labor force was associated with children body composition. However, when the household features (living arrangements, household ethnicity, size, food security and socioeconomic status) were incorporated, maternal employment was no longer statically significant. Household features are crucial factors for understanding the overweight and obesity prevalence levels in Mexican school-age children, despite the mother having a paid job. Copyright: © 2018 Permanyer.

Measuring demand for flat water recreation using a two-stage/disequilibrium travel cost model with adjustment for overdispersion and self-selection

NASA Astrophysics Data System (ADS)

McKean, John R.; Johnson, Donn; Taylor, R. Garth

2003-04-01

An alternate travel cost model is applied to an on-site sample to estimate the value of flat water recreation on the impounded lower Snake River. Four contiguous reservoirs would be eliminated if the dams are breached to protect endangered Pacific salmon and steelhead trout. The empirical method applies truncated negative binomial regression with adjustment for endogenous stratification. The two-stage decision model assumes that recreationists allocate their time among work and leisure prior to deciding among consumer goods. The allocation of time and money among goods in the second stage is conditional on the predetermined work time and income. The second stage is a disequilibrium labor market which also applies if employers set work hours or if recreationists are not in the labor force. When work time is either predetermined, fixed by contract, or nonexistent, recreationists must consider separate prices and budgets for time and money.

Confidence of compliance: a Bayesian approach for percentile standards.

PubMed

McBride, G B; Ellis, J C

2001-04-01

Rules for assessing compliance with percentile standards commonly limit the number of exceedances permitted in a batch of samples taken over a defined assessment period. Such rules are commonly developed using classical statistical methods. Results from alternative Bayesian methods are presented (using beta-distributed prior information and a binomial likelihood), resulting in "confidence of compliance" graphs. These allow simple reading of the consumer's risk and the supplier's risks for any proposed rule. The influence of the prior assumptions required by the Bayesian technique on the confidence results is demonstrated, using two reference priors (uniform and Jeffreys') and also using optimistic and pessimistic user-defined priors. All four give less pessimistic results than does the classical technique, because interpreting classical results as "confidence of compliance" actually invokes a Bayesian approach with an extreme prior distribution. Jeffreys' prior is shown to be the most generally appropriate choice of prior distribution. Cost savings can be expected using rules based on this approach.

Cell Phone Use While Driving: Prospective Association with Emerging Adult Use.

PubMed

Trivedi, Neha; Haynie, Denise; Bible, Joe; Liu, Danping; Simons-Morton, Bruce

2017-09-01

Secondary task engagement such as cell phone use while driving is a common behavior among adolescents and emerging adults. Texting and other distracting cell phone use in this population contributes to the high rate of fatal car crashes. Peer engagement in similar risky driving behaviors, such as texting, could socially influence driver phone use behavior. The present study investigates the prospective association between peer and emerging adult texting while driving the first year after high school. Surveys were conducted with a national sample of emerging adults and their nominated peers. Binomial logistic regression analyses, adjusting for gender, race/ethnicity, parental education, and family affluence, showed that participants (n=212) with peers (n=675) who reported frequently texting while driving, were significantly more likely to text while driving the following year (odds ratio, 3.01; 95% CI, 1.19-7.59; P=0.05). The findings are consistent with the idea that peer texting behavior influences the prevalence of texting while driving among emerging adults. Copyright © 2017 Elsevier Ltd. All rights reserved.

Prevalence and Correlates of Smoking among Low-Income Adults Residing in New York City Public Housing Developments-2015.

PubMed

Feinberg, A; Lopez, P M; Wyka, K; Islam, N; Seidl, L; Drackett, E; Mata, A; Pinzon, J; Baker, M R; Lopez, J; Trinh-Shevrin, C; Shelley, D; Bailey, Z; Maybank, K A; Thorpe, L E

2017-08-01

To guide targeted cessation and prevention programming, this study assessed smoking prevalence and described sociodemographic, health, and healthcare use characteristics of adult smokers in public housing. Self-reported data were analyzed from a random sample of 1664 residents aged 35 and older in ten New York City public housing developments in East/Central Harlem. Smoking prevalence was 20.8%. Weighted log-binomial models identified to be having Medicaid, not having a personal doctor, and using health clinics for routine care were positively associated with smoking. Smokers without a personal doctor were less likely to receive provider quit advice. While most smokers in these public housing developments had health insurance, a personal doctor, and received provider cessation advice in the last year (72.4%), persistently high smoking rates suggest that such cessation advice may be insufficient. Efforts to eliminate differences in tobacco use should consider place-based smoking cessation interventions that extend cessation support beyond clinical settings.

Health care usage among immigrants and native-born elderly populations in eleven European countries: results from SHARE

PubMed Central

Guillén, Montserrat; Crimmins, Eileen M.

2013-01-01

Differences in health care utilization of immigrants 50 years of age and older relative to the native-born populations in eleven European countries are investigated. Negative binomial and zero-inflated Poisson regression are used to examine differences between immigrants and native-borns in number of doctor visits, visits to general practitioners, and hospital stays using the 2004 Survey of Health, Ageing, and Retirement in Europe database. In the pooled European sample and in some individual countries, older immigrants use from 13 to 20% more health services than native-borns after demographic characteristics are controlled. After controlling for the need for health care, differences between immigrants and native-borns in the use of physicians, but not hospitals, are reduced by about half. These are not changed much with the incorporation of indicators of socioeconomic status and extra insurance coverage. Higher country-level relative expenditures on health, paying physicians a fee-for-service, and physician density are associated with higher usage of physician services among immigrants. PMID:21660564

Hope and Hopelessness: The Role of Hope in Buffering the Impact of Hopelessness on Suicidal Ideation.

PubMed

Huen, Jenny M Y; Ip, Brian Y T; Ho, Samuel M Y; Yip, Paul S F

2015-01-01

The present study investigated whether hope and hopelessness are better conceptualized as a single construct of bipolar spectrum or two distinct constructs and whether hope can moderate the relationship between hopelessness and suicidal ideation. Hope, hopelessness, and suicidal ideation were measured in a community sample of 2106 participants through a population-based household survey. Confirmatory factor analyses showed that a measurement model with separate, correlated second-order factors of hope and hopelessness provided a good fit to the data and was significantly better than that of the model collapsing hope and hopelessness into a single second-order factor. Negative binomial regression showed that hope and hopelessness interacted such that the effect of hopelessness on suicidal ideation was lower in individuals with higher hope than individuals with lower hope. Hope and hopelessness are two distinct but correlated constructs. Hope can act as a resilience factor that buffers the impact of hopelessness on suicidal ideation. Inducing hope in people may be a promising avenue for suicide prevention.

Protecting Construction Worker Health and Safety in Ontario, Canada: Identifying a Union Safety Effect.

PubMed

Amick, Benjamin C; Hogg-Johnson, Sheilah; Latour-Villamil, Desiree; Saunders, Ron

2015-12-01

Do Ontario unionized construction firms have lower workers' compensation claims rates compared with nonunion firms? Building trade and construction trade association lists of union contractors were linked to Workplace Safety and Insurance Board claims data for 2006 to 2012. Data were pooled for 2006 to 2012, and negative binomial regressions conducted with adjustment to estimate a union safety effect. The sample included 5797 unionized and 38,626 nonunion construction firms. Total claims rates were 13% higher (1.13, 1.09 to 1.18) in unionized firms because of higher allowed no-lost-time claim rates (1.28, 1.23 to 1.34), whereas the lost-time claims rate was 14% lower (0.86, 0.82 to 0.91). Unionized construction firms compared with nonunion firms have higher no-lost-time and lower lost-time claims rates. Unionized firms may encourage occupational injury reporting and reduce risks through training and hazard identification and control strategies.

Validation of fixed sample size plans for monitoring lepidopteran pests of Brassica oleracea crops in North Korea.

PubMed

Hamilton, A J; Waters, E K; Kim, H J; Pak, W S; Furlong, M J

2009-06-01

The combined action of two lepidoteran pests, Plutella xylostella L. (Plutellidae) and Pieris rapae L. (Pieridae),causes significant yield losses in cabbage (Brassica oleracea variety capitata) crops in the Democratic People's Republic of Korea. Integrated pest management (IPM) strategies for these cropping systems are in their infancy, and sampling plans have not yet been developed. We used statistical resampling to assess the performance of fixed sample size plans (ranging from 10 to 50 plants). First, the precision (D = SE/mean) of the plans in estimating the population mean was assessed. There was substantial variation in achieved D for all sample sizes, and sample sizes of at least 20 and 45 plants were required to achieve the acceptable precision level of D < or = 0.3 at least 50 and 75% of the time, respectively. Second, the performance of the plans in classifying the population density relative to an economic threshold (ET) was assessed. To account for the different damage potentials of the two species the ETs were defined in terms of standard insects (SIs), where 1 SI = 1 P. rapae = 5 P. xylostella larvae. The plans were implemented using different economic thresholds (ETs) for the three growth stages of the crop: precupping (1 SI/plant), cupping (0.5 SI/plant), and heading (4 SI/plant). Improvement in the classification certainty with increasing sample sizes could be seen through the increasing steepness of operating characteristic curves. Rather than prescribe a particular plan, we suggest that the results of these analyses be used to inform practitioners of the relative merits of the different sample sizes.

A consolidated environmental monitoring plan for Aberdeen Proving Ground, Maryland

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

Ebinger, M.H.; Hansen, W.R.

1997-04-01

The US Army operates facilities in Edgewood and Aberdeen under several licenses from the Nuclear Regulatory Commission (NRC). Compliance with each license is time consuming and could potentially result in duplicated efforts to demonstrate compliance with existing environmental regulations. The goal of the ERM plan is to provide the sampling necessary to ensure that operations at Edgewood and Aberdeen are within applicable regulatory guidelines and to provide a means of ensuring that adverse effects to the environment are minimized. Existing sampling plans and environmental data generated from those plans are briefly reviewed as part of the development of the presentmore » ERM plan. The new ERM plan was designed to provide data that can be used for assessing risks to the environment and to humans using Aberdeen and Edgewood areas. Existing sampling is modified and new sampling is proposed based on the results of the long-term DU fate study. In that study, different environmental pathways were identified that would show transport of DU at Aberdeen. Those pathways would also be impacted by other radioactive constituents from Aberdeen and Edgewood areas. The ERM plan presented in this document includes sampling from Edgewood and Aberdeen facilities. The main radioactive constituents of concern at Edgewood are C, P, N, S, H, I, Co, Cs, Ca, Sr and U that are used in radiolabeling different compounds and tracers for different reactions and syntheses. Air and water sampling are the thrust of efforts at the Edgewood area.« less

The Evaluation of Carpet Steam/Heat Cleaners as Biological Sampling Device

DTIC Science & Technology

2011-12-08

Vacuum Cleaner Evaluation as sampling Device Test Plan DHS Page 16 of 16 Fumigants , and Issues Related to Laboratory-scale Studies. Appl. Environ...ECBC Wet/dry Vacuum Cleaner Evaluation as sampling Device Test Plan DHS Page 1 of 16 Test Plan for The Evaluation of Carpet Steam...b. ABSTRACT unclassified c. THIS PAGE unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 ECBC Wet/dry Vacuum Cleaner

Igniting Creativity and Planning for Your Gifted Students.

ERIC Educational Resources Information Center

Russell, Don W., Ed.

The collection of instructional plans is designed to offer samples of strategies and ideas to teachers involved with gifted students. Approximately 30 plans are presented for the following areas (sample subtopics in science (atomic fusion), social studies (mores and folkways), mathematics (spatial relations), health and physiology, philosophy, and…