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.

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.

Mental health status and healthcare utilization among community dwelling older adults.

PubMed

Adepoju, Omolola; Lin, Szu-Hsuan; Mileski, Michael; Kruse, Clemens Scott; Mask, Andrew

2018-04-27

Shifts in mental health utilization patterns are necessary to allow for meaningful access to care for vulnerable populations. There have been long standing issues in how mental health is provided, which has caused problems in that care being efficacious for those seeking it. To assess the relationship between mental health status and healthcare utilization among adults ≥65 years. A negative binomial regression model was used to assess the relationship between mental health status and healthcare utilization related to office-based physician visits, while a two-part model, consisting of logistic regression and negative binomial regression, was used to separately model emergency visits and inpatient services. The receipt of care in office-based settings were marginally higher for subjects with mental health difficulties. Both probabilities and counts of inpatient hospitalizations were similar across mental health categories. The count of ER visits was similar across mental health categories; however, the probability of having an emergency department visit was marginally higher for older adults who reported mental health difficulties in 2012. These findings are encouraging and lend promise to the recent initiatives on addressing gaps in mental healthcare services.

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.

Analyzing hospitalization data: potential limitations of Poisson regression.

PubMed

Weaver, Colin G; Ravani, Pietro; Oliver, Matthew J; Austin, Peter C; Quinn, Robert R

2015-08-01

Poisson regression is commonly used to analyze hospitalization data when outcomes are expressed as counts (e.g. number of days in hospital). However, data often violate the assumptions on which Poisson regression is based. More appropriate extensions of this model, while available, are rarely used. We compared hospitalization data between 206 patients treated with hemodialysis (HD) and 107 treated with peritoneal dialysis (PD) using Poisson regression and compared results from standard Poisson regression with those obtained using three other approaches for modeling count data: negative binomial (NB) regression, zero-inflated Poisson (ZIP) regression and zero-inflated negative binomial (ZINB) regression. We examined the appropriateness of each model and compared the results obtained with each approach. During a mean 1.9 years of follow-up, 183 of 313 patients (58%) were never hospitalized (indicating an excess of 'zeros'). The data also displayed overdispersion (variance greater than mean), violating another assumption of the Poisson model. Using four criteria, we determined that the NB and ZINB models performed best. According to these two models, patients treated with HD experienced similar hospitalization rates as those receiving PD {NB rate ratio (RR): 1.04 [bootstrapped 95% confidence interval (CI): 0.49-2.20]; ZINB summary RR: 1.21 (bootstrapped 95% CI 0.60-2.46)}. Poisson and ZIP models fit the data poorly and had much larger point estimates than the NB and ZINB models [Poisson RR: 1.93 (bootstrapped 95% CI 0.88-4.23); ZIP summary RR: 1.84 (bootstrapped 95% CI 0.88-3.84)]. We found substantially different results when modeling hospitalization data, depending on the approach used. Our results argue strongly for a sound model selection process and improved reporting around statistical methods used for modeling count data. © The Author 2015. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Gaussian Process Regression Model in Spatial Logistic Regression

NASA Astrophysics Data System (ADS)

Sofro, A.; Oktaviarina, A.

2018-01-01

Spatial analysis has developed very quickly in the last decade. One of the favorite approaches is based on the neighbourhood of the region. Unfortunately, there are some limitations such as difficulty in prediction. Therefore, we offer Gaussian process regression (GPR) to accommodate the issue. In this paper, we will focus on spatial modeling with GPR for binomial data with logit link function. The performance of the model will be investigated. We will discuss the inference of how to estimate the parameters and hyper-parameters and to predict as well. Furthermore, simulation studies will be explained in the last section.

Measurement error and outcome distributions: Methodological issues in regression analyses of behavioral coding data.

PubMed

Holsclaw, Tracy; Hallgren, Kevin A; Steyvers, Mark; Smyth, Padhraic; Atkins, David C

2015-12-01

Behavioral coding is increasingly used for studying mechanisms of change in psychosocial treatments for substance use disorders (SUDs). However, behavioral coding data typically include features that can be problematic in regression analyses, including measurement error in independent variables, non normal distributions of count outcome variables, and conflation of predictor and outcome variables with third variables, such as session length. Methodological research in econometrics has shown that these issues can lead to biased parameter estimates, inaccurate standard errors, and increased Type I and Type II error rates, yet these statistical issues are not widely known within SUD treatment research, or more generally, within psychotherapy coding research. Using minimally technical language intended for a broad audience of SUD treatment researchers, the present paper illustrates the nature in which these data issues are problematic. We draw on real-world data and simulation-based examples to illustrate how these data features can bias estimation of parameters and interpretation of models. A weighted negative binomial regression is introduced as an alternative to ordinary linear regression that appropriately addresses the data characteristics common to SUD treatment behavioral coding data. We conclude by demonstrating how to use and interpret these models with data from a study of motivational interviewing. SPSS and R syntax for weighted negative binomial regression models is included in online supplemental materials. (c) 2016 APA, all rights reserved).

Measurement error and outcome distributions: Methodological issues in regression analyses of behavioral coding data

PubMed Central

Holsclaw, Tracy; Hallgren, Kevin A.; Steyvers, Mark; Smyth, Padhraic; Atkins, David C.

2015-01-01

Behavioral coding is increasingly used for studying mechanisms of change in psychosocial treatments for substance use disorders (SUDs). However, behavioral coding data typically include features that can be problematic in regression analyses, including measurement error in independent variables, non-normal distributions of count outcome variables, and conflation of predictor and outcome variables with third variables, such as session length. Methodological research in econometrics has shown that these issues can lead to biased parameter estimates, inaccurate standard errors, and increased type-I and type-II error rates, yet these statistical issues are not widely known within SUD treatment research, or more generally, within psychotherapy coding research. Using minimally-technical language intended for a broad audience of SUD treatment researchers, the present paper illustrates the nature in which these data issues are problematic. We draw on real-world data and simulation-based examples to illustrate how these data features can bias estimation of parameters and interpretation of models. A weighted negative binomial regression is introduced as an alternative to ordinary linear regression that appropriately addresses the data characteristics common to SUD treatment behavioral coding data. We conclude by demonstrating how to use and interpret these models with data from a study of motivational interviewing. SPSS and R syntax for weighted negative binomial regression models is included in supplementary materials. PMID:26098126

A Time Series Analysis: Weather Factors, Human Migration and Malaria Cases in Endemic Area of Purworejo, Indonesia, 2005–2014

PubMed Central

REJEKI, Dwi Sarwani Sri; NURHAYATI, Nunung; AJI, Budi; MURHANDARWATI, E. Elsa Herdiana; KUSNANTO, Hari

2018-01-01

Background: Climatic and weather factors become important determinants of vector-borne diseases transmission like malaria. This study aimed to prove relationships between weather factors with considering human migration and previous case findings and malaria cases in endemic areas in Purworejo during 2005–2014. Methods: This study employed ecological time series analysis by using monthly data. The independent variables were the maximum temperature, minimum temperature, maximum humidity, minimum humidity, precipitation, human migration, and previous malaria cases, while the dependent variable was positive malaria cases. Three models of count data regression analysis i.e. Poisson model, quasi-Poisson model, and negative binomial model were applied to measure the relationship. The least Akaike Information Criteria (AIC) value was also performed to find the best model. Negative binomial regression analysis was considered as the best model. Results: The model showed that humidity (lag 2), precipitation (lag 3), precipitation (lag 12), migration (lag1) and previous malaria cases (lag 12) had a significant relationship with malaria cases. Conclusion: Weather, migration and previous malaria cases factors need to be considered as prominent indicators for the increase of malaria case projection. PMID:29900134

Stability of a Model Explaining Selected Extramusical Influences on Solo and Small-Ensemble Festival Ratings

ERIC Educational Resources Information Center

Bergee, Martin J.; Westfall, Claude R.

2005-01-01

This is the third study in a line of inquiry whose purpose has been to develop a theoretical model of selected extra musical variables' influence on solo and small-ensemble festival ratings. Authors of the second of these (Bergee & McWhirter, 2005) had used binomial logistic regression as the basis for their model-formulation strategy. Their…

A Negative Binomial Regression Model for Accuracy Tests

ERIC Educational Resources Information Center

Hung, Lai-Fa

2012-01-01

Rasch used a Poisson model to analyze errors and speed in reading tests. An important property of the Poisson distribution is that the mean and variance are equal. However, in social science research, it is very common for the variance to be greater than the mean (i.e., the data are overdispersed). This study embeds the Rasch model within an…

Logistic quantile regression provides improved estimates for bounded avian counts: a case study of California Spotted Owl fledgling production

Treesearch

Brian S. Cade; Barry R. Noon; Rick D. Scherer; John J. Keane

2017-01-01

Counts of avian fledglings, nestlings, or clutch size that are bounded below by zero and above by some small integer form a discrete random variable distribution that is not approximated well by conventional parametric count distributions such as the Poisson or negative binomial. We developed a logistic quantile regression model to provide estimates of the empirical...

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.

Socio-environmental predictors of Barmah forest virus transmission in coastal areas, Queensland, Australia.

PubMed

Naish, Suchithra; Hu, Wenbiao; Nicholls, Neville; Mackenzie, John S; Dale, Pat; McMichael, Anthony J; Tong, Shilu

2009-02-01

To assess the socio-environmental predictors of Barmah forest virus (BFV) transmission in coastal areas, Queensland, Australia. Data on BFV notified cases, climate, tidal levels and socioeconomic index for area (SEIFA) in six coastal cities, Queensland, for the period 1992-2001 were obtained from the relevant government agencies. Negative binomial regression models were used to assess the socio-environmental predictors of BFV transmission. The results show that maximum and minimum temperature, rainfall, relative humidity, high and low tide were statistically significantly associated with BFV incidence at lags 0-2 months. The fitted negative binomial regression models indicate a significant independent association of each of maximum temperature (beta = 0.139, P = 0.000), high tide (beta = 0.005, P = 0.000) and SEIFA index (beta = -0.010, P = 0.000) with BFV transmission after adjustment for confounding variables. The transmission of BFV disease in Queensland coastal areas seemed to be determined by a combination of local social and environmental factors. The model developed in this study may have applications in the control and prevention of BFV disease in these areas.

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.

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.

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…

A statistical model to estimate the impact of a hepatitis A vaccination programme.

PubMed

Oviedo, Manuel; Pilar Muñoz, M; Domínguez, Angela; Borras, Eva; Carmona, Gloria

2008-11-11

A program of routine hepatitis A+B vaccination in preadolescents was introduced in 1998 in Catalonia, a region situated in the northeast of Spain. The objective of this study was to quantify the reduction in the incidence of hepatitis A in order to differentiate the natural reduction of the incidence of hepatitis A from that produced due to the vaccination programme and to predict the evolution of the disease in forthcoming years. A generalized linear model (GLM) using negative binomial regression was used to estimate the incidence rates of hepatitis A in Catalonia by year, age group and vaccination. Introduction of the vaccine reduced cases by 5.5 by year (p-value<0.001), but there was a significant interaction between the year of report and vaccination that smoothed this reduction (p-value<0.001). The reduction was not equal in all age groups, being greater in the 12-18 years age group, which fell from a mean rate of 8.15 per 100,000 person/years in the pre-vaccination period (1992-1998) to 1.4 in the vaccination period (1999-2005). The model predicts the evolution accurately for the group of vaccinated subjects. Negative binomial regression is more appropriate than Poisson regression when observed variance exceeds the observed mean (overdispersed count data), can cause a variable apparently contribute more on the model of what really makes it.

Modelling infant mortality rate in Central Java, Indonesia use generalized poisson regression method

NASA Astrophysics Data System (ADS)

Prahutama, Alan; Sudarno

2018-05-01

The infant mortality rate is the number of deaths under one year of age occurring among the live births in a given geographical area during a given year, per 1,000 live births occurring among the population of the given geographical area during the same year. This problem needs to be addressed because it is an important element of a country’s economic development. High infant mortality rate will disrupt the stability of a country as it relates to the sustainability of the population in the country. One of regression model that can be used to analyze the relationship between dependent variable Y in the form of discrete data and independent variable X is Poisson regression model. Recently The regression modeling used for data with dependent variable is discrete, among others, poisson regression, negative binomial regression and generalized poisson regression. In this research, generalized poisson regression modeling gives better AIC value than poisson regression. The most significant variable is the Number of health facilities (X1), while the variable that gives the most influence to infant mortality rate is the average breastfeeding (X9).

Racial Threat and White Opposition to Bilingual Education in Texas

ERIC Educational Resources Information Center

Hempel, Lynn M.; Dowling, Julie A.; Boardman, Jason D.; Ellison, Christopher G.

2013-01-01

This study examines local contextual conditions that influence opposition to bilingual education among non-Hispanic Whites, net of individual-level characteristics. Data from the Texas Poll (N = 615) are used in conjunction with U.S. Census data to test five competing hypotheses using binomial and multinomial logistic regression models. Our…

An empirical study of statistical properties of variance partition coefficients for multi-level logistic regression models

USGS Publications Warehouse

Li, Ji; Gray, B.R.; Bates, D.M.

2008-01-01

Partitioning the variance of a response by design levels is challenging for binomial and other discrete outcomes. Goldstein (2003) proposed four definitions for variance partitioning coefficients (VPC) under a two-level logistic regression model. In this study, we explicitly derived formulae for multi-level logistic regression model and subsequently studied the distributional properties of the calculated VPCs. Using simulations and a vegetation dataset, we demonstrated associations between different VPC definitions, the importance of methods for estimating VPCs (by comparing VPC obtained using Laplace and penalized quasilikehood methods), and bivariate dependence between VPCs calculated at different levels. Such an empirical study lends an immediate support to wider applications of VPC in scientific data analysis.

Logistic regression for dichotomized counts.

PubMed

Preisser, John S; Das, Kalyan; Benecha, Habtamu; Stamm, John W

2016-12-01

Sometimes there is interest in a dichotomized outcome indicating whether a count variable is positive or zero. Under this scenario, the application of ordinary logistic regression may result in efficiency loss, which is quantifiable under an assumed model for the counts. In such situations, a shared-parameter hurdle model is investigated for more efficient estimation of regression parameters relating to overall effects of covariates on the dichotomous outcome, while handling count data with many zeroes. One model part provides a logistic regression containing marginal log odds ratio effects of primary interest, while an ancillary model part describes the mean count of a Poisson or negative binomial process in terms of nuisance regression parameters. Asymptotic efficiency of the logistic model parameter estimators of the two-part models is evaluated with respect to ordinary logistic regression. Simulations are used to assess the properties of the models with respect to power and Type I error, the latter investigated under both misspecified and correctly specified models. The methods are applied to data from a randomized clinical trial of three toothpaste formulations to prevent incident dental caries in a large population of Scottish schoolchildren. © The Author(s) 2014.

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

Robust inference in the negative binomial regression model with an application to falls data.

PubMed

Aeberhard, William H; Cantoni, Eva; Heritier, Stephane

2014-12-01

A popular way to model overdispersed count data, such as the number of falls reported during intervention studies, is by means of the negative binomial (NB) distribution. Classical estimating methods are well-known to be sensitive to model misspecifications, taking the form of patients falling much more than expected in such intervention studies where the NB regression model is used. We extend in this article two approaches for building robust M-estimators of the regression parameters in the class of generalized linear models to the NB distribution. The first approach achieves robustness in the response by applying a bounded function on the Pearson residuals arising in the maximum likelihood estimating equations, while the second approach achieves robustness by bounding the unscaled deviance components. For both approaches, we explore different choices for the bounding functions. Through a unified notation, we show how close these approaches may actually be as long as the bounding functions are chosen and tuned appropriately, and provide the asymptotic distributions of the resulting estimators. Moreover, we introduce a robust weighted maximum likelihood estimator for the overdispersion parameter, specific to the NB distribution. Simulations under various settings show that redescending bounding functions yield estimates with smaller biases under contamination while keeping high efficiency at the assumed model, and this for both approaches. We present an application to a recent randomized controlled trial measuring the effectiveness of an exercise program at reducing the number of falls among people suffering from Parkinsons disease to illustrate the diagnostic use of such robust procedures and their need for reliable inference. © 2014, The International Biometric Society.

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.

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

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.

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.

Binomial outcomes in dataset with some clusters of size two: can the dependence of twins be accounted for? A simulation study comparing the reliability of statistical methods based on a dataset of preterm infants.

PubMed

Sauzet, Odile; Peacock, Janet L

2017-07-20

The analysis of perinatal outcomes often involves datasets with some multiple births. These are datasets mostly formed of independent observations and a limited number of clusters of size two (twins) and maybe of size three or more. This non-independence needs to be accounted for in the statistical analysis. Using simulated data based on a dataset of preterm infants we have previously investigated the performance of several approaches to the analysis of continuous outcomes in the presence of some clusters of size two. Mixed models have been developed for binomial outcomes but very little is known about their reliability when only a limited number of small clusters are present. Using simulated data based on a dataset of preterm infants we investigated the performance of several approaches to the analysis of binomial outcomes in the presence of some clusters of size two. Logistic models, several methods of estimation for the logistic random intercept models and generalised estimating equations were compared. The presence of even a small percentage of twins means that a logistic regression model will underestimate all parameters but a logistic random intercept model fails to estimate the correlation between siblings if the percentage of twins is too small and will provide similar estimates to logistic regression. The method which seems to provide the best balance between estimation of the standard error and the parameter for any percentage of twins is the generalised estimating equations. This study has shown that the number of covariates or the level two variance do not necessarily affect the performance of the various methods used to analyse datasets containing twins but when the percentage of small clusters is too small, mixed models cannot capture the dependence between siblings.

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.

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.

Understanding poisson regression.

PubMed

Hayat, Matthew J; Higgins, Melinda

2014-04-01

Nurse investigators often collect study data in the form of counts. Traditional methods of data analysis have historically approached analysis of count data either as if the count data were continuous and normally distributed or with dichotomization of the counts into the categories of occurred or did not occur. These outdated methods for analyzing count data have been replaced with more appropriate statistical methods that make use of the Poisson probability distribution, which is useful for analyzing count data. The purpose of this article is to provide an overview of the Poisson distribution and its use in Poisson regression. Assumption violations for the standard Poisson regression model are addressed with alternative approaches, including addition of an overdispersion parameter or negative binomial regression. An illustrative example is presented with an application from the ENSPIRE study, and regression modeling of comorbidity data is included for illustrative purposes. Copyright 2014, SLACK Incorporated.

Do Barriers to Crime Prevention Moderate the Effects of Situational Crime Prevention Policies on Violent Crime in High Schools?

ERIC Educational Resources Information Center

Sevigny, Eric L.; Zhang, Gary

2018-01-01

This study investigates how barriers to school-based crime prevention programming moderate the effects of situational crime prevention (SCP) policies on levels of violent crime in U.S. public high schools. Using data from the 2008 School Survey on Crime and Safety, we estimate a series of negative binomial regression models with interactions to…

Variable selection for zero-inflated and overdispersed data with application to health care demand in Germany

PubMed Central

Wang, Zhu; Shuangge, Ma; Wang, Ching-Yun

2017-01-01

In health services and outcome research, count outcomes are frequently encountered and often have a large proportion of zeros. The zero-inflated negative binomial (ZINB) regression model has important applications for this type of data. With many possible candidate risk factors, this paper proposes new variable selection methods for the ZINB model. We consider maximum likelihood function plus a penalty including the least absolute shrinkage and selection operator (LASSO), smoothly clipped absolute deviation (SCAD) and minimax concave penalty (MCP). An EM (expectation-maximization) algorithm is proposed for estimating the model parameters and conducting variable selection simultaneously. This algorithm consists of estimating penalized weighted negative binomial models and penalized logistic models via the coordinated descent algorithm. Furthermore, statistical properties including the standard error formulae are provided. A simulation study shows that the new algorithm not only has more accurate or at least comparable estimation, also is more robust than the traditional stepwise variable selection. The proposed methods are applied to analyze the health care demand in Germany using an open-source R package mpath. PMID:26059498

Review and Recommendations for Zero-inflated Count Regression Modeling of Dental Caries Indices in Epidemiological Studies

PubMed Central

Stamm, John W.; Long, D. Leann; Kincade, Megan E.

2012-01-01

Over the past five to ten years, zero-inflated count regression models have been increasingly applied to the analysis of dental caries indices (e.g., DMFT, dfms, etc). The main reason for that is linked to the broad decline in children’s caries experience, such that dmf and DMF indices more frequently generate low or even zero counts. This article specifically reviews the application of zero-inflated Poisson and zero-inflated negative binomial regression models to dental caries, with emphasis on the description of the models and the interpretation of fitted model results given the study goals. The review finds that interpretations provided in the published caries research are often imprecise or inadvertently misleading, particularly with respect to failing to discriminate between inference for the class of susceptible persons defined by such models and inference for the sampled population in terms of overall exposure effects. Recommendations are provided to enhance the use as well as the interpretation and reporting of results of count regression models when applied to epidemiological studies of dental caries. PMID:22710271

Sickness absence and psychosocial job quality: an analysis from a longitudinal survey of working Australians, 2005-2012.

PubMed

Milner, Allison; Butterworth, Peter; Bentley, Rebecca; Kavanagh, Anne M; LaMontagne, Anthony D

2015-05-15

Sickness absence is associated with adverse health, organizational, and societal outcomes. Using data from a longitudinal cohort study of working Australians (the Household, Income and Labour Dynamics in Australia (HILDA) Survey), we examined the relationship between changes in individuals' overall psychosocial job quality and variation in sickness absence. The outcome variables were paid sickness absence (yes/no) and number of days of paid sickness absence in the past year (2005-2012). The main exposure variable was psychosocial job quality, measured using a psychosocial job quality index (levels of job control, demands and complexity, insecurity, and perceptions of unfair pay). Analysis was conducted using longitudinal fixed-effects logistic regression models and negative binomial regression models. There was a dose-response relationship between the number of psychosocial job stressors reported by an individual and the odds of paid sickness absence (1 adversity: odds ratio (OR) = 1.26, 95% confidence interval (CI): 1.09, 1.45 (P = 0.002); 2 adversities: OR = 1.28, 95% CI: 1.09, 1.51 (P = 0.002); ≥3 adversities: OR = 1.58, 95% CI: 1.29, 1.94 (P < 0.001)). The negative binomial regression models also indicated that respondents reported a greater number of days of sickness absence in response to worsening psychosocial job quality. These results suggest that workplace interventions aiming to improve the quality of work could help reduce sickness absence. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Adjusting for overdispersion in piecewise exponential regression models to estimate excess mortality rate in population-based research.

PubMed

Luque-Fernandez, Miguel Angel; Belot, Aurélien; Quaresma, Manuela; Maringe, Camille; Coleman, Michel P; Rachet, Bernard

2016-10-01

In population-based cancer research, piecewise exponential regression models are used to derive adjusted estimates of excess mortality due to cancer using the Poisson generalized linear modelling framework. However, the assumption that the conditional mean and variance of the rate parameter given the set of covariates x i are equal is strong and may fail to account for overdispersion given the variability of the rate parameter (the variance exceeds the mean). Using an empirical example, we aimed to describe simple methods to test and correct for overdispersion. We used a regression-based score test for overdispersion under the relative survival framework and proposed different approaches to correct for overdispersion including a quasi-likelihood, robust standard errors estimation, negative binomial regression and flexible piecewise modelling. All piecewise exponential regression models showed the presence of significant inherent overdispersion (p-value <0.001). However, the flexible piecewise exponential model showed the smallest overdispersion parameter (3.2 versus 21.3) for non-flexible piecewise exponential models. We showed that there were no major differences between methods. However, using a flexible piecewise regression modelling, with either a quasi-likelihood or robust standard errors, was the best approach as it deals with both, overdispersion due to model misspecification and true or inherent overdispersion.

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

PubMed

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

2016-11-01

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

Modeling the frequency of opposing left-turn conflicts at signalized intersections using generalized linear regression models.

PubMed

Zhang, Xin; Liu, Pan; Chen, Yuguang; Bai, Lu; Wang, Wei

2014-01-01

The primary objective of this study was to identify whether the frequency of traffic conflicts at signalized intersections can be modeled. The opposing left-turn conflicts were selected for the development of conflict predictive models. Using data collected at 30 approaches at 20 signalized intersections, the underlying distributions of the conflicts under different traffic conditions were examined. Different conflict-predictive models were developed to relate the frequency of opposing left-turn conflicts to various explanatory variables. The models considered include a linear regression model, a negative binomial model, and separate models developed for four traffic scenarios. The prediction performance of different models was compared. The frequency of traffic conflicts follows a negative binominal distribution. The linear regression model is not appropriate for the conflict frequency data. In addition, drivers behaved differently under different traffic conditions. Accordingly, the effects of conflicting traffic volumes on conflict frequency vary across different traffic conditions. The occurrences of traffic conflicts at signalized intersections can be modeled using generalized linear regression models. The use of conflict predictive models has potential to expand the uses of surrogate safety measures in safety estimation and evaluation.

Prediction of different ovarian responses using anti-Müllerian hormone following a long agonist treatment protocol for IVF.

PubMed

Heidar, Z; Bakhtiyari, M; Mirzamoradi, M; Zadehmodarres, S; Sarfjoo, F S; Mansournia, M A

2015-09-01

The purpose of this study was to predict the poor and excessive ovarian response using anti-Müllerian hormone (AMH) levels following a long agonist protocol in IVF candidates. Through a prospective cohort study, the type of relationship and appropriate scale for AMH were determined using the fractional polynomial regression. To determine the effect of AMH on the outcomes of ovarian stimulation and different ovarian responses, the multi-nominal and negative binomial regression models were fitted using backward stepwise method. The ovarian response of study subject who entered a standard long-term treatment cycle with GnRH agonist was evaluated using prediction model, separately and in combined models with (ROC) curves. The use of standard long-term treatments with GnRH agonist led to positive pregnancy test results in 30% of treated patients. With each unit increase in the log of AMH, the odds ratio of having poor response compared to normal response decreases by 64% (OR 0.36, 95% CI 0.19-0.68). Also the results of negative binomial regression model indicated that for one unit increase in the log of AMH blood levels, the odds of releasing an oocyte increased 24% (OR 1.24, 95% CI 1.14-1.35). The optimal cut-off points of AMH for predicting excessive and poor ovarian responses were 3.4 and 1.2 ng/ml, respectively, with area under curves of 0.69 (0.60-0.77) and 0.76 (0.66-0.86), respectively. By considering the age of the patient undergoing infertility treatment as a variable affecting ovulation, use of AMH levels showed to be a good test to discriminate between different ovarian responses.

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.

[Spatial epidemiological study on malaria epidemics in Hainan province].

PubMed

Wen, Liang; Shi, Run-He; Fang, Li-Qun; Xu, De-Zhong; Li, Cheng-Yi; Wang, Yong; Yuan, Zheng-Quan; Zhang, Hui

2008-06-01

To better understand the characteristics of spatial distribution of malaria epidemics in Hainan province and to explore the relationship between malaria epidemics and environmental factors, as well to develop prediction model on malaria epidemics. Data on Malaria and meteorological factors were collected in all 19 counties in Hainan province from May to Oct., 2000, and the proportion of land use types of these counties in this period were extracted from digital map of land use in Hainan province. Land surface temperatures (LST) were extracted from MODIS images and elevations of these counties were extracted from DEM of Hainan province. The coefficients of correlation of malaria incidences and these environmental factors were then calculated with SPSS 13.0, and negative binomial regression analysis were done using SAS 9.0. The incidence of malaria showed (1) positive correlations to elevation, proportion of forest land area and grassland area; (2) negative correlations to the proportion of cultivated area, urban and rural residents and to industrial enterprise area, LST; (3) no correlations to meteorological factors, proportion of water area, and unemployed land area. The prediction model of malaria which came from negative binomial regression analysis was: I (monthly, unit: 1/1,000,000) = exp (-1.672-0.399xLST). Spatial distribution of malaria epidemics was associated with some environmental factors, and prediction model of malaria epidemic could be developed with indexes which extracted from satellite remote sensing images.

Analysis of Binary Adherence Data in the Setting of Polypharmacy: A Comparison of Different Approaches

PubMed Central

Esserman, Denise A.; Moore, Charity G.; Roth, Mary T.

2009-01-01

Older community dwelling adults often take multiple medications for numerous chronic diseases. Non-adherence to these medications can have a large public health impact. Therefore, the measurement and modeling of medication adherence in the setting of polypharmacy is an important area of research. We apply a variety of different modeling techniques (standard linear regression; weighted linear regression; adjusted linear regression; naïve logistic regression; beta-binomial (BB) regression; generalized estimating equations (GEE)) to binary medication adherence data from a study in a North Carolina based population of older adults, where each medication an individual was taking was classified as adherent or non-adherent. In addition, through simulation we compare these different methods based on Type I error rates, bias, power, empirical 95% coverage, and goodness of fit. We find that estimation and inference using GEE is robust to a wide variety of scenarios and we recommend using this in the setting of polypharmacy when adherence is dichotomously measured for multiple medications per person. PMID:20414358

Dispersion models and sampling of cacao mirid bug Sahlbergella singularis (Hemiptera: Miridae) on Theobroma Cacao in southern Cameroon.

PubMed

Bisseleua, D H B; Vidal, Stefan

2011-02-01

The spatio-temporal distribution of Sahlbergella singularis Haglung, a major pest of cacao trees (Theobroma cacao) (Malvaceae), was studied for 2 yr in traditional cacao forest gardens in the humid forest area of southern Cameroon. The first objective was to analyze the dispersion of this insect on cacao trees. The second objective was to develop sampling plans based on fixed levels of precision for estimating S. singularis populations. The following models were used to analyze the data: Taylor's power law, Iwao's patchiness regression, the Nachman model, and the negative binomial distribution. Our results document that Taylor's power law was a better fit for the data than the Iwao and Nachman models. Taylor's b and Iwao's β were both significantly >1, indicating that S. singularis aggregated on specific trees. This result was further supported by the calculated common k of 1.75444. Iwao's α was significantly <0, indicating that the basic distribution component of S. singularis was the individual insect. Comparison of negative binomial (NBD) and Nachman models indicated that the NBD model was appropriate for studying S. singularis distribution. Optimal sample sizes for fixed precision levels of 0.10, 0.15, and 0.25 were estimated with Taylor's regression coefficients. Required sample sizes increased dramatically with increasing levels of precision. This is the first study on S. singularis dispersion in cacao plantations. Sampling plans, presented here, should be a tool for research on population dynamics and pest management decisions of mirid bugs on cacao. © 2011 Entomological Society of America

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.

A general framework for the use of logistic regression models in meta-analysis.

PubMed

Simmonds, Mark C; Higgins, Julian Pt

2016-12-01

Where individual participant data are available for every randomised trial in a meta-analysis of dichotomous event outcomes, "one-stage" random-effects logistic regression models have been proposed as a way to analyse these data. Such models can also be used even when individual participant data are not available and we have only summary contingency table data. One benefit of this one-stage regression model over conventional meta-analysis methods is that it maximises the correct binomial likelihood for the data and so does not require the common assumption that effect estimates are normally distributed. A second benefit of using this model is that it may be applied, with only minor modification, in a range of meta-analytic scenarios, including meta-regression, network meta-analyses and meta-analyses of diagnostic test accuracy. This single model can potentially replace the variety of often complex methods used in these areas. This paper considers, with a range of meta-analysis examples, how random-effects logistic regression models may be used in a number of different types of meta-analyses. This one-stage approach is compared with widely used meta-analysis methods including Bayesian network meta-analysis and the bivariate and hierarchical summary receiver operating characteristic (ROC) models for meta-analyses of diagnostic test accuracy. © The Author(s) 2014.

Variable selection for zero-inflated and overdispersed data with application to health care demand in Germany.

PubMed

Wang, Zhu; Ma, Shuangge; Wang, Ching-Yun

2015-09-01

In health services and outcome research, count outcomes are frequently encountered and often have a large proportion of zeros. The zero-inflated negative binomial (ZINB) regression model has important applications for this type of data. With many possible candidate risk factors, this paper proposes new variable selection methods for the ZINB model. We consider maximum likelihood function plus a penalty including the least absolute shrinkage and selection operator (LASSO), smoothly clipped absolute deviation (SCAD), and minimax concave penalty (MCP). An EM (expectation-maximization) algorithm is proposed for estimating the model parameters and conducting variable selection simultaneously. This algorithm consists of estimating penalized weighted negative binomial models and penalized logistic models via the coordinated descent algorithm. Furthermore, statistical properties including the standard error formulae are provided. A simulation study shows that the new algorithm not only has more accurate or at least comparable estimation, but also is more robust than the traditional stepwise variable selection. The proposed methods are applied to analyze the health care demand in Germany using the open-source R package mpath. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Tobit analysis of vehicle accident rates on interstate highways.

PubMed

Anastasopoulos, Panagiotis Ch; Tarko, Andrew P; Mannering, Fred L

2008-03-01

There has been an abundance of research that has used Poisson models and its variants (negative binomial and zero-inflated models) to improve our understanding of the factors that affect accident frequencies on roadway segments. This study explores the application of an alternate method, tobit regression, by viewing vehicle accident rates directly (instead of frequencies) as a continuous variable that is left-censored at zero. Using data from vehicle accidents on Indiana interstates, the estimation results show that many factors relating to pavement condition, roadway geometrics and traffic characteristics significantly affect vehicle accident rates.

Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theory.

PubMed

Lord, Dominique; Washington, Simon P; Ivan, John N

2005-01-01

There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states-perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of "excess" zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate how crash data give rise to "excess" zeros frequently observed in crash data. It is shown that the Poisson and other mixed probabilistic structures are approximations assumed for modeling the motor vehicle crash process. Furthermore, it is demonstrated that under certain (fairly common) circumstances excess zeros are observed-and that these circumstances arise from low exposure and/or inappropriate selection of time/space scales and not an underlying dual state process. In conclusion, carefully selecting the time/space scales for analysis, including an improved set of explanatory variables and/or unobserved heterogeneity effects in count regression models, or applying small-area statistical methods (observations with low exposure) represent the most defensible modeling approaches for datasets with a preponderance of zeros.

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.

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.

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...

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.

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.

Reliability of environmental sampling culture results using the negative binomial intraclass correlation coefficient.

PubMed

Aly, Sharif S; Zhao, Jianyang; Li, Ben; Jiang, Jiming

2014-01-01

The Intraclass Correlation Coefficient (ICC) is commonly used to estimate the similarity between quantitative measures obtained from different sources. Overdispersed data is traditionally transformed so that linear mixed model (LMM) based ICC can be estimated. A common transformation used is the natural logarithm. The reliability of environmental sampling of fecal slurry on freestall pens has been estimated for Mycobacterium avium subsp. paratuberculosis using the natural logarithm transformed culture results. Recently, the negative binomial ICC was defined based on a generalized linear mixed model for negative binomial distributed data. The current study reports on the negative binomial ICC estimate which includes fixed effects using culture results of environmental samples. Simulations using a wide variety of inputs and negative binomial distribution parameters (r; p) showed better performance of the new negative binomial ICC compared to the ICC based on LMM even when negative binomial data was logarithm, and square root transformed. A second comparison that targeted a wider range of ICC values showed that the mean of estimated ICC closely approximated the true ICC.

Recent patterns in antibiotic use for children with group A streptococcal infections in Japan.

PubMed

Okubo, Yusuke; Michihata, Nobuaki; Morisaki, Naho; Kinoshita, Noriko; Miyairi, Isao; Urayama, Kevin Y; Yasunaga, Hideo

2017-11-13

Antibiotics are the most frequently prescribed medicines for children, however inappropriate antibiotic prescribing is prevalent. This study investigated recent trends in antibiotic use and factors associated with appropriate antibiotic selection among children with group A streptococcal infections in Japan. Records of outpatients aged <18years with a diagnosis of group A streptococcal infection were obtained using the Japan Medical Data Center database. Prescription patterns for antibiotics were investigated and factors associated with penicillin use were evaluated using a multivariable log-binomial regression model. Overall, 5030 patients with a diagnosis of group A streptococcal infection were identified. The most commonly prescribed antibiotics were third-generation cephalosporins (53.3%), followed by penicillins (40.1%). In the multivariable log-binomial regression analysis, out-of-hours visits were independently associated with penicillin prescriptions [prevalence ratio (PR)=1.10, 95% confidence interval (CI) 1.03-1.18], whereas clinical departments other than paediatrics and internal medicine were related to non-penicillin prescriptions (PR=0.57, 95% CI 0.46-0.71). Third-generation cephalosporins were overprescribed for children with group A streptococcal infections. This investigation provides important information for promoting education for physicians and for constructing health policies for appropriate antibiotic prescription. Copyright © 2017. Published by Elsevier Ltd.

Community covariates of malnutrition based mortality among older adults.

PubMed

Lee, Matthew R; Berthelot, Emily R

2010-05-01

The purpose of this study was to identify community level covariates of malnutrition-based mortality among older adults. A community level framework was delineated which explains rates of malnutrition-related mortality among older adults as a function of community levels of socioeconomic disadvantage, disability, and social isolation among members of this group. County level data on malnutrition mortality of people 65 years of age and older for the period 2000-2003 were drawn from the CDC WONDER system databases. County level measures of older adult socioeconomic disadvantage, disability, and social isolation were derived from the 2000 US Census of Population and Housing. Negative binomial regression models adjusting for the size of the population at risk, racial composition, urbanism, and region were estimated to assess the relationships among these indicators. Results from negative binomial regression analysis yielded the following: a standard deviation increase in socioeconomic/physical disadvantage was associated with a 12% increase in the rate of malnutrition mortality among older adults (p < 0.001), whereas a standard deviation increase in social isolation was associated with a 5% increase in malnutrition mortality among older adults (p < 0.05). Community patterns of malnutrition based mortality among older adults are partly a function of levels of socioeconomic and physical disadvantage and social isolation among older adults. 2010 Elsevier Inc. All rights reserved.

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.

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

Not in My Back Yard: A Comparative Analysis of Crime Around Publicly Funded Drug Treatment Centers, Liquor Stores, Convenience Stores, and Corner Stores in One Mid-Atlantic City.

PubMed

Furr-Holden, C Debra M; Milam, Adam J; Nesoff, Elizabeth D; Johnson, Renee M; Fakunle, David O; Jennings, Jacky M; Thorpe, Roland J

2016-01-01

This research examined whether publicly funded drug treatment centers (DTCs) were associated with violent crime in excess of the violence happening around other commercial businesses. Violent crime data and locations of community entities were geocoded and mapped. DTCs and other retail outlets were matched based on a Neighborhood Disadvantage score at the census tract level. Street network buffers ranging from 100 to 1,400 feet were placed around each location. Negative binomial regression models were used to estimate the relationship between the count of violent crimes and the distance from each business type. Compared with the mean count of violent crime around drug treatment centers, the mean count of violent crime (M = 2.87) was significantly higher around liquor stores (M = 3.98; t test; p < .01) and corner stores (M = 3.78; t test; p < .01), and there was no statistically significant difference between the count around convenience stores (M = 2.65; t test; p = .32). In the adjusted negative binomial regression models, there was a negative and significant relationship between the count of violent crime and the distance from drug treatment centers (β = -.069, p < .01), liquor stores (β = -.081, p < .01), corner stores (β = -.116, p < .01), and convenience stores (β = -.154, p < .01). Violent crime associated with drug treatment centers is similar to that associated with liquor stores and is less frequent than that associated with convenience stores and corner stores.

[Epidemiology of scrub typhus and influencing factors in Yunnan province, 2006-2013].

PubMed

Sun, Y; Shi, C; Li, X L; Fang, L Q; Cao, W C

2018-01-10

Objective: To understand the epidemiological characteristics of scrub typhu s and influencing factors in Yunnan province, and provide further information for the prevention and control of scrub typhus. Methods: Based on the incidence data of scrub typhus reported in Yunnan from 2006 to 2013, the epidemiological characteristics of scrub typhus were analyzed and related environmental factors were identified with panel negative binomial regression model. Results: A total of 8 980 scrub typhus cases were reported during 2006-2013 in Yunnan. The average annual incidence was 2.46/100 000, with an uptrend observed. Natural focus expansion was found, affecting 71.3% of the counties in 2013. The epidemic mainly occurred in summer and autumn with the incidence peak during July-October. The annual incidence was higher in females than in males. More cases occurred in children and farmers, the proportions of cases in farmers and pre-school aged children showed an obvious increase. Panel negative binomial regression model indicated that the transmission risk of scrub typhus was positive associated with monthly temperature and monthly relative humidity. Furthermore, an "U" pattern between the risk and the increased coverage of cropland and grassland as well as an "inverted-U" pattern between the risk and increased coverage of shrub were observed. Conclusion: It is necessary to strengthen the scrub typhus surveillance in warm and moist areas as well as the areas with high coverage of cropland and grassland in Yunnan, and the health education in children and farmers who are at high risk.

A crash-prediction model for multilane roads.

PubMed

Caliendo, Ciro; Guida, Maurizio; Parisi, Alessandra

2007-07-01

Considerable research has been carried out in recent years to establish relationships between crashes and traffic flow, geometric infrastructure characteristics and environmental factors for two-lane rural roads. Crash-prediction models focused on multilane rural roads, however, have rarely been investigated. In addition, most research has paid but little attention to the safety effects of variables such as stopping sight distance and pavement surface characteristics. Moreover, the statistical approaches have generally included Poisson and Negative Binomial regression models, whilst Negative Multinomial regression model has been used to a lesser extent. Finally, as far as the authors are aware, prediction models involving all the above-mentioned factors have still not been developed in Italy for multilane roads, such as motorways. Thus, in this paper crash-prediction models for a four-lane median-divided Italian motorway were set up on the basis of accident data observed during a 5-year monitoring period extending between 1999 and 2003. The Poisson, Negative Binomial and Negative Multinomial regression models, applied separately to tangents and curves, were used to model the frequency of accident occurrence. Model parameters were estimated by the Maximum Likelihood Method, and the Generalized Likelihood Ratio Test was applied to detect the significant variables to be included in the model equation. Goodness-of-fit was measured by means of both the explained fraction of total variation and the explained fraction of systematic variation. The Cumulative Residuals Method was also used to test the adequacy of a regression model throughout the range of each variable. The candidate set of explanatory variables was: length (L), curvature (1/R), annual average daily traffic (AADT), sight distance (SD), side friction coefficient (SFC), longitudinal slope (LS) and the presence of a junction (J). Separate prediction models for total crashes and for fatal and injury crashes only were considered. For curves it is shown that significant variables are L, 1/R and AADT, whereas for tangents they are L, AADT and junctions. The effect of rain precipitation was analysed on the basis of hourly rainfall data and assumptions about drying time. It is shown that a wet pavement significantly increases the number of crashes. The models developed in this paper for Italian motorways appear to be useful for many applications such as the detection of critical factors, the estimation of accident reduction due to infrastructure and pavement improvement, and the predictions of accidents counts when comparing different design options. Thus this research may represent a point of reference for engineers in adjusting or designing multilane roads.

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

Factors Associated with Dental Caries in a Group of American Indian Children at age 36 Months

PubMed Central

Warren, John J.; Blanchette, Derek; Dawson, Deborah V.; Marshall, Teresa A.; Phipps, Kathy R.; Starr, Delores; Drake, David R.

2015-01-01

Objectives Early childhood caries (ECC) is rampant among American Indian children, but there has been relatively little study of this problem. This paper reports on risk factors for caries for a group of American Indian children at age 36 months as part of a longitudinal study. Methods Pregnant women from a Northern Plains Tribal community were recruited to participate in a longitudinal study of caries and caries risk factors. Standardized dental examinations were completed on children and questionnaires were completed by mothers at baseline and when children were 4, 8, 12, 16, 22, 28 and 36 months of age. Examinations were surface-specific for dental caries, and the questionnaires collected data on demographic, dietary and behavioral factors. Non-parametric bivariate tests and logistic regression models were used to identify risk factors for caries at 36 months, and negative binomial regression was used to identify factors related to caries severity (dmf counts). Results Among the 232 children, and caries prevalence for cavitated lesions was 80%, with an additional 15% having only non-cavitated lesions. The mean dmfs was 9.6, and of the total dmfs, nearly 62% of affected surfaces were decayed, 31% were missing, and 7% were filled. Logistic regression identified higher added sugar beverage consumption, younger maternal age at baseline, higher maternal DMFS at baseline, and greater number of people in the household as significant (p<0.05) risk factors. Negative binomial regression found that only maternal DMFS was associated with child dmf counts. Conclusions By the age of 36 months, dental caries is nearly universal in this population of American Indian children. Caries risk factors included sugared beverage consumption, greater household size and maternal factors, but further analyses are needed to better understand caries in this population. PMID:26544674

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.

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.

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.

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.

Environmental, Spatial, and Sociodemographic Factors Associated with Nonfatal Injuries in Indonesia.

PubMed

Irianti, Sri; Prasetyoputra, Puguh

2017-01-01

Background . The determinants of injuries and their reoccurrence in Indonesia are not well understood, despite their importance in the prevention of injuries. Therefore, this study seeks to investigate the environmental, spatial, and sociodemographic factors associated with the reoccurrence of injuries among Indonesian people. Methods . Data from the 2013 round of the Indonesia Baseline Health Research (IBHR 2013) were analysed using a two-part hurdle regression model. A logit regression model was chosen for the zero-hurdle part , while a zero-truncated negative binomial regression model was selected for the counts part . Odds ratio (OR) and incidence rate ratio (IRR) were the measures of association, respectively. Results . The results suggest that living in a household with distant drinking water source, residing in slum areas, residing in Eastern Indonesia, having low educational attainment, being men, and being poorer are positively related to the likelihood of experiencing injury. Moreover, being a farmer or fishermen, having low educational attainment, and being men are positively associated with the frequency of injuries. Conclusion . This study would be useful to prioritise injury prevention programs in Indonesia based on the environmental, spatial, and sociodemographic characteristics.

Coronary artery calcium distributions in older persons in the AGES-Reykjavik study

PubMed Central

Gudmundsson, Elias Freyr; Gudnason, Vilmundur; Sigurdsson, Sigurdur; Launer, Lenore J.; Harris, Tamara B.; Aspelund, Thor

2013-01-01

Coronary Artery Calcium (CAC) is a sign of advanced atherosclerosis and an independent risk factor for cardiac events. Here, we describe CAC-distributions in an unselected aged population and compare modelling methods to characterize CAC-distribution. CAC is difficult to model because it has a skewed and zero inflated distribution with over-dispersion. Data are from the AGES-Reykjavik sample, a large population based study [2002-2006] in Iceland of 5,764 persons aged 66-96 years. Linear regressions using logarithmic- and Box-Cox transformations on CAC+1, quantile regression and a Zero-Inflated Negative Binomial model (ZINB) were applied. Methods were compared visually and with the PRESS-statistic, R2 and number of detected associations with concurrently measured variables. There were pronounced differences in CAC according to sex, age, history of coronary events and presence of plaque in the carotid artery. Associations with conventional coronary artery disease (CAD) risk factors varied between the sexes. The ZINB model provided the best results with respect to the PRESS-statistic, R2, and predicted proportion of zero scores. The ZINB model detected similar numbers of associations as the linear regression on ln(CAC+1) and usually with the same risk factors. PMID:22990371

Factors affecting road mortality of white-tailed deer in eastern South Dakota

USGS Publications Warehouse

Grovenburg, Troy W.; Jenks, Jonathan A.; Klaver, Robert W.; Monteith, Kevin L.; Galster, Dwight H.; Schauer, Ron J.; Morlock, Wilbert W.; Delger, Joshua A.

2008-01-01

White-tailed deer (Odocoileus virginianus) mortalities (n = 4,433) caused by collisions with automobiles during 2003 were modeled in 35 counties in eastern South Dakota. Seventeen independent variables and 5 independent variable interactions were evaluated to explain deer mortalities. A negative binomial regression model (Ln Y = 1.25 – 0.12 [percentage tree coverage] + 0.0002 [county area] + 5.39 [county hunter success rate] + 0.0023 [vehicle proxy 96–104 km/hr roads], model deviance = 33.43, χ2 = 27.53, df = 27) was chosen using a combination of a priori model selection and AICc. Management options include use of the model to predict road mortalities and to increase the number of hunting licenses, which could result in fewer DVCs.

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.

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.

Comparison and Field Validation of Binomial Sampling Plans for Oligonychus perseae (Acari: Tetranychidae) on Hass Avocado in Southern California.

PubMed

Lara, Jesus R; Hoddle, Mark S

2015-08-01

Oligonychus perseae Tuttle, Baker, & Abatiello is a foliar pest of 'Hass' avocados [Persea americana Miller (Lauraceae)]. The recommended action threshold is 50-100 motile mites per leaf, but this count range and other ecological factors associated with O. perseae infestations limit the application of enumerative sampling plans in the field. Consequently, a comprehensive modeling approach was implemented to compare the practical application of various binomial sampling models for decision-making of O. perseae in California. An initial set of sequential binomial sampling models were developed using three mean-proportion modeling techniques (i.e., Taylor's power law, maximum likelihood, and an empirical model) in combination with two-leaf infestation tally thresholds of either one or two mites. Model performance was evaluated using a robust mite count database consisting of >20,000 Hass avocado leaves infested with varying densities of O. perseae and collected from multiple locations. Operating characteristic and average sample number results for sequential binomial models were used as the basis to develop and validate a standardized fixed-size binomial sampling model with guidelines on sample tree and leaf selection within blocks of avocado trees. This final validated model requires a leaf sampling cost of 30 leaves and takes into account the spatial dynamics of O. perseae to make reliable mite density classifications for a 50-mite action threshold. Recommendations for implementing this fixed-size binomial sampling plan to assess densities of O. perseae in commercial California avocado orchards are discussed. © The Authors 2015. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A semi-nonparametric Poisson regression model for analyzing motor vehicle crash data.

PubMed

Ye, Xin; Wang, Ke; Zou, Yajie; Lord, Dominique

2018-01-01

This paper develops a semi-nonparametric Poisson regression model to analyze motor vehicle crash frequency data collected from rural multilane highway segments in California, US. Motor vehicle crash frequency on rural highway is a topic of interest in the area of transportation safety due to higher driving speeds and the resultant severity level. Unlike the traditional Negative Binomial (NB) model, the semi-nonparametric Poisson regression model can accommodate an unobserved heterogeneity following a highly flexible semi-nonparametric (SNP) distribution. Simulation experiments are conducted to demonstrate that the SNP distribution can well mimic a large family of distributions, including normal distributions, log-gamma distributions, bimodal and trimodal distributions. Empirical estimation results show that such flexibility offered by the SNP distribution can greatly improve model precision and the overall goodness-of-fit. The semi-nonparametric distribution can provide a better understanding of crash data structure through its ability to capture potential multimodality in the distribution of unobserved heterogeneity. When estimated coefficients in empirical models are compared, SNP and NB models are found to have a substantially different coefficient for the dummy variable indicating the lane width. The SNP model with better statistical performance suggests that the NB model overestimates the effect of lane width on crash frequency reduction by 83.1%.

Evaluation of the Use of Zero-Augmented Regression Techniques to Model Incidence of Campylobacter Infections in FoodNet.

PubMed

Tremblay, Marlène; Crim, Stacy M; Cole, Dana J; Hoekstra, Robert M; Henao, Olga L; Döpfer, Dörte

2017-10-01

The Foodborne Diseases Active Surveillance Network (FoodNet) is currently using a negative binomial (NB) regression model to estimate temporal changes in the incidence of Campylobacter infection. FoodNet active surveillance in 483 counties collected data on 40,212 Campylobacter cases between years 2004 and 2011. We explored models that disaggregated these data to allow us to account for demographic, geographic, and seasonal factors when examining changes in incidence of Campylobacter infection. We hypothesized that modeling structural zeros and including demographic variables would increase the fit of FoodNet's Campylobacter incidence regression models. Five different models were compared: NB without demographic covariates, NB with demographic covariates, hurdle NB with covariates in the count component only, hurdle NB with covariates in both zero and count components, and zero-inflated NB with covariates in the count component only. Of the models evaluated, the nonzero-augmented NB model with demographic variables provided the best fit. Results suggest that even though zero inflation was not present at this level, individualizing the level of aggregation and using different model structures and predictors per site might be required to correctly distinguish between structural and observational zeros and account for risk factors that vary geographically.

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.

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.

Time series regression model for infectious disease and weather.

PubMed

Imai, Chisato; Armstrong, Ben; Chalabi, Zaid; Mangtani, Punam; Hashizume, Masahiro

2015-10-01

Time series regression has been developed and long used to evaluate the short-term associations of air pollution and weather with mortality or morbidity of non-infectious diseases. The application of the regression approaches from this tradition to infectious diseases, however, is less well explored and raises some new issues. We discuss and present potential solutions for five issues often arising in such analyses: changes in immune population, strong autocorrelations, a wide range of plausible lag structures and association patterns, seasonality adjustments, and large overdispersion. The potential approaches are illustrated with datasets of cholera cases and rainfall from Bangladesh and influenza and temperature in Tokyo. Though this article focuses on the application of the traditional time series regression to infectious diseases and weather factors, we also briefly introduce alternative approaches, including mathematical modeling, wavelet analysis, and autoregressive integrated moving average (ARIMA) models. Modifications proposed to standard time series regression practice include using sums of past cases as proxies for the immune population, and using the logarithm of lagged disease counts to control autocorrelation due to true contagion, both of which are motivated from "susceptible-infectious-recovered" (SIR) models. The complexity of lag structures and association patterns can often be informed by biological mechanisms and explored by using distributed lag non-linear models. For overdispersed models, alternative distribution models such as quasi-Poisson and negative binomial should be considered. Time series regression can be used to investigate dependence of infectious diseases on weather, but may need modifying to allow for features specific to this context. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

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.

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)

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.

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.

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.

Quality of maternity care and its determinants along the continuum in Kenya: A structural equation modeling analysis

PubMed Central

Mendez, Bomar Rojas

2017-01-01

Background Improving access to delivery services does not guarantee access to quality obstetric care and better survival, and therefore, concerns for quality of maternal and newborn care in low- and middle-income countries have been raised. Our study explored characteristics associated with the quality of initial assessment, intrapartum, and immediate postpartum and newborn care, and further assessed the relationships along the continuum of care. Methods The 2010 Service Provision Assessment data of Kenya for 627 routine deliveries of women aged 15–49 were used. Quality of care measures were assessed using recently validated quality of care measures during initial assessment, intrapartum, and postpartum periods. Data were analyzed with negative binomial regression and structural equation modeling technique. Results The negative binomial regression results identified a number of determinants of quality, such as the level of health facilities, managing authority, presence of delivery fee, central electricity supply and clinical guideline for maternal and neonatal care. Our structural equation modeling (SEM) further demonstrated that facility characteristics were important determinants of quality for initial assessment and postpartum care, while characteristics at the provider level became more important in shaping the quality of intrapartum care. Furthermore we also noted that quality of initial assessment had a positive association with quality of intrapartum care (β = 0.71, p < 0.001), which in turn was positively associated with the quality of newborn and immediate postpartum care (β = 1.29, p = 0.004). Conclusions A continued focus on quality of care along the continuum of maternity care is important not only to mothers but also their newborns. Policymakers should therefore ensure that required resources, as well as adequate supervision and emphasis on the quality of obstetric care, are available. PMID:28520771

The association between major depression prevalence and sex becomes weaker with age.

PubMed

Patten, Scott B; Williams, Jeanne V A; Lavorato, Dina H; Wang, Jian Li; Bulloch, Andrew G M; Sajobi, Tolulope

2016-02-01

Women have a higher prevalence of major depressive episodes (MDE) than men, and the annual prevalence of MDE declines with age. Age by sex interactions may occur (a weakening of the sex effect with age), but are easily overlooked since individual studies lack statistical power to detect interactions. The objective of this study was to evaluate age by sex interactions in MDE prevalence. In Canada, a series of 10 national surveys conducted between 1996 and 2013 assessed MDE prevalence in respondents over the age of 14. Treating age as a continuous variable, binomial and linear regression was used to model age by sex interactions in each survey. To increase power, the survey-specific interaction coefficients were then pooled using meta-analytic methods. The estimated interaction terms were homogeneous. In the binomial regression model I (2) was 31.2 % and was not statistically significant (Q statistic = 13.1, df = 9, p = 0.159). The pooled estimate (-0.004) was significant (z = 3.13, p = 0.002), indicating that the effect of sex became weaker with increasing age. This resulted in near disappearance of the sex difference in the 75+ age group. This finding was also supported by an examination of age- and sex-specific estimates pooled across the surveys. The association of MDE prevalence with sex becomes weaker with age. The interaction may reflect biological effect modification. Investigators should test for, and consider inclusion of age by sex interactions in epidemiological analyses of MDE prevalence.

Association between month of birth and melanoma risk: fact or fiction?

PubMed

Fiessler, Cornelia; Pfahlberg, Annette B; Keller, Andrea K; Radespiel-Tröger, Martin; Uter, Wolfgang; Gefeller, Olaf

2017-04-01

Evidence on the effect of ultraviolet radiation (UVR) exposure in infancy on melanoma risk in later life is scarce. Three recent studies suggest that people born in spring carry a higher melanoma risk. Our study aimed at verifying whether such a seasonal pattern of melanoma risk actually exists. Data from the population-based Cancer Registry Bavaria (CRB) on the birth months of 28 374 incident melanoma cases between 2002 and 2012 were analysed and compared with data from the Bavarian State Office for Statistics and Data Processing on the birth month distribution in the Bavarian population. Crude and adjusted analyses using negative binomial regression models were performed in the total study group and supplemented by several subgroup analyses. In the crude analysis, the birth months March-May were over-represented among melanoma cases. Negative binomial regression models adjusted only for sex and birth year revealed a seasonal association between melanoma risk and birth month with 13-21% higher relative incidence rates for March, April and May compared with the reference December. However, after additionally adjusting for the birth month distribution of the Bavarian population, these risk estimates decreased markedly and no association with the birth month was observed any more. Similar results emerged in all subgroup analyses. Our large registry-based study provides no evidence that people born in spring carry a higher risk for developing melanoma in later life and thus lends no support to the hypothesis of higher UVR susceptibility during the first months of life. © The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association

Not in My Back Yard: A Comparative Analysis of Crime Around Publicly Funded Drug Treatment Centers, Liquor Stores, Convenience Stores, and Corner Stores in One Mid-Atlantic City

PubMed Central

Furr-Holden, C. Debra M.; Milam, Adam J.; Nesoff, Elizabeth D.; Johnson, Renee M.; Fakunle, David O.; Jennings, Jacky M.; Thorpe, Roland J.

2016-01-01

Objective: This research examined whether publicly funded drug treatment centers (DTCs) were associated with violent crime in excess of the violence happening around other commercial businesses. Method: Violent crime data and locations of community entities were geocoded and mapped. DTCs and other retail outlets were matched based on a Neighborhood Disadvantage score at the census tract level. Street network buffers ranging from 100 to 1,400 feet were placed around each location. Negative binomial regression models were used to estimate the relationship between the count of violent crimes and the distance from each business type. Results: Compared with the mean count of violent crime around drug treatment centers, the mean count of violent crime (M = 2.87) was significantly higher around liquor stores (M = 3.98; t test; p < .01) and corner stores (M = 3.78; t test; p < .01), and there was no statistically significant difference between the count around convenience stores (M = 2.65; t test; p = .32). In the adjusted negative binomial regression models, there was a negative and significant relationship between the count of violent crime and the distance from drug treatment centers (β = -.069, p < .01), liquor stores (β = -.081, p < .01), corner stores (β = -.116, p < .01), and convenience stores (β = -.154, p < .01). Conclusions: Violent crime associated with drug treatment centers is similar to that associated with liquor stores and is less frequent than that associated with convenience stores and corner stores. PMID:26751351

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.

Developing a dengue forecast model using machine learning: A case study in China.

PubMed

Guo, Pi; Liu, Tao; Zhang, Qin; Wang, Li; Xiao, Jianpeng; Zhang, Qingying; Luo, Ganfeng; Li, Zhihao; He, Jianfeng; Zhang, Yonghui; Ma, Wenjun

2017-10-01

In China, dengue remains an important public health issue with expanded areas and increased incidence recently. Accurate and timely forecasts of dengue incidence in China are still lacking. We aimed to use the state-of-the-art machine learning algorithms to develop an accurate predictive model of dengue. Weekly dengue cases, Baidu search queries and climate factors (mean temperature, relative humidity and rainfall) during 2011-2014 in Guangdong were gathered. A dengue search index was constructed for developing the predictive models in combination with climate factors. The observed year and week were also included in the models to control for the long-term trend and seasonality. Several machine learning algorithms, including the support vector regression (SVR) algorithm, step-down linear regression model, gradient boosted regression tree algorithm (GBM), negative binomial regression model (NBM), least absolute shrinkage and selection operator (LASSO) linear regression model and generalized additive model (GAM), were used as candidate models to predict dengue incidence. Performance and goodness of fit of the models were assessed using the root-mean-square error (RMSE) and R-squared measures. The residuals of the models were examined using the autocorrelation and partial autocorrelation function analyses to check the validity of the models. The models were further validated using dengue surveillance data from five other provinces. The epidemics during the last 12 weeks and the peak of the 2014 large outbreak were accurately forecasted by the SVR model selected by a cross-validation technique. Moreover, the SVR model had the consistently smallest prediction error rates for tracking the dynamics of dengue and forecasting the outbreaks in other areas in China. The proposed SVR model achieved a superior performance in comparison with other forecasting techniques assessed in this study. The findings can help the government and community respond early to dengue epidemics.

Investigation of shipping accident injury severity and mortality.

PubMed

Weng, Jinxian; Yang, Dong

2015-03-01

Shipping movements are operated in a complex and high-risk environment. Fatal shipping accidents are the nightmares of seafarers. With ten years' worldwide ship accident data, this study develops a binary logistic regression model and a zero-truncated binomial regression model to predict the probability of fatal shipping accidents and corresponding mortalities. The model results show that both the probability of fatal accidents and mortalities are greater for collision, fire/explosion, contact, grounding, sinking accidents occurred in adverse weather conditions and darkness conditions. Sinking has the largest effects on the increment of fatal accident probability and mortalities. The results also show that the bigger number of mortalities is associated with shipping accidents occurred far away from the coastal area/harbor/port. In addition, cruise ships are found to have more mortalities than non-cruise ships. The results of this study are beneficial for policy-makers in proposing efficient strategies to prevent fatal shipping accidents. Copyright © 2015 Elsevier Ltd. All rights reserved.

Determinants of The Grade A Embryos in Infertile Women; Zero-Inflated Regression Model.

PubMed

Almasi-Hashiani, Amir; Ghaheri, Azadeh; Omani Samani, Reza

2017-10-01

In assisted reproductive technology, it is important to choose high quality embryos for embryo transfer. The aim of the present study was to determine the grade A embryo count and factors related to it in infertile women. This historical cohort study included 996 infertile women. The main outcome was the number of grade A embryos. Zero-Inflated Poisson (ZIP) regression and Zero-Inflated Negative Binomial (ZINB) regression were used to model the count data as it contained excessive zeros. Stata software, version 13 (Stata Corp, College Station, TX, USA) was used for all statistical analyses. After adjusting for potential confounders, results from the ZINB model show that for each unit increase in the number 2 pronuclear (2PN) zygotes, we get an increase of 1.45 times as incidence rate ratio (95% confidence interval (CI): 1.23-1.69, P=0.001) in the expected grade A embryo count number, and for each increase in the cleavage day we get a decrease 0.35 times (95% CI: 0.20-0.61, P=0.001) in expected grade A embryo count. There is a significant association between both the number of 2PN zygotes and cleavage day with the number of grade A embryos in both ZINB and ZIP regression models. The estimated coefficients are more plausible than values found in earlier studies using less relevant models. Copyright© by Royan Institute. All rights reserved.

Magnitude of virologic blips is associated with a higher risk for virologic rebound in HIV-infected individuals: a recurrent events analysis.

PubMed

Grennan, J Troy; Loutfy, Mona R; Su, DeSheng; Harrigan, P Richard; Cooper, Curtis; Klein, Marina; Machouf, Nima; Montaner, Julio S G; Rourke, Sean; Tsoukas, Christos; Hogg, Bob; Raboud, Janet

2012-04-15

The importance of human immunodeficiency virus (HIV) blip magnitude on virologic rebound has been raised in clinical guidelines relating to viral load assays. Antiretroviral-naive individuals initiating combination antiretroviral therapy (cART) after 1 January 2000 and achieving virologic suppression were studied. Negative binomial models were used to identify blip correlates. Recurrent event models were used to determine the association between blips and rebound by incorporating multiple periods of virologic suppression per individual. 3550 participants (82% male; median age, 40 years) were included. In a multivariable negative binomial regression model, the Amplicor assay was associated with a lower blip rate than branched DNA (rate ratio, 0.69; P < .01), controlling for age, sex, region, baseline HIV-1 RNA and CD4 count, AIDS-defining illnesses, year of cART initiation, cART type, and HIV-1 RNA testing frequency. In a multivariable recurrent event model controlling for age, sex, intravenous drug use, cART start year, cART type, assay type, and HIV-1 RNA testing frequency, blips of 500-999 copies/mL were associated with virologic rebound (hazard ratio, 2.70; P = .002), whereas blips of 50-499 were not. HIV-1 RNA assay was an important determinant of blip rates and should be considered in clinical guidelines. Blips ≥500 copies/mL were associated with increased rebound risk.

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.

Understanding logistic regression analysis.

PubMed

Sperandei, Sandro

2014-01-01

Logistic regression is used to obtain odds ratio in the presence of more than one explanatory variable. The procedure is quite similar to multiple linear regression, with the exception that the response variable is binomial. The result is the impact of each variable on the odds ratio of the observed event of interest. The main advantage is to avoid confounding effects by analyzing the association of all variables together. In this article, we explain the logistic regression procedure using examples to make it as simple as possible. After definition of the technique, the basic interpretation of the results is highlighted and then some special issues are discussed.

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…

Applied Prevalence Ratio estimation with different Regression models: An example from a cross-national study on substance use research.

PubMed

Espelt, Albert; Marí-Dell'Olmo, Marc; Penelo, Eva; Bosque-Prous, Marina

2016-06-14

To examine the differences between Prevalence Ratio (PR) and Odds Ratio (OR) in a cross-sectional study and to provide tools to calculate PR using two statistical packages widely used in substance use research (STATA and R). We used cross-sectional data from 41,263 participants of 16 European countries participating in the Survey on Health, Ageing and Retirement in Europe (SHARE). The dependent variable, hazardous drinking, was calculated using the Alcohol Use Disorders Identification Test - Consumption (AUDIT-C). The main independent variable was gender. Other variables used were: age, educational level and country of residence. PR of hazardous drinking in men with relation to women was estimated using Mantel-Haenszel method, log-binomial regression models and poisson regression models with robust variance. These estimations were compared to the OR calculated using logistic regression models. Prevalence of hazardous drinkers varied among countries. Generally, men have higher prevalence of hazardous drinking than women [PR=1.43 (1.38-1.47)]. Estimated PR was identical independently of the method and the statistical package used. However, OR overestimated PR, depending on the prevalence of hazardous drinking in the country. In cross-sectional studies, where comparisons between countries with differences in the prevalence of the disease or condition are made, it is advisable to use PR instead of OR.

Topics in Bayesian Hierarchical Modeling and its Monte Carlo Computations

NASA Astrophysics Data System (ADS)

Tak, Hyung Suk

The first chapter addresses a Beta-Binomial-Logit model that is a Beta-Binomial conjugate hierarchical model with covariate information incorporated via a logistic regression. Various researchers in the literature have unknowingly used improper posterior distributions or have given incorrect statements about posterior propriety because checking posterior propriety can be challenging due to the complicated functional form of a Beta-Binomial-Logit model. We derive data-dependent necessary and sufficient conditions for posterior propriety within a class of hyper-prior distributions that encompass those used in previous studies. Frequency coverage properties of several hyper-prior distributions are also investigated to see when and whether Bayesian interval estimates of random effects meet their nominal confidence levels. The second chapter deals with a time delay estimation problem in astrophysics. When the gravitational field of an intervening galaxy between a quasar and the Earth is strong enough to split light into two or more images, the time delay is defined as the difference between their travel times. The time delay can be used to constrain cosmological parameters and can be inferred from the time series of brightness data of each image. To estimate the time delay, we construct a Gaussian hierarchical model based on a state-space representation for irregularly observed time series generated by a latent continuous-time Ornstein-Uhlenbeck process. Our Bayesian approach jointly infers model parameters via a Gibbs sampler. We also introduce a profile likelihood of the time delay as an approximation of its marginal posterior distribution. The last chapter specifies a repelling-attracting Metropolis algorithm, a new Markov chain Monte Carlo method to explore multi-modal distributions in a simple and fast manner. This algorithm is essentially a Metropolis-Hastings algorithm with a proposal that consists of a downhill move in density that aims to make local modes repelling, followed by an uphill move in density that aims to make local modes attracting. The downhill move is achieved via a reciprocal Metropolis ratio so that the algorithm prefers downward movement. The uphill move does the opposite using the standard Metropolis ratio which prefers upward movement. This down-up movement in density increases the probability of a proposed move to a different mode.

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.

Factors associated with dental caries in a group of American Indian children at age 36 months.

PubMed

Warren, John J; Blanchette, Derek; Dawson, Deborah V; Marshall, Teresa A; Phipps, Kathy R; Starr, Delores; Drake, David R

2016-04-01

Early childhood caries (ECC) is rampant among American Indian children, but there has been relatively little study of this problem. This article reports on risk factors for caries for a group of American Indian children at age 36 months as part of a longitudinal study. Pregnant women from a Northern Plains Tribal community were recruited to participate in a longitudinal study of caries and caries risk factors. Standardized dental examinations were completed on children, and questionnaires were completed by mothers at baseline and when children were 4, 8, 12, 16, 22, 28, and 36 months of age. Examinations were surface-specific for dental caries, and the questionnaires collected data on demographic, dietary, and behavioral factors. Nonparametric bivariate tests and logistic regression models were used to identify risk factors for caries at 36 months, and negative binomial regression was used to identify factors related to caries severity (dmf counts). Among the 232 children, and caries prevalence for cavitated lesions was 80%, with an additional 15% having only noncavitated lesions. The mean dmfs was 9.6, and of the total dmfs, nearly 62% of affected surfaces were decayed, 31% were missing, and 7% were filled. Logistic regression identified higher added-sugar beverage consumption, younger maternal age at baseline, higher maternal DMFS at baseline, and greater number of people in the household as significant (P < 0.05) risk factors. Negative binomial regression found that only maternal DMFS was associated with child dmf counts. By the age of 36 months, dental caries is nearly universal in this population of American Indian children. Caries risk factors included sugared beverage consumption, greater household size, and maternal factors, but further analyses are needed to better understand caries in this population. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Cocoa Farmers’ Compliance with Safety Precautions in Spraying Agrochemicals and Use of Personal Protective Equipment (PPE) in Cameroon

PubMed Central

2018-01-01

The inability of farmers to comply with essential precautions in the course of spraying agrochemicals remains a policy dilemma, especially in developing countries. The objectives of this paper were to assess compliance of cocoa farmers with agrochemical safety measures, analyse the factors explaining involvement of cocoa farmers in the practice of reusing agrochemical containers and wearing of personal protective equipment (PPE). Data were collected with structured questionnaires from 667 cocoa farmers from the Centre and South West regions in Cameroon. Data analyses were carried out with Probit regression and Negative Binomial regression models. The results showed that average cocoa farm sizes were 3.55 ha and 2.82 ha in South West and Centre regions, respectively, and 89.80% and 42.64% complied with manufacturers’ instructions in the use of insecticides. Eating or drinking while spraying insecticides and fungicides was reported by 4.20% and 5.10% of all farmers in the two regions, respectively. However, 37.78% and 57.57% of all farmers wore hand gloves and safety boots while spraying insecticides in the South West and Centre regions of Cameroon, respectively. In addition, 7.80% of all the farmers would wash agrochemical containers and use them at home, while 42.43% would wash and use them on their farms. Probit regression results showed that probability of reusing agrochemical containers was significantly influenced (p < 0.05) by region of residence of cocoa farmers, gender, possession of formal education and farming as primary occupation. The Negative Binomial regression results showed that the log of number PPE worn was significantly influenced (p < 0.10) by region, marital status, attainment of formal education, good health, awareness of manufacturers’ instructions, land area and contact index. It was among others concluded that efforts to train farmers on the need to be familiar with manufacturers’ instructions and use PPE would enhance their safety in the course of spraying agrochemicals. PMID:29438333

Cocoa Farmers' Compliance with Safety Precautions in Spraying Agrochemicals and Use of Personal Protective Equipment (PPE) in Cameroon.

PubMed

Oyekale, Abayomi Samuel

2018-02-13

The inability of farmers to comply with essential precautions in the course of spraying agrochemicals remains a policy dilemma, especially in developing countries. The objectives of this paper were to assess compliance of cocoa farmers with agrochemical safety measures, analyse the factors explaining involvement of cocoa farmers in the practice of reusing agrochemical containers and wearing of personal protective equipment (PPE). Data were collected with structured questionnaires from 667 cocoa farmers from the Centre and South West regions in Cameroon. Data analyses were carried out with Probit regression and Negative Binomial regression models. The results showed that average cocoa farm sizes were 3.55 ha and 2.82 ha in South West and Centre regions, respectively, and 89.80% and 42.64% complied with manufacturers' instructions in the use of insecticides. Eating or drinking while spraying insecticides and fungicides was reported by 4.20% and 5.10% of all farmers in the two regions, respectively. However, 37.78% and 57.57% of all farmers wore hand gloves and safety boots while spraying insecticides in the South West and Centre regions of Cameroon, respectively. In addition, 7.80% of all the farmers would wash agrochemical containers and use them at home, while 42.43% would wash and use them on their farms. Probit regression results showed that probability of reusing agrochemical containers was significantly influenced ( p < 0.05) by region of residence of cocoa farmers, gender, possession of formal education and farming as primary occupation. The Negative Binomial regression results showed that the log of number PPE worn was significantly influenced ( p < 0.10) by region, marital status, attainment of formal education, good health, awareness of manufacturers' instructions, land area and contact index. It was among others concluded that efforts to train farmers on the need to be familiar with manufacturers' instructions and use PPE would enhance their safety in the course of spraying agrochemicals.

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.

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

[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.

Gingival recession and associated factors in a homogeneous Mexican adult male population: A cross-sectional study

PubMed Central

Minaya-Sánchez, Mirna; Medina-Solís, Carlo E.; Vallejos-Sánchez, Ana A.; Marquez-Corona, Maria L.; Pontigo-Loyola, América P.; Islas-Granillo, Horacio; Maupomé, Gerardo

2012-01-01

Background: Diverse variables are implicated in the pathogenesis of gingival recession; more detailed knowledge about the relationship between the clinical presentation of gingival recession and assorted risk indicators may lead to improved patient monitoring, early intervention, and subsequent prevention. The objective was to evaluate clinically gingival recession in a homogeneous Mexican adult male population and to determine the strength of association with related factors. Method: A cross-sectional study was carried out in a largely homogeneous group in terms of ethnic background, socioeconomic status, gender, occupation, and medical/dental insurance, in Campeche, Mexico. Periodontal examinations were undertaken to determine diverse clinical dental variables. All periodontal clinical examinations were assessed using the Florida Probe System, a dental chair and one examiner. Questionnaires were used to collect diverse risk indicators. Statistical analyses were undertaken with negative binomial regression models. Results: The mean number of sites with gingival recession per subject was 6.73±5.81; the prevalence was 87.6%. In the negative binomial regression model we observed that for (i) each year of age, and (ii) each percentage unit of increase in sites with plaque, and (iii) with suppuration, mean sites with gingival recession increased 2.9%, 1.0% and 13.0%, respectively. Having a spouse was associated with gingival recession. Conclusions: We observed association between gingival recession, and sociodemographic and clinical parameters. Patients need to be educated about risk indicators for gingival recession as well as the preventive maneuvers that may be implemented to minimize its occurrence. The potential of improved oral self-care to prevent a largely benign condition such as gingival recession is important, given the associated disorders that may ensue root exposure, such as root caries and root hypersensitivity. Key words:Oral health, periodontal health, gingival recession, adults, Mexico. PMID:22549678

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.

[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.

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 ...

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…

Antibiotic Resistances in Livestock: A Comparative Approach to Identify an Appropriate Regression Model for Count Data

PubMed Central

Hüls, Anke; Frömke, Cornelia; Ickstadt, Katja; Hille, Katja; Hering, Johanna; von Münchhausen, Christiane; Hartmann, Maria; Kreienbrock, Lothar

2017-01-01

Antimicrobial resistance in livestock is a matter of general concern. To develop hygiene measures and methods for resistance prevention and control, epidemiological studies on a population level are needed to detect factors associated with antimicrobial resistance in livestock holdings. In general, regression models are used to describe these relationships between environmental factors and resistance outcome. Besides the study design, the correlation structures of the different outcomes of antibiotic resistance and structural zero measurements on the resistance outcome as well as on the exposure side are challenges for the epidemiological model building process. The use of appropriate regression models that acknowledge these complexities is essential to assure valid epidemiological interpretations. The aims of this paper are (i) to explain the model building process comparing several competing models for count data (negative binomial model, quasi-Poisson model, zero-inflated model, and hurdle model) and (ii) to compare these models using data from a cross-sectional study on antibiotic resistance in animal husbandry. These goals are essential to evaluate which model is most suitable to identify potential prevention measures. The dataset used as an example in our analyses was generated initially to study the prevalence and associated factors for the appearance of cefotaxime-resistant Escherichia coli in 48 German fattening pig farms. For each farm, the outcome was the count of samples with resistant bacteria. There was almost no overdispersion and only moderate evidence of excess zeros in the data. Our analyses show that it is essential to evaluate regression models in studies analyzing the relationship between environmental factors and antibiotic resistances in livestock. After model comparison based on evaluation of model predictions, Akaike information criterion, and Pearson residuals, here the hurdle model was judged to be the most appropriate model. PMID:28620609

Covariate Imbalance and Adjustment for Logistic Regression Analysis of Clinical Trial Data

PubMed Central

Ciolino, Jody D.; Martin, Reneé H.; Zhao, Wenle; Jauch, Edward C.; Hill, Michael D.; Palesch, Yuko Y.

2014-01-01

In logistic regression analysis for binary clinical trial data, adjusted treatment effect estimates are often not equivalent to unadjusted estimates in the presence of influential covariates. This paper uses simulation to quantify the benefit of covariate adjustment in logistic regression. However, International Conference on Harmonization guidelines suggest that covariate adjustment be pre-specified. Unplanned adjusted analyses should be considered secondary. Results suggest that that if adjustment is not possible or unplanned in a logistic setting, balance in continuous covariates can alleviate some (but never all) of the shortcomings of unadjusted analyses. The case of log binomial regression is also explored. PMID:24138438

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…

Modeling factors influencing the demand for emergency department services in Ontario: a comparison of methods.

PubMed

Moineddin, Rahim; Meaney, Christopher; Agha, Mohammad; Zagorski, Brandon; Glazier, Richard Henry

2011-08-19

Emergency departments are medical treatment facilities, designed to provide episodic care to patients suffering from acute injuries and illnesses as well as patients who are experiencing sporadic flare-ups of underlying chronic medical conditions which require immediate attention. Supply and demand for emergency department services varies across geographic regions and time. Some persons do not rely on the service at all whereas; others use the service on repeated occasions. Issues regarding increased wait times for services and crowding illustrate the need to investigate which factors are associated with increased frequency of emergency department utilization. The evidence from this study can help inform policy makers on the appropriate mix of supply and demand targeted health care policies necessary to ensure that patients receive appropriate health care delivery in an efficient and cost-effective manner. The purpose of this report is to assess those factors resulting in increased demand for emergency department services in Ontario. We assess how utilization rates vary according to the severity of patient presentation in the emergency department. We are specifically interested in the impact that access to primary care physicians has on the demand for emergency department services. Additionally, we wish to investigate these trends using a series of novel regression models for count outcomes which have yet to be employed in the domain of emergency medical research. Data regarding the frequency of emergency department visits for the respondents of Canadian Community Health Survey (CCHS) during our study interval (2003-2005) are obtained from the National Ambulatory Care Reporting System (NACRS). Patients' emergency department utilizations were linked with information from the Canadian Community Health Survey (CCHS) which provides individual level medical, socio-demographic, psychological and behavioral information for investigating predictors of increased emergency department utilization. Six different multiple regression models for count data were fitted to assess the influence of predictors on demand for emergency department services, including: Poisson, Negative Binomial, Zero-Inflated Poisson, Zero-Inflated Negative Binomial, Hurdle Poisson, and Hurdle Negative Binomial. Comparison of competing models was assessed by the Vuong test statistic. The CCHS cycle 2.1 respondents were a roughly equal mix of males (50.4%) and females (49.6%). The majority (86.2%) were young-middle aged adults between the ages of 20-64, living in predominantly urban environments (85.9%), with mid-high household incomes (92.2%) and well-educated, receiving at least a high-school diploma (84.1%). Many participants reported no chronic disease (51.9%), fell into a small number (0-5) of ambulatory diagnostic groups (62.3%), and perceived their health status as good/excellent (88.1%); however, were projected to have high Resource Utilization Band levels of health resource utilization (68.2%). These factors were largely stable for CCHS cycle 3.1 respondents. Factors influencing demand for emergency department services varied according to the severity of triage scores at initial presentation. For example, although a non-significant predictor of the odds of emergency department utilization in high severity cases, access to a primary care physician was a statistically significant predictor of the likelihood of emergency department utilization (OR: 0.69; 95% CI OR: 0.63-0.75) and the rate of emergency department utilization (RR: 0.57; 95% CI RR: 0.50-0.66) in low severity cases. Using a theoretically appropriate hurdle negative binomial regression model this unique study illustrates that access to a primary care physician is an important predictor of both the odds and rate of emergency department utilization in Ontario. Restructuring primary care services, with aims of increasing access to undersupplied populations may result in decreased emergency department utilization rates by approximately 43% for low severity triage level cases.

Spatial distribution of psychotic disorders in an urban area of France: an ecological study.

PubMed

Pignon, Baptiste; Schürhoff, Franck; Baudin, Grégoire; Ferchiou, Aziz; Richard, Jean-Romain; Saba, Ghassen; Leboyer, Marion; Kirkbride, James B; Szöke, Andrei

2016-05-18

Previous analyses of neighbourhood variations of non-affective psychotic disorders (NAPD) have focused mainly on incidence. However, prevalence studies provide important insights on factors associated with disease evolution as well as for healthcare resource allocation. This study aimed to investigate the distribution of prevalent NAPD cases in an urban area in France. The number of cases in each neighbourhood was modelled as a function of potential confounders and ecological variables, namely: migrant density, economic deprivation and social fragmentation. This was modelled using statistical models of increasing complexity: frequentist models (using Poisson and negative binomial regressions), and several Bayesian models. For each model, assumptions validity were checked and compared as to how this fitted to the data, in order to test for possible spatial variation in prevalence. Data showed significant overdispersion (invalidating the Poisson regression model) and residual autocorrelation (suggesting the need to use Bayesian models). The best Bayesian model was Leroux's model (i.e. a model with both strong correlation between neighbouring areas and weaker correlation between areas further apart), with economic deprivation as an explanatory variable (OR = 1.13, 95% CI [1.02-1.25]). In comparison with frequentist methods, the Bayesian model showed a better fit. The number of cases showed non-random spatial distribution and was linked to economic deprivation.

Predictors of the number of under-five malnourished children in Bangladesh: application of the generalized poisson regression model

PubMed Central

2013-01-01

Background Malnutrition is one of the principal causes of child mortality in developing countries including Bangladesh. According to our knowledge, most of the available studies, that addressed the issue of malnutrition among under-five children, considered the categorical (dichotomous/polychotomous) outcome variables and applied logistic regression (binary/multinomial) to find their predictors. In this study malnutrition variable (i.e. outcome) is defined as the number of under-five malnourished children in a family, which is a non-negative count variable. The purposes of the study are (i) to demonstrate the applicability of the generalized Poisson regression (GPR) model as an alternative of other statistical methods and (ii) to find some predictors of this outcome variable. Methods The data is extracted from the Bangladesh Demographic and Health Survey (BDHS) 2007. Briefly, this survey employs a nationally representative sample which is based on a two-stage stratified sample of households. A total of 4,460 under-five children is analysed using various statistical techniques namely Chi-square test and GPR model. Results The GPR model (as compared to the standard Poisson regression and negative Binomial regression) is found to be justified to study the above-mentioned outcome variable because of its under-dispersion (variance < mean) property. Our study also identify several significant predictors of the outcome variable namely mother’s education, father’s education, wealth index, sanitation status, source of drinking water, and total number of children ever born to a woman. Conclusions Consistencies of our findings in light of many other studies suggest that the GPR model is an ideal alternative of other statistical models to analyse the number of under-five malnourished children in a family. Strategies based on significant predictors may improve the nutritional status of children in Bangladesh. PMID:23297699

Developing a dengue forecast model using machine learning: A case study in China

PubMed Central

Zhang, Qin; Wang, Li; Xiao, Jianpeng; Zhang, Qingying; Luo, Ganfeng; Li, Zhihao; He, Jianfeng; Zhang, Yonghui; Ma, Wenjun

2017-01-01

Background In China, dengue remains an important public health issue with expanded areas and increased incidence recently. Accurate and timely forecasts of dengue incidence in China are still lacking. We aimed to use the state-of-the-art machine learning algorithms to develop an accurate predictive model of dengue. Methodology/Principal findings Weekly dengue cases, Baidu search queries and climate factors (mean temperature, relative humidity and rainfall) during 2011–2014 in Guangdong were gathered. A dengue search index was constructed for developing the predictive models in combination with climate factors. The observed year and week were also included in the models to control for the long-term trend and seasonality. Several machine learning algorithms, including the support vector regression (SVR) algorithm, step-down linear regression model, gradient boosted regression tree algorithm (GBM), negative binomial regression model (NBM), least absolute shrinkage and selection operator (LASSO) linear regression model and generalized additive model (GAM), were used as candidate models to predict dengue incidence. Performance and goodness of fit of the models were assessed using the root-mean-square error (RMSE) and R-squared measures. The residuals of the models were examined using the autocorrelation and partial autocorrelation function analyses to check the validity of the models. The models were further validated using dengue surveillance data from five other provinces. The epidemics during the last 12 weeks and the peak of the 2014 large outbreak were accurately forecasted by the SVR model selected by a cross-validation technique. Moreover, the SVR model had the consistently smallest prediction error rates for tracking the dynamics of dengue and forecasting the outbreaks in other areas in China. Conclusion and significance The proposed SVR model achieved a superior performance in comparison with other forecasting techniques assessed in this study. The findings can help the government and community respond early to dengue epidemics. PMID:29036169

The role of ENSO in understanding changes in Colombia's annual malaria burden by region, 1960–2006

PubMed Central

Mantilla, Gilma; Oliveros, Hugo; Barnston, Anthony G

2009-01-01

Background Malaria remains a serious problem in Colombia. The number of malaria cases is governed by multiple climatic and non-climatic factors. Malaria control policies, and climate controls such as rainfall and temperature variations associated with the El Niño/Southern Oscillation (ENSO), have been associated with malaria case numbers. Using historical climate data and annual malaria case number data from 1960 to 2006, statistical models are developed to isolate the effects of climate in each of Colombia's five contrasting geographical regions. Methods Because year to year climate variability associated with ENSO causes interannual variability in malaria case numbers, while changes in population and institutional control policy result in more gradual trends, the chosen predictors in the models are annual indices of the ENSO state (sea surface temperature [SST] in the tropical Pacific Ocean) and time reference indices keyed to two major malaria trends during the study period. Two models were used: a Poisson and a Negative Binomial regression model. Two ENSO indices, two time reference indices, and one dummy variable are chosen as candidate predictors. The analysis was conducted using the five geographical regions to match the similar aggregation used by the National Institute of Health for its official reports. Results The Negative Binomial regression model is found better suited to the malaria cases in Colombia. Both the trend variables and the ENSO measures are significant predictors of malaria case numbers in Colombia as a whole, and in two of the five regions. A one degree Celsius change in SST (indicating a weak to moderate ENSO event) is seen to translate to an approximate 20% increase in malaria cases, holding other variables constant. Conclusion Regional differentiation in the role of ENSO in understanding changes in Colombia's annual malaria burden during 1960–2006 was found, constituting a new approach to use ENSO as a significant predictor of the malaria cases in Colombia. These results naturally point to additional needed work: (1) refining the regional and seasonal dependence of climate on the ENSO state, and of malaria on the climate variables; (2) incorporating ENSO-related climate variability into dynamic malaria models. PMID:19133152

Detection of influenza-like illness aberrations by directly monitoring Pearson residuals of fitted negative binomial regression models.

PubMed

Chan, Ta-Chien; Teng, Yung-Chu; Hwang, Jing-Shiang

2015-02-21

Emerging novel influenza outbreaks have increasingly been a threat to the public and a major concern of public health departments. Real-time data in seamless surveillance systems such as health insurance claims data for influenza-like illnesses (ILI) are ready for analysis, making it highly desirable to develop practical techniques to analyze such readymade data for outbreak detection so that the public can receive timely influenza epidemic warnings. This study proposes a simple and effective approach to analyze area-based health insurance claims data including outpatient and emergency department (ED) visits for early detection of any aberrations of ILI. The health insurance claims data during 2004-2009 from a national health insurance research database were used for developing early detection methods. The proposed approach fitted the daily new ILI visits and monitored the Pearson residuals directly for aberration detection. First, negative binomial regression was used for both outpatient and ED visits to adjust for potentially influential factors such as holidays, weekends, seasons, temporal dependence and temperature. Second, if the Pearson residuals exceeded 1.96, aberration signals were issued. The empirical validation of the model was done in 2008 and 2009. In addition, we designed a simulation study to compare the time of outbreak detection, non-detection probability and false alarm rate between the proposed method and modified CUSUM. The model successfully detected the aberrations of 2009 pandemic (H1N1) influenza virus in northern, central and southern Taiwan. The proposed approach was more sensitive in identifying aberrations in ED visits than those in outpatient visits. Simulation studies demonstrated that the proposed approach could detect the aberrations earlier, and with lower non-detection probability and mean false alarm rate in detecting aberrations compared to modified CUSUM methods. The proposed simple approach was able to filter out temporal trends, adjust for temperature, and issue warning signals for the first wave of the influenza epidemic in a timely and accurate manner.

Bayesian propensity scores for high-dimensional causal inference: A comparison of drug-eluting to bare-metal coronary stents.

PubMed

Spertus, Jacob V; Normand, Sharon-Lise T

2018-04-23

High-dimensional data provide many potential confounders that may bolster the plausibility of the ignorability assumption in causal inference problems. Propensity score methods are powerful causal inference tools, which are popular in health care research and are particularly useful for high-dimensional data. Recent interest has surrounded a Bayesian treatment of propensity scores in order to flexibly model the treatment assignment mechanism and summarize posterior quantities while incorporating variance from the treatment model. We discuss methods for Bayesian propensity score analysis of binary treatments, focusing on modern methods for high-dimensional Bayesian regression and the propagation of uncertainty. We introduce a novel and simple estimator for the average treatment effect that capitalizes on conjugacy of the beta and binomial distributions. Through simulations, we show the utility of horseshoe priors and Bayesian additive regression trees paired with our new estimator, while demonstrating the importance of including variance from the treatment regression model. An application to cardiac stent data with almost 500 confounders and 9000 patients illustrates approaches and facilitates comparison with existing alternatives. As measured by a falsifiability endpoint, we improved confounder adjustment compared with past observational research of the same problem. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Work-related injuries involving a hand or fingers among union carpenters in Washington State, 1989 to 2008.

PubMed

Lipscomb, Hester J; Schoenfisch, Ashley; Cameron, Wilfrid

2013-07-01

We evaluated work-related injuries involving a hand or fingers and associated costs among a cohort of 24,830 carpenters between 1989 and 2008. Injury rates and rate ratios were calculated by using Poisson regression to explore higher risk on the basis of age, sex, time in the union, predominant work, and calendar time. Negative binomial regression was used to model dollars paid per claim after adjustment for inflation and discounting. Hand injuries accounted for 21.1% of reported injuries and 9.5% of paid lost time injuries. Older carpenters had proportionately more amputations, fractures, and multiple injuries, but their rates of these more severe injuries were not higher. Costs exceeded $21 million, a cost burden of $0.11 per hour worked. Older carpenters' higher proportion of serious injuries in the absence of higher rates likely reflects age-related reporting differences.

Mental Health Symptoms Among Student Service Members/Veterans and Civilian College Students.

PubMed

Cleveland, Sandi D; Branscum, Adam J; Bovbjerg, Viktor E; Thorburn, Sheryl

2015-01-01

The aim of this study was to investigate if and to what extent student service members/veterans differ from civilian college students in the prevalence of self-reported symptoms of poor mental health. The Fall 2011 implementation of the American College Health Association-National College Health Assessment included 27,774 respondents from 44 colleges and universities. Participants were matched using propensity scores, and the prevalence of symptoms was compared using logistic regression and zero-inflated negative binomial regression models. The odds of feeling overwhelmed in the last 12 months were significantly lower among student service members/veterans with a history of hazardous duty (odd ratio [OR] = 0.46, adjusted p value <.05) compared with civilian students. Military service, with and without hazardous duty deployment, was not a significant predictor of the total number of symptoms of poor mental health. Current student service members/veterans may not be disproportionately affected by poor psychological functioning.

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.

Perceived health status and daily activity participation of older Malaysians.

PubMed

Ng, Sor Tho; Tengku-Aizan, Hamid; Tey, Nai Peng

2011-07-01

This article investigates the influence of perceived health status on the daily activity participation of older Malaysians. Data from the Survey on Perceptions of Needs and Problems of the Elderly, which was conducted in 1999, were used. The negative binomial regression results show that older persons with good perceived health status reported more varieties of daily activity participation, especially among the uneducated and those with below-average self-esteem. The multinomial logistic regression model suggests that older persons with good perceived health status tended to engage daily in paid work only or with leisure activities, whereas those perceived to have poor health were more likely to engage in leisure activities only or leisure and family role activities. Promotion of a healthy lifestyle at a younger age encourages every person to monitor and take responsibility for their own health, which is a necessary strategy to ensure active participation at an older age, and thus improve their well-being.

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...

A Monte Carlo Risk Analysis of Life Cycle Cost Prediction.

DTIC Science & Technology

1975-09-01

process which occurs with each FLU failure. With this in mind there is no alternative other than the binomial distribution. 24 GOR/SM/75D-6 With all of...Weibull distribution of failures as selected by user. For each failure of the ith FLU, the model then samples from the binomial distribution to deter- mine...which is sampled from the binomial . Neither of the two conditions for normality are met, i.e., that RTS Ie close to .5 and the number of samples close

Enumerative and binomial sampling plans for citrus mealybug (Homoptera: pseudococcidae) in citrus groves.

PubMed

Martínez-Ferrer, María Teresa; Ripollés, José Luís; Garcia-Marí, Ferran

2006-06-01

The spatial distribution of the citrus mealybug, Planococcus citri (Risso) (Homoptera: Pseudococcidae), was studied in citrus groves in northeastern Spain. Constant precision sampling plans were designed for all developmental stages of citrus mealybug under the fruit calyx, for late stages on fruit, and for females on trunks and main branches; more than 66, 286, and 101 data sets, respectively, were collected from nine commercial fields during 1992-1998. Dispersion parameters were determined using Taylor's power law, giving aggregated spatial patterns for citrus mealybug populations in three locations of the tree sampled. A significant relationship between the number of insects per organ and the percentage of occupied organs was established using either Wilson and Room's binomial model or Kono and Sugino's empirical formula. Constant precision (E = 0.25) sampling plans (i.e., enumerative plans) for estimating mean densities were developed using Green's equation and the two binomial models. For making management decisions, enumerative counts may be less labor-intensive than binomial sampling. Therefore, we recommend enumerative sampling plans for the use in an integrated pest management program in citrus. Required sample sizes for the range of population densities near current management thresholds, in the three plant locations calyx, fruit, and trunk were 50, 110-330, and 30, respectively. Binomial sampling, especially the empirical model, required a higher sample size to achieve equivalent levels of precision.

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.

A review of statistical estimators for risk-adjusted length of stay: analysis of the Australian and new Zealand Intensive Care Adult Patient Data-Base, 2008-2009.

PubMed

Moran, John L; Solomon, Patricia J

2012-05-16

For the analysis of length-of-stay (LOS) data, which is characteristically right-skewed, a number of statistical estimators have been proposed as alternatives to the traditional ordinary least squares (OLS) regression with log dependent variable. Using a cohort of patients identified in the Australian and New Zealand Intensive Care Society Adult Patient Database, 2008-2009, 12 different methods were used for estimation of intensive care (ICU) length of stay. These encompassed risk-adjusted regression analysis of firstly: log LOS using OLS, linear mixed model [LMM], treatment effects, skew-normal and skew-t models; and secondly: unmodified (raw) LOS via OLS, generalised linear models [GLMs] with log-link and 4 different distributions [Poisson, gamma, negative binomial and inverse-Gaussian], extended estimating equations [EEE] and a finite mixture model including a gamma distribution. A fixed covariate list and ICU-site clustering with robust variance were utilised for model fitting with split-sample determination (80%) and validation (20%) data sets, and model simulation was undertaken to establish over-fitting (Copas test). Indices of model specification using Bayesian information criterion [BIC: lower values preferred] and residual analysis as well as predictive performance (R2, concordance correlation coefficient (CCC), mean absolute error [MAE]) were established for each estimator. The data-set consisted of 111663 patients from 131 ICUs; with mean(SD) age 60.6(18.8) years, 43.0% were female, 40.7% were mechanically ventilated and ICU mortality was 7.8%. ICU length-of-stay was 3.4(5.1) (median 1.8, range (0.17-60)) days and demonstrated marked kurtosis and right skew (29.4 and 4.4 respectively). BIC showed considerable spread, from a maximum of 509801 (OLS-raw scale) to a minimum of 210286 (LMM). R2 ranged from 0.22 (LMM) to 0.17 and the CCC from 0.334 (LMM) to 0.149, with MAE 2.2-2.4. Superior residual behaviour was established for the log-scale estimators. There was a general tendency for over-prediction (negative residuals) and for over-fitting, the exception being the GLM negative binomial estimator. The mean-variance function was best approximated by a quadratic function, consistent with log-scale estimation; the link function was estimated (EEE) as 0.152(0.019, 0.285), consistent with a fractional-root function. For ICU length of stay, log-scale estimation, in particular the LMM, appeared to be the most consistently performing estimator(s). Neither the GLM variants nor the skew-regression estimators dominated.

General Strain Theory as a Basis for the Design of School Interventions

ERIC Educational Resources Information Center

Moon, Byongook; Morash, Merry

2013-01-01

The research described in this article applies general strain theory to identify possible points of intervention for reducing delinquency of students in two middle schools. Data were collected from 296 youths, and separate negative binomial regression analyses were used to identify predictors of violent, property, and status delinquency. Emotional…

The Effectiveness of an Electronic Security Management System in a Privately Owned Apartment Complex

ERIC Educational Resources Information Center

Greenberg, David F.; Roush, Jeffrey B.

2009-01-01

Poisson and negative binomial regression methods are used to analyze the monthly time series data to determine the effects of introducing an integrated security management system including closed-circuit television (CCTV), door alarm monitoring, proximity card access, and emergency call boxes to a large privately-owned complex of apartment…

Campaign Strategies and Voter Approval of School Referenda: A Mixed Methods Analysis

ERIC Educational Resources Information Center

Johnson, Paul A.; Ingle, William Kyle

2009-01-01

Drawing from state administrative data and surveys of superintendents in Ohio, this mixed methods study examined factors associated with voters' approval of local school levies. Utilizing binomial logistic regression, this study found that new levies and poverty rates were significantly associated with a decrease in the likelihood of passage.…

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.

[Optimal extraction of effective constituents from Aralia elata by central composite design and response surface methodology].

PubMed

Lv, Shao-Wa; Liu, Dong; Hu, Pan-Pan; Ye, Xu-Yan; Xiao, Hong-Bin; Kuang, Hai-Xue

2010-03-01

To optimize the process of extracting effective constituents from Aralia elata by response surface methodology. The independent variables were ethanol concentration, reflux time and solvent fold, the dependent variable was extraction rate of total saponins in Aralia elata. Linear or no-linear mathematic models were used to estimate the relationship between independent and dependent variables. Response surface methodology was used to optimize the process of extraction. The prediction was carried out through comparing the observed and predicted values. Regression coefficient of binomial fitting complex model was as high as 0.9617, the optimum conditions of extraction process were 70% ethanol, 2.5 hours for reflux, 20-fold solvent and 3 times for extraction. The bias between observed and predicted values was -2.41%. It shows the optimum model is highly predictive.

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.

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.

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.

Comparison of modeling methods to predict the spatial distribution of deep-sea coral and sponge in the Gulf of Alaska

NASA Astrophysics Data System (ADS)

Rooper, Christopher N.; Zimmermann, Mark; Prescott, Megan M.

2017-08-01

Deep-sea coral and sponge ecosystems are widespread throughout most of Alaska's marine waters, and are associated with many different species of fishes and invertebrates. These ecosystems are vulnerable to the effects of commercial fishing activities and climate change. We compared four commonly used species distribution models (general linear models, generalized additive models, boosted regression trees and random forest models) and an ensemble model to predict the presence or absence and abundance of six groups of benthic invertebrate taxa in the Gulf of Alaska. All four model types performed adequately on training data for predicting presence and absence, with regression forest models having the best overall performance measured by the area under the receiver-operating-curve (AUC). The models also performed well on the test data for presence and absence with average AUCs ranging from 0.66 to 0.82. For the test data, ensemble models performed the best. For abundance data, there was an obvious demarcation in performance between the two regression-based methods (general linear models and generalized additive models), and the tree-based models. The boosted regression tree and random forest models out-performed the other models by a wide margin on both the training and testing data. However, there was a significant drop-off in performance for all models of invertebrate abundance ( 50%) when moving from the training data to the testing data. Ensemble model performance was between the tree-based and regression-based methods. The maps of predictions from the models for both presence and abundance agreed very well across model types, with an increase in variability in predictions for the abundance data. We conclude that where data conforms well to the modeled distribution (such as the presence-absence data and binomial distribution in this study), the four types of models will provide similar results, although the regression-type models may be more consistent with biological theory. For data with highly zero-inflated distributions and non-normal distributions such as the abundance data from this study, the tree-based methods performed better. Ensemble models that averaged predictions across the four model types, performed better than the GLM or GAM models but slightly poorer than the tree-based methods, suggesting ensemble models might be more robust to overfitting than tree methods, while mitigating some of the disadvantages in predictive performance of regression methods.

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.

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.

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.

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.

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.

Multiple imputation for handling missing outcome data when estimating the relative risk.

PubMed

Sullivan, Thomas R; Lee, Katherine J; Ryan, Philip; Salter, Amy B

2017-09-06

Multiple imputation is a popular approach to handling missing data in medical research, yet little is known about its applicability for estimating the relative risk. Standard methods for imputing incomplete binary outcomes involve logistic regression or an assumption of multivariate normality, whereas relative risks are typically estimated using log binomial models. It is unclear whether misspecification of the imputation model in this setting could lead to biased parameter estimates. Using simulated data, we evaluated the performance of multiple imputation for handling missing data prior to estimating adjusted relative risks from a correctly specified multivariable log binomial model. We considered an arbitrary pattern of missing data in both outcome and exposure variables, with missing data induced under missing at random mechanisms. Focusing on standard model-based methods of multiple imputation, missing data were imputed using multivariate normal imputation or fully conditional specification with a logistic imputation model for the outcome. Multivariate normal imputation performed poorly in the simulation study, consistently producing estimates of the relative risk that were biased towards the null. Despite outperforming multivariate normal imputation, fully conditional specification also produced somewhat biased estimates, with greater bias observed for higher outcome prevalences and larger relative risks. Deleting imputed outcomes from analysis datasets did not improve the performance of fully conditional specification. Both multivariate normal imputation and fully conditional specification produced biased estimates of the relative risk, presumably since both use a misspecified imputation model. Based on simulation results, we recommend researchers use fully conditional specification rather than multivariate normal imputation and retain imputed outcomes in the analysis when estimating relative risks. However fully conditional specification is not without its shortcomings, and so further research is needed to identify optimal approaches for relative risk estimation within the multiple imputation framework.

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.

Forecast of severe fever with thrombocytopenia syndrome incidence with meteorological factors.

PubMed

Sun, Ji-Min; Lu, Liang; Liu, Ke-Ke; Yang, Jun; Wu, Hai-Xia; Liu, Qi-Yong

2018-06-01

Severe fever with thrombocytopenia syndrome (SFTS) is emerging and some studies reported that SFTS incidence was associated with meteorological factors, while no report on SFTS forecast models was reported up to date. In this study, we constructed and compared three forecast models using autoregressive integrated moving average (ARIMA) model, negative binomial regression model (NBM), and quasi-Poisson generalized additive model (GAM). The dataset from 2011 to 2015 were used for model construction and the dataset in 2016 were used for external validity assessment. All the three models fitted the SFTS cases reasonably well during the training process and forecast process, while the NBM model forecasted better than other two models. Moreover, we demonstrated that temperature and relative humidity played key roles in explaining the temporal dynamics of SFTS occurrence. Our study contributes to better understanding of SFTS dynamics and provides predictive tools for the control and prevention of SFTS. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

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

Utilization of accident databases and fuzzy sets to estimate frequency of HazMat transport accidents.

PubMed

Qiao, Yuanhua; Keren, Nir; Mannan, M Sam

2009-08-15

Risk assessment and management of transportation of hazardous materials (HazMat) require the estimation of accident frequency. This paper presents a methodology to estimate hazardous materials transportation accident frequency by utilizing publicly available databases and expert knowledge. The estimation process addresses route-dependent and route-independent variables. Negative binomial regression is applied to an analysis of the Department of Public Safety (DPS) accident database to derive basic accident frequency as a function of route-dependent variables, while the effects of route-independent variables are modeled by fuzzy logic. The integrated methodology provides the basis for an overall transportation risk analysis, which can be used later to develop a decision support system.

Statistical procedures for analyzing mental health services data.

PubMed

Elhai, Jon D; Calhoun, Patrick S; Ford, Julian D

2008-08-15

In mental health services research, analyzing service utilization data often poses serious problems, given the presence of substantially skewed data distributions. This article presents a non-technical introduction to statistical methods specifically designed to handle the complexly distributed datasets that represent mental health service use, including Poisson, negative binomial, zero-inflated, and zero-truncated regression models. A flowchart is provided to assist the investigator in selecting the most appropriate method. Finally, a dataset of mental health service use reported by medical patients is described, and a comparison of results across several different statistical methods is presented. Implications of matching data analytic techniques appropriately with the often complexly distributed datasets of mental health services utilization variables are discussed.

Perceived Prevalence of Teasing and Bullying Predicts High School Dropout Rates

ERIC Educational Resources Information Center

Cornell, Dewey; Gregory, Anne; Huang, Francis; Fan, Xitao

2013-01-01

This prospective study of 276 Virginia public high schools found that the prevalence of teasing and bullying (PTB) as perceived by both 9th-grade students and teachers was predictive of dropout rates for this cohort 4 years later. Negative binomial regression indicated that one standard deviation increases in student- and teacher-reported PTB were…

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…

An empirical tool to evaluate the safety of cyclists: Community based, macro-level collision prediction models using negative binomial regression.

PubMed

Wei, Feng; Lovegrove, Gordon

2013-12-01

Today, North American governments are more willing to consider compact neighborhoods with increased use of sustainable transportation modes. Bicycling, one of the most effective modes for short trips with distances less than 5km is being encouraged. However, as vulnerable road users (VRUs), cyclists are more likely to be injured when involved in collisions. In order to create a safe road environment for them, evaluating cyclists' road safety at a macro level in a proactive way is necessary. In this paper, different generalized linear regression methods for collision prediction model (CPM) development are reviewed and previous studies on micro-level and macro-level bicycle-related CPMs are summarized. On the basis of insights gained in the exploration stage, this paper also reports on efforts to develop negative binomial models for bicycle-auto collisions at a community-based, macro-level. Data came from the Central Okanagan Regional District (CORD), of British Columbia, Canada. The model results revealed two types of statistical associations between collisions and each explanatory variable: (1) An increase in bicycle-auto collisions is associated with an increase in total lane kilometers (TLKM), bicycle lane kilometers (BLKM), bus stops (BS), traffic signals (SIG), intersection density (INTD), and arterial-local intersection percentage (IALP). (2) A decrease in bicycle collisions was found to be associated with an increase in the number of drive commuters (DRIVE), and in the percentage of drive commuters (DRP). These results support our hypothesis that in North America, with its current low levels of bicycle use (<4%), we can initially expect to see an increase in bicycle collisions as cycle mode share increases. However, as bicycle mode share increases beyond some unknown 'critical' level, our hypothesis also predicts a net safety improvement. To test this hypothesis and to further explore the statistical relationships between bicycle mode split and overall road safety, future research needs to pursue further development and application of community-based, macro-level CPMs. Copyright © 2012. Published by Elsevier Ltd.

Meta-analysis of diagnostic tests accounting for disease prevalence: a new model using trivariate copulas.

PubMed

Hoyer, A; Kuss, O

2015-05-20

In real life and somewhat contrary to biostatistical textbook knowledge, sensitivity and specificity (and not only predictive values) of diagnostic tests can vary with the underlying prevalence of disease. In meta-analysis of diagnostic studies, accounting for this fact naturally leads to a trivariate expansion of the traditional bivariate logistic regression model with random study effects. In this paper, a new model is proposed using trivariate copulas and beta-binomial marginal distributions for sensitivity, specificity, and prevalence as an expansion of the bivariate model. Two different copulas are used, the trivariate Gaussian copula and a trivariate vine copula based on the bivariate Plackett copula. This model has a closed-form likelihood, so standard software (e.g., SAS PROC NLMIXED) can be used. The results of a simulation study have shown that the copula models perform at least as good but frequently better than the standard model. The methods are illustrated by two examples. Copyright © 2015 John Wiley & Sons, Ltd.

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...

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.

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.

Factors associated with the frequency of monitoring of liver enzymes, renal function and lipid laboratory markers among individuals initiating combination antiretroviral therapy: a cohort study.

PubMed

Gillis, Jennifer; Bayoumi, Ahmed M; Burchell, Ann N; Cooper, Curtis; Klein, Marina B; Loutfy, Mona; Machouf, Nima; Montaner, Julio Sg; Tsoukas, Chris; Hogg, Robert S; Raboud, Janet

2015-10-26

As the average age of the HIV-positive population increases, there is increasing need to monitor patients for the development of comorbidities as well as for drug toxicities. We examined factors associated with the frequency of measurement of liver enzymes, renal function tests, and lipid levels among participants of the Canadian Observational Cohort (CANOC) collaboration which follows people who initiated HIV antiretroviral therapy in 2000 or later. We used zero-inflated negative binomial regression models to examine the associations of demographic and clinical characteristics with the rates of measurement during follow-up. Generalized estimating equations with a logit link were used to examine factors associated with gaps of 12 months or more between measurements. Electronic laboratory data were available for 3940 of 7718 CANOC participants. The median duration of electronic follow-up was 3.5 years. The median (interquartile) rates of tests per year were 2.76 (1.60, 3.73), 2.55 (1.44, 3.38) and 1.42 (0.50, 2.52) for liver, renal and lipid parameters, respectively. In multivariable zero-inflated negative binomial regression models, individuals infected through injection drug use (IDU) were significantly less likely to have any measurements. Among participants with at least one measurement, rates of measurement of liver, renal and lipid tests were significantly lower for younger individuals and Aboriginal Peoples. Hepatitis C co-infected individuals with a history of IDU had lower rates of measurement and were at greater risk of having 12 month gaps between measurements. Hepatitis C co-infected participants infected through IDU were at increased risk of gaps in testing, despite publicly funded health care and increased risk of comorbid conditions. This should be taken into consideration in analyses examining factors associated with outcomes based on laboratory parameters.

Which Types of Televised Anti-Tobacco Campaigns Prompt More Quitline Calls from Disadvantaged Groups?

ERIC Educational Resources Information Center

Durkin, Sarah J.; Wakefield, Melanie A.; Spittal, Matthew J.

2011-01-01

To examine the efficacy of different types of mass media ads in driving lower socio-economic smokers (SES) to utilize quitlines. This study collected all 33 719 calls to the Victorian quitline in Australia over a 2-year period. Negative binomial regressions examined the relationship between weekly levels of exposure to different types of…

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.

Establishing endangered species recovery criteria using predictive simulation modeling

USGS Publications Warehouse

McGowan, Conor P.; Catlin, Daniel H.; Shaffer, Terry L.; Gratto-Trevor, Cheri L.; Aron, Carol

2014-01-01

Listing a species under the Endangered Species Act (ESA) and developing a recovery plan requires U.S. Fish and Wildlife Service to establish specific and measurable criteria for delisting. Generally, species are listed because they face (or are perceived to face) elevated risk of extinction due to issues such as habitat loss, invasive species, or other factors. Recovery plans identify recovery criteria that reduce extinction risk to an acceptable level. It logically follows that the recovery criteria, the defined conditions for removing a species from ESA protections, need to be closely related to extinction risk. Extinction probability is a population parameter estimated with a model that uses current demographic information to project the population into the future over a number of replicates, calculating the proportion of replicated populations that go extinct. We simulated extinction probabilities of piping plovers in the Great Plains and estimated the relationship between extinction probability and various demographic parameters. We tested the fit of regression models linking initial abundance, productivity, or population growth rate to extinction risk, and then, using the regression parameter estimates, determined the conditions required to reduce extinction probability to some pre-defined acceptable threshold. Binomial regression models with mean population growth rate and the natural log of initial abundance were the best predictors of extinction probability 50 years into the future. For example, based on our regression models, an initial abundance of approximately 2400 females with an expected mean population growth rate of 1.0 will limit extinction risk for piping plovers in the Great Plains to less than 0.048. Our method provides a straightforward way of developing specific and measurable recovery criteria linked directly to the core issue of extinction risk. Published by Elsevier Ltd.

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.

The Effect of Sharrows, Painted Bicycle Lanes and Physically Protected Paths on the Severity of Bicycle Injuries Caused by Motor Vehicles.

PubMed

Wall, Stephen P; Lee, David C; Frangos, Spiros G; Sethi, Monica; Heyer, Jessica H; Ayoung-Chee, Patricia; DiMaggio, Charles J

2016-01-01

We conducted individual and ecologic analyses of prospectively collected data from 839 injured bicyclists who collided with motorized vehicles and presented to Bellevue Hospital, an urban Level-1 trauma center in New York City, from December 2008 to August 2014. Variables included demographics, scene information, rider behaviors, bicycle route availability, and whether the collision occurred before the road segment was converted to a bicycle route. We used negative binomial modeling to assess the risk of injury occurrence following bicycle path or lane implementation. We dichotomized U.S. National Trauma Data Bank Injury Severity Scores (ISS) into none/mild (0-8) versus moderate, severe, or critical (>8) and used adjusted multivariable logistic regression to model the association of ISS with collision proximity to sharrows (i.e., bicycle lanes designated for sharing with cars), painted bicycle lanes, or physically protected paths. Negative binomial modeling of monthly counts, while adjusting for pedestrian activity, revealed that physically protected paths were associated with 23% fewer injuries. Painted bicycle lanes reduced injury risk by nearly 90% (IDR 0.09, 95% CI 0.02-0.33). Holding all else equal, compared to no bicycle route, a bicycle injury nearby sharrows was nearly twice as likely to be moderate, severe, or critical (adjusted odds ratio 1.94; 95% confidence interval (CI) 0.91-4.15). Painted bicycle lanes and physically protected paths were 1.52 (95% CI 0.85-2.71) and 1.66 (95% CI 0.85-3.22) times as likely to be associated with more than mild injury respectively.

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).

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.

Homicide mortality rates in Canada, 2000-2009: Youth at increased risk.

PubMed

Basham, C Andrew; Snider, Carolyn

2016-10-20

To estimate and compare Canadian homicide mortality rates (HMRs) and trends in HMRs across age groups, with a focus on trends for youth. Data for the period of 2000 to 2009 were collected from Statistics Canada's CANSIM (Canadian Statistical Information Management) Table 102-0540 with the following ICD-10-CA coded external causes of death: X85 to Y09 (assault) and Y87.1 (sequelae of assault). Annual population counts from 2000 to 2009 were obtained from Statistics Canada's CANSIM Table 051-0001. Both death and population counts were organized into five-year age groups. A random effects negative binomial regression analysis was conducted to estimate age group-specific rates, rate ratios, and trends in homicide mortality. There were 9,878 homicide deaths in Canada during the study period. The increase in the overall homicide mortality rate (HMR) of 0.3% per year was not statistically significant (95% CI: -1.1% to +1.8%). Canadians aged 15-19 years and 20-24 years had the highest HMRs during the study period, and experienced statistically significant annual increases in their HMRs of 3% and 4% respectively (p < 0.05). A general, though not statistically significant, decrease in the HMR was observed for all age groups 50+ years. A fixed effects negative binomial regression model showed that the HMR for males was higher than for females over the study period [RRfemale/male = 0.473 (95% CI: 0.361, 0.621)], but no significant difference in sex-specific trends in the HMR was found. An increasing risk of homicide mortality was identified among Canadian youth, ages 15-24, over the 10-year study period. Research that seeks to understand the reasons for the increased homicide risk facing Canada's youth, and public policy responses to reduce this risk, are warranted.

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

Modeling recall memory for emotional objects in Alzheimer's disease.

PubMed

Sundstrøm, Martin

2011-07-01

To examine whether emotional memory (EM) of objects with self-reference in Alzheimer's disease (AD) can be modeled with binomial logistic regression in a free recall and an object recognition test to predict EM enhancement. Twenty patients with AD and twenty healthy controls were studied. Six objects (three presented as gifts) were shown to each participant. Ten minutes later, a free recall and a recognition test were applied. The recognition test had target-objects mixed with six similar distracter objects. Participants were asked to name any object in the recall test and identify each object in the recognition test as known or unknown. The total of gift objects recalled in AD patients (41.6%) was larger than neutral objects (13.3%) and a significant EM recall effect for gifts was found (Wilcoxon: p < .003). EM was not found for recognition in AD patients due to a ceiling effect. Healthy older adults scored overall higher in recall and recognition but showed no EM enhancement due to a ceiling effect. A logistic regression showed that likelihood of emotional recall memory can be modeled as a function of MMSE score (p < .014) and object status (p < .0001) as gift or non-gift. Recall memory was enhanced in AD patients for emotional objects indicating that EM in mild to moderate AD although impaired can be provoked with strong emotional load. The logistic regression model suggests that EM declines with the progression of AD rather than disrupts and may be a useful tool for evaluating magnitude of emotional load.

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…

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.

Trend estimation in populations with imperfect detection

USGS Publications Warehouse

Kery, Marc; Dorazio, Robert M.; Soldaat, Leo; Van Strien, Arco; Zuiderwijk, Annie; Royle, J. Andrew

2009-01-01

1. Trends of animal populations are of great interest in ecology but cannot be directly observed owing to imperfect detection. Binomial mixture models use replicated counts to estimate abundance, corrected for detection, in demographically closed populations. Here, we extend these models to open populations and illustrate them using sand lizard Lacerta agilis counts from the national Dutch reptile monitoring scheme. 2. Our model requires replicated counts from multiple sites in each of several periods, within which population closure is assumed. Counts are described by a hierarchical generalized linear model, where the state model deals with spatio-temporal patterns in true abundance and the observation model with imperfect counts, given that true state. We used WinBUGS to fit the model to lizard counts from 208 transects with 1–10 (mean 3) replicate surveys during each spring 1994–2005. 3. Our state model for abundance contained two independent log-linear Poisson regressions on year for coastal and inland sites, and random site effects to account for unexplained heterogeneity. The observation model for detection of an individual lizard contained effects of region, survey date, temperature, observer experience and random survey effects. 4. Lizard populations increased in both regions but more steeply on the coast. Detectability increased over the first few years of the study, was greater on the coast and for the most experienced observers, and highest around 1 June. Interestingly, the population increase inland was not detectable when the observed counts were analysed without account of detectability. The proportional increase between 1994 and 2005 in total lizard abundance across all sites was estimated at 86% (95% CRI 35–151). 5. Synthesis and applications. Open-population binomial mixture models are attractive for studying true population dynamics while explicitly accounting for the observation process, i.e. imperfect detection. We emphasize the important conceptual benefit provided by temporal replicate observations in terms of the interpretability of animal counts.

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.

A quantile count model of water depth constraints on Cape Sable seaside sparrows

USGS Publications Warehouse

Cade, B.S.; Dong, Q.

2008-01-01

1. A quantile regression model for counts of breeding Cape Sable seaside sparrows Ammodramus maritimus mirabilis (L.) as a function of water depth and previous year abundance was developed based on extensive surveys, 1992-2005, in the Florida Everglades. The quantile count model extends linear quantile regression methods to discrete response variables, providing a flexible alternative to discrete parametric distributional models, e.g. Poisson, negative binomial and their zero-inflated counterparts. 2. Estimates from our multiplicative model demonstrated that negative effects of increasing water depth in breeding habitat on sparrow numbers were dependent on recent occupation history. Upper 10th percentiles of counts (one to three sparrows) decreased with increasing water depth from 0 to 30 cm when sites were not occupied in previous years. However, upper 40th percentiles of counts (one to six sparrows) decreased with increasing water depth for sites occupied in previous years. 3. Greatest decreases (-50% to -83%) in upper quantiles of sparrow counts occurred as water depths increased from 0 to 15 cm when previous year counts were 1, but a small proportion of sites (5-10%) held at least one sparrow even as water depths increased to 20 or 30 cm. 4. A zero-inflated Poisson regression model provided estimates of conditional means that also decreased with increasing water depth but rates of change were lower and decreased with increasing previous year counts compared to the quantile count model. Quantiles computed for the zero-inflated Poisson model enhanced interpretation of this model but had greater lack-of-fit for water depths > 0 cm and previous year counts 1, conditions where the negative effect of water depths were readily apparent and fitted better with the quantile count model.

Payment systems and oral health in Swedish dental care: Observations over six years.

PubMed

Andås, C A; Hakeberg, M

2016-12-01

The aim of this longitudinal study of patients in regular dental care was to compare the findings of manifest caries and fillings after a 6-year adherence to either of two optional payment models, the traditional fee-for service (FFS) model, or the new capitation model 'Dental Care for Health' (DCH). Data on manifest caries lesions, the number of fillings and a number of background variables were collected from both a register and a questionnaire completed by 6,299 regular dental patients who met the inclusion criteria. The influence of payment system adherence and background variables on the number of manifest caries lesions at study end was examined by the means of negative binomial regression analysis. The incidence rate ratio of manifest caries lesions after six years in FFS was 1.5 compared to DCH, after controlling for age, gender, education and pre-baseline caries incidence. The number of fillings was higher in FFS than in DCH at study start and at study end, and was also described by a steeper slope. At group level, this study showed a statistically significant difference between the caries situation after six years in DCH compared with FFS, when some important background factors, including pre-baseline caries, were kept constant in a regression model. Copyright© 2016 Dennis Barber Ltd

High-risk regions and outbreak modelling of tularemia in humans.

PubMed

Desvars-Larrive, A; Liu, X; Hjertqvist, M; Sjöstedt, A; Johansson, A; Rydén, P

2017-02-01

Sweden reports large and variable numbers of human tularemia cases, but the high-risk regions are anecdotally defined and factors explaining annual variations are poorly understood. Here, high-risk regions were identified by spatial cluster analysis on disease surveillance data for 1984-2012. Negative binomial regression with five previously validated predictors (including predicted mosquito abundance and predictors based on local weather data) was used to model the annual number of tularemia cases within the high-risk regions. Seven high-risk regions were identified with annual incidences of 3·8-44 cases/100 000 inhabitants, accounting for 56·4% of the tularemia cases but only 9·3% of Sweden's population. For all high-risk regions, most cases occurred between July and September. The regression models explained the annual variation of tularemia cases within most high-risk regions and discriminated between years with and without outbreaks. In conclusion, tularemia in Sweden is concentrated in a few high-risk regions and shows high annual and seasonal variations. We present reproducible methods for identifying tularemia high-risk regions and modelling tularemia cases within these regions. The results may help health authorities to target populations at risk and lay the foundation for developing an early warning system for outbreaks.

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

Using Financial Ratios to Select Companies for Tax Auditing: A Preliminary Study

NASA Astrophysics Data System (ADS)

Marghescu, Dorina; Kallio, Minna; Back, Barbro

Tax auditing procedures include an investigation of the accounting records of a company and of other sources of information in order to assess whether the taxation has been based on correct and complete information. When there are found discrepancies between the accounting information and the real situation, the taxation should be corrected so that the eventual tax defaults are assessed and debited. The paper analyzes to what extent the financial performance of a company can be used as an indicator of tax defaults. We focus on one type of tax, namely employer's contribution, and four financial ratios. We evaluate the model in a study of Finnish companies by using a binomial logistic regression analysis. The study is exploratory and at a preliminary stage.

Spatiotemporal analysis of the relationship between socioeconomic factors and stroke in the Portuguese mainland population under 65 years old.

PubMed

Oliveira, André; Cabral, António J R; Mendes, Jorge M; Martins, Maria R O; Cabral, Pedro

2015-11-04

Stroke risk has been shown to display varying patterns of geographic distribution amongst countries but also between regions of the same country. Traditionally a disease of older persons, a global 25% increase in incidence instead was noticed between 1990 and 2010 in persons aged 20-≤64 years, particularly in low- and medium-income countries. Understanding spatial disparities in the association between socioeconomic factors and stroke is critical to target public health initiatives aiming to mitigate or prevent this disease, including in younger persons. We aimed to identify socioeconomic determinants of geographic disparities of stroke risk in people <65 years old, in municipalities of mainland Portugal, and the spatiotemporal variation of the association between these determinants and stroke risk during two study periods (1992-1996 and 2002-2006). Poisson and negative binomial global regression models were used to explore determinants of disease risk. Geographically weighted regression (GWR) represents a distinctive approach, allowing estimation of local regression coefficients. Models for both study periods were identified. Significant variables included education attainment, work hours per week and unemployment. Local Poisson GWR models achieved the best fit and evidenced spatially varying regression coefficients. Spatiotemporal inequalities were observed in significant variables, with dissimilarities between men and women. This study contributes to a better understanding of the relationship between stroke and socioeconomic factors in the population <65 years of age, one age group seldom analysed separately. It can thus help to improve the targeting of public health initiatives, even more in a context of economic crisis.

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.

Period prevalence and factors associated with road traffic crashes among young adults in Kuwait.

PubMed

Aldhafeeri, Eisa; Alshammari, Farah; Jafar, Hana; Malhas, Haya; Botras, Marina; Alnasrallah, Noor; Akhtar, Saeed

2018-05-01

This cross-sectional study assessed one-year period prevalence of road traffic crashes (RTCs) and examined the factors associated with RTCs among young adults in Kuwait. During December 2016, 1500 students enrolled in 15 colleges of Kuwait University were invited to participate in the study. Students 18 years old or older and who drive by themselves were eligible. Data were collected using a structured self-administered questionnaire. One-year period prevalence of RTCs (≥1 vs. none) was computed. Multivariable log-binomial regression model was used to identify the risk factors associated with one-year period prevalence of RTCs. Of 1500 invited individuals, 1465 (97.7%) participated, of which 71.4% (1046/1465) were female, 56.4% (804/1426) were aged between 21 and 25 years, and 67.1% (980/1460) were Kuwaitis. One-year period prevalence of RTC was 38.9%. The final multivariable log-binomial regression model showed that after adjusting for the influences of other variables in the model, participants were more likely to have had at least one RTC during the past year, if they habitually sped over limit (adjusted PR = 1.19; 95% confidence interval (CI): 1.04-1.36), crossed a red light (adjusted PR = 1.33; 95% CI: 1.16-1.52), or if they have had three or more speeding tickets (adjusted PR = 1.40; 95% CI: 1.13-1.73) compared to those who reportedly had no RTC during the same period. One-year period prevalence of RTCs among university students in Kuwait, though relatively lower than the reported figures in similar populations elsewhere in the region, is yet high enough to warrant diligent attention. Habitual speeding, having had three or more speeding tickets, and the practice of crossing a red light were significantly and independently associated with at least one RTC during the past year. Targeted education and enforcement of existing traffic laws may reduce the RTCs frequency in this relatively young population. Future studies may look at impact of such interventions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Effects of health intervention programs and arsenic exposure on child mortality from acute lower respiratory infections in rural Bangladesh.

PubMed

Jochem, Warren C; Razzaque, Abdur; Root, Elisabeth Dowling

2016-09-01

Respiratory infections continue to be a public health threat, particularly to young children in developing countries. Understanding the geographic patterns of diseases and the role of potential risk factors can help improve future mitigation efforts. Toward this goal, this paper applies a spatial scan statistic combined with a zero-inflated negative-binomial regression to re-examine the impacts of a community-based treatment program on the geographic patterns of acute lower respiratory infection (ALRI) mortality in an area of rural Bangladesh. Exposure to arsenic-contaminated drinking water is also a serious threat to the health of children in this area, and the variation in exposure to arsenic must be considered when evaluating the health interventions. ALRI mortality data were obtained for children under 2 years old from 1989 to 1996 in the Matlab Health and Demographic Surveillance System. This study period covers the years immediately following the implementation of an ALRI control program. A zero-inflated negative binomial (ZINB) regression model was first used to simultaneously estimate mortality rates and the likelihood of no deaths in groups of related households while controlling for socioeconomic status, potential arsenic exposure, and access to care. Next a spatial scan statistic was used to assess the location and magnitude of clusters of ALRI mortality. The ZINB model was used to adjust the scan statistic for multiple social and environmental risk factors. The results of the ZINB models and spatial scan statistic suggest that the ALRI control program was successful in reducing child mortality in the study area. Exposure to arsenic-contaminated drinking water was not associated with increased mortality. Higher socioeconomic status also significantly reduced mortality rates, even among households who were in the treatment program area. Community-based ALRI interventions can be effective at reducing child mortality, though socioeconomic factors may continue to influence mortality patterns. The combination of spatial and non-spatial methods used in this paper has not been applied previously in the literature, and this study demonstrates the importance of such approaches for evaluating and improving public health intervention programs.

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.

Relationship between suicide rate and economic growth and stock market in the People's Republic of China: 2004-2013.

PubMed

Yin, Honglei; Xu, Lin; Shao, Yechang; Li, Liping; Wan, Chengsong

2016-01-01

The objective of this study was to estimate the features of suicide rate and its association with economic development and stock market during the past decade in the People's Republic of China. Official data were gathered and analyzed in the People's Republic of China during the period 2004-2013. Nationwide suicide rate was stratified by four year age-groups, sex, urban/rural areas, and regions (East, Central, and West). Annual economic indexes including gross domestic product (GDP) per capita and rural and urban income per capita were all adjusted for inflation. Variation coefficient of market index (VCMI) was also included as an economic index to measure the fluctuation of the stock market. Negative binomial regression was performed to examine the time trend of region-level suicide rates and effects of sex, age, urban/rural area, region, and economic index on the suicide rates. Suicide rates of each age-group, sex, urban/rural area, and region were generally decreased from 2004 to 2013, while annual GDP per capita and rural and urban income per capita were generally increased by year. VCMI fluctuated largely, which peaked around 2009 and decreased after that time. Negative binomial regression showed that the decreased suicide rate in East and Central rural areas was the main cause of the decrease in suicide rate in the People's Republic of China. Suicide rate in the People's Republic of China for the study period increased with age and was higher in rural than in urban area, higher in males than in females, and the highest in the Central region. When GDP per capita increased by 2,787 RMB, the suicide rate decreased by 0.498 times. VCMI showed no significant relationship with suicide rate in the negative binomial regression. Suicide rate decreased in 2004-2013; varied among different age-groups, sex, urban/rural areas, and regions; and was negatively associated with the economic growth in the People's Republic of China. Stock market showed no relationship with suicide rate, but this finding needs to be verified in a future study.

Relationship between suicide rate and economic growth and stock market in the People’s Republic of China: 2004–2013

PubMed Central

Yin, Honglei; Xu, Lin; Shao, Yechang; Li, Liping; Wan, Chengsong

2016-01-01

Objectives The objective of this study was to estimate the features of suicide rate and its association with economic development and stock market during the past decade in the People’s Republic of China. Methods Official data were gathered and analyzed in the People’s Republic of China during the period 2004–2013. Nationwide suicide rate was stratified by four year age-groups, sex, urban/rural areas, and regions (East, Central, and West). Annual economic indexes including gross domestic product (GDP) per capita and rural and urban income per capita were all adjusted for inflation. Variation coefficient of market index (VCMI) was also included as an economic index to measure the fluctuation of the stock market. Negative binomial regression was performed to examine the time trend of region-level suicide rates and effects of sex, age, urban/rural area, region, and economic index on the suicide rates. Results Suicide rates of each age-group, sex, urban/rural area, and region were generally decreased from 2004 to 2013, while annual GDP per capita and rural and urban income per capita were generally increased by year. VCMI fluctuated largely, which peaked around 2009 and decreased after that time. Negative binomial regression showed that the decreased suicide rate in East and Central rural areas was the main cause of the decrease in suicide rate in the People’s Republic of China. Suicide rate in the People’s Republic of China for the study period increased with age and was higher in rural than in urban area, higher in males than in females, and the highest in the Central region. When GDP per capita increased by 2,787 RMB, the suicide rate decreased by 0.498 times. VCMI showed no significant relationship with suicide rate in the negative binomial regression. Conclusion Suicide rate decreased in 2004–2013; varied among different age-groups, sex, urban/rural areas, and regions; and was negatively associated with the economic growth in the People’s Republic of China. Stock market showed no relationship with suicide rate, but this finding needs to be verified in a future study. PMID:27994468

Estimating the Prevalence of Atrial Fibrillation from A Three-Class Mixture Model for Repeated Diagnoses

PubMed Central

Li, Liang; Mao, Huzhang; Ishwaran, Hemant; Rajeswaran, Jeevanantham; Ehrlinger, John; Blackstone, Eugene H.

2016-01-01

Atrial fibrillation (AF) is an abnormal heart rhythm characterized by rapid and irregular heart beat, with or without perceivable symptoms. In clinical practice, the electrocardiogram (ECG) is often used for diagnosis of AF. Since the AF often arrives as recurrent episodes of varying frequency and duration and only the episodes that occur at the time of ECG can be detected, the AF is often underdiagnosed when a limited number of repeated ECGs are used. In studies evaluating the efficacy of AF ablation surgery, each patient undergo multiple ECGs and the AF status at the time of ECG is recorded. The objective of this paper is to estimate the marginal proportions of patients with or without AF in a population, which are important measures of the efficacy of the treatment. The underdiagnosis problem is addressed by a three-class mixture regression model in which a patient’s probability of having no AF, paroxysmal AF, and permanent AF is modeled by auxiliary baseline covariates in a nested logistic regression. A binomial regression model is specified conditional on a subject being in the paroxysmal AF group. The model parameters are estimated by the EM algorithm. These parameters are themselves nuisance parameters for the purpose of this research, but the estimators of the marginal proportions of interest can be expressed as functions of the data and these nuisance parameters and their variances can be estimated by the sandwich method. We examine the performance of the proposed methodology in simulations and two real data applications. PMID:27983754

Estimating the prevalence of atrial fibrillation from a three-class mixture model for repeated diagnoses.

PubMed

Li, Liang; Mao, Huzhang; Ishwaran, Hemant; Rajeswaran, Jeevanantham; Ehrlinger, John; Blackstone, Eugene H

2017-03-01

Atrial fibrillation (AF) is an abnormal heart rhythm characterized by rapid and irregular heartbeat, with or without perceivable symptoms. In clinical practice, the electrocardiogram (ECG) is often used for diagnosis of AF. Since the AF often arrives as recurrent episodes of varying frequency and duration and only the episodes that occur at the time of ECG can be detected, the AF is often underdiagnosed when a limited number of repeated ECGs are used. In studies evaluating the efficacy of AF ablation surgery, each patient undergoes multiple ECGs and the AF status at the time of ECG is recorded. The objective of this paper is to estimate the marginal proportions of patients with or without AF in a population, which are important measures of the efficacy of the treatment. The underdiagnosis problem is addressed by a three-class mixture regression model in which a patient's probability of having no AF, paroxysmal AF, and permanent AF is modeled by auxiliary baseline covariates in a nested logistic regression. A binomial regression model is specified conditional on a subject being in the paroxysmal AF group. The model parameters are estimated by the Expectation-Maximization (EM) algorithm. These parameters are themselves nuisance parameters for the purpose of this research, but the estimators of the marginal proportions of interest can be expressed as functions of the data and these nuisance parameters and their variances can be estimated by the sandwich method. We examine the performance of the proposed methodology in simulations and two real data applications. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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.

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.

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.

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.

M5 model tree based predictive modeling of road accidents on non-urban sections of highways in India.

PubMed

Singh, Gyanendra; Sachdeva, S N; Pal, Mahesh

2016-11-01

This work examines the application of M5 model tree and conventionally used fixed/random effect negative binomial (FENB/RENB) regression models for accident prediction on non-urban sections of highway in Haryana (India). Road accident data for a period of 2-6 years on different sections of 8 National and State Highways in Haryana was collected from police records. Data related to road geometry, traffic and road environment related variables was collected through field studies. Total two hundred and twenty two data points were gathered by dividing highways into sections with certain uniform geometric characteristics. For prediction of accident frequencies using fifteen input parameters, two modeling approaches: FENB/RENB regression and M5 model tree were used. Results suggest that both models perform comparably well in terms of correlation coefficient and root mean square error values. M5 model tree provides simple linear equations that are easy to interpret and provide better insight, indicating that this approach can effectively be used as an alternative to RENB approach if the sole purpose is to predict motor vehicle crashes. Sensitivity analysis using M5 model tree also suggests that its results reflect the physical conditions. Both models clearly indicate that to improve safety on Indian highways minor accesses to the highways need to be properly designed and controlled, the service roads to be made functional and dispersion of speeds is to be brought down. Copyright © 2016 Elsevier Ltd. All rights reserved.

The relationship between non-communicable disease occurrence and poverty-evidence from demographic surveillance in Matlab, Bangladesh.

PubMed

Mirelman, Andrew J; Rose, Sherri; Khan, Jahangir Am; Ahmed, Sayem; Peters, David H; Niessen, Louis W; Trujillo, Antonio J

2016-07-01

In low-income countries, a growing proportion of the disease burden is attributable to non-communicable diseases (NCDs). There is little knowledge, however, of their impact on wealth, human capital, economic growth or household poverty. This article estimates the risk of being poor after an NCD death in the rural, low-income area of Matlab, Bangladesh. In a matched cohort study, we estimated the 2-year relative risk (RR) of being poor in Matlab households with an NCD death in 2010. Three separate measures of household economic status were used as outcomes: an asset-based index, self-rated household economic condition and total household landholding. Several estimation methods were used including contingency tables, log-binomial regression and regression standardization and machine learning. Households with an NCD death had a large and significant risk of being poor. The unadjusted RR of being poor after death was 1.19, 1.14 and 1.10 for the asset quintile, self-rated condition and landholding outcomes. Adjusting for household and individual level independent variables with log-binomial regression gave RRs of 1.19 [standard error (SE) 0.09], 1.16 (SE 0.07) and 1.14 (SE 0.06), which were found to be exactly the same using regression standardization (SE: 0.09, 0.05, 0.03). Machine learning-based standardization produced slightly smaller RRs though still in the same order of magnitude. The findings show that efforts to address the burden of NCD may also combat household poverty and provide a return beyond improved health. Future work should attempt to disentangle the mechanisms through which economic impacts from an NCD death occur. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.

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.

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

A Stab in the Dark?: A Research Note on Temporal Patterns of Street Robbery.

PubMed

Tompson, Lisa; Bowers, Kate

2013-11-01

Test the influence of darkness in the street robbery crime event alongside temperature. Negative binomial regression models tested darkness and temperature as predictors of street robbery. Units of analysis were four 6-hr time intervals in two U.K. study areas that have different levels of darkness and variations of temperature throughout the year. Darkness is a key factor related to robbery events in both study areas. Traversing from full daylight to full darkness increased the predicted volume of robbery by a multiple of 2.6 in London and 1.2 in Glasgow. Temperature was significant only in the London study area. Interaction terms did not enhance the predictive power of the models. Darkness is an important driving factor in seasonal variation of street robbery. A further implication of the research is that time of the day patterns are crucial to understanding seasonal trends in crime data.

Older driver fitness-to-drive evaluation using naturalistic driving data.

PubMed

Guo, Feng; Fang, Youjia; Antin, Jonathan F

2015-09-01

As our driving population continues to age, it is becoming increasingly important to find a small set of easily administered fitness metrics that can meaningfully and reliably identify at-risk seniors requiring more in-depth evaluation of their driving skills and weaknesses. Sixty driver assessment metrics related to fitness-to-drive were examined for 20 seniors who were followed for a year using the naturalistic driving paradigm. Principal component analysis and negative binomial regression modeling approaches were used to develop parsimonious models relating the most highly predictive of the driver assessment metrics to the safety-related outcomes observed in the naturalistic driving data. This study provides important confirmation using naturalistic driving methods of the relationship between contrast sensitivity and crash-related events. The results of this study provide crucial information on the continuing journey to identify metrics and protocols that could be applied to determine seniors' fitness to drive. Published by Elsevier Ltd.

Influenza vaccine coverage, influenza-associated morbidity and all-cause mortality in Catalonia (Spain).

PubMed

Muñoz, M Pilar; Soldevila, Núria; Martínez, Anna; Carmona, Glòria; Batalla, Joan; Acosta, Lesly M; Domínguez, Angela

2011-07-12

The objective of this work was to study the behaviour of influenza with respect to morbidity and all-cause mortality in Catalonia, and their association with influenza vaccination coverage. The study was carried out over 13 influenza seasons, from epidemiological week 40 of 1994 to week 20 of 2007, and included confirmed cases of influenza and all-cause mortality. Two generalized linear models were fitted: influenza-associated morbidity was modelled by Poisson regression and all-cause mortality by negative binomial regression. The seasonal component was modelled with the periodic function formed by the sum of the sinus and cosines. Expected influenza mortality during periods of influenza virus circulation was estimated by Poisson regression and its confidence intervals using the Bootstrap approach. Vaccination coverage was associated with a reduction in influenza-associated morbidity (p<0.001), but not with a reduction in all-cause mortality (p=0.149). In the case of influenza-associated morbidity, an increase of 5% in vaccination coverage represented a reduction of 3% in the incidence rate of influenza. There was a positive association between influenza-associated morbidity and all-cause mortality. Excess mortality attributable to influenza epidemics was estimated as 34.4 (95% CI: 28.4-40.8) weekly deaths. In conclusion, all-cause mortality is a good indicator of influenza surveillance and vaccination coverage is associated with a reduction in influenza-associated morbidity but not with all-cause mortality. Copyright © 2011 Elsevier Ltd. All rights reserved.

Consideration of species community composition in statistical ...

EPA Pesticide Factsheets

Diseases are increasing in marine ecosystems, and these increases have been attributed to a number of environmental factors including climate change, pollution, and overfishing. However, many studies pool disease prevalence into taxonomic groups, disregarding host species composition when comparing sites or assessing environmental impacts on patterns of disease presence. We used simulated data under a known environmental effect to assess the ability of standard statistical methods (binomial and linear regression, ANOVA) to detect a significant environmental effect on pooled disease prevalence with varying species abundance distributions and relative susceptibilities to disease. When one species was more susceptible to a disease and both species only partially overlapped in their distributions, models tended to produce a greater number of false positives (Type I error). Differences in disease risk between regions or along an environmental gradient tended to be underestimated, or even in the wrong direction, when highly susceptible taxa had reduced abundances in impacted sites, a situation likely to be common in nature. Including relative abundance as an additional variable in regressions improved model accuracy, but tended to be conservative, producing more false negatives (Type II error) when species abundance was strongly correlated with the environmental effect. Investigators should be cautious of underlying assumptions of species similarity in susceptib

Maternal Early Life Factors Associated with Hormone Levels and the Risk of Having a Child with an Autism Spectrum Disorder in the Nurses Health Study II

ERIC Educational Resources Information Center

Lyall, Kristen; Pauls, David L.; Santangelo, Susan; Spiegelman, Donna; Ascherio, Alberto

2011-01-01

It is not known whether reproductive factors early in the mother's life influence risk of autism spectrum disorders (ASD). We assessed maternal age at menarche, menstrual cycle characteristics during adolescence, oral contraceptive use prior to first birth, body shape, and body mass index (BMI) in association with ASD using binomial regression in…

Factors Associated with Hospital Length of Stay among Cancer Patients with Febrile Neutropenia

PubMed Central

Rosa, Regis G.; Goldani, Luciano Z.

2014-01-01

Purpose This study sought to evaluate factors associated with hospital length of stay in cancer patients with febrile neutropenia. Methods A prospective cohort study was performed at a single tertiary referral hospital in southern Brazil from October 2009 to August 2011. All adult cancer patients with febrile neutropenia admitted to the hematology ward were evaluated. Stepwise random-effects negative binomial regression was performed to identify risk factors for prolonged length of hospital stay. Results In total, 307 cases of febrile neutropenia were evaluated. The overall median length of hospital stay was 16 days (interquartile range 18 days). According to multiple negative binomial regression analysis, hematologic neoplasms (P = 0.003), high-dose chemotherapy regimens (P<0.001), duration of neutropenia (P<0.001), and bloodstream infection involving Gram-negative multi-drug-resistant bacteria (P = 0.003) were positively associated with prolonged hospital length of stay in patients with febrile neutropenia. The condition index showed no evidence of multi-collinearity effect among the independent variables. Conclusions Hematologic neoplasms, high-dose chemotherapy regimens, prolonged periods of neutropenia, and bloodstream infection with Gram-negative multi-drug-resistant bacteria are predictors of prolonged length hospital of stay among adult cancer patients with febrile neutropenia. PMID:25285790

Trends in incidence of occupational asthma, contact dermatitis, noise-induced hearing loss, carpal tunnel syndrome and upper limb musculoskeletal disorders in European countries from 2000 to 2012.

PubMed

Stocks, S Jill; McNamee, Roseanne; van der Molen, Henk F; Paris, Christophe; Urban, Pavel; Campo, Giuseppe; Sauni, Riitta; Martínez Jarreta, Begoña; Valenty, Madeleine; Godderis, Lode; Miedinger, David; Jacquetin, Pascal; Gravseth, Hans M; Bonneterre, Vincent; Telle-Lamberton, Maylis; Bensefa-Colas, Lynda; Faye, Serge; Mylle, Godewina; Wannag, Axel; Samant, Yogindra; Pal, Teake; Scholz-Odermatt, Stefan; Papale, Adriano; Schouteden, Martijn; Colosio, Claudio; Mattioli, Stefano; Agius, Raymond

2015-04-01

The European Union (EU) strategy for health and safety at work underlines the need to reduce the incidence of occupational diseases (OD), but European statistics to evaluate this common goal are scarce. We aim to estimate and compare changes in incidence over time for occupational asthma, contact dermatitis, noise-induced hearing loss (NIHL), carpal tunnel syndrome (CTS) and upper limb musculoskeletal disorders across 10 European countries. OD surveillance systems that potentially reflected nationally representative trends in incidence within Belgium, the Czech Republic, Finland, France, Italy, the Netherlands, Norway, Spain, Switzerland and the UK provided data. Case counts were analysed using a negative binomial regression model with year as the main covariate. Many systems collected data from networks of 'centres', requiring the use of a multilevel negative binomial model. Some models made allowance for changes in compensation or reporting rules. Reports of contact dermatitis and asthma, conditions with shorter time between exposure to causal substances and OD, were consistently declining with only a few exceptions. For OD with physical causal exposures there was more variation between countries. Reported NIHL was increasing in Belgium, Spain, Switzerland and the Netherlands and decreasing elsewhere. Trends in CTS and upper limb musculoskeletal disorders varied widely within and between countries. This is the first direct comparison of trends in OD within Europe and is consistent with a positive impact of European initiatives addressing exposures relevant to asthma and contact dermatitis. Taking a more flexible approach allowed comparisons of surveillance data between and within countries without harmonisation of data collection methods. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Applying quantile regression for modeling equivalent property damage only crashes to identify accident blackspots.

PubMed

Washington, Simon; Haque, Md Mazharul; Oh, Jutaek; Lee, Dongmin

2014-05-01

Hot spot identification (HSID) aims to identify potential sites-roadway segments, intersections, crosswalks, interchanges, ramps, etc.-with disproportionately high crash risk relative to similar sites. An inefficient HSID methodology might result in either identifying a safe site as high risk (false positive) or a high risk site as safe (false negative), and consequently lead to the misuse the available public funds, to poor investment decisions, and to inefficient risk management practice. Current HSID methods suffer from issues like underreporting of minor injury and property damage only (PDO) crashes, challenges of accounting for crash severity into the methodology, and selection of a proper safety performance function to model crash data that is often heavily skewed by a preponderance of zeros. Addressing these challenges, this paper proposes a combination of a PDO equivalency calculation and quantile regression technique to identify hot spots in a transportation network. In particular, issues related to underreporting and crash severity are tackled by incorporating equivalent PDO crashes, whilst the concerns related to the non-count nature of equivalent PDO crashes and the skewness of crash data are addressed by the non-parametric quantile regression technique. The proposed method identifies covariate effects on various quantiles of a population, rather than the population mean like most methods in practice, which more closely corresponds with how black spots are identified in practice. The proposed methodology is illustrated using rural road segment data from Korea and compared against the traditional EB method with negative binomial regression. Application of a quantile regression model on equivalent PDO crashes enables identification of a set of high-risk sites that reflect the true safety costs to the society, simultaneously reduces the influence of under-reported PDO and minor injury crashes, and overcomes the limitation of traditional NB model in dealing with preponderance of zeros problem or right skewed dataset. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

Measuring women's cumulative neighborhood deprivation exposure using longitudinally linked vital records: a method for life course MCH research.

PubMed

Kramer, Michael R; Dunlop, Anne L; Hogue, Carol J R

2014-02-01

A life course conceptual framework for MCH research demands new tools for understanding population health and measuring exposures. We propose a method for measuring population-based socio-environmental trajectories for women of reproductive age. We merged maternal longitudinally-linked births to Georgia-resident women from 1994 to 2007 with census economic and social measures using residential geocodes to create woman-centered socio-environmental trajectories. We calculated a woman's neighborhood deprivation index (NDI) at the time of each of her births and, from these, we calculated a cumulative NDI. We fit Loess curves to describe average life course NDI trajectories and binomial regression models to test specific life course theory hypotheses relating cumulative NDI to risk for preterm birth. Of the 1,815,944 total live births, we linked 1,000,437 live births to 413,048 unique women with two or more births. Record linkage had high specificity but relatively low sensitivity which appears non-differential with respect to maternal characteristics. Georgia women on average experienced upward mobility across the life course, although differences by race, early life neighborhood quality, and age at first birth produced differences in cumulative NDI. Adjusted binomial models found evidence for modification of the effect of history of prior preterm birth and advancing age on risk for preterm birth by cumulative NDI. The creation of trajectories from geocoded maternal longitudinally-linked vital records is one method to carry out life course MCH research. We discuss approaches for investigating the impact of truncation of the life course, selection bias from migration, and misclassification of cumulative exposure.

Crime Seasonality: Examining the Temporal Fluctuations of Property Crime in Cities With Varying Climates.

PubMed

Linning, Shannon J; Andresen, Martin A; Brantingham, Paul J

2017-12-01

This study investigates whether crime patterns fluctuate periodically throughout the year using data containing different property crime types in two Canadian cities with differing climates. Using police report data, a series of ordinary least squares (OLS; Vancouver, British Columbia) and negative binomial (Ottawa, Ontario) regressions were employed to examine the corresponding temporal patterns of property crime in Vancouver (2003-2013) and Ottawa (2006-2008). Moreover, both aggregate and disaggregate models were run to examine whether different weather and temporal variables had a distinctive impact on particular offences. Overall, results suggest that cities that experience greater variations in weather throughout the year have more distinct increases of property offences in the summer months and that different climate variables affect certain crime types, thus advocating for disaggregate analysis in the future.

Linking crime guns: the impact of ballistics imaging technology on the productivity of the Boston Police Department's Ballistics Unit.

PubMed

Braga, Anthony A; Pierce, Glenn L

2004-07-01

Ballistics imaging technology has received national attention as a potent tool for moving the law enforcement response to violent gun criminals forward by linking multiple crime scenes to one firearm. This study examines the impact of ballistics imaging technology on the productivity of the Boston Police Department's Ballistics Unit. Using negative binomial regression models to analyze times series data on ballistics matches, we find that ballistics imaging technology was associated with a more than sixfold increase in the monthly number of ballistics matches made by the Boston Police Department's Ballistics Unit. Cost-effectiveness estimates and qualitative evidence also suggest that ballistics imaging technology allows law enforcement agencies to make hits that would not have been possible using traditional ballistics methods.

Unmarried Mothers’ Postnatal School Enrollment: The Role and Intersection of Demographic and Socioeconomic Characteristics

PubMed Central

Radey, Melissa

2017-01-01

Drawing from a theoretical model of educational decisions and intersectionality theory, this study examined demographic, socioeconomic, and public assistance characteristics that influence unmarried mothers’ postnatal enrollment. Using the Fragile Families and Child Wellbeing Study (FFCWS), binomial and multinomial regression techniques were used to examine unmarried mothers’ enrollment in their child’s first nine years. Results showed unmarried mothers’ educational commitment coupled with the influence of race and class indicate that they need additional opportunities to optimize their educations and job opportunities. Targeting outreach and enrollment assistance to underrepresented groups can reduce social-origin inequalities. Important directions for future research include understanding unmarried mothers’ rationale for school enrollment and considering how race and class work in combination to support or deter enrollment. PMID:29151656

Civic communities and urban violence.

PubMed

Doucet, Jessica M; Lee, Matthew R

2015-07-01

Civic communities have a spirit of entrepreneurialism, a locally invested population and an institutional structure fostering civic engagement. Prior research, mainly confined to studying rural communities and fairly large geographic areas, has demonstrated that civic communities have lower rates of violence. The current study analyzes the associations between the components of civic communities and homicide rates for New Orleans neighborhoods (census tracts) in the years following Hurricane Katrina. Results from negative binomial regression models adjusting for spatial autocorrelation reveal that community homicide rates are lower where an entrepreneurial business climate is more pronounced and where there is more local investment. Additionally, an interaction between the availability of civic institutions and resource disadvantage reveals that the protective effects of civic institutions are only evident in disadvantaged communities. Copyright © 2015 Elsevier Inc. All rights reserved.

Infant Mortality and Income in 4 World Cities: New York, London, Paris, and Tokyo

PubMed Central

Rodwin, Victor G.; Neuberg, Leland G.

2005-01-01

Objectives. We investigated the association between average income or deprivation and infant mortality rate across neighborhoods of 4 world cities. Methods. Using a maximum likelihood negative binomial regression model that controls for births, we analyzed data for 1988–1992 and 1993–1997. Results. In Manhattan, for both periods, we found an association (.05% significance level) between income and infant mortality. In Tokyo, for both periods, and in Paris and London for period 1, we found none (5% significance level). For period 2, the association just missed statistical significance for Paris, whereas for London it was significant (5% level). Conclusions. In stark contrast to Tokyo, Paris, and London, the association of income and infant mortality rate was strongly evident in Manhattan. PMID:15623865

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.

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 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.

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.

[Determinants of health care utilization in Costa Rica].

PubMed

Morera Salas, Melvin; Aparicio Llanos, Amada

2010-01-01

To analyze the determinants of health care utilization (visits to the doctor) in Costa Rica using an econometric approach. Data were drawn from the National Survey of Health for Costa Rica 2006. We modeled the Grossman approach to the demand for health services by using a standard negative binomial regression, and used a hurdle model for the principal-agent specification. The factors determining healthcare utilization were level of education, self-assessed health, number of declared chronic diseases and geographic region of residence. The number of outpatient visits to the doctor depends on the proxies for medical need, but we found no multivariate association between the use of outpatient visits and income or insurance status. This result suggests that there is no problem with access in the public - almost universal - Costa Rican health system. No conclusive results were obtained on the influence of the physician on the frequency of use of health care services, as postulated by the principal-agent model. Copyright © 2010 SESPAS. Published by Elsevier Espana. All rights reserved.

Statistical inference involving binomial and negative binomial parameters.

PubMed

García-Pérez, Miguel A; Núñez-Antón, Vicente

2009-05-01

Statistical inference about two binomial parameters implies that they are both estimated by binomial sampling. There are occasions in which one aims at testing the equality of two binomial parameters before and after the occurrence of the first success along a sequence of Bernoulli trials. In these cases, the binomial parameter before the first success is estimated by negative binomial sampling whereas that after the first success is estimated by binomial sampling, and both estimates are related. This paper derives statistical tools to test two hypotheses, namely, that both binomial parameters equal some specified value and that both parameters are equal though unknown. Simulation studies are used to show that in small samples both tests are accurate in keeping the nominal Type-I error rates, and also to determine sample size requirements to detect large, medium, and small effects with adequate power. Additional simulations also show that the tests are sufficiently robust to certain violations of their assumptions.

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.

Racial/Ethnic Differences in Expectations Regarding Aging Among Older Adults.

PubMed

Menkin, Josephine A; Guan, Shu-Sha Angie; Araiza, Daniel; Reyes, Carmen E; Trejo, Laura; Choi, Sarah E; Willis, Phyllis; Kotick, John; Jimenez, Elizabeth; Ma, Sina; McCreath, Heather E; Chang, Emiley; Witarama, Tuff; Sarkisian, Catherine A

2017-08-01

The study identifies differences in age-expectations between older adults from Korean, Chinese, Latino, and African American backgrounds living in the United States. This study uses baseline demographic, age-expectation, social, and health data from 229 racial/ethnic minority seniors in a stroke-prevention intervention trial. Unadjusted regression models and pair-wise comparisons tested for racial/ethnic differences in age-expectations, overall, and across domain subscales (e.g., physical-health expectations). Adjusted regression models tested whether age-expectations differed across racial/ethnic groups after controlling for demographic, social, and health variables. Regression and negative binomial models tested whether age-expectations were consistently associated with health and well-being across racial/ethnic groups. Age-expectations differed by race/ethnicity, overall and for each subscale. African American participants expected the least age-related functional decline and Chinese American participants expected the most decline. Although African American participants expected less decline than Latino participants in unadjusted models, they had comparable expectations adjusting for education. Latino and African American participants consistently expected less decline than Korean and Chinese Americans. Acculturation was not consistently related to age-expectations among immigrant participants over and above ethnicity. Although some previously observed links between expectations and health replicated across racial/ethnic groups, in adjusted models age-expectations were only related to depression for Latino participants. With a growing racial/ethnic minority older population in the United States, it is important to note older adults' age-expectations differ by race/ethnicity. Moreover, expectation-health associations may not always generalize across diverse samples. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Modeling the effects of AADT on predicting multiple-vehicle crashes at urban and suburban signalized intersections.

PubMed

Chen, Chen; Xie, Yuanchang

2016-06-01

Annual Average Daily Traffic (AADT) is often considered as a main covariate for predicting crash frequencies at urban and suburban intersections. A linear functional form is typically assumed for the Safety Performance Function (SPF) to describe the relationship between the natural logarithm of expected crash frequency and covariates derived from AADTs. Such a linearity assumption has been questioned by many researchers. This study applies Generalized Additive Models (GAMs) and Piecewise Linear Negative Binomial (PLNB) regression models to fit intersection crash data. Various covariates derived from minor-and major-approach AADTs are considered. Three different dependent variables are modeled, which are total multiple-vehicle crashes, rear-end crashes, and angle crashes. The modeling results suggest that a nonlinear functional form may be more appropriate. Also, the results show that it is important to take into consideration the joint safety effects of multiple covariates. Additionally, it is found that the ratio of minor to major-approach AADT has a varying impact on intersection safety and deserves further investigations. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

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.

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.

Loneliness as a public health issue: the impact of loneliness on health care utilization among older adults.

PubMed

Gerst-Emerson, Kerstin; Jayawardhana, Jayani

2015-05-01

We aimed to determine whether loneliness is associated with higher health care utilization among older adults in the United States. We used panel data from the Health and Retirement Study (2008 and 2012) to examine the long-term impact of loneliness on health care use. The sample was limited to community-dwelling persons in the United States aged 60 years and older. We used negative binomial regression models to determine the impact of loneliness on physician visits and hospitalizations. Under 2 definitions of loneliness, we found that a sizable proportion of those aged 60 years and older in the United States reported loneliness. Regression results showed that chronic loneliness (those lonely both in 2008 and 4 years later) was significantly and positively associated with physician visits (β = 0.075, SE = 0.034). Loneliness was not significantly associated with hospitalizations. Loneliness is a significant public health concern among elders. In addition to easing a potential source of suffering, the identification and targeting of interventions for lonely elders may significantly decrease physician visits and health care costs.

Contributory factors to traffic crashes at signalized intersections in Hong Kong.

PubMed

Wong, S C; Sze, N N; Li, Y C

2007-11-01

Efficient geometric design and signal timing not only improve operational performance at signalized intersections by expanding capacity and reducing traffic delays, but also result in an appreciable reduction in traffic conflicts, and thus better road safety. Information on the incidence of crashes, traffic flow, geometric design, road environment, and traffic control at 262 signalized intersections in Hong Kong during 2002 and 2003 are incorporated into a crash prediction model. Poisson regression and negative binomial regression are used to quantify the influence of possible contributory factors on the incidence of killed and severe injury (KSI) crashes and slight injury crashes, respectively, while possible interventions by traffic flow are controlled. The results for the incidence of slight injury crashes reveal that the road environment, degree of curvature, and presence of tram stops are significant factors, and that traffic volume has a diminishing effect on the crash risk. The presence of tram stops, number of pedestrian streams, road environment, proportion of commercial vehicles, average lane width, and degree of curvature increase the risk of KSI crashes, but the effect of traffic volume is negligible.

Statistical guides to estimating the number of undiscovered mineral deposits: an example with porphyry copper deposits

USGS Publications Warehouse

Singer, Donald A.; Menzie, W.D.; Cheng, Qiuming; Bonham-Carter, G. F.

2005-01-01

Estimating numbers of undiscovered mineral deposits is a fundamental part of assessing mineral resources. Some statistical tools can act as guides to low variance, unbiased estimates of the number of deposits. The primary guide is that the estimates must be consistent with the grade and tonnage models. Another statistical guide is the deposit density (i.e., the number of deposits per unit area of permissive rock in well-explored control areas). Preliminary estimates and confidence limits of the number of undiscovered deposits in a tract of given area may be calculated using linear regression and refined using frequency distributions with appropriate parameters. A Poisson distribution leads to estimates having lower relative variances than the regression estimates and implies a random distribution of deposits. Coefficients of variation are used to compare uncertainties of negative binomial, Poisson, or MARK3 empirical distributions that have the same expected number of deposits as the deposit density. Statistical guides presented here allow simple yet robust estimation of the number of undiscovered deposits in permissive terranes. 

Crash data modeling with a generalized estimator.

PubMed

Ye, Zhirui; Xu, Yueru; Lord, Dominique

2018-08-01

The investigation of relationships between traffic crashes and relevant factors is important in traffic safety management. Various methods have been developed for modeling crash data. In real world scenarios, crash data often display the characteristics of over-dispersion. However, on occasions, some crash datasets have exhibited under-dispersion, especially in cases where the data are conditioned upon the mean. The commonly used models (such as the Poisson and the NB regression models) have associated limitations to cope with various degrees of dispersion. In light of this, a generalized event count (GEC) model, which can be generally used to handle over-, equi-, and under-dispersed data, is proposed in this study. This model was first applied to case studies using data from Toronto, characterized by over-dispersion, and then to crash data from railway-highway crossings in Korea, characterized with under-dispersion. The results from the GEC model were compared with those from the Negative binomial and the hyper-Poisson models. The cases studies show that the proposed model provides good performance for crash data characterized with over- and under-dispersion. Moreover, the proposed model simplifies the modeling process and the prediction of crash data. Copyright © 2018 Elsevier Ltd. All rights reserved.

Modeling Polio Data Using the First Order Non-Negative Integer-Valued Autoregressive, INAR(1), Model

NASA Astrophysics Data System (ADS)

Vazifedan, Turaj; Shitan, Mahendran

Time series data may consists of counts, such as the number of road accidents, the number of patients in a certain hospital, the number of customers waiting for service at a certain time and etc. When the value of the observations are large it is usual to use Gaussian Autoregressive Moving Average (ARMA) process to model the time series. However if the observed counts are small, it is not appropriate to use ARMA process to model the observed phenomenon. In such cases we need to model the time series data by using Non-Negative Integer valued Autoregressive (INAR) process. The modeling of counts data is based on the binomial thinning operator. In this paper we illustrate the modeling of counts data using the monthly number of Poliomyelitis data in United States between January 1970 until December 1983. We applied the AR(1), Poisson regression model and INAR(1) model and the suitability of these models were assessed by using the Index of Agreement(I.A.). We found that INAR(1) model is more appropriate in the sense it had a better I.A. and it is natural since the data are counts.

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.

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%).

Differences in spousal influence on smoking cessation by gender and education among Japanese couples.

PubMed

Takagi, Daisuke; Kondo, Naoki; Takada, Misato; Hashimoto, Hideki

2014-11-19

Previous studies have reported that spousal non-smoking has a spillover effect on the partner's cessation. However, discussion is lacking on the factors modifying that association. We examined whether the spillover effect of spousal non-smoking was associated with the couple's educational attainment. We used paired marital data from the Japanese Study on Stratification, Health, Income, and Neighborhood (J-SHINE), which targeted residents aged 25-50 years in four Japanese municipalities. We selected a spouse smoker at the time of marriage (target respondent), and set his/her smoking status change (continued or quit smoking after marriage) as an outcome, regressed on the counterpart's smoking status (continued smoking or non-smoking) and combinations of each couple's educational attainment as explanatory variables using log-binomial regression models (n =1001 targets; 708 men and 293 women). Regression results showed that a counterpart who previously quit smoking or was a never-smoker was associated with the target male spouse's subsequent cessation. However, for women, the association between husband's non-smoking and their own cessation was significant only for couples in which both spouses were highly educated. Our findings suggest that a spouse's smoking status is important for smoking cessation interventions in men. For women, however, a couple's combined educational attainment may matter in the interventions.

Predictors and outcomes of non-adherence in patients receiving maintenance hemodialysis.

PubMed

Tohme, Fadi; Mor, Maria K; Pena-Polanco, Julio; Green, Jamie A; Fine, Michael J; Palevsky, Paul M; Weisbord, Steven D

2017-08-01

Predictors of and outcomes associated with non-adherent behavior among patients on chronic hemodialysis (HD) have been incompletely elucidated. We conducted a post hoc analysis of data from the SMILE trial to identify patient factors associated with non-adherence to dialysis-related treatments and the associations of non-adherence with clinical outcomes. We defined non-adherence as missed HD and abbreviated HD. We used negative binomial regression to model the associations of demographic and clinical factors with measures of non-adherence, and negative binomial and Cox regression to analyze the associations of non-adherence with hospitalizations and mortality, respectively. We followed 286 patients for up to 24 months. Factors independently associated with missing HD included Tuesday/Thursday/Saturday HD schedule [incident rate ratio (IRR) 1.85, p < 0.01], current smoking (IRR 2.22, p < 0.01), higher pain score (IRR 1.04, p < 0.01), lower healthy literacy (IRR 3.01, p < 0.01), lower baseline quality of life (IRR 0.89, p = 0.01), and younger age (IRR 1.35, p < 0.01). Factors independently associated with abbreviating HD included dialysis vintage (IRR 1.07, p < 0.01), higher pain score (IRR 1.02, p < 0.01), current non-smoking (IRR 1.32, p = 0.03), and younger age (IRR 1.22, p < 0.01). Abbreviating HD was independently associated with an increased number of total (IRR 1.70, p < 0.01) and ESRD-related (IRR 1.66, p < 0.01) hospitalizations, while missing HD was independently associated with mortality (HR 2.36, p = 0.04). We identified several previously described and novel factors independently associated with non-adherence to HD-related treatments, and independent associations of non-adherence with hospitalization and mortality. These findings should inform the development and implementation of interventions to improve adherence and reduce health resource utilization.

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.

The role of vaspin as a predictor of coronary angiography result in SCAD (stable coronary artery disease) patients.

PubMed

Stančík, Matej; Ságová, Ivana; Kantorová, Ema; Mokáň, Marián

2017-05-08

The role of vaspin in the pathogenesis of stable coronary artery disease (SCAD) have been repeatedly addressed in clinical studies. However, from the point of view of clinical practice, the results of earlier studies are still inconclusive. The data of 106 SCAD patients who received coronary angiography and 85 coronary artery disease-free controls were collected and analysed. The patients were divided into subgroups according to their pre-test probability (PTP) and according to the result of coronary angiography. Fasting vaspin concentrations were compared between subgroups of SCAD patients and between target group and controls. The effect of age and smoking on the result of coronary angiography was compared to the effect of vaspin using the binomial regression. We did not find significant difference in vaspin level between target group and controls. Unless the pre-test probability was taken into account, we did not find vaspin difference in the target group, when dividing patients on the basis of presence/absence of significant coronary stenosis. In the subgroup of SCAD patients with PTP between 15% - 65%, those with significant coronary stenoses had higher mean vaspin concentration (0,579 ± 0,898 ng/ml) than patients without significant stenoses. (0,379 ± 0,732 ng/ml) (t = -2595; p = 0,012; d = 0,658; 1-β = 0,850). Age, smoking status and vaspin significantly contributed to the HSCS prediction in binomial regression model in patients with low PTP (OR: 1.1, 4.9, 8.7, respectively). According to our results, vaspin cannot be used as an independent marker for the presence of CAD in general population. However, our results indicate that measuring vaspin in SCAD patients might be clinically useful in patients with PTP below 66%.

Temporal association between the influenza virus and respiratory syncytial virus (RSV): RSV as a predictor of seasonal influenza.

PubMed

Míguez, A; Iftimi, A; Montes, F

2016-09-01

Epidemiologists agree that there is a prevailing seasonality in the presentation of epidemic waves of respiratory syncytial virus (RSV) infections and influenza. The aim of this study is to quantify the potential relationship between the activity of RSV, with respect to the influenza virus, in order to use the RSV seasonal curve as a predictor of the evolution of an influenza virus epidemic wave. Two statistical tools, logistic regression and time series, are used for predicting the evolution of influenza. Both logistic models and time series of influenza consider RSV information from previous weeks. Data consist of influenza and confirmed RSV cases reported in Comunitat Valenciana (Spain) during the period from week 40 (2010) to week 8 (2014). Binomial logistic regression models used to predict the two states of influenza wave, basal or peak, result in a rate of correct classification higher than 92% with the validation set. When a finer three-states categorization is established, basal, increasing peak and decreasing peak, the multinomial logistic model performs well in 88% of cases of the validation set. The ARMAX model fits well for influenza waves and shows good performance for short-term forecasts up to 3 weeks. The seasonal evolution of influenza virus can be predicted a minimum of 4 weeks in advance using logistic models based on RSV. It would be necessary to study more inter-pandemic seasons to establish a stronger relationship between the epidemic waves of both viruses.

The gap between suicide characteristics in the print media and in the population.

PubMed

Niederkrotenthaler, Thomas; Till, Benedikt; Herberth, Arno; Voracek, Martin; Kapusta, Nestor D; Etzersdorfer, Elmar; Strauss, Markus; Sonneck, Gernot

2009-08-01

Programmes to educate media professionals about suicide are increasingly established, but information about which suicide cases are most likely to be reported in the mass media is sparse. We applied binomial tests to compare frequencies of social characteristics of all domestic suicides in the 13 largest Austrian print media in 2005 with frequencies of suicide characteristics in the population. Additionally, each reported suicide case was linked to its respective entry in the suicide database. We performed a logistic regression analysis, with presence of an article as outcome, and sex of the suicide case, age, religious affiliation, family status, conduction of an autopsy and location of the suicide as explaining variables. Time of the year and federal state where the suicide happened was controlled for. Binomial tests showed that suicides involving murder or murder attempt were over-represented in the media. Reporting on mental disorders was under-represented. In the regression analysis, the likelihood of a report was negatively associated with the age of suicide cases. Foreign citizenship was a further predictor of a suicide report. The methods of drowning, jumping, shooting and rare methods were more likely to be reported than hanging, which is the most frequent suicide method in Austria. Suicide characteristics in the media are not representative of the population. The identified discrepancies provide a basis for tailor-made education of mass media professionals.

Violent video games and delinquent behavior in adolescents: A risk factor perspective.

PubMed

Exelmans, Liese; Custers, Kathleen; Van den Bulck, Jan

2015-05-01

Over the years, criminological research has identified a number of risk factors that contribute to the development of aggressive and delinquent behavior. Although studies have identified media violence in general and violent video gaming in particular as significant predictors of aggressive behavior, exposure to violent video games has been largely omitted from the risk factor literature on delinquent behavior. This cross-sectional study therefore investigates the relationship between violent video game play and adolescents' delinquent behavior using a risk factor approach. An online survey was completed by 3,372 Flemish adolescents, aged 12-18 years old. Data were analyzed by means of negative binomial regression modelling. Results indicated a significant contribution of violent video games in delinquent behavior over and beyond multiple known risk variables (peer delinquency, sensation seeking, prior victimization, and alienation). Moreover, the final model that incorporated the gaming genres proved to be significantly better than the model without the gaming genres. Results provided support for a cumulative and multiplicative risk model for delinquent behavior. Aggr. Behav. 41:267-279, 2015. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

Morbidity and Health Risk Factors Among New Mexico Miners: A Comparison Across Mining Sectors.

PubMed

Shumate, Alice M; Yeoman, Kristin; Victoroff, Tristan; Evans, Kandace; Karr, Roger; Sanchez, Tami; Sood, Akshay; Laney, Anthony Scott

2017-08-01

This study examines differences in chronic health outcomes between coal, uranium, metal, and nonmetal miners. In a cross-sectional study using data from a health screening program for current and former New Mexico miners, log-binomial logistic regression models were used to estimate relative risks of respiratory and heart disease, cancer, osteoarthritis, and back pain associated with mining in each sector as compared with coal, adjusting for other relevant risk factors. Differential risks in angina, pulmonary symptoms, asthma, cancer, osteoarthritis, and back pain between mining sectors were found. New Mexico miners experience different chronic health challenges across sectors. These results demonstrate the importance of using comparable data to understand how health risks differ across mining sectors. Further investigation among a broader geographic population of miners will help identify the health priorities and needs in each sector.

Employee resistance and injury during commercial robberies.

PubMed

Jones, Jennifer; Casteel, Carri; Peek-Asa, Corinne

2015-05-01

To examine the association between employee resistance and injury and examine whether type or location of property stolen was associated with employee resistance during commercial robberies in a large metropolitan city. Robbery data were abstracted from police crime reports between 2008 and 2012. Log binomial regression models were used to identify predictors of employee resistance and to evaluate the association between employee resistance and injury. Employees resisted a robber in nearly half of all robbery events. Active employee resistance was significantly associated with employee injury (Adj PR: 1.49, 95% confidence interval, 1.34 to 1.65). Goods being stolen were associated with active employee resistance and employee injury, whereas cash only being stolen was inversely associated with employee injury. Results suggest that employee training in nonresistance can be an important strategy in protecting employees working with the exchange of cash and goods.

Determinants of the lethality of climate-related disasters in the Caribbean Community (CARICOM): a cross-country analysis

PubMed Central

Andrewin, Aisha N.; Rodriguez-Llanes, Jose M.; Guha-Sapir, Debarati

2015-01-01

Floods and storms are climate-related hazards posing high mortality risk to Caribbean Community (CARICOM) nations. However risk factors for their lethality remain untested. We conducted an ecological study investigating risk factors for flood and storm lethality in CARICOM nations for the period 1980–2012. Lethality - deaths versus no deaths per disaster event- was the outcome. We examined biophysical and social vulnerability proxies and a decadal effect as predictors. We developed our regression model via multivariate analysis using a generalized logistic regression model with quasi-binomial distribution; removal of multi-collinear variables and backward elimination. Robustness was checked through subset analysis. We found significant positive associations between lethality, percentage of total land dedicated to agriculture (odds ratio [OR] 1.032; 95% CI: 1.013–1.053) and percentage urban population (OR 1.029, 95% CI 1.003–1.057). Deaths were more likely in the 2000–2012 period versus 1980–1989 (OR 3.708, 95% CI 1.615–8.737). Robustness checks revealed similar coefficients and directions of association. Population health in CARICOM nations is being increasingly impacted by climate-related disasters connected to increasing urbanization and land use patterns. Our findings support the evidence base for setting sustainable development goals (SDG). PMID:26153115

Factors Associated with Sexual Violence against Men Who Have Sex with Men and Transgendered Individuals in Karnataka, India

PubMed Central

Shaw, Souradet Y.; Lorway, Robert R.; Deering, Kathleen N.; Avery, Lisa; Mohan, H. L.; Bhattacharjee, Parinita; Reza-Paul, Sushena; Isac, Shajy; Ramesh, Banadakoppa M.; Washington, Reynold; Moses, Stephen; Blanchard, James F.

2012-01-01

Objectives There is a lack of information on sexual violence (SV) among men who have sex with men and transgendered individuals (MSM-T) in southern India. As SV has been associated with HIV vulnerability, this study examined health related behaviours and practices associated with SV among MSM-T. Design Data were from cross-sectional surveys from four districts in Karnataka, India. Methods Multivariable logistic regression models were constructed to examine factors related to SV. Multivariable negative binomial regression models examined the association between physician visits and SV. Results A total of 543 MSM-T were included in the study. Prevalence of SV was 18% in the past year. HIV prevalence among those reporting SV was 20%, compared to 12% among those not reporting SV (p = .104). In multivariable models, and among sex workers, those reporting SV were more likely to report anal sex with 5+ casual sex partners in the past week (AOR: 4.1; 95%CI: 1.2–14.3, p = .029). Increased physician visits among those reporting SV was reported only for those involved in sex work (ARR: 1.7; 95%CI: 1.1–2.7, p = .012). Conclusions These results demonstrate high levels of SV among MSM-T populations, highlighting the importance of integrating interventions to reduce violence as part of HIV prevention programs and health services. PMID:22448214

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.

A preliminary investigation of the relationships between historical crash and naturalistic driving.

PubMed

Pande, Anurag; Chand, Sai; Saxena, Neeraj; Dixit, Vinayak; Loy, James; Wolshon, Brian; Kent, Joshua D

2017-04-01

This paper describes a project that was undertaken using naturalistic driving data collected via Global Positioning System (GPS) devices to demonstrate a proof-of-concept for proactive safety assessments of crash-prone locations. The main hypothesis for the study is that the segments where drivers have to apply hard braking (higher jerks) more frequently might be the "unsafe" segments with more crashes over a long-term. The linear referencing methodology in ArcMap was used to link the GPS data with roadway characteristic data of US Highway 101 northbound (NB) and southbound (SB) in San Luis Obispo, California. The process used to merge GPS data with quarter-mile freeway segments for traditional crash frequency analysis is also discussed in the paper. A negative binomial regression analyses showed that proportion of high magnitude jerks while decelerating on freeway segments (from the driving data) was significantly related with the long-term crash frequency of those segments. A random parameter negative binomial model with uniformly distributed parameter for ADT and a fixed parameter for jerk provided a statistically significant estimate for quarter-mile segments. The results also indicated that roadway curvature and the presence of auxiliary lane are not significantly related with crash frequency for the highway segments under consideration. The results from this exploration are promising since the data used to derive the explanatory variable(s) can be collected using most off-the-shelf GPS devices, including many smartphones. Copyright © 2017 Elsevier Ltd. All rights reserved.

Marginalized zero-altered models for longitudinal count data.

PubMed

Tabb, Loni Philip; Tchetgen, Eric J Tchetgen; Wellenius, Greg A; Coull, Brent A

2016-10-01

Count data often exhibit more zeros than predicted by common count distributions like the Poisson or negative binomial. In recent years, there has been considerable interest in methods for analyzing zero-inflated count data in longitudinal or other correlated data settings. A common approach has been to extend zero-inflated Poisson models to include random effects that account for correlation among observations. However, these models have been shown to have a few drawbacks, including interpretability of regression coefficients and numerical instability of fitting algorithms even when the data arise from the assumed model. To address these issues, we propose a model that parameterizes the marginal associations between the count outcome and the covariates as easily interpretable log relative rates, while including random effects to account for correlation among observations. One of the main advantages of this marginal model is that it allows a basis upon which we can directly compare the performance of standard methods that ignore zero inflation with that of a method that explicitly takes zero inflation into account. We present simulations of these various model formulations in terms of bias and variance estimation. Finally, we apply the proposed approach to analyze toxicological data of the effect of emissions on cardiac arrhythmias.

Marginalized zero-altered models for longitudinal count data

PubMed Central

Tabb, Loni Philip; Tchetgen, Eric J. Tchetgen; Wellenius, Greg A.; Coull, Brent A.

2015-01-01

Count data often exhibit more zeros than predicted by common count distributions like the Poisson or negative binomial. In recent years, there has been considerable interest in methods for analyzing zero-inflated count data in longitudinal or other correlated data settings. A common approach has been to extend zero-inflated Poisson models to include random effects that account for correlation among observations. However, these models have been shown to have a few drawbacks, including interpretability of regression coefficients and numerical instability of fitting algorithms even when the data arise from the assumed model. To address these issues, we propose a model that parameterizes the marginal associations between the count outcome and the covariates as easily interpretable log relative rates, while including random effects to account for correlation among observations. One of the main advantages of this marginal model is that it allows a basis upon which we can directly compare the performance of standard methods that ignore zero inflation with that of a method that explicitly takes zero inflation into account. We present simulations of these various model formulations in terms of bias and variance estimation. Finally, we apply the proposed approach to analyze toxicological data of the effect of emissions on cardiac arrhythmias. PMID:27867423

Dental enamel defects, caries experience and oral health-related quality of life: a cohort study.

PubMed

Arrow, P

2017-06-01

The impact of enamel defects of the first permanent molars on caries experience and child oral health-related quality of life was evaluated in a cohort study. Children who participated in a study of enamel defects of the first permanent molars 8 years earlier were invited for a follow-up assessment. Consenting children completed the Child Perception Questionnaire and the faces Modified Child Dental Anxiety Scale, and were examined by two calibrated examiners. ANOVA, Kruskal-Wallis, negative binomial and logistic regression were used for data analyses. One hundred and eleven children returned a completed questionnaire and 91 were clinically examined. Negative binomial regression found that oral health impacts were associated with gender (boys, risk ratio (RR) = 0.73, P = 0.03) and decayed, missing or filled permanent teeth (DMFT) (RR = 1.1, P = 0.04). The mean DMFT of children were sound (0.9, standard deviation (SD) = 1.4), diffuse defects (0.8, SD = 1.7), demarcated defects (1.5, SD = 1.4) and pit defects (1.3, SD = 2.3) (Kruskal-Wallis, P = 0.05). Logistic regression of first permanent molar caries found higher odds of caries experience with baseline primary tooth caries experience (odds ratio (OR) = 1.5, P = 0.01), the number of teeth affected by enamel defects (OR = 1.9, P = 0.05) and lower odds with the presence of diffuse enamel defects (OR = 0.1, P = 0.04). The presence of diffuse enamel defects was associated with lower odds of caries experience. © 2016 Australian Dental Association.

New diagnostic index for sarcopenia in patients with cardiovascular diseases

PubMed Central

Kai, Hisashi; Shibata, Rei; Niiyama, Hiroshi; Nishiyama, Yasuhiro; Murohara, Toyoaki; Yoshida, Noriko; Katoh, Atsushi; Ikeda, Hisao

2017-01-01

Background Sarcopenia is an aging and disease-related syndrome characterized by progressive and generalized loss of skeletal muscle mass and strength, with the risk of frailty and poor quality of life. Sarcopenia is diagnosed by a decrease in skeletal muscle index (SMI) and reduction of either handgrip strength or gait speed. However, measurement of SMI is difficult for general physicians because it requires special equipment for bioelectrical impedance assay or dual-energy X-ray absorptiometry. The purpose of this study was, therefore, to explore a novel, simple diagnostic method of sarcopenia evaluation in patients with cardiovascular diseases (CVD). Methods We retrospectively investigated 132 inpatients with CVD (age: 72±12 years, age range: 27–93 years, males: 61%) Binomial logistic regression and correlation analyses were used to assess the associations of sarcopenia with simple physical data and biomarkers, including muscle-related inflammation makers and nutritional markers. Results Sarcopenia was present in 29.5% of the study population. Serum concentrations of adiponectin and sialic acid were significantly higher in sarcopenic than non-sarcopenic CVD patients. Stepwise multivariate binomial logistic regression analysis revealed that adiponectin, sialic acid, sex, age, and body mass index were independent factors for sarcopenia detection. Sarcopenia index, obtained from the diagnostic regression formula for sarcopenia detection including the five independent factors, indicated a high accuracy in ROC curve analysis (sensitivity 94.9%, specificity 69.9%) and the cutoff value for sarcopenia detection was -1.6134. Sarcopenia index had a significant correlation with the conventional diagnostic parameters of sarcopenia. Conclusions Our new sarcopenia index using simple parameters would be useful for diagnosing sarcopenia in CVD patients. PMID:28542531

The Relationship Between Gun Ownership and Stranger and Nonstranger Firearm Homicide Rates in the United States, 1981–2010

PubMed Central

Negussie, Yamrot; Vanture, Sarah; Pleskunas, Jane; Ross, Craig S.; King, Charles

2014-01-01

Objectives. We examined the relationship between gun ownership and stranger versus nonstranger homicide rates. Methods. Using data from the Supplemental Homicide Reports of the Federal Bureau of Investigation’s Uniform Crime Reports for all 50 states for 1981 to 2010, we modeled stranger and nonstranger homicide rates as a function of state-level gun ownership, measured by a proxy, controlling for potential confounders. We used a negative binomial regression model with fixed effects for year, accounting for clustering of observations among states by using generalized estimating equations. Results. We found no robust, statistically significant correlation between gun ownership and stranger firearm homicide rates. However, we found a positive and significant association between gun ownership and nonstranger firearm homicide rates. The incidence rate ratio for nonstranger firearm homicide rate associated with gun ownership was 1.014 (95% confidence interval = 1.009, 1.019). Conclusions. Our findings challenge the argument that gun ownership deters violent crime, in particular, homicides. PMID:25121817

The relationship between gun ownership and stranger and nonstranger firearm homicide rates in the United States, 1981-2010.

PubMed

Siegel, Michael; Negussie, Yamrot; Vanture, Sarah; Pleskunas, Jane; Ross, Craig S; King, Charles

2014-10-01

We examined the relationship between gun ownership and stranger versus nonstranger homicide rates. Using data from the Supplemental Homicide Reports of the Federal Bureau of Investigation's Uniform Crime Reports for all 50 states for 1981 to 2010, we modeled stranger and nonstranger homicide rates as a function of state-level gun ownership, measured by a proxy, controlling for potential confounders. We used a negative binomial regression model with fixed effects for year, accounting for clustering of observations among states by using generalized estimating equations. We found no robust, statistically significant correlation between gun ownership and stranger firearm homicide rates. However, we found a positive and significant association between gun ownership and nonstranger firearm homicide rates. The incidence rate ratio for nonstranger firearm homicide rate associated with gun ownership was 1.014 (95% confidence interval=1.009, 1.019). Our findings challenge the argument that gun ownership deters violent crime, in particular, homicides.

Searching for the Kinkeepers: Historian Gender, Age, and Type 2 Diabetes Family History.

PubMed

Giordimaina, Alicia M; Sheldon, Jane P; Kiedrowski, Lesli A; Jayaratne, Toby Epstein

2015-12-01

Kinkeepers facilitate family communication and may be key to family medical history collection and dissemination. Middle-aged women are frequently kinkeepers. Using type 2 diabetes (T2DM) as a model, we explored whether the predicted gender and age effects of kinkeeping can be extended to family medical historians. Through a U.S. telephone survey, nondiabetic Mexican Americans (n = 385), Blacks (n = 387), and Whites (n = 396) reported family histories of T2DM. Negative binomial regressions used age and gender to predict the number of affected relatives reported. Models were examined for the gender gap, parabolic age effect, and gender-by-age interaction predicted by kinkeeping. Results demonstrated support for gender and parabolic age effects but only among Whites. Kinkeeping may have application to the study of White family medical historians, but not Black or Mexican American historians, perhaps because of differences in family structure, salience of T2DM, and/or gender roles. © 2015 Society for Public Health Education.

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.

Marital status and survival of patients with oral cavity squamous cell carcinoma: a population-based study.

PubMed

Shi, Xiao; Zhang, Ting-Ting; Hu, Wei-Ping; Ji, Qing-Hai

2017-04-25

The relationship between marital status and oral cavity squamous cell carcinoma (OCSCC) survival has not been explored. The objective of our study was to evaluate the impact of marital status on OCSCC survival and investigate the potential mechanisms. Married patients had better 5-year cancer-specific survival (CSS) (66.7% vs 54.9%) and 5-year overall survival (OS) (56.0% vs 41.1%). In multivariate Cox regression models, unmarried patients also showed higher mortality risk for both CSS (Hazard Ratio [HR]: 1.260, 95% confidence interval (CI): 1.187-1.339, P < 0.001) and OS (HR: 1.328, 95% CI: 1.266-1.392, P < 0.001). Multivariate logistic regression showed married patients were more likely to be diagnosed at earlier stage (P < 0.001) and receive surgery (P < 0.001). Married patients still demonstrated better prognosis in the 1:1 matched group analysis (CSS: 62.9% vs 60.8%, OS: 52.3% vs 46.5%). 11022 eligible OCSCC patients were identified from Surveillance, Epidemiology, and End Results (SEER) database, including 5902 married and 5120 unmarried individuals. Kaplan-Meier analysis, Log-rank test and Cox proportional hazards regression model were used to analyze survival and mortality risk. Influence of marital status on stage, age at diagnosis and selection of treatment was determined by binomial and multinomial logistic regression. Propensity score matching method was adopted to perform a 1:1 matched cohort. Marriage has an independently protective effect on OCSCC survival. Earlier diagnosis and more sufficient treatment are possible explanations. Besides, even after 1:1 matching, survival advantage of married group still exists, indicating that spousal support from other aspects may also play an important role.

Marital status and survival of patients with oral cavity squamous cell carcinoma: a population-based study

PubMed Central

Shi, Xiao; Zhang, Ting-ting; Hu, Wei-ping; Ji, Qing-hai

2017-01-01

Background The relationship between marital status and oral cavity squamous cell carcinoma (OCSCC) survival has not been explored. The objective of our study was to evaluate the impact of marital status on OCSCC survival and investigate the potential mechanisms. Results Married patients had better 5-year cancer-specific survival (CSS) (66.7% vs 54.9%) and 5-year overall survival (OS) (56.0% vs 41.1%). In multivariate Cox regression models, unmarried patients also showed higher mortality risk for both CSS (Hazard Ratio [HR]: 1.260, 95% confidence interval (CI): 1.187–1.339, P < 0.001) and OS (HR: 1.328, 95% CI: 1.266–1.392, P < 0.001). Multivariate logistic regression showed married patients were more likely to be diagnosed at earlier stage (P < 0.001) and receive surgery (P < 0.001). Married patients still demonstrated better prognosis in the 1:1 matched group analysis (CSS: 62.9% vs 60.8%, OS: 52.3% vs 46.5%). Materials and Methods 11022 eligible OCSCC patients were identified from Surveillance, Epidemiology, and End Results (SEER) database, including 5902 married and 5120 unmarried individuals. Kaplan-Meier analysis, Log-rank test and Cox proportional hazards regression model were used to analyze survival and mortality risk. Influence of marital status on stage, age at diagnosis and selection of treatment was determined by binomial and multinomial logistic regression. Propensity score matching method was adopted to perform a 1:1 matched cohort. Conclusions Marriage has an independently protective effect on OCSCC survival. Earlier diagnosis and more sufficient treatment are possible explanations. Besides, even after 1:1 matching, survival advantage of married group still exists, indicating that spousal support from other aspects may also play an important role. PMID:28415710

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…

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.

Development of binomial sequential sampling plans for forecasting Listronotus maculicollis (Coleoptera: Curculionidae) larvae based on the relationship to adult counts and turfgrass damage.

PubMed

McGraw, Benjamin A; Koppenhöfer, Albrecht M

2009-06-01

Binomial sequential sampling plans were developed to forecast weevil Listronotus maculicollis Kirby (Coleoptera: Curculionidae), larval damage to golf course turfgrass and aid in the development of integrated pest management programs for the weevil. Populations of emerging overwintered adults were sampled over a 2-yr period to determine the relationship between adult counts, larval density, and turfgrass damage. Larval density and composition of preferred host plants (Poa annua L.) significantly affected the expression of turfgrass damage. Multiple regression indicates that damage may occur in moderately mixed P. annua stands with as few as 10 larvae per 0.09 m2. However, > 150 larvae were required before damage became apparent in pure Agrostis stolonifera L. plots. Adult counts during peaks in emergence as well as cumulative counts across the emergence period were significantly correlated to future densities of larvae. Eight binomial sequential sampling plans based on two tally thresholds for classifying infestation (T = 1 and two adults) and four adult density thresholds (0.5, 0.85, 1.15, and 1.35 per 3.34 m2) were developed to forecast the likelihood of turfgrass damage by using adult counts during peak emergence. Resampling for validation of sample plans software was used to validate sampling plans with field-collected data sets. All sampling plans were found to deliver accurate classifications (correct decisions were made between 84.4 and 96.8%) in a practical timeframe (average sampling cost < 22.7 min).

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.

Dispersion and sampling of adult Dermacentor andersoni in rangeland in Western North America.

PubMed

Rochon, K; Scoles, G A; Lysyk, T J

2012-03-01

A fixed precision sampling plan was developed for off-host populations of adult Rocky Mountain wood tick, Dermacentor andersoni (Stiles) based on data collected by dragging at 13 locations in Alberta, Canada; Washington; and Oregon. In total, 222 site-date combinations were sampled. Each site-date combination was considered a sample, and each sample ranged in size from 86 to 250 10 m2 quadrats. Analysis of simulated quadrats ranging in size from 10 to 50 m2 indicated that the most precise sample unit was the 10 m2 quadrat. Samples taken when abundance < 0.04 ticks per 10 m2 were more likely to not depart significantly from statistical randomness than samples taken when abundance was greater. Data were grouped into ten abundance classes and assessed for fit to the Poisson and negative binomial distributions. The Poisson distribution fit only data in abundance classes < 0.02 ticks per 10 m2, while the negative binomial distribution fit data from all abundance classes. A negative binomial distribution with common k = 0.3742 fit data in eight of the 10 abundance classes. Both the Taylor and Iwao mean-variance relationships were fit and used to predict sample sizes for a fixed level of precision. Sample sizes predicted using the Taylor model tended to underestimate actual sample sizes, while sample sizes estimated using the Iwao model tended to overestimate actual sample sizes. Using a negative binomial with common k provided estimates of required sample sizes closest to empirically calculated sample sizes.

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.

Logistic quantile regression provides improved estimates for bounded avian counts: A case study of California Spotted Owl fledgling production

USGS Publications Warehouse

Cade, Brian S.; Noon, Barry R.; Scherer, Rick D.; Keane, John J.

2017-01-01

Counts of avian fledglings, nestlings, or clutch size that are bounded below by zero and above by some small integer form a discrete random variable distribution that is not approximated well by conventional parametric count distributions such as the Poisson or negative binomial. We developed a logistic quantile regression model to provide estimates of the empirical conditional distribution of a bounded discrete random variable. The logistic quantile regression model requires that counts are randomly jittered to a continuous random variable, logit transformed to bound them between specified lower and upper values, then estimated in conventional linear quantile regression, repeating the 3 steps and averaging estimates. Back-transformation to the original discrete scale relies on the fact that quantiles are equivariant to monotonic transformations. We demonstrate this statistical procedure by modeling 20 years of California Spotted Owl fledgling production (0−3 per territory) on the Lassen National Forest, California, USA, as related to climate, demographic, and landscape habitat characteristics at territories. Spotted Owl fledgling counts increased nonlinearly with decreasing precipitation in the early nesting period, in the winter prior to nesting, and in the prior growing season; with increasing minimum temperatures in the early nesting period; with adult compared to subadult parents; when there was no fledgling production in the prior year; and when percentage of the landscape surrounding nesting sites (202 ha) with trees ≥25 m height increased. Changes in production were primarily driven by changes in the proportion of territories with 2 or 3 fledglings. Average variances of the discrete cumulative distributions of the estimated fledgling counts indicated that temporal changes in climate and parent age class explained 18% of the annual variance in owl fledgling production, which was 34% of the total variance. Prior fledgling production explained as much of the variance in the fledgling counts as climate, parent age class, and landscape habitat predictors. Our logistic quantile regression model can be used for any discrete response variables with fixed upper and lower bounds.

Joint model for a diagnostic test without a gold standard in the presence of a dependent terminal event.

PubMed

Luo, Sheng; Su, Xiao; DeSantis, Stacia M; Huang, Xuelin; Yi, Min; Hunt, Kelly K

2014-07-10

Breast cancer patients after breast conservation therapy often develop ipsilateral breast tumor relapse (IBTR), whose classification (true local recurrence versus new ipsilateral primary tumor) is subject to error, and there is no available gold standard. Some patients may die because of breast cancer before IBTR develops. Because this terminal event may be related to the individual patient's unobserved disease status and time to IBTR, the terminal mechanism is non-ignorable. This article presents a joint analysis framework to model the binomial regression with misclassified binary outcome and the correlated time to IBTR, subject to a dependent terminal event and in the absence of a gold standard. Shared random effects are used to link together two survival times. The proposed approach is evaluated by a simulation study and is applied to a breast cancer data set consisting of 4477 breast cancer patients. The proposed joint model can be conveniently fit using adaptive Gaussian quadrature tools implemented in SAS 9.3 (SAS Institute Inc., Cary, NC, USA) procedure NLMIXED. Copyright © 2014 John Wiley & Sons, Ltd.

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.

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.

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.

Variable selection for distribution-free models for longitudinal zero-inflated count responses.

PubMed

Chen, Tian; Wu, Pan; Tang, Wan; Zhang, Hui; Feng, Changyong; Kowalski, Jeanne; Tu, Xin M

2016-07-20

Zero-inflated count outcomes arise quite often in research and practice. Parametric models such as the zero-inflated Poisson and zero-inflated negative binomial are widely used to model such responses. Like most parametric models, they are quite sensitive to departures from assumed distributions. Recently, new approaches have been proposed to provide distribution-free, or semi-parametric, alternatives. These methods extend the generalized estimating equations to provide robust inference for population mixtures defined by zero-inflated count outcomes. In this paper, we propose methods to extend smoothly clipped absolute deviation (SCAD)-based variable selection methods to these new models. Variable selection has been gaining popularity in modern clinical research studies, as determining differential treatment effects of interventions for different subgroups has become the norm, rather the exception, in the era of patent-centered outcome research. Such moderation analysis in general creates many explanatory variables in regression analysis, and the advantages of SCAD-based methods over their traditional counterparts render them a great choice for addressing this important and timely issues in clinical research. We illustrate the proposed approach with both simulated and real study data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Indicators of Dysphagia in Aged Care Facilities.

PubMed

Pu, Dai; Murry, Thomas; Wong, May C M; Yiu, Edwin M L; Chan, Karen M K

2017-09-18

The current cross-sectional study aimed to investigate risk factors for dysphagia in elderly individuals in aged care facilities. A total of 878 individuals from 42 aged care facilities were recruited for this study. The dependent outcome was speech therapist-determined swallowing function. Independent factors were Eating Assessment Tool score, oral motor assessment score, Mini-Mental State Examination, medical history, and various functional status ratings. Binomial logistic regression was used to identify independent variables associated with dysphagia in this cohort. Two statistical models were constructed. Model 1 used variables from case files without the need for hands-on assessment, and Model 2 used variables that could be obtained from hands-on assessment. Variables positively associated with dysphagia identified in Model 1 were male gender, total dependence for activities of daily living, need for feeding assistance, mobility, requiring assistance walking or using a wheelchair, and history of pneumonia. Variables positively associated with dysphagia identified in Model 2 were Mini-Mental State Examination score, edentulousness, and oral motor assessments score. Cognitive function, dentition, and oral motor function are significant indicators associated with the presence of swallowing in the elderly. When assessing the frail elderly, case file information can help clinicians identify frail elderly individuals who may be suffering from dysphagia.

Bus accident analysis of routes with/without bus priority.

PubMed

Goh, Kelvin Chun Keong; Currie, Graham; Sarvi, Majid; Logan, David

2014-04-01

This paper summarises findings on road safety performance and bus-involved accidents in Melbourne along roads where bus priority measures had been applied. Results from an empirical analysis of the accident types revealed significant reduction in the proportion of accidents involving buses hitting stationary objects and vehicles, which suggests the effect of bus priority in addressing manoeuvrability issues for buses. A mixed-effects negative binomial (MENB) regression and back-propagation neural network (BPNN) modelling of bus accidents considering wider influences on accident rates at a route section level also revealed significant safety benefits when bus priority is provided. Sensitivity analyses done on the BPNN model showed general agreement in the predicted accident frequency between both models. The slightly better performance recorded by the MENB model results suggests merits in adopting a mixed effects modelling approach for accident count prediction in practice given its capability to account for unobserved location and time-specific factors. A major implication of this research is that bus priority in Melbourne's context acts to improve road safety and should be a major consideration for road management agencies when implementing bus priority and road schemes. Copyright © 2013 Elsevier Ltd. All rights reserved.

The influence of economic incentives linked to road safety indicators on accidents: the case of toll concessions in Spain.

PubMed

Rangel, Thais; Vassallo, José Manuel; Herraiz, Israel

2013-10-01

The goal of this paper is to evaluate whether the incentives incorporated in toll highway concession contracts in order to encourage private operators to adopt measures to reduce accidents are actually effective at improving safety. To this end, we implemented negative binomial regression models using information about highway characteristics and accident data from toll highway concessions in Spain from 2007 to 2009. Our results show that even though road safety is highly influenced by variables that are not managed by the contractor, such as the annual average daily traffic (AADT), the percentage of heavy vehicles on the highway, number of lanes, number of intersections and average speed; the implementation of these incentives has a positive influence on the reduction of accidents and injuries. Consequently, this measure seems to be an effective way of improving safety performance in road networks. Copyright © 2013 Elsevier Ltd. All rights reserved.

Environmental Risk Factors influencing Bicycle Theft: A Spatial Analysis in London, UK.

PubMed

Mburu, Lucy Waruguru; Helbich, Marco

2016-01-01

Urban authorities are continuously drawing up policies to promote cycling among commuters. However, these initiatives are counterproductive for the targeted objectives because they increase opportunities for bicycle theft. This paper explores Inner London as a case study to address place-specific risk factors for bicycle theft at the street-segment level while controlling for seasonal variation. The presence of certain public amenities (e.g., bicycle stands, railway stations, pawnshops) was evaluated against locations of bicycle theft between 2013 and 2016 and risk effects were estimated using negative binomial regression models. Results showed that a greater level of risk stemmed from land-use facilities than from area-based socioeconomic status. The presence of facilities such as train stations, vacant houses, pawnbrokers and payday lenders increased bicycle theft, but no evidence was found that linked police stations with crime levels. The findings have significant implications for urban crime prevention with respect to non-residential land use.

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.

The Effect of Exposure to Ultraviolet Radiation in Infancy on Melanoma Risk.

PubMed

Gefeller, Olaf; Fiessler, Cornelia; Radespiel-Tröger, Martin; Uter, Wolfgang; Pfahlberg, Annette B

2016-01-01

Evidence on the effect of ultraviolet radiation (UVR) exposure in infancy on melanoma risk in later life is scarce. Three recent studies suffering from methodological shortcomings suggested that people born in spring carry a higher melanoma risk. Data from the Bavarian population-based cancer registry on 28374 incident melanoma cases between 2002 and 2012 were analyzed to reexamine this finding. Crude and adjusted analyses - using negative binomial regression models - were performed addressing the relationship. In the crude analysis, the birth months March - May were significantly overrepresented among melanoma cases. However, after additionally adjusting for the birth month distribution of the Bavarian population, the ostensible seasonal effect disappeared. Similar results emerged in all subgroup analyses. Our large registry-based study provides no evidence that people born in spring carry a higher risk for developing melanoma in later life and thus lends no support to the hypothesis of higher UVR-susceptibility during the first months of life.

[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.

The role of self-efficacy and motivation to explain the effect of motivational interviewing time on changes in risky sexual behavior among people living with HIV: a mediation analysis.

PubMed

Chariyeva, Zulfiya; Golin, Carol E; Earp, Jo Anne; Maman, Suzanne; Suchindran, Chirayath; Zimmer, Catherine

2013-02-01

Little is known about the amount of Motivational Interviewing (MI) needed to reduce risky sexual behavior among People Living with HIV/AIDS (PLWHA) or the roles self-efficacy and motivation to practice safer sex play. Among 183 PLWHA who received safer sex MI and were surveyed every 4 months over a 12 month period, we used hierarchical negative binomial regression models to examine the association between amount of counseling time and sexual risk behavior. We performed mediation analysis to evaluate whether changes in self-efficacy and motivation explained this association. This study found that as MI time and number of provided sessions increased, participants' sexual risk behavior decreased. The effect of MI time and number of sessions on sexual behavior was mediated by self-efficacy but not by motivation to practice safer sex.

The Role of Self-Efficacy and Motivation to Explain the Effect of Motivational Interviewing Time on Changes in Risky Sexual Behavior among People Living with HIV: A Mediation Analysis

PubMed Central

Golin, Carol E.; Earp, Jo Anne; Maman, Suzanne; Suchindran, Chirayath; Zimmer, Catherine

2014-01-01

Little is known about the amount of Motivational Interviewing (MI) needed to reduce risky sexual behavior among People Living with HIV/AIDS (PLWHA) or the roles self-efficacy and motivation to practice safer sex play. Among 183 PLWHA who received safer sex MI and were surveyed every 4 months over a 12 month period, we used hierarchical negative binomial regression models to examine the association between amount of counseling time and sexual risk behavior. We performed mediation analysis to evaluate whether changes in self-efficacy and motivation explained this association. This study found that as MI time and number of provided sessions increased, participants’ sexual risk behavior decreased. The effect of MI time and number of sessions on sexual behavior was mediated by self-efficacy but not by motivation to practice safer sex. PMID:22228069

Adult Children's Education and Parents' Functional Limitations in Mexico.

PubMed

Yahirun, Jenjira J; Sheehan, Connor M; Hayward, Mark D

2016-04-01

This article asks how adult children's education influences older parents' physical health in Mexico, a context where older adults often lack access to institutional resources and rely on kin, primarily children, as a main source of support. Using logistic and negative binomial regression models and data from the first wave of the Mexican Health and Aging Study (N = 9,661), we find that parents whose children all completed high school are less likely to report any functional limitations as well as fewer limitations compared to parents with no children who completed high school. This association remains significant even after accounting for parent and offspring-level characteristics, including parents' income that accounts for children's financial transfers to parents. Future research should aim to understand the mechanisms that explain the association between adult children's education and changes to parents' health over time. © The Author(s) 2015.

Study of the uses of Information and Communication Technologies by Pain Treatment Unit Physicians.

PubMed

Muriel Fernandez, Jorge; Sánchez Ledesma, María José; López Millan, Manuel; García Cenador, María Begoña

2017-05-01

Adequate use of Information and Communication Technologies (ICTs) in health has been shown to save the patient and caregiver time, improve access to the health system, improve diagnosis and control of disease or treatment. All this results in cost savings, and more importantly, they help improve the quality of service and the lives of patients. The purpose of this study is to analyse the differences in the uses of this ICTs between those physicians that belong to Pain Treatment Units (PU) and other physicians that work in pain not linked to these PUs. An online survey, generated by Netquest online survey tool, was sent to both groups of professionals and the data collected was statistical analysed through a logistic regression methodology which is the Logit binomial model. Our results show that those physicians that belong to PUs use ICTs more frequently and consider it more relevant to their clinical practice.

Clinical reasoning in feline epilepsy: Which combination of clinical information is useful?

PubMed

Stanciu, Gabriela-Dumitrita; Packer, Rowena Mary Anne; Pakozdy, Akos; Solcan, Gheorghe; Volk, Holger Andreas

2017-07-01

We sought to identify the association between clinical risk factors and the diagnosis of idiopathic epilepsy (IE) or structural epilepsy (SE) in cats, using statistical models to identify combinations of discrete parameters from the patient signalment, history and neurological examination findings that could suggest the most likely diagnosis. Data for 138 cats with recurrent seizures were reviewed, of which 110 were valid for inclusion. Seizure aetiology was classified as IE in 57% and SE in 43% of cats. Binomial logistic regression analyses demonstrated that pedigree status, older age at seizure onset (particularly >7years old), abnormal neurological examinations, and ictal vocalisation were associated with a diagnosis of SE compared to IE, and that ictal salivation was more likely to be associated with a diagnosis of IE than SE. These findings support the importance of considering inter-ictal neurological deficits and seizure history in clinical reasoning. Copyright © 2017 Elsevier Ltd. All rights reserved.

Health information exchange and healthcare utilization.

PubMed

Vest, Joshua R

2009-06-01

Health information exchange (HIE) makes previously inaccessible data available to clinicians, resulting in more complete information. This study tested the hypotheses that HIE information access reduced emergency room visits and inpatient hospitalizations for ambulatory care sensitive conditions among medically indigent adults. HIE access was quantified by how frequently system users' accessed patients' data. Encounter counts were modeled using zero inflated binomial regression. HIE was not accessed for 43% of individuals. Patient factors associated with accessed data included: prior utilization, chronic conditions, and age. Higher levels of information access were significantly associated with increased counts of all encounter types. Results indicate system users were more likely to access HIE for patients for whom the information might be considered most beneficial. Ultimately, these results imply that HIE information access did not transform care in the ways many would expect. Expectations in utilization reductions, however logical, may have to be reevaluated or postponed.

Adult Children’s Education and Parents’ Functional Limitations in Mexico

PubMed Central

Yahirun, Jenjira J.; Sheehan, Connor M.; Hayward, Mark D.

2016-01-01

This article asks how adult children’s education influences older parents’ physical health in Mexico, a context where older adults often lack access to institutional resources and rely on kin, primarily children, as a main source of support. Using logistic and negative binomial regression models and data from the first wave of the Mexican Health and Aging Study (N = 9,661), we find that parents whose children all completed high school are less likely to report any functional limitations as well as fewer limitations compared to parents with no children who completed high school. This association remains significant even after accounting for parent and offspring-level characteristics, including parents’ income that accounts for children’s financial transfers to parents. Future research should aim to understand the mechanisms that explain the association between adult children’s education and changes to parents’ health over time. PMID:26966254

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.

Use of clinical practice guidelines by dentists: findings from the Japanese dental practice-based research network.

PubMed

Kakudate, Naoki; Yokoyama, Yoko; Sumida, Futoshi; Matsumoto, Yuki; Gordan, Valeria V; Gilbert, Gregg H

2017-02-01

The objectives of this study were to: (1) examine differences in the use of dental clinical practice guidelines among Japanese dentists, and (2) identify characteristics associated with the number of guidelines used by participating dentists. We conducted a cross-sectional study consisting of a questionnaire survey in Japan between July 2014 and May 2015. The study queried dentists working in outpatient dental practices who are affiliated with the Dental Practice-Based Research Network Japan (n = 148). They were asked whether they have used each of 15 Japanese dental clinical guidelines. Associations between the number of guidelines used by participants and specific characteristics were analysed via negative binomial regression analysis. The mean number of guidelines used by participating dentists was 2.5 ± 2.9 [standard deviation (SD)]. Rate of use of guidelines showed substantial variation, from 5% to 34% among dentists. The proportion of dentists that used guidelines was the highest among oral medicine specialists, who had the highest proportion for 10 of 15 guidelines. Negative binomial regression analysis identified three factors significantly associated with the number of guidelines used: 'years since graduation from dental school', 'specialty practice' and 'practice busyness'. These results suggest that the use of clinical practice guidelines by Japanese dentists may still be inadequate. Training in the use of the guidelines could be given to dental students as undergraduate education and to young clinicians as continuing education. © 2016 John Wiley & Sons, Ltd.

Loneliness as a Public Health Issue: The Impact of Loneliness on Health Care Utilization Among Older Adults

PubMed Central

Jayawardhana, Jayani

2015-01-01

Objectives. We aimed to determine whether loneliness is associated with higher health care utilization among older adults in the United States. Methods. We used panel data from the Health and Retirement Study (2008 and 2012) to examine the long-term impact of loneliness on health care use. The sample was limited to community-dwelling persons in the United States aged 60 years and older. We used negative binomial regression models to determine the impact of loneliness on physician visits and hospitalizations. Results. Under 2 definitions of loneliness, we found that a sizable proportion of those aged 60 years and older in the United States reported loneliness. Regression results showed that chronic loneliness (those lonely both in 2008 and 4 years later) was significantly and positively associated with physician visits (β = 0.075, SE = 0.034). Loneliness was not significantly associated with hospitalizations. Conclusions. Loneliness is a significant public health concern among elders. In addition to easing a potential source of suffering, the identification and targeting of interventions for lonely elders may significantly decrease physician visits and health care costs. PMID:25790413

Resistant to the recession: low-income adults' maintenance of cooking and away-from-home eating behaviors during times of economic turbulence.

PubMed

Smith, Lindsey P; Ng, Shu Wen; Popkin, Barry M

2014-05-01

We examined the effects of state-level unemployment rates during the recession of 2008 on patterns of home food preparation and away-from-home (AFH) eating among low-income and minority populations. We analyzed pooled cross-sectional data on 118 635 adults aged 18 years or older who took part in the American Time Use Study. Multinomial logistic regression models stratified by gender were used to evaluate the associations between state-level unemployment, poverty, race/ethnicity, and time spent cooking, and log binomial regression was used to assess respondents' AFH consumption patterns. High state-level unemployment was associated with only trivial increases in respondents' cooking patterns and virtually no change in their AFH eating patterns. Low-income and racial/ethnic minority groups were not disproportionately affected by the recession. Even during a major economic downturn, US adults are resistant to food-related behavior change. More work is needed to understand whether this reluctance to change is attributable to time limits, lack of knowledge or skill related to food preparation, or lack of access to fresh produce and raw ingredients.

Resistant to the Recession: Low-Income Adults’ Maintenance of Cooking and Away-From-Home Eating Behaviors During Times of Economic Turbulence

PubMed Central

Smith, Lindsey P.; Ng, Shu Wen

2014-01-01

Objectives. We examined the effects of state-level unemployment rates during the recession of 2008 on patterns of home food preparation and away-from-home (AFH) eating among low-income and minority populations. Methods. We analyzed pooled cross-sectional data on 118 635 adults aged 18 years or older who took part in the American Time Use Study. Multinomial logistic regression models stratified by gender were used to evaluate the associations between state-level unemployment, poverty, race/ethnicity, and time spent cooking, and log binomial regression was used to assess respondents’ AFH consumption patterns. Results. High state-level unemployment was associated with only trivial increases in respondents’ cooking patterns and virtually no change in their AFH eating patterns. Low-income and racial/ethnic minority groups were not disproportionately affected by the recession. Conclusions. Even during a major economic downturn, US adults are resistant to food-related behavior change. More work is needed to understand whether this reluctance to change is attributable to time limits, lack of knowledge or skill related to food preparation, or lack of access to fresh produce and raw ingredients. PMID:24625145

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.

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.

Longitudinal Analysis of Gender Differences in Academic Productivity among Medical Faculty across 24 Medical Schools in the United States

PubMed Central

Raj, Anita; Carr, Phyllis L.; Kaplan, Samantha E.; Terrin, Norma; Breeze, Janis L.; Freund, Karen M.

2017-01-01

Purpose This study examines gender differences in academic productivity, as indicated by publications and federal grant funding acquisition, among a longitudinal cohort of medical faculty from 24 medical schools across the United States, 1995 to 2012. Method Data for this research was taken from the National Faculty Study involving a survey with medical faculty recruited from medical schools in 1995, and followed up in 2012. Data included surveys and publication and grant funding databases. Outcomes were number of publications, h-index and principal investigator on a federal grant in the prior two years. Gender differences were assessed using negative binomial regression models for publication and h-index outcomes, and logistic regression for the grant funding outcome; analyses adjusted for race/ethnicity, rank, specialty area and years since first academic appointment. Results Data were available for 1,244 of the 1,275 (98%) subjects eligible for the follow up study. Men were significantly more likely than women to be married/partnered, have children, and hold the rank of professor (P < .0001). Adjusted regression models document that women have a lower rate of publication (relative number = .71; 95% CI = .63, .81; P < .0001) and h-index (relative number = .81; 95% CI = .73, .90; P < .0001) relative to men, though there was no gender difference in grant funding. Conclusions Women faculty acquire federal funding at similar rates as male faculty, yet lag behind in terms of publications and their impact. Medical academia must consider how to help address ongoing gender disparities in publication records. PMID:27276002

An analysis of first-time blood donors return behaviour using regression models.

PubMed

Kheiri, S; Alibeigi, Z

2015-08-01

Blood products have a vital role in saving many patients' lives. The aim of this study was to analyse blood donor return behaviour. Using a cross-sectional follow-up design of 5-year duration, 864 first-time donors who had donated blood were selected using a systematic sampling. The behaviours of donors via three response variables, return to donation, frequency of return to donation and the time interval between donations, were analysed based on logistic regression, negative binomial regression and Cox's shared frailty model for recurrent events respectively. Successful return to donation rated at 49·1% and the deferral rate was 13·3%. There was a significant reverse relationship between the frequency of return to donation and the time interval between donations. Sex, body weight and job had an effect on return to donation; weight and frequency of donation during the first year had a direct effect on the total frequency of donations. Age, weight and job had a significant effect on the time intervals between donations. Aging decreases the chances of return to donation and increases the time interval between donations. Body weight affects the three response variables, i.e. the higher the weight, the more the chances of return to donation and the shorter the time interval between donations. There is a positive correlation between the frequency of donations in the first year and the total number of return to donations. Also, the shorter the time interval between donations is, the higher the frequency of donations. © 2015 British Blood Transfusion Society.

Clinicians' adherence to clinical practice guidelines for cardiac function monitoring during antipsychotic treatment: a retrospective report on 434 patients with severe mental illness.

PubMed

Manchia, Mirko; Firinu, Giorgio; Carpiniello, Bernardo; Pinna, Federica

2017-03-31

Severe mental illness (SMI) has considerable excess morbidity and mortality, a proportion of which is explained by cardiovascular diseases, caused in part by antipsychotic (AP) induced QT-related arrhythmias and sudden death by Torsade de Point (TdP). The implementation of evidence-based recommendations for cardiac function monitoring might reduce the incidence of these AP-related adverse events. To investigate clinicians' adherence to cardiac function monitoring before and after starting AP, we performed a retrospective assessment of 434 AP-treated SMI patients longitudinally followed-up for 5 years at an academic community mental health center. We classified antipsychotics according to their risk of inducing QT-related arrhythmias and TdP (Center for Research on Therapeutics, University of Arizona). We used univariate tests and multinomial or binary logistic regression model for data analysis. Univariate and multinomial regression analysis showed that psychiatrists were more likely to perform pre-treatment electrocardiogram (ECG) and electrolyte testing with AP carrying higher cardiovascular risk, but not on the basis of AP pharmacological class. Univariate and binomial regression analysis showed that cardiac function parameters (ECG and electrolyte balance) were more frequently monitored during treatment with second generation AP than with first generation AP. Our data show the presence of weaknesses in the cardiac function monitoring of AP-treated SMI patients, and might guide future interventions to tackle them.

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.

Consumption of fast food, sugar-sweetened beverages, artificially-sweetened beverages and allostatic load among young adults.

PubMed

van Draanen, Jenna; Prelip, Michael; Upchurch, Dawn M

2018-06-01

This study investigates the associations between recent consumption of fast foods, sugar-sweetened beverages, and artificially-sweetened beverages on level of allostatic load, a measure of cumulative biological risk, in young adults in the US. Data from Wave IV of the National Longitudinal Study of Adolescent to Adult Health were analyzed. Negative binomial regression models were used to estimate the associations between consumption of fast foods, sugar-sweetened, and artificially-sweetened beverages and allostatic load. Poisson and logistic regression models were used to estimate the associations between these diet parameters and combined biomarkers of physiological subsystems that comprise our measure of allostatic load. All analyses were weighted and findings are representative of young adults in the US, ages 24-34 in 2008 (n = 11,562). Consumption of fast foods, sugar-sweetened, and artificially-sweetened beverages were associated with higher allostatic load at a bivariate level. Accounting for demographics and medication use, only artificially-sweetened beverages remained significantly associated with allostatic load. When all three dietary components were simultaneously included in a model, both sugar- and artificially-sweetened beverage consumption were associated with higher allostatic load. Differences in allostatic load emerge early in the life course and young adults consuming sugar- or artificially-sweetened beverages have higher allostatic load, net of demographics and medication use. Public health messages to young adults may need to include cautions about both sugar- and artificially-sweetened beverages.

Hydrological modeling of geophysical parameters of arboviral and protozoan disease vectors in Internally Displaced People camps in Gulu, Uganda.

PubMed

Jacob, Benjamin G; Muturi, Ephantus J; Caamano, Erick X; Gunter, James T; Mpanga, Enoch; Ayine, Robert; Okelloonen, Joseph; Nyeko, Jack Pen-Mogi; Shililu, Josephat I; Githure, John I; Regens, James L; Novak, Robert J; Kakoma, Ibulaimu

2008-03-14

The aim of this study was to determine if remotely sensed data and Digital Elevation Model (DEM) can test relationships between Culex quinquefasciatus and Anopheles gambiae s.l. larval habitats and environmental parameters within Internally Displaced People (IDP) campgrounds in Gulu, Uganda. A total of 65 georeferenced aquatic habitats in various IDP camps were studied to compare the larval abundance of Cx. quinquefasciatus and An. gambiae s.l. The aquatic habitat dataset were overlaid onto Land Use Land Cover (LULC) maps retrieved from Landsat imagery with 150 m x 150 m grid cells stratified by levels of drainage. The LULC change was estimated over a period of 14 years. Poisson regression analyses and Moran's I statistics were used to model relationships between larval abundance and environmental predictors. Individual larval habitat data were further evaluated in terms of their covariations with spatial autocorrelation by regressing them on candidate spatial filter eigenvectors. Multispectral QuickBird imagery classification and DEM-based GIS methods were generated to evaluate stream flow direction and accumulation for identification of immature Cx. quinquefasciatus and An. gambiae s.l. and abundance. The main LULC change in urban Gulu IDP camps was non-urban to urban, which included about 71.5 % of the land cover. The regression models indicate that counts of An. gambiae s.l. larvae were associated with shade while Cx. quinquefasciatus were associated with floating vegetation. Moran's I and the General G statistics for mosquito density by species and instars, identified significant clusters of high densities of Anopheles; larvae, however, Culex are not consistently clustered. A stepwise negative binomial regression decomposed the immature An. gambiae s.l. data into empirical orthogonal bases. The data suggest the presence of roughly 11% to 28 % redundant information in the larval count samples. The DEM suggest a positive correlation for Culex (0.24) while for Anopheles there was a negative correlation (-0.23) for a local model distance to stream. These data demonstrate that optical remote sensing; geostatistics and DEMs can be used to identify parameters associated with Culex and Anopheles aquatic habitats.

Hydrological modeling of geophysical parameters of arboviral and protozoan disease vectors in Internally Displaced People camps in Gulu, Uganda

PubMed Central

Jacob, Benjamin G; Muturi, Ephantus J; Caamano, Erick X; Gunter, James T; Mpanga, Enoch; Ayine, Robert; Okelloonen, Joseph; Nyeko, Jack Pen-Mogi; Shililu, Josephat I; Githure, John I; Regens, James L; Novak, Robert J; Kakoma, Ibulaimu

2008-01-01

Background The aim of this study was to determine if remotely sensed data and Digital Elevation Model (DEM) can test relationships between Culex quinquefasciatus and Anopheles gambiae s.l. larval habitats and environmental parameters within Internally Displaced People (IDP) campgrounds in Gulu, Uganda. A total of 65 georeferenced aquatic habitats in various IDP camps were studied to compare the larval abundance of Cx. quinquefasciatus and An. gambiae s.l. The aquatic habitat dataset were overlaid onto Land Use Land Cover (LULC) maps retrieved from Landsat imagery with 150 m × 150 m grid cells stratified by levels of drainage. The LULC change was estimated over a period of 14 years. Poisson regression analyses and Moran's I statistics were used to model relationships between larval abundance and environmental predictors. Individual larval habitat data were further evaluated in terms of their covariations with spatial autocorrelation by regressing them on candidate spatial filter eigenvectors. Multispectral QuickBird imagery classification and DEM-based GIS methods were generated to evaluate stream flow direction and accumulation for identification of immature Cx. quinquefasciatus and An. gambiae s.l. and abundance. Results The main LULC change in urban Gulu IDP camps was non-urban to urban, which included about 71.5 % of the land cover. The regression models indicate that counts of An. gambiae s.l. larvae were associated with shade while Cx. quinquefasciatus were associated with floating vegetation. Moran's I and the General G statistics for mosquito density by species and instars, identified significant clusters of high densities of Anopheles; larvae, however, Culex are not consistently clustered. A stepwise negative binomial regression decomposed the immature An. gambiae s.l. data into empirical orthogonal bases. The data suggest the presence of roughly 11% to 28 % redundant information in the larval count samples. The DEM suggest a positive correlation for Culex (0.24) while for Anopheles there was a negative correlation (-0.23) for a local model distance to stream. Conclusion These data demonstrate that optical remote sensing; geostatistics and DEMs can be used to identify parameters associated with Culex and Anopheles aquatic habitats. PMID:18341699

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.

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.

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.

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.

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.

Can Bayesian models play a role in dental caries epidemiology? Evidence from an application to the BELCAP data set.

PubMed

Matranga, Domenica; Firenze, Alberto; Vullo, Angela

2013-10-01

The aim of this study was to show the potential of Bayesian analysis in statistical modelling of dental caries data. Because of the bounded nature of the dmft (DMFT) index, zero-inflated binomial (ZIB) and beta-binomial (ZIBB) models were considered. The effects of incorporating prior information available about the parameters of models were also shown. The data set used in this study was the Belo Horizonte Caries Prevention (BELCAP) study (Böhning et al. (1999)), consisting of five variables collected among 797 Brazilian school children designed to evaluate four programmes for reducing caries. Only the eight primary molar teeth were considered in the data set. A data augmentation algorithm was used for estimation. Firstly, noninformative priors were used to express our lack of knowledge about the regression parameters. Secondly, prior information about the probability of being a structural zero dmft and the probability of being caries affected in the subpopulation of susceptible children was incorporated. With noninformative priors, the best fitting model was the ZIBB. Education (OR = 0.76, 95% CrI: 0.59, 0.99), all interventions (OR = 0.46, 95% CrI: 0.35, 0.62), rinsing (OR = 0.61, 95% CrI: 0.47, 0.80) and hygiene (OR = 0.65, 95% CrI: 0.49, 0.86) were demonstrated to be factors protecting children from being caries affected. Being male increased the probability of being caries diseased (OR = 1.19, 95% CrI: 1.01, 1.42). However, after incorporating informative priors, ZIB models' estimates were not influenced, while ZIBB models reduced deviance and confirmed the association with all interventions and rinsing only. In our application, Bayesian estimates showed a similar accuracy and precision than likelihood-based estimates, although they offered many computational advantages and the possibility of expressing all forms of uncertainty in terms of probability. The overdispersion parameter could expound why the introduction of prior information had significant effects on the parameters of the ZIBB model, while ZIB estimates remained unchanged. Finally, the best performance of ZIBB compared to the ZIB model was shown to catch overdispersion in data. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

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...

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.

Seasonality of Viral Encephalitis and Associated Environmental Risk Factors in Son La and Thai Binh Provinces in Vietnam from 2004 to 2013.

PubMed

Lee, Hu Suk; Nguyen-Viet, Hung; Lee, Mihye; Duc, Phuc Pham; Grace, Delia

2017-01-11

In Vietnam, Japanese encephalitis virus accounts for 12-71% of viral encephalitis (VE) cases followed by enteroviruses and dengue virus among identified pathogens. This study is the first attempt to evaluate the seasonality of VE and associated environmental risk factors in two provinces from 2004 to 2013 using a seasonal trend-decomposition procedure based on loess regression and negative binomial regression models. We found seasonality with a peak of VE in August and June in Son La and Thai Binh, respectively. In Son La, the model showed that for every 1°C increase in average monthly temperature, there was a 4.0% increase in monthly VE incidence. There was a gradual decline in incidence rates as the relative humidity rose to its mean value (80%) and a dramatic rise in incidence rate as the relative humidity rose past 80%. Another model found that a 100 mm rise in precipitation in the preceding and same months corresponded to an increase in VE incidence of 23% and 21%, respectively. In Thai Binh, our model showed that a 1°C increase in temperature corresponded with a 9% increase in VE incidence. Another model found that VE incidence increased as monthly precipitation rose to its mean value of 130 mm but declined gradually as precipitation levels rose beyond that. The last model showed that a monthly increase in duration of sunshine of 1 hour corresponded to a 0.6% increase in VE incidence. The findings may assist clinicians by improving the evidence for diagnosis. © The American Society of Tropical Medicine and Hygiene.

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.

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.

An integrated model for detecting significant chromatin interactions from high-resolution Hi-C data

PubMed Central

Carty, Mark; Zamparo, Lee; Sahin, Merve; González, Alvaro; Pelossof, Raphael; Elemento, Olivier; Leslie, Christina S.

2017-01-01

Here we present HiC-DC, a principled method to estimate the statistical significance (P values) of chromatin interactions from Hi-C experiments. HiC-DC uses hurdle negative binomial regression account for systematic sources of variation in Hi-C read counts—for example, distance-dependent random polymer ligation and GC content and mappability bias—and model zero inflation and overdispersion. Applied to high-resolution Hi-C data in a lymphoblastoid cell line, HiC-DC detects significant interactions at the sub-topologically associating domain level, identifying potential structural and regulatory interactions supported by CTCF binding sites, DNase accessibility, and/or active histone marks. CTCF-associated interactions are most strongly enriched in the middle genomic distance range (∼700 kb–1.5 Mb), while interactions involving actively marked DNase accessible elements are enriched both at short (<500 kb) and longer (>1.5 Mb) genomic distances. There is a striking enrichment of longer-range interactions connecting replication-dependent histone genes on chromosome 6, potentially representing the chromatin architecture at the histone locus body. PMID:28513628

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.

Gun control and suicide: the impact of state firearm regulations in the United States, 1995-2004.

PubMed

Rodríguez Andrés, Antonio; Hempstead, Katherine

2011-06-01

To empirically assess the impact of firearm regulation on male suicides. A negative binomial regression model was applied by using a panel of state level data for the years 1995-2004. The model was used to identify the association between several firearm regulations and male suicide rates. Our empirical analysis suggest that firearms regulations which function to reduce overall gun availability have a significant deterrent effect on male suicide, while regulations that seek to prohibit high risk individuals from owning firearms have a lesser effect. Restricting access to lethal means has been identified as an effective approach to suicide prevention, and firearms regulations are one way to reduce gun availability. The analysis suggests that gun control measures such as permit and licensing requirements have a negative effect on suicide rates among males. Since there is considerable heterogeneity among states with regard to gun control, these results suggest that there are opportunities for many states to reduce suicide by expanding their firearms regulations. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Hope and Hopelessness: The Role of Hope in Buffering the Impact of Hopelessness on Suicidal Ideation

PubMed Central

Huen, Jenny M. Y.; Ip, Brian Y. T.; Ho, Samuel M. Y.; Yip, Paul S. F.

2015-01-01

Objectives 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. Methods Hope, hopelessness, and suicidal ideation were measured in a community sample of 2106 participants through a population-based household survey. Results 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. Conclusions 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. PMID:26107687

Social vulnerability and the natural and built environment: a model of flood casualties in Texas.

PubMed

Zahran, Sammy; Brody, Samuel D; Peacock, Walter Gillis; Vedlitz, Arnold; Grover, Himanshu

2008-12-01

Studies on the impacts of hurricanes, tropical storms, and tornados indicate that poor communities of colour suffer disproportionately in human death and injury.(2) Few quantitative studies have been conducted on the degree to which flood events affect socially vulnerable populations. We address this research void by analysing 832 countywide flood events in Texas from 1997-2001. Specifically, we examine whether geographic localities characterised by high percentages of socially vulnerable populations experience significantly more casualties due to flood events, adjusting for characteristics of the natural and built environment. Zero-inflated negative binomial regression models indicate that the odds of a flood casualty increase with the level of precipitation on the day of a flood event, flood duration, property damage caused by the flood, population density, and the presence of socially vulnerable populations. Odds decrease with the number of dams, the level of precipitation on the day before a recorded flood event, and the extent to which localities have enacted flood mitigation strategies. The study concludes with comments on hazard-resilient communities and protection of casualty-prone populations.

Individual-level exposure to disaster, neighborhood environmental characteristics, and their independent and combined associations with depressive symptoms in women.

PubMed

Gaston, Symielle A; Volaufova, Julia; Peters, Edward S; Ferguson, Tekeda F; Robinson, William T; Nugent, Nicole; Trapido, Edward J; Rung, Ariane L

2017-09-01

The severity of the stress response to experiencing disaster depends on individual exposure and background stress prior to the event. To date, there is limited research on the interaction between neighborhood environmental stress and experiencing an oil spill, and their effects on depression. The objective of the current study was to assess if the association between exposure to the Deepwater Horizon Oil Spill (DHOS) and depressive symptoms varied by neighborhood characteristics. US Census data (2010) and longitudinal data collected in two waves (2012-2014 and 2014-2016) from female residents [N = 889 (Wave I), 737 (Wave II)] of an area highly affected by the DHOS were analyzed. Multilevel and individual-level negative binomial regressions were performed to estimate associations with depressive symptoms in both waves. An interaction term was included to estimate effect modification of the association between DHOS exposure and depressive symptoms by neighborhood characteristics. Generalized estimating equations were applied to the negative binomial regression testing longitudinal associations. Census tract-level neighborhood characteristics were not associated with depressive symptoms. Exposure to the DHOS and neighborhood physical disorder were associated with depressive symptoms cross-sectionally. There was no evidence of effect modification; however, physical/environmental exposure to the DHOS was associated with increased depressive symptoms only among women living in areas with physical disorder. Exposure to the DHOS remained associated with depressive symptoms over time. Findings support the enduring consequences of disaster exposure on depressive symptoms in women and identify potential targets for post-disaster intervention based on residential characteristics.

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.

Continuity Between DSM-5 Section II and III Personality Disorders in a Dutch Clinical Sample.

PubMed

Orbons, Irene M J; Rossi, Gina; Verheul, Roel; Schoutrop, Mirjam J A; Derksen, Jan L L; Segal, Daniel L; van Alphen, Sebastiaan P J

2018-05-14

The goal of this study was to evaluate the continuity across the Section II personality disorders (PDs) and the proposed Section III model of PDs in the Diagnostic and Statistical Manual of Mental Disorders (5th ed. [DSM-5]; American Psychiatric Association, 2013a ). More specifically, we analyzed association between the DSM-5 Section III pathological trait facets and Section II PDs among 110 Dutch adults (M age = 35.8 years, range = 19-60 years) receiving mental health care. We administered the Structured Clinical Interview for DSM-IV Axis II Disorders to all participants. Participants also completed the self-report Personality Inventory for DSM-5 (PID-5) as a measure of pathological trait facets. The distributions underlying the dependent variable were modeled as criterion counts, using negative binomial regression. The results provided some support for the validity of the PID-5 and the DSM-5 Section III Alternative Model, although analyses did not show a perfect match. Both at the trait level and the domain level, analyses showed mixed evidence of significant relationships between the PID-5 trait facets and domains with the traditional DSM-IV PDs.

Associations among habitat characteristics and meningeal worm prevalence in eastern South Dakota, USA

USGS Publications Warehouse

Jacques, Christopher N.; Jenks, Jonathan A.; Klaver, Robert W.; Dubay, Shelli A.

2017-01-01

Few studies have evaluated how wetland and forest characteristics influence the prevalence of meningeal worm (Parelaphostrongylus tenuis) infection of deer throughout the grassland biome of central North America. We used previously collected, county-level prevalence data to evaluate associations between habitat characteristics and probability of meningeal worm infection in white-tailed deer (Odocoileus virginianus) across eastern South Dakota, US. The highest-ranked binomial regression model for detecting probability of meningeal worm infection was spring temperature + summer precipitation + percent wetland; weight of evidence (wi=0.71) favored this model over alternative models, though predictive capability was low (Receiver operating characteristic=0.62). Probability of meningeal worm infection increased by 1.3- and 1.6-fold for each 1-cm and 1-C increase in summer precipitation and spring temperature, respectively. Similarly, probability of infection increased 1.2-fold for each 1% increase in wetland habitat. Our findings highlight the importance of wetland habitat in predicting meningeal worm infection across eastern South Dakota. Future research is warranted to evaluate the relationships between climatic conditions (e.g., drought, wet cycles) and deer habitat selection in maintaining P. tenuis along the western boundary of the parasite.

Using exceedance probabilities to detect anomalies in routinely recorded animal health data, with particular reference to foot-and-mouth disease in Viet Nam.

PubMed

Richards, K K; Hazelton, M L; Stevenson, M A; Lockhart, C Y; Pinto, J; Nguyen, L

2014-10-01

The widespread availability of computer hardware and software for recording and storing disease event information means that, in theory, we have the necessary information to carry out detailed analyses of factors influencing the spatial distribution of disease in animal populations. However, the reliability of such analyses depends on data quality, with anomalous records having the potential to introduce significant bias and lead to inappropriate decision making. In this paper we promote the use of exceedance probabilities as a tool for detecting anomalies when applying hierarchical spatio-temporal models to animal health data. We illustrate this methodology through a case study data on outbreaks of foot-and-mouth disease (FMD) in Viet Nam for the period 2006-2008. A flexible binomial logistic regression was employed to model the number of FMD infected communes within each province of the country. Standard analyses of the residuals from this model failed to identify problems, but exceedance probabilities identified provinces in which the number of reported FMD outbreaks was unexpectedly low. This finding is interesting given that these provinces are on major cattle movement pathways through Viet Nam. Copyright © 2014 Elsevier Ltd. All rights reserved.

Serum Vitamin D Levels and Markers of Severity of Childhood Asthma in Costa Rica

PubMed Central

Brehm, John M.; Celedón, Juan C.; Soto-Quiros, Manuel E.; Avila, Lydiana; Hunninghake, Gary M.; Forno, Erick; Laskey, Daniel; Sylvia, Jody S.; Hollis, Bruce W.; Weiss, Scott T.; Litonjua, Augusto A.

2009-01-01

Rationale: Maternal vitamin D intake during pregnancy has been inversely associated with asthma symptoms in early childhood. However, no study has examined the relationship between measured vitamin D levels and markers of asthma severity in childhood. Objectives: To determine the relationship between measured vitamin D levels and both markers of asthma severity and allergy in childhood. Methods: We examined the relation between 25-hydroxyvitamin D levels (the major circulating form of vitamin D) and markers of allergy and asthma severity in a cross-sectional study of 616 Costa Rican children between the ages of 6 and 14 years. Linear, logistic, and negative binomial regressions were used for the univariate and multivariate analyses. Measurements and Main Results: Of the 616 children with asthma, 175 (28%) had insufficient levels of vitamin D (<30 ng/ml). In multivariate linear regression models, vitamin D levels were significantly and inversely associated with total IgE and eosinophil count. In multivariate logistic regression models, a log10 unit increase in vitamin D levels was associated with reduced odds of any hospitalization in the previous year (odds ratio [OR], 0.05; 95% confidence interval [CI], 0.004–0.71; P = 0.03), any use of antiinflammatory medications in the previous year (OR, 0.18; 95% CI, 0.05–0.67; P = 0.01), and increased airway responsiveness (a ≤8.58-μmol provocative dose of methacholine producing a 20% fall in baseline FEV1 [OR, 0.15; 95% CI, 0.024–0.97; P = 0.05]). Conclusions: Our results suggest that vitamin D insufficiency is relatively frequent in an equatorial population of children with asthma. In these children, lower vitamin D levels are associated with increased markers of allergy and asthma severity. PMID:19179486

Black Clouds vs Random Variation in Hospital Admissions.

PubMed

Ong, Luei Wern; Dawson, Jeffrey D; Ely, John W

2018-06-01

Physicians often accuse their peers of being "black clouds" if they repeatedly have more than the average number of hospital admissions while on call. Our purpose was to determine whether the black-cloud phenomenon is real or explainable by random variation. We analyzed hospital admissions to the University of Iowa family medicine service from July 1, 2010 to June 30, 2015. Analyses were stratified by peer group (eg, night shift attending physicians, day shift senior residents). We analyzed admission numbers to find evidence of black-cloud physicians (those with significantly more admissions than their peers) and white-cloud physicians (those with significantly fewer admissions). The statistical significance of whether there were actual differences across physicians was tested with mixed-effects negative binomial regression. The 5-year study included 96 physicians and 6,194 admissions. The number of daytime admissions ranged from 0 to 10 (mean 2.17, SD 1.63). Night admissions ranged from 0 to 11 (mean 1.23, SD 1.22). Admissions increased from 1,016 in the first year to 1,523 in the fifth year. We found 18 white-cloud and 16 black-cloud physicians in simple regression models that did not control for this upward trend. After including study year and other potential confounding variables in the regression models, there were no significant associations between physicians and admission numbers and therefore no true black or white clouds. In this study, apparent black-cloud and white-cloud physicians could be explained by random variation in hospital admissions. However, this randomness incorporated a wide range in workload among physicians, with potential impact on resident education at the low end and patient safety at the high end.

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

Influences on physicians' adoption of electronic detailing (e-detailing).

PubMed

Alkhateeb, Fadi M; Doucette, William R

2009-01-01

E-detailing means using digital technology: internet, video conferencing and interactive voice response. There are two types of e-detailing: interactive (virtual) and video. Currently, little is known about what factors influence physicians' adoption of e-detailing. The objectives of this study were to test a model of physicians' adoption of e-detailing and to describe physicians using e-detailing. A mail survey was sent to a random sample of 2000 physicians practicing in Iowa. Binomial logistic regression was used to test the model of influences on physician adoption of e-detailing. On the basis of Rogers' model of adoption, the independent variables included relative advantage, compatibility, complexity, peer influence, attitudes, years in practice, presence of restrictive access to traditional detailing, type of specialty, academic affiliation, type of practice setting and control variables. A total of 671 responses were received giving a response rate of 34.7%. A total of 141 physicians (21.0%) reported using of e-detailing. The overall adoption model for using either type of e-detailing was found to be significant. Relative advantage, peer influence, attitudes, type of specialty, presence of restrictive access and years of practice had significant influences on physician adoption of e-detailing. The model of adoption of innovation is useful to explain physicians' adoption of e-detailing.

Effects of Cognition, Function, and Behavioral and Psychological Symptoms on Medicare Expenditures and Health Care Utilization for Persons With Dementia.

PubMed

Jutkowitz, Eric; Kane, Robert L; Dowd, Bryan; Gaugler, Joseph E; MacLehose, Richard F; Kuntz, Karen M

2017-06-01

Clinical features of dementia (cognition, function, and behavioral/psychological symptoms [BPSD]) may differentially affect Medicare expenditures/health care utilization. We linked cross-sectional data from the Aging, Demographics, and Memory Study to Medicare data to evaluate the association between dementia clinical features among those with dementia and Medicare expenditures/health care utilization (n = 234). Cognition was evaluated using the Mini-Mental State Examination (MMSE). Function was evaluated as the number of functional limitations (0-10). BPSD was evaluated as the number of symptoms (0-12). Expenditures were estimated with a generalized linear model (log-link and gamma distribution). Number of hospitalizations, institutional outpatient visits, and physician visits were estimated with a negative binomial regression. Medicare covered skilled nursing days were estimated with a zero-inflated negative binomial model. Cognition and BPSD were not associated with expenditures. Among individuals with less than seven functional limitations, one additional limitation was associated with $123 (95% confidence interval: $19-$227) additional monthly Medicare spending. Better cognition and poorer function were associated with more hospitalizations among those with an MMSE less than three and less than six functional limitations, respectively. BPSD had no effect on hospitalizations. Poorer function and fewer BPSD were associated with more skilled nursing among individuals with one to seven functional limitations and more than four symptoms, respectively. Cognition had no effect on skilled nursing care. No clinical feature was associated with institutional outpatient care. Of individuals with an MMSE less than 15, poorer cognition was associated with fewer physician visits. Among those with more than six functional limitations, poorer function was associated with fewer physician visits. Poorer function, not cognition or BPSD, was associated with higher Medicare expenditures. © The Author 2017. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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...

Intraurban Differences in the Use of Ambulatory Health Services in a Large Brazilian City

PubMed Central

Lima-Costa, Maria Fernanda; Proietti, Fernando Augusto; Cesar, Cibele C.; Macinko, James

2010-01-01

A major goal of health systems is to reduce inequities in access to services, that is, to ensure that health care is provided based on health needs rather than social or economic factors. This study aims to identify the determinants of health services utilization among adults in a large Brazilian city and intraurban disparities in health care use. We combine household survey data with census-derived classification of social vulnerability of each household’s census tract. The dependent variable was utilization of physician services in the prior 12 months, and the independent variables included predisposing factors, health needs, enabling factors, and context. Prevalence ratios and 95% confidence intervals were estimated by the Hurdle regression model, which combined Poisson regression analysis of factors associated with any doctor visits (dichotomous variable) and zero-truncated negative binomial regression for the analysis of factors associated with the number of visits among those who had at least one. Results indicate that the use of health services was greater among women and increased with age, and was determined primarily by health needs and whether the individual had a regular doctor, even among those living in areas of the city with the worst socio-environmental indicators. The experience of Belo Horizonte may have implications for other world cities, particularly in the development and use of a comprehensive index to identify populations at risk and in order to guide expansion of primary health care services as a means of enhancing equity in health. PMID:21104332

Risk factors for persistent cervical intraepithelial neoplasia grades 1 and 2: managed by watchful waiting.

PubMed

Ho, Gloria Y F; Einstein, Mark H; Romney, Seymour L; Kadish, Anna S; Abadi, Maria; Mikhail, Magdy; Basu, Jayasri; Thysen, Benjamin; Reimers, Laura; Palan, Prabhudas R; Trim, Shelly; Soroudi, Nafisseh; Burk, Robert D

2011-10-01

: This study examines risk factors for persistent cervical intraepithelial neoplasia (CIN) and examines whether human papillomavirus (HPV) testing predicts persistent lesions. : Women with histologically diagnosed CIN 1 or CIN 2 (n = 206) were followed up every 3 months without treatment. Human papillomavirus genotyping, plasma levels of ascorbic acid, and red blood cell folate levels were obtained. Cervical biopsy at 12 months determined the presence of CIN. Relative risk (RR) was estimated by log-linked binomial regression models. : At 12 months, 70% of CIN 1 versus 54% of CIN 2 lesions spontaneously regressed (p < .001). Levels of folate or ascorbic acid were not associated with persistent CIN at 12 months. Compared with HPV-negative women, those with multiple HPV types (RRs ranged from 1.68 to 2.17 at each follow-up visit) or high-risk types (RRs range = 1.74-2.09) were at increased risk for persistent CIN; women with HPV-16/18 had the highest risk (RRs range = 1.91-2.21). Persistent infection with a high-risk type was also associated with persistent CIN (RRs range = 1.50-2.35). Typing for high-risk HPVs at 6 months only had a sensitivity of 46% in predicting persistence of any lesions at 12 months. : Spontaneous regression of CIN 1 and 2 occurs frequently within 12 months. Human papillomavirus infection is the major risk factor for persistent CIN. However, HPV testing cannot reliably predict persistence of any lesion.

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.

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.

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…

Harnessing Youth and Young Adult Culture: Improving the Reach and Engagement of the truth® Campaign.

PubMed

Hair, Elizabeth; Pitzer, Lindsay; Bennett, Morgane; Halenar, Michael; Rath, Jessica; Cantrell, Jennifer; Dorrler, Nicole; Asche, Eric; Vallone, Donna

2017-07-01

The national youth and young adult tobacco prevention mass media campaign, truth®, relaunched in 2014 with the goal of creating "the generation that ends smoking." The objective of this study was to assess whether the strategy of airing truth ads during popular, culturally relevant televised events was associated with higher ad and brand awareness and increases in social media engagement. Awareness of six truth advertisements that aired during popular television events and self-reported social media engagement were assessed via cross-sectional online surveys of youth and young adults aged 15-21 years. Social engagement was also measured using separate Twitter and YouTube metrics. Logistic regression models predicted self-reported social engagement and any ad awareness, and a negative binomial regression predicted the total social media engagement across digital platforms. The study found that viewing a popular televised event was associated with higher odds of ad awareness and social engagement. The results also indicate that levels of social media engagement for an event period are greater than for a nonevent period. The findings demonstrate that premiering advertisements during a popular, culturally relevant televised event is associated with higher awareness of truth ads and increased social engagement related to the campaign, controlling for variables that might also influence the response to campaign messages.

Secondhand smoke exposure in the workplace.

PubMed

Skeer, Margie; Cheng, Debbie M; Rigotti, Nancy A; Siegel, Michael

2005-05-01

Currently, there is little understanding of the relationship between the strength of workplace smoking policies and the likelihood and duration, not just the likelihood, of exposure to secondhand smoke at work. This study assessed self-reported exposure to secondhand smoke at work in hours per week among a cross-sectional sample of 3650 Massachusetts adults who were employed primarily at a single worksite outside the home that was not mainly outdoors. The sample data were from a larger longitudinal study designed to examine the effect of community-based tobacco control interventions on adult and youth smoking behavior. Participants were identified through a random-digit-dialing telephone survey. Multiple logistic regression and zero-inflated negative binomial regression models were used to estimate the independent effect of workplace smoking policies on the likelihood and duration of exposure to secondhand smoke. Compared to employees whose workplace banned smoking completely, those whose workplace provided designated smoking areas had 2.9 times the odds of being exposed to secondhand smoke and 1.74 times the duration of exposure, while those with no restrictions had 10.27 times the odds of being exposed and 6.34 times the duration of exposure. Workplace smoking policies substantially reduce the likelihood of self-reported secondhand smoke exposure among employees in the workplace and also greatly affect the duration of exposure.

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.

The influence of neighborhood characteristics on the relationship between discrimination and increased drug-using social ties among illicit drug users.

PubMed

Crawford, Natalie D; Borrell, Luisa N; Galea, Sandro; Ford, Chandra; Latkin, Carl; Fuller, Crystal M

2013-04-01

Social discrimination may isolate drug users into higher risk relationships, particularly in disadvantaged neighborhood environments where drug trade occurs. We used negative binomial regression accounting for clustering of individuals within their recruitment neighborhood to investigate the relationship between high-risk drug ties with various forms of social discrimination, neighborhood minority composition, poverty and education. Results show that experiencing discrimination due to drug use is significantly associated with more drug ties in neighborhoods with fewer blacks. Future social network and discrimination research should assess the role of neighborhood social cohesion.

Modeling Zero-Inflated and Overdispersed Count Data: An Empirical Study of School Suspensions

ERIC Educational Resources Information Center

Desjardins, Christopher David

2016-01-01

The purpose of this article is to develop a statistical model that best explains variability in the number of school days suspended. Number of school days suspended is a count variable that may be zero-inflated and overdispersed relative to a Poisson model. Four models were examined: Poisson, negative binomial, Poisson hurdle, and negative…

Children at risk: A comparison of child pedestrian traffic collisions in Santiago, Chile, and Seoul, South Korea.

PubMed

Blazquez, Carola; Lee, Jae Seung; Zegras, Christopher

2016-01-01

We examine and compare pedestrian-vehicle collisions and injury outcomes involving school-age children between 5 and 18 years of age in the capital cities of Santiago, Chile, and Seoul, South Korea. We conduct descriptive analysis of the child pedestrian-vehicle collision (P-VC) data (904 collisions for Santiago and 3,505 for Seoul) reported by the police between 2010 and 2011. We also statistically analyze factors associated with child P-VCs, by both incident severity and age group, using 3 regression models: negative binomial, probit, and spatial lag models. Descriptive statistics suggest that child pedestrians in Seoul have a higher risk of being involved in traffic crashes than their counterparts in Santiago. However, in Seoul a greater proportion of children are unharmed as a result of these incidents, whereas more child pedestrians are killed in Santiago. Younger children in Seoul suffer more injuries from P-VCs than in Santiago. The majority of P-VCs in both cities tend to occur in the afternoon and evening, at intersections in Santiago and at midblock locations in Seoul. Our model results suggest that the resident population of children is positively associated with P-VCs in both cities, and school concentrations apparently increase P-VC risk among older children in Santiago. Bus stops are associated with higher P-VCs in Seoul, and subway stations relate to higher P-VCs among older children in Santiago. Zone-level land use mix was negatively related to child P-VCs in Seoul but not in Santiago. Arterial roads are associated with fewer P-VCs, especially for younger children in both cities. A share of collector roads is associated with increased P-VCs in Seoul but fewer P-VCs in Santiago. Hilliness is related to fewer P-VCs in both cities. Differences in these model results for Santiago and Seoul warrant additional analysis, as do the differences in results across model type (negative binomial versus spatial lag models). To reduce child P-VCs, this study suggests the need to assess subway station and bus stop area conditions in Santiago and Seoul, respectively; areas with high density of schools in Santiago; areas with greater concentrations of children in both cities; and collector roads in Seoul.

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.

Analysis of overdispersed count data: application to the Human Papillomavirus Infection in Men (HIM) Study.

PubMed

Lee, J-H; Han, G; Fulp, W J; Giuliano, A R

2012-06-01

The Poisson model can be applied to the count of events occurring within a specific time period. The main feature of the Poisson model is the assumption that the mean and variance of the count data are equal. However, this equal mean-variance relationship rarely occurs in observational data. In most cases, the observed variance is larger than the assumed variance, which is called overdispersion. Further, when the observed data involve excessive zero counts, the problem of overdispersion results in underestimating the variance of the estimated parameter, and thus produces a misleading conclusion. We illustrated the use of four models for overdispersed count data that may be attributed to excessive zeros. These are Poisson, negative binomial, zero-inflated Poisson and zero-inflated negative binomial models. The example data in this article deal with the number of incidents involving human papillomavirus infection. The four models resulted in differing statistical inferences. The Poisson model, which is widely used in epidemiology research, underestimated the standard errors and overstated the significance of some covariates.

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.

Do US Ambient Air Lead Levels Have a Significant Impact on Childhood Blood Lead Levels: Results of a National Study

PubMed Central

Brink, LuAnn L.; Talbott, Evelyn O.; Sharma, Ravi K.; Marsh, Gary M.; Wu, Wen Chi; Rager, Judith R.; Strosnider, Heather M.

2013-01-01

Introduction. Although lead paint and leaded gasoline have not been used in the US for thirty years, thousands of US children continue to have blood lead levels (BLLs) of concern. Methods. We investigated the potential association of modeled air lead levels and BLLs ≥ 10 μg/dL using a large CDC database with BLLs on children aged 0–3 years. Percent of children with BLLs ≥ 10 μg/dL (2000–2007) by county and proportion of pre-50 housing and SES variables were merged with the US EPA's National Air Toxics Assessment (NATA) modeled air lead data. Results. The proportion with BLL ≥ 10 μg/dL was 1.24% in the highest air lead counties, and the proportion with BLL ≥ 10 μg/dL was 0.36% in the lowest air lead counties, resulting in a crude prevalence ratio of 3.4. Further analysis using multivariate negative binomial regression revealed that NATA lead was a significant predictor of % BLL ≥ 10 μg/dL after controlling for percent pre-l950 housing, percent rural, and percent black. A geospatial regression revealed that air lead, percent older housing, and poverty were all significant predictors of % BLL ≥ 10 μg/dL. Conclusions. More emphasis should be given to potential sources of ambient air lead near residential areas. PMID:23983719

The differences in healthcare utilization for dental caries based on the implementation of water fluoridation in South Korea.

PubMed

Cho, Myung-Soo; Han, Kyu-Tae; Park, Sohee; Moon, Ki Tae; Park, Eun-Cheol

2016-11-08

There were some debates about the water fluoridation program in South Korea, even if the program had generally substantial effectiveness. Because the out-of-pocket expenditures for dental care were higher in South Korea than in other countries, an efficient solution was needed. Therefore, we examined the relationship between the implementation of water fluoridation and the utilization of dental care. We used the National Health Insurance Service National Sample Cohort. In this study, data finally included 472,250 patients who were newly diagnosed with dental caries during 2003-2013. We performed survival analysis using cox proportional hazard model, negative binomial-regression, and regression analyses using generalized estimating equation models. There were 48.49 % outpatient dental care visit during study period. Individuals with water fluoridation had a lower risk of dental care visits (HR = 0.949, 95 % CI = 0.928-0.971). Among the individuals who experienced a dental care visit, those with water fluoridation program had a lower number of dental care visits (β = -0.029), and the period of water fluoridation had an inverse association with the dental care expenditures. The implementation of water fluoridation programs and these periods are associated with reducing the utilization of dental health care. Considering these positive impacts, healthcare professionals must consider preventive strategies for activating water fluoridation programs, such as changes in public perception and relations, for the effective management of dental care in South Korea.

Influence of physician factors on the effectiveness of a continuing medical education intervention.

PubMed

Flores, Sergio; Reyes, Hortensia; Perez-Cuevas, Ricardo

2006-01-01

Continuing medical education (CME) is essential for improving the quality of care in primary health care settings. This study's objective was to determine how the characteristics of family physicians influenced the effectiveness of a multifaceted CME intervention to improve the management of acute respiratory infection (ARI) or type 2 diabetes (DM2). A secondary analysis was conducted based on data from 121 family physicians, who participated in the educational intervention study. The outcome variable was positive change in physician's performance for treatment of ARI or DM2. The exposure variable was multifaceted CME intervention. Independent variables were professional physicians and organizational characteristics. Analysis included log binomial regression modeling. Factors influencing positive change included, for ARI, participation in the CME intervention and medical director interested in that condition and for DM2, participation in the CME intervention, medical director interested in DM2, and being a teacher. Physicians' characteristics and organizational environment influence the effectiveness of educational intervention and are therefore relevant to the implementation of CME strategies.

Environmental Risk Factors influencing Bicycle Theft: A Spatial Analysis in London, UK

PubMed Central

Helbich, Marco

2016-01-01

Urban authorities are continuously drawing up policies to promote cycling among commuters. However, these initiatives are counterproductive for the targeted objectives because they increase opportunities for bicycle theft. This paper explores Inner London as a case study to address place-specific risk factors for bicycle theft at the street-segment level while controlling for seasonal variation. The presence of certain public amenities (e.g., bicycle stands, railway stations, pawnshops) was evaluated against locations of bicycle theft between 2013 and 2016 and risk effects were estimated using negative binomial regression models. Results showed that a greater level of risk stemmed from land-use facilities than from area-based socioeconomic status. The presence of facilities such as train stations, vacant houses, pawnbrokers and payday lenders increased bicycle theft, but no evidence was found that linked police stations with crime levels. The findings have significant implications for urban crime prevention with respect to non-residential land use. PMID:27643788

Syphilis Among U.S.-Bound Refugees, 2009-2013.

PubMed

Nyangoma, E N; Olson, C K; Painter, J A; Posey, D L; Stauffer, W M; Naughton, M; Zhou, W; Kamb, M; Benoit, S R

2017-08-01

U.S. immigration regulations require clinical and serologic screening for syphilis for all U.S.-bound refugees 15 years of age and older. We reviewed syphilis screening results for all U.S.-bound refugees from January 1, 2009 through December 31, 2013. We calculated age-adjusted prevalence by region and nationality and assessed factors associated with syphilis seropositivity using multivariable log binomial regression models. Among 233,446 refugees, we identified 874 syphilis cases (373 cases per 100,000 refugees). The highest overall age-adjusted prevalence rates of syphilis seropositivity were observed among refugees from Africa (1340 cases per 100,000), followed by East Asia and the Pacific (397 cases per 100,000). In most regions, male sex, increasing age, and living in non-refugee camp settings were associated with syphilis seropositivity. Future analysis of test results, stage of infection, and treatment delivery overseas is warranted in order to determine the extent of transmission risk and benefits of the screening program.

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.

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.

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

Occupational class differences in suicide: evidence of changes over time and during the global financial crisis in Australia.

PubMed

Milner, Alison J; Niven, Heather; LaMontagne, Anthony D

2015-09-21

Previous research showed an increase in Australian suicide rates during the Global Financial Crisis (GFC). There has been no research investigating whether suicide rates by occupational class changed during the GFC. The aim of this study was to investigate whether the GFC-associated increase in suicide rates in employed Australians may have masked changes by occupational class. Negative binomial regression models were used to investigate Rate Ratios (RRs) in suicide by occupational class. Years of the GFC (2007, 2008, 2009) were compared to the baseline years 2001-2006. There were widening disparities between a number of the lower class occupations and the highest class occupations during the years 2007, 2008, and 2009 for males, but less evidence of differences for females. Occupational disparities in suicide rates widened over the GFC period. There is a need for programs to be responsive to economic downturns, and to prioritise the occupational groups most affected.

Interdependence in Health and Functioning Among Older Spousal Caregivers and Care Recipients.

PubMed

Hoffman, Geoffrey J; Burgard, Sarah; Mendez-Luck, Carolyn A; Gaugler, Joseph E

2018-06-01

Older spousal caregiving relationships involve support that may be affected by the health of either the caregiver or care recipient. We conducted a longitudinal analysis using pooled data from 4,632 community-dwelling spousal care recipients and caregivers aged ⩾50 from the 2002 to 2014 waves of the Health and Retirement Study. We specified logistic and negative binomial regression models using lagged predictor variables to assess the role of partner health status on spousal caregiver and care recipient health care utilization and physical functioning outcomes. Care recipients' odds of hospitalization, odds ratio (OR): 0.83, p<.001, decreased when caregivers had more ADL difficulties. When spouses were in poorer versus better health, care recipients' bed days decreased (4.69 vs. 2.54) while caregivers' bed days increased (0.20 vs. 0.96). Providers should consider the dual needs of caregivers caring for care recipients and their own health care needs, in adopting a family-centered approach to management of older adult long-term care needs.

The relationship between perceived discrimination and high-risk social ties among illicit drug users in New York City, 2006-2009.

PubMed

Crawford, Natalie D; Ford, Chandra; Galea, Sandro; Latkin, Carl; Jones, Kandice C; Fuller, Crystal M

2013-01-01

Discrimination can influence risk of disease by promoting unhealthy behaviors (e.g., smoking, alcohol use). Whether it influences the formation of high-risk social ties that facilitate HIV transmission is unclear. Using cross-sectional data from a cohort of illicit drug users, this study examined the association between discrimination based on race, drug use and prior incarceration and risky sex and drug ties. Negative binomial regression models were performed. Participants who reported discrimination based on race and drug use had significantly more sex and drug-using ties. But, after accounting for both racial and drug use discrimination, only racial discrimination was associated with increased sex, drug-using, and injecting ties. Drug users who experience discrimination and subsequently develop more sex and drug-using ties, increase their risk of contracting HIV. Future longitudinal studies illuminating the pathways linking discrimination and social network development may guide intervention development and identify drug-using subpopulations at high risk for disease transmission.

Clinical Decision Making and Mental Health Service Use Among Persons With Severe Mental Illness Across Europe.

PubMed

Cosh, Suzanne; Zenter, Nadja; Ay, Esra-Sultan; Loos, Sabine; Slade, Mike; De Rosa, Corrado; Luciano, Mario; Berecz, Roland; Glaub, Theodora; Munk-Jørgensen, Povl; Krogsgaard Bording, Malene; Rössler, Wulf; Kawohl, Wolfram; Puschner, Bernd

2017-09-01

The study explored relationships between preferences for and experiences of clinical decision making (CDM) with service use among persons with severe mental illness. Data from a prospective observational study in six European countries were examined. Associations of baseline staff-rated (N=213) and patient-rated (N=588) preferred and experienced decision making with service use were examined at baseline by using binomial regressions and at 12-month follow-up by using multilevel models. A preference by patients and staff for active patient involvement in decision making, rather than shared or passive decision making, was associated with longer hospital admissions and higher costs at baseline and with increases in admissions over 12 months (p=.043). Low patient-rated satisfaction with an experienced clinical decision was also related to increased costs over the study period (p=.005). A preference for shared decision making may reduce health care costs by reducing inpatient admissions. Patient satisfaction with decisions was a predictor of costs, and clinicians should maximize patient satisfaction with CDM.

Perceived interparental conflict and early adolescents' friendships: the role of attachment security and emotion regulation.

PubMed

Schwarz, Beate; Stutz, Melanie; Ledermann, Thomas

2012-09-01

Although there is strong evidence for the effect of interparental conflict on adolescents' internalizing and externalizing problems, little is known about the effect on the quality of adolescents' relationships. The current study investigates the link between adolescents' friendships and interparental conflict as reported by both parents and adolescents. It considers early adolescents' emotion regulation ability and attachment security as mediators. The analysis is based on a longitudinal study with two waves separated by 12 months. The participants were 180 two-parent families and their adolescent children (50.5 % girls), the average age of the latter being 10.61 years (SD = 0.41) at the outset (Time 1). Binomial logistic regression analysis revealed that perceived interparental conflict increased the risk of instability in friendship relationships across the 1-year period. Structural equation modeling analysis indicated that the association between perceived interparental conflict and friendship quality was mediated by emotion regulation and attachment security. The discussion focuses on mechanisms whereby interparental conflict influences early adolescents' friendship relationships.

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.

Safety-in-numbers: Estimates based on a sample of pedestrian crossings in Norway.

PubMed

Elvik, Rune

2016-06-01

Safety-in-numbers denotes the tendency for the risk of accident for each road user to decline as the number of road users increases. Safety-in-numbers implies that a doubling of the number of road users will be associated with less than a doubling of the number of accidents. This paper investigates safety-in-numbers in 239 pedestrian crossings in Oslo and its suburbs. Accident prediction models were fitted by means of negative binomial regression. The models indicate a very strong safety-in-numbers effect. In the final model, the coefficients for traffic volume were 0.05 for motor vehicles, 0.07 for pedestrians and 0.12 for cyclists. The coefficient for motor vehicles implies that the number of accidents is almost independent of the number of motor vehicles. The safety-in-numbers effect found in this paper is stronger than reported in any other study dealing with safety-in-numbers. It should be noted that the model explained only 21% of the systematic variation in the number of accidents. It therefore cannot be ruled out that the results are influenced by omitted variable bias. Any such bias would, however, have to be very large to eliminate the safety-in-numbers effect. Copyright © 2016 Elsevier Ltd. All rights reserved.

Outbreaks of Tularemia in a Boreal Forest Region Depends on Mosquito Prevalence

PubMed Central

Rydén, Patrik; Björk, Rafael; Schäfer, Martina L.; Lundström, Jan O.; Petersén, Bodil; Lindblom, Anders; Forsman, Mats; Sjöstedt, Anders

2012-01-01

Background. We aimed to evaluate the potential association of mosquito prevalence in a boreal forest area with transmission of the bacterial disease tularemia to humans, and model the annual variation of disease using local weather data. Methods. A prediction model for mosquito abundance was built using weather and mosquito catch data. Then a negative binomial regression model based on the predicted mosquito abundance and local weather data was built to predict annual numbers of humans contracting tularemia in Dalarna County, Sweden. Results. Three hundred seventy humans were diagnosed with tularemia between 1981 and 2007, 94% of them during 7 summer outbreaks. Disease transmission was concentrated along rivers in the area. The predicted mosquito abundance was correlated (0.41, P < .05) with the annual number of human cases. The predicted mosquito peaks consistently preceded the median onset time of human tularemia (temporal correlation, 0.76; P < .05). Our final predictive model included 5 environmental variables and identified 6 of the 7 outbreaks. Conclusions. This work suggests that a high prevalence of mosquitoes in late summer is a prerequisite for outbreaks of tularemia in a tularemia-endemic boreal forest area of Sweden and that environmental variables can be used as risk indicators. PMID:22124130

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

Understanding Phlebotomus perniciosus abundance in south-east Spain: assessing the role of environmental and anthropic factors.

PubMed

Risueño, José; Muñoz, Clara; Pérez-Cutillas, Pedro; Goyena, Elena; Gonzálvez, Moisés; Ortuño, María; Bernal, Luis Jesús; Ortiz, Juana; Alten, Bulent; Berriatua, Eduardo

2017-04-19

Leishmaniosis is associated with Phlebotomus sand fly vector density, but our knowledge of the environmental framework that regulates highly overdispersed vector abundance distributions is limited. We used a standardized sampling procedure in the bioclimatically diverse Murcia Region in Spain and multilevel regression models for count data to estimate P. perniciosus abundance in relation to environmental and anthropic factors. Twenty-five dog and sheep premises were sampled for sand flies using adhesive and light-attraction traps, from late May to early October 2015. Temperature, relative humidity and other animal- and premise-related data recorded on site and other environmental data were extracted from digital databases using a geographical information system. The relationship between sand fly abundance and explanatory variables was analysed using binomial regression models. The total number of sand flies captured, mostly with light-attraction traps, was 3,644 specimens, including 80% P. perniciosus, the main L. infantum vector in Spain. Abundance varied between and within zones and was positively associated with increasing altitude from 0 to 900 m above sea level, except from 500 to 700 m where it was low. Populations peaked in July and especially during a 3-day heat wave when relative humidity and wind speed plummeted. Regression models indicated that climate and not land use or soil characteristics have the greatest impact on this species density on a large geographical scale. In contrast, micro-environmental factors such as animal building characteristics and husbandry practices affect sand fly population size on a smaller scale. A standardised sampling procedure and statistical analysis for highly overdispersed distributions allow reliable estimation of P. perniciosus abundance and identification of environmental drivers. While climatic variables have the greatest impact at macro-environmental scale, anthropic factors may be determinant at a micro-geographical scale. These finding may be used to elaborate predictive distribution maps useful for vector and pathogen control programs.

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…

Estimating safety effects of pavement management factors utilizing Bayesian random effect models.

PubMed

Jiang, Ximiao; Huang, Baoshan; Zaretzki, Russell L; Richards, Stephen; Yan, Xuedong

2013-01-01

Previous studies of pavement management factors that relate to the occurrence of traffic-related crashes are rare. Traditional research has mostly employed summary statistics of bidirectional pavement quality measurements in extended longitudinal road segments over a long time period, which may cause a loss of important information and result in biased parameter estimates. The research presented in this article focuses on crash risk of roadways with overall fair to good pavement quality. Real-time and location-specific data were employed to estimate the effects of pavement management factors on the occurrence of crashes. This research is based on the crash data and corresponding pavement quality data for the Tennessee state route highways from 2004 to 2009. The potential temporal and spatial correlations among observations caused by unobserved factors were considered. Overall 6 models were built accounting for no correlation, temporal correlation only, and both the temporal and spatial correlations. These models included Poisson, negative binomial (NB), one random effect Poisson and negative binomial (OREP, ORENB), and two random effect Poisson and negative binomial (TREP, TRENB) models. The Bayesian method was employed to construct these models. The inference is based on the posterior distribution from the Markov chain Monte Carlo (MCMC) simulation. These models were compared using the deviance information criterion. Analysis of the posterior distribution of parameter coefficients indicates that the pavement management factors indexed by Present Serviceability Index (PSI) and Pavement Distress Index (PDI) had significant impacts on the occurrence of crashes, whereas the variable rutting depth was not significant. Among other factors, lane width, median width, type of terrain, and posted speed limit were significant in affecting crash frequency. The findings of this study indicate that a reduction in pavement roughness would reduce the likelihood of traffic-related crashes. Hence, maintaining a low level of pavement roughness is strongly suggested. In addition, the results suggested that the temporal correlation among observations was significant and that the ORENB model outperformed all other models.

Spatiotemporal hurdle models for zero-inflated count data: Exploring trends in emergency department visits.

PubMed

Neelon, Brian; Chang, Howard H; Ling, Qiang; Hastings, Nicole S

2016-12-01

Motivated by a study exploring spatiotemporal trends in emergency department use, we develop a class of two-part hurdle models for the analysis of zero-inflated areal count data. The models consist of two components-one for the probability of any emergency department use and one for the number of emergency department visits given use. Through a hierarchical structure, the models incorporate both patient- and region-level predictors, as well as spatially and temporally correlated random effects for each model component. The random effects are assigned multivariate conditionally autoregressive priors, which induce dependence between the components and provide spatial and temporal smoothing across adjacent spatial units and time periods, resulting in improved inferences. To accommodate potential overdispersion, we consider a range of parametric specifications for the positive counts, including truncated negative binomial and generalized Poisson distributions. We adopt a Bayesian inferential approach, and posterior computation is handled conveniently within standard Bayesian software. Our results indicate that the negative binomial and generalized Poisson hurdle models vastly outperform the Poisson hurdle model, demonstrating that overdispersed hurdle models provide a useful approach to analyzing zero-inflated spatiotemporal data. © The Author(s) 2014.

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.

Risk Factors for Proximal Junctional Kyphosis Associated With Dual-rod Growing-rod Surgery for Early-onset Scoliosis.

PubMed

Watanabe, Kota; Uno, Koki; Suzuki, Teppei; Kawakami, Noriaki; Tsuji, Taichi; Yanagida, Haruhisa; Ito, Manabu; Hirano, Toru; Yamazaki, Ken; Minami, Shohei; Taneichi, Hiroshi; Imagama, Shiro; Takeshita, Katsushi; Yamamoto, Takuya; Matsumoto, Morio

2016-10-01

A retrospective, multicenter study. To identify risk factors for proximal junctional kyphosis (PJK) when treating early-onset scoliosis (EOS) with dual-rod growing-rod (GR) procedure. The risk factors for PJK associated with GR treatment for EOS have not been adequately studied. We evaluated clinical and radiographic results from 88 patients with EOS who underwent dual-rod GR surgery in 12 spine centers in Japan. The mean age at the time of the initial surgery was 6.5±2.2 years (range, 1.5-9.8 y), and the mean follow-up period was 3.9±2.6 years (range, 2.0-12.0 y). Risk factors for PJK were analyzed by binomial multiple logistic regression analysis. The potential factors analyzed were sex, etiology, age, the number of rod-lengthening procedures, coronal and sagittal parameters on radiographs, the type of foundation (pedicle screws or hooks), the uppermost level of the proximal foundation, and the lowermost level of the distal foundation. PJK developed in 23 patients (26%); in 19 of these, the proximal foundation became dislodged following PJK. Binomial multiple logistic regression analysis identified the following significant independent risk factors for PJK: a lower instrumented vertebra at or cranial to L3 [odds ratio (OR), 3.32], a proximal thoracic scoliosis of ≥40 degrees (OR, 2.95), and a main thoracic kyphosis of ≥60 degrees (OR, 5.08). The significant independent risk factors for PJK during dual-rod GR treatment for EOS were a lower instrumented vertebra at or cranial to L3, a proximal thoracic scoliosis of ≥40 degrees, and a main thoracic kyphosis of ≥60 degrees.

Influence of prehospital airway management on neurological outcome in patients transferred to a heart attack centre following out-of-hospital cardiac arrest.

PubMed

Edwards, Timothy; Williams, Julia; Cottee, Michaela

2018-05-11

To describe the association between prehospital airway management and neurological outcomes in patients transferred by the ambulance service directly to a heart attack centre (HAC) post-return of spontaneous circulation (ROSC). A retrospective observational cohort study in which ambulance records were reviewed to determine prehospital airway management strategy and collect physiological and demographic data. HAC notes were obtained to determine in-hospital management and quantify neurological outcome via the cerebral performance category (CPC) scale. Statistical analyses were performed via χ 2 -test, Mann-Whitney U-test, odds ratios and binomial logistic regression. Two hundred and twenty patients were included between August 2013 and August 2014, with complete outcome data obtained for 209. Median age of patients with complete outcome data was 67 years and 71.3% were male (n = 149). Airway management was provided using a supraglottic airway (SGA) in 72.7% of cases (n = 152) with the remainder undergoing endotracheal intubation (ETI). There was no significant difference in the proportion of patients who had a good neurological outcome (CPC 1 and 2) at discharge between the SGA and ETI groups (P = 0.29). Binomial logistic regression incorporating factors known to influence outcome demonstrated no significant difference in neurological outcomes between the SGA and ETI groups (adjusted OR 0.73, 95% CI 0.34-1.56). In this observational study, there was no significant difference in the proportion of good neurological outcomes in patients managed with SGA versus ETI during cardiac arrest and in the post-ROSC transfer phase. Further research is required to provide more definitive evidence in relation to the optimal airway management strategy in out-of-hospital cardiac arrest. © 2018 Australasian College for Emergency Medicine and Australasian Society for Emergency Medicine.

Investigating Individual Differences in Toddler Search with Mixture Models

ERIC Educational Resources Information Center

Berthier, Neil E.; Boucher, Kelsea; Weisner, Nina

2015-01-01

Children's performance on cognitive tasks is often described in categorical terms in that a child is described as either passing or failing a test, or knowing or not knowing some concept. We used binomial mixture models to determine whether individual children could be classified as passing or failing two search tasks, the DeLoache model room…

Predicting motor vehicle collisions using Bayesian neural network models: an empirical analysis.

PubMed

Xie, Yuanchang; Lord, Dominique; Zhang, Yunlong

2007-09-01

Statistical models have frequently been used in highway safety studies. They can be utilized for various purposes, including establishing relationships between variables, screening covariates and predicting values. Generalized linear models (GLM) and hierarchical Bayes models (HBM) have been the most common types of model favored by transportation safety analysts. Over the last few years, researchers have proposed the back-propagation neural network (BPNN) model for modeling the phenomenon under study. Compared to GLMs and HBMs, BPNNs have received much less attention in highway safety modeling. The reasons are attributed to the complexity for estimating this kind of model as well as the problem related to "over-fitting" the data. To circumvent the latter problem, some statisticians have proposed the use of Bayesian neural network (BNN) models. These models have been shown to perform better than BPNN models while at the same time reducing the difficulty associated with over-fitting the data. The objective of this study is to evaluate the application of BNN models for predicting motor vehicle crashes. To accomplish this objective, a series of models was estimated using data collected on rural frontage roads in Texas. Three types of models were compared: BPNN, BNN and the negative binomial (NB) regression models. The results of this study show that in general both types of neural network models perform better than the NB regression model in terms of data prediction. Although the BPNN model can occasionally provide better or approximately equivalent prediction performance compared to the BNN model, in most cases its prediction performance is worse than the BNN model. In addition, the data fitting performance of the BPNN model is consistently worse than the BNN model, which suggests that the BNN model has better generalization abilities than the BPNN model and can effectively alleviate the over-fitting problem without significantly compromising the nonlinear approximation ability. The results also show that BNNs could be used for other useful analyses in highway safety, including the development of accident modification factors and for improving the prediction capabilities for evaluating different highway design alternatives.

Adjusted Wald Confidence Interval for a Difference of Binomial Proportions Based on Paired Data

ERIC Educational Resources Information Center

Bonett, Douglas G.; Price, Robert M.

2012-01-01

Adjusted Wald intervals for binomial proportions in one-sample and two-sample designs have been shown to perform about as well as the best available methods. The adjusted Wald intervals are easy to compute and have been incorporated into introductory statistics courses. An adjusted Wald interval for paired binomial proportions is proposed here and…

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.

Forecasting asthma-related hospital admissions in London using negative binomial models.

PubMed

Soyiri, Ireneous N; Reidpath, Daniel D; Sarran, Christophe

2013-05-01

Health forecasting can improve health service provision and individual patient outcomes. Environmental factors are known to impact chronic respiratory conditions such as asthma, but little is known about the extent to which these factors can be used for forecasting. Using weather, air quality and hospital asthma admissions, in London (2005-2006), two related negative binomial models were developed and compared with a naive seasonal model. In the first approach, predictive forecasting models were fitted with 7-day averages of each potential predictor, and then a subsequent multivariable model is constructed. In the second strategy, an exhaustive search of the best fitting models between possible combinations of lags (0-14 days) of all the environmental effects on asthma admission was conducted. Three models were considered: a base model (seasonal effects), contrasted with a 7-day average model and a selected lags model (weather and air quality effects). Season is the best predictor of asthma admissions. The 7-day average and seasonal models were trivial to implement. The selected lags model was computationally intensive, but of no real value over much more easily implemented models. Seasonal factors can predict daily hospital asthma admissions in London, and there is a little evidence that additional weather and air quality information would add to forecast accuracy.

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

Leavers, Movers, and Stayers: The Role of Workplace Conditions in Teacher Mobility Decisions

ERIC Educational Resources Information Center

Kukla-Acevedo, Sharon

2009-01-01

The author explored whether 3 workplace conditions were related to teacher mobility decisions. The modeling strategy incorporated a series of binomial and multinomial logistic models to estimate the effects of administrative support, classroom control, and behavioral climate on teachers' decisions to quit teaching or switch schools. The results…

Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment.

PubMed

Gierliński, Marek; Cole, Christian; Schofield, Pietà; Schurch, Nicholas J; Sherstnev, Alexander; Singh, Vijender; Wrobel, Nicola; Gharbi, Karim; Simpson, Gordon; Owen-Hughes, Tom; Blaxter, Mark; Barton, Geoffrey J

2015-11-15

High-throughput RNA sequencing (RNA-seq) is now the standard method to determine differential gene expression. Identifying differentially expressed genes crucially depends on estimates of read-count variability. These estimates are typically based on statistical models such as the negative binomial distribution, which is employed by the tools edgeR, DESeq and cuffdiff. Until now, the validity of these models has usually been tested on either low-replicate RNA-seq data or simulations. A 48-replicate RNA-seq experiment in yeast was performed and data tested against theoretical models. The observed gene read counts were consistent with both log-normal and negative binomial distributions, while the mean-variance relation followed the line of constant dispersion parameter of ∼0.01. The high-replicate data also allowed for strict quality control and screening of 'bad' replicates, which can drastically affect the gene read-count distribution. RNA-seq data have been submitted to ENA archive with project ID PRJEB5348. g.j.barton@dundee.ac.uk. © The Author 2015. Published by Oxford University Press.

Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment

PubMed Central

Cole, Christian; Schofield, Pietà; Schurch, Nicholas J.; Sherstnev, Alexander; Singh, Vijender; Wrobel, Nicola; Gharbi, Karim; Simpson, Gordon; Owen-Hughes, Tom; Blaxter, Mark; Barton, Geoffrey J.

2015-01-01

Motivation: High-throughput RNA sequencing (RNA-seq) is now the standard method to determine differential gene expression. Identifying differentially expressed genes crucially depends on estimates of read-count variability. These estimates are typically based on statistical models such as the negative binomial distribution, which is employed by the tools edgeR, DESeq and cuffdiff. Until now, the validity of these models has usually been tested on either low-replicate RNA-seq data or simulations. Results: A 48-replicate RNA-seq experiment in yeast was performed and data tested against theoretical models. The observed gene read counts were consistent with both log-normal and negative binomial distributions, while the mean-variance relation followed the line of constant dispersion parameter of ∼0.01. The high-replicate data also allowed for strict quality control and screening of ‘bad’ replicates, which can drastically affect the gene read-count distribution. Availability and implementation: RNA-seq data have been submitted to ENA archive with project ID PRJEB5348. Contact: g.j.barton@dundee.ac.uk PMID:26206307

Examining the relationship between the prevalence of guns and homicide rates in the USA using a new and improved state-level gun ownership proxy.

PubMed

Siegel, Michael; Ross, Craig S; King, Charles

2014-12-01

Determining the relationship between gun ownership levels and firearm homicide rates is critical to inform public health policy. Previous research has shown that state-level gun ownership, as measured by a widely used proxy, is positively associated with firearm homicide rates. A newly developed proxy measure that incorporates the hunting license rate in addition to the proportion of firearm suicides correlates more highly with state-level gun ownership. To corroborate previous research, we used this new proxy to estimate the association of state-level gun ownership with total, firearm, and non-firearm homicides. Using state-specific data for the years 1981-2010, we modelled these rates as a function of gun ownership level, controlling for potential confounding factors. We used a negative binomial regression model and accounted for clustering of observations among states. We found that state-level gun ownership as measured by the new proxy, is significantly associated with firearm and total homicides but not with non-firearm homicides. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

The effects of temperament, psychopathy, and childhood trauma among delinquent youth: A test of DeLisi and Vaughn's temperament-based theory of crime.

PubMed

DeLisi, Matt; Fox, Bryanna H; Fully, Matthew; Vaughn, Michael G

Recent interest among criminologists on the construct of temperament has been fueled by DeLisi and Vaughn's (2014) temperament-based theory of antisocial behavior. Their theory suggests that core self-regulation capacity and negative emotionality are the most salient temperament features for understanding the emergence and maintenance of antisocial and violent behavior, even among offending populations. The present study tests the relative effects of these temperamental features along with psychopathic traits and trauma in their association with violent and non-violent delinquency in a sample of 252 juvenile offenders. Results from a series of negative binomial regression models indicate that temperament was uniformly more strongly associated with violent and non-violent delinquency than psychopathic traits and childhood traumatic events. Exploratory classification models suggested that temperament and psychopathy possessed similar predictive capacity, but neither surpassed prior history of violence and delinquency as a predictor of future offending. Overall, findings are supportive of DeLisi and Vaughn's temperament-based theory and suggest temperament as conceptualized and measured in the present study may play an important role as a risk factor for violent and non-violent delinquency. Copyright © 2018 Elsevier Ltd. All rights reserved.

Effects of Rural Mutual Health Care on outpatient service utilization in Chinese village medical institutions: evidence from panel data.

PubMed

Zhou, Zhongliang; Gao, Jianmin; Xue, Qinxiang; Yang, Xiaowei; Yan, Ju'e

2009-07-01

To solve the problem of 'Kan bing nan, kan bing gui' (medical treatment is difficult to access and expensive), a Harvard-led research team implemented a community-based health insurance scheme known as Rural Mutual Health Care (RMHC) in Chinese rural areas from 2004 to 2006. Two major policies adopted by RMHC included insurance coverage of outpatient services (demand-side policy) and drug policy (supply-side policy). This paper focuses on the effects of these two policies on outpatient service utilization in Chinese village clinics. The data used in this study are from 3-year household follow-up surveys. A generalized negative binomial regression model and a Heckman selection model were constructed using panel data from 2005 to 2007. The results indicate that the price elasticities of demand for outpatient visits and per-visit outpatient expenses were -1.5 and -0.553, respectively. After implementing the supply-side policy, outpatient visits and per-visit outpatient expenses decreased by 94.7 and 55.9%, respectively, controlling for insurance coverage. These findings can be used to make recommendations to the Chinese government on improving the health care system.

Immigrants from Mexico experience serious behavioral and psychiatric problems at far lower rates than US-born Americans.

PubMed

Salas-Wright, Christopher P; Vaughn, Michael G; Goings, Trenette Clark

2017-10-01

To examine the prevalence of self-reported criminal and violent behavior, substance use disorders, and mental disorders among Mexican immigrants vis-à-vis the US born. Study findings are based on national data collected between 2012 and 2013. Binomial logistic regression was employed to examine the relationship between immigrant status and behavioral/psychiatric outcomes. Mexican immigrants report substantially lower levels of criminal and violent behaviors, substance use disorders, and mental disorders compared to US-born individuals. While some immigrants from Mexico have serious behavioral and psychiatric problems, Mexican immigrants in general experience such problems at far lower rates than US-born individuals.

Should the poor have no medicines to cure? A study on the association between social class and social security among the rural migrant workers in urban China.

PubMed

Guan, Ming

2017-11-07

The rampant urbanization and medical marketization in China have resulted in increased vulnerabilities to health and socioeconomic disparities among the rural migrant workers in urban China. In the Chinese context, the socioeconomic characteristics of rural migrant workers have attracted considerable research attention in the recent past years. However, to date, no previous studies have explored the association between the socioeconomic factors and social security among the rural migrant workers in urban China. This study aims to explore the association between socioeconomic inequity and social security inequity and the subsequent associations with medical inequity and reimbursement rejection. Data from a regionally representative sample of 2009 Survey of Migrant Workers in Pearl River Delta in China were used for analyses. Multiple logistic regressions were used to analyze the impacts of socioeconomic factors on the eight dimensions of social security (sick pay, paid leave, maternity pay, medical insurance, pension insurance, occupational injury insurance, unemployment insurance, and maternity insurance) and the impacts of social security on medical reimbursement rejection. The zero-inflated negative binomial regression model (ZINB regression) was adopted to explore the relationship between socioeconomic factors and hospital visits among the rural migrant workers with social security. The study population consisted of 848 rural migrant workers with high income who were young and middle-aged, low-educated, and covered by social security. Reimbursement rejection and abusive supervision for the rural migrant workers were observed. Logistic regression analysis showed that there were significant associations between socioeconomic factors and social security. ZINB regression showed that there were significant associations between socioeconomic factors and hospital visits among the rural migrant workers. Also, several dimensions of social security had significant associations with reimbursement rejections. This study showed that social security inequity, medical inequity, and reimbursement inequity happened to the rural migrant workers simultaneously. Future policy should strengthen health justice and enterprises' medical responsibilities to the employed rural migrant workers.

Distribution, occupancy, and habitat correlates of American martens (Martes americana) in Rocky Mountain National Park, Colorado

USGS Publications Warehouse

Baldwin, R.A.; Bender, L.C.

2008-01-01

A clear understanding of habitat associations of martens (Martes americana) is necessary to effectively manage and monitor populations. However, this information was lacking for martens in most of their southern range, particularly during the summer season. We studied the distribution and habitat correlates of martens from 2004 to 2006 in Rocky Mountain National Park (RMNP) across 3 spatial scales: site-specific, home-range, and landscape. We used remote-sensored cameras from early August through late October to inventory occurrence of martens and modeled occurrence as a function of habitat and landscape variables using binary response (BR) and binomial count (BC) logistic regression, and occupancy modeling (OM). We also assessed which was the most appropriate modeling technique for martens in RMNP. Of the 3 modeling techniques, OM appeared to be most appropriate given the explanatory power of derived models and its incorporation of detection probabilities, although the results from BR and BC provided corroborating evidence of important habitat correlates. Location of sites in the western portion of the park, riparian mixed-conifer stands, and mixed-conifer with aspen patches were most frequently positively correlated with occurrence of martens, whereas more xeric and open sites were avoided. Additionally, OM yielded unbiased occupancy values ranging from 91% to 100% and 20% to 30% for the western and eastern portions of RMNP, respectively. ?? 2008 American Society of Mammalogists.

Experimental design and data analysis of Ago-RIP-Seq experiments for the identification of microRNA targets.

PubMed

Tichy, Diana; Pickl, Julia Maria Anna; Benner, Axel; Sültmann, Holger

2017-03-31

The identification of microRNA (miRNA) target genes is crucial for understanding miRNA function. Many methods for the genome-wide miRNA target identification have been developed in recent years; however, they have several limitations including the dependence on low-confident prediction programs and artificial miRNA manipulations. Ago-RNA immunoprecipitation combined with high-throughput sequencing (Ago-RIP-Seq) is a promising alternative. However, appropriate statistical data analysis algorithms taking into account the experimental design and the inherent noise of such experiments are largely lacking.Here, we investigate the experimental design for Ago-RIP-Seq and examine biostatistical methods to identify de novo miRNA target genes. Statistical approaches considered are either based on a negative binomial model fit to the read count data or applied to transformed data using a normal distribution-based generalized linear model. We compare them by a real data simulation study using plasmode data sets and evaluate the suitability of the approaches to detect true miRNA targets by sensitivity and false discovery rates. Our results suggest that simple approaches like linear regression models on (appropriately) transformed read count data are preferable. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Negative Urgency, Distress Tolerance, and Substance Abuse Among College Students

PubMed Central

Kaiser, Alison J.; Milich, Richard; Lynam, Donald R.; Charnigo, Richard J.

2012-01-01

Objective Negative affect has been consistently linked with substance use/problems in prior research. The present study sought to build upon these findings by exploring how an individual’s characteristic responding to negative affect impacts substance abuse risk. Trait negative affect was examined in relation to substance abuse outcomes along with two variables tapping into response to negative affect: Distress Tolerance, an individual’s perceived ability to tolerate negative affect, and Negative Urgency, the tendency to act rashly while experiencing distress. Method Participants were 525 first-year college students (48.1% male, 81.1% Caucasian), who completed self-report measures assessing personality traits and alcohol-related problems, and a structured interview assessing past and current substance use. Relations were tested using Zero-Inflated Negative Binomial regression models, and each of the personality variables was tested in a model on its own, and in a model where all three traits were accounted for. Results Negative Urgency emerged as the best predictor, relating to every one of the substance use outcome variables even when trait negative affect and Distress Tolerance were accounted for. Conclusions These findings suggest that Negative Urgency is an important factor to consider in developing prevention and intervention efforts aimed at reducing substance use and problems. PMID:22698894

The Protective Effects of Family Support on the Relationship between Official Intervention and General Delinquency across the Life Course.

PubMed

Dong, Beidi; Krohn, Marvin D

2017-03-01

Previous research on the labeling perspective has identified mediational processes and the long-term effects of official intervention in the life course. However, it is not yet clear what factors may moderate the relationship between labeling and subsequent offending. The current study integrates Cullen's (1994) social support theory to examine how family social support conditions the criminogenic, stigmatizing effects of official intervention on delinquency and whether such protective effects vary by developmental stage. Using longitudinal data from the Rochester Youth Development Study, we estimated negative binomial regression models to investigate the relationships between police arrest, family social support, and criminal offending during both adolescence and young adulthood. Police arrest is a significant predictor of self-reported delinquency in both the adolescent and adult models. Expressive family support exhibits main effects in the adolescent models; instrumental family support exhibits main effects at both developmental stages. Additionally, instrumental family support diminishes some of the predicted adverse effects of official intervention in adulthood. Perception of family support can be critical in reducing general delinquency as well as buffering against the adverse effects of official intervention on subsequent offending. Policies and programs that work with families subsequent to a criminal justice intervention should emphasize the importance of providing a supportive environment for those who are labeled.

The relationship between patient data and pooled clinical management decisions.

PubMed

Ludbrook, G I; O'Loughlin, E J; Corcoran, T B; Grant, C

2013-01-01

A strong relationship between patient data and preoperative clinical decisions could potentially be used to support clinical decisions in preoperative management. The aim of this exploratory study was to determine the relationship between key patient data and pooled clinical opinions on management. In a previous study, panels of anaesthetists compared the quality of computer-assisted patient health assessments with outpatient consultations and made decisions on the need for preoperative tests, no preoperative outpatient assessment, possible postoperative intensive care unit/high dependency unit requirements and aspiration prophylaxis. In the current study, the relationship between patient data and these decisions was examined using binomial logistic regression analysis. Backward stepwise regression was used to identify independent predictors of each decision (at P >0.15), which were then incorporated into a predictive model. The number of factors related to each decision varied: blood picture (four factors), biochemistry (six factors), coagulation studies (three factors), electrocardiography (eight factors), chest X-ray (seven factors), preoperative outpatient assessment (17 factors), intensive care unit requirement (eight factors) and aspiration prophylaxis (one factor). The factor types also varied, but included surgical complexity, age, gender, number of medications or comorbidities, body mass index, hypertension, central nervous system condition, heart disease, sleep apnoea, smoking, persistent pain and stroke. Models based on these relationships usually demonstrated good sensitivity and specificity, with receiver operating characteristics in the following areas under curve: blood picture (0.75), biochemistry (0.86), coagulation studies (0.71), electrocardiography (0.90), chest X-ray (0.85), outpatient assessment (0.85), postoperative intensive care unit requirement (0.88) and aspiration prophylaxis (0.85). These initial results suggest modelling of patient data may have utility supporting clinicians' preoperative decisions.

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

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.

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.

Perfluoroalkyl substances measured in breast milk and child neuropsychological development in a Norwegian birth cohort study.

PubMed

Forns, J; Iszatt, N; White, R A; Mandal, S; Sabaredzovic, A; Lamoree, M; Thomsen, C; Haug, L S; Stigum, H; Eggesbø, M

2015-10-01

Perfluoroalkyl substances (PFASs) are chemicals with potential neurotoxic effects although the current evidence is still limited. This study investigated the association between perinatal exposure to perfluorooctanesulfonic acid (PFOS) and perfluorooctanoic acid (PFOA) and neuropsychological development assessed at 6, 12 and 24 months. We measured PFOS and PFOA in breast milk samples collected one month after delivery by mothers of children participating in the HUMIS study (Norway). Cognitive and psychomotor development was measured at 6 and at 24 months using the Ages and Stages Questionnaire (ASQ-II). Behavioral development was assessed using the infant-toddler symptom checklist (ITSC) at 12 and at 24 months. Weighted logistic regression and weighted negative binomial regression models were applied to analyze the associations between PFASs and ASQ-II and ITSC, respectively. The median concentration of PFOS was 110 ng/L, while the median for PFOA was 40 ng/L. We did not detect an increased risk of having an abnormal score in ASQ-II at 6 months or 24 months. Moreover, no consistent increase in behavioral problems assessed at 12 and 24 months by ITSC questionnaire was detected. We observed no association between perinatal PFOS and PFOA exposure and early neuropsychological development. Further longitudinal studies are needed to confirm the effects of these compounds on neuropsychological development in older children. Copyright © 2015. Published by Elsevier Ltd.

FEMALE SEX AND DISCONTINUATION OF ISONIAZID DUE TO ADVERSE EFFECTS DURING THE TREATMENT OF LATENT TUBERCULOSIS

PubMed Central

Pettit, April C.; Bethel, James; Hirsch-Moverman, Yael; Colson, Paul W.; Sterling, Timothy R.

2013-01-01

SUMMARY Objectives To determine the rate of and risk factors for discontinuation of isoniazid due to adverse effects during the treatment of latent tuberculosis infection in a large, multi-site study. Methods The Tuberculosis Epidemiologic Studies Consortium (TBESC) conducted a prospective study from March 2007–September 2008 among adults initiating isoniazid for treatment of LTBI at 12 sites in the US and Canada. The relative risk for isoniazid discontinuation due to adverse effects was determined using negative binomial regression. Adjusted models were constructed using forward stepwise regression. Results Of 1,306 persons initiating isoniazid, 617 (47.2%, 95% CI 44.5–50.0%) completed treatment and 196 (15.0%, 95% CI 13.1–17.1%) discontinued due to adverse effects. In multivariable analysis, female sex (RR 1.67, 95% CI 1.32–2.10, p<0.001) and current alcohol use (RR 1.41, 95% CI 1.13–1.77, p=0.003) were independently associated with isoniazid discontinuation due to adverse effects. Conclusions The rate of discontinuation of isoniazid due to adverse effects was substantially higher than reported earlier. Women were at increased risk of discontinuing isoniazid due to adverse effects; close monitoring of women for adverse effects may be warranted. Current alcohol use was also associated with isoniazid discontinuation; counseling patients to abstain from alcohol could decrease discontinuation due to adverse effects. PMID:23845828

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.

Plant selection for ethnobotanical uses on the Amalfi Coast (Southern Italy).

PubMed

Savo, V; Joy, R; Caneva, G; McClatchey, W C

2015-07-15

Many ethnobotanical studies have investigated selection criteria for medicinal and non-medicinal plants. In this paper we test several statistical methods using different ethnobotanical datasets in order to 1) define to which extent the nature of the datasets can affect the interpretation of results; 2) determine if the selection for different plant uses is based on phylogeny, or other selection criteria. We considered three different ethnobotanical datasets: two datasets of medicinal plants and a dataset of non-medicinal plants (handicraft production, domestic and agro-pastoral practices) and two floras of the Amalfi Coast. We performed residual analysis from linear regression, the binomial test and the Bayesian approach for calculating under-used and over-used plant families within ethnobotanical datasets. Percentages of agreement were calculated to compare the results of the analyses. We also analyzed the relationship between plant selection and phylogeny, chorology, life form and habitat using the chi-square test. Pearson's residuals for each of the significant chi-square analyses were examined for investigating alternative hypotheses of plant selection criteria. The three statistical analysis methods differed within the same dataset, and between different datasets and floras, but with some similarities. In the two medicinal datasets, only Lamiaceae was identified in both floras as an over-used family by all three statistical methods. All statistical methods in one flora agreed that Malvaceae was over-used and Poaceae under-used, but this was not found to be consistent with results of the second flora in which one statistical result was non-significant. All other families had some discrepancy in significance across methods, or floras. Significant over- or under-use was observed in only a minority of cases. The chi-square analyses were significant for phylogeny, life form and habitat. Pearson's residuals indicated a non-random selection of woody species for non-medicinal uses and an under-use of plants of temperate forests for medicinal uses. Our study showed that selection criteria for plant uses (including medicinal) are not always based on phylogeny. The comparison of different statistical methods (regression, binomial and Bayesian) under different conditions led to the conclusion that the most conservative results are obtained using regression analysis.

Compulsive cell phone use and history of motor vehicle crash.

PubMed

O'Connor, Stephen S; Whitehill, Jennifer M; King, Kevin M; Kernic, Mary A; Boyle, Linda Ng; Bresnahan, Brian W; Mack, Christopher D; Ebel, Beth E

2013-10-01

Few studies have examined the psychological factors underlying the association between cell phone use and motor vehicle crash. We sought to examine the factor structure and convergent validity of a measure of problematic cell phone use, and to explore whether compulsive cell phone use is associated with a history of motor vehicle crash. We recruited a sample of 383 undergraduate college students to complete an online assessment that included cell phone use and driving history. We explored the dimensionality of the Cell Phone Overuse Scale (CPOS) using factor analytic methods. Ordinary least-squares regression models were used to examine associations between identified subscales and measures of impulsivity, alcohol use, and anxious relationship style, to establish convergent validity. We used negative binomial regression models to investigate associations between the CPOS and motor vehicle crash incidence. We found the CPOS to be composed of four subscales: anticipation, activity interfering, emotional reaction, and problem recognition. Each displayed significant associations with aspects of impulsivity, problematic alcohol use, and anxious relationship style characteristics. Only the anticipation subscale demonstrated statistically significant associations with reported motor vehicle crash incidence, controlling for clinical and demographic characteristics (relative ratio, 1.13; confidence interval, 1.01-1.26). For each 1-point increase on the 6-point anticipation subscale, risk for previous motor vehicle crash increased by 13%. Crash risk is strongly associated with heightened anticipation about incoming phone calls or messages. The mean score on the CPOS is associated with increased risk of motor vehicle crash but does not reach statistical significance. Copyright © 2013 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Increased diagnostic activity in general practice during the year preceding colorectal cancer diagnosis.

PubMed

Hansen, Pernille Libach; Hjertholm, Peter; Vedsted, Peter

2015-08-01

Accurate diagnostic activity in general practice before colorectal cancer (CRC) diagnosis is crucial for an early detection of CRC. This study aimed to investigate the rates of daytime consultations, hemoglobin (Hb) measurements and medicine prescriptions for hemorrhoids in general practice in the year preceding CRC diagnosis. Using Danish registries, we conducted a population-based matched cohort study including CRC patients aged 40-80 years (n = 19,209) and matched references (n = 192,090). We calculated odds ratios (ORs) using a conditional logistical regression model and incidence rate ratios (IRRs) using a negative binomial regression model. The CRC patients had significantly more consultations from 9 months before diagnosis and significantly increased rates of Hb measurements from up to 17 months before diagnosis compared with references. Furthermore, up to 18 months before diagnosis, CRC patients had significantly higher rates of prescriptions for hemorrhoids; and 2 months before diagnosis, the IRR was 12.24 (95% confidence interval (CI): 10.29-14.55) for men. The positive predictive value (PPV) of CRC for having a first-time prescription for hemorrhoids was highest among men aged 70-80 years [PPV = 3.2% (95% CI: 2.8-3.7)]. High prescription rates were predominantly seen among rectal cancer patients, whereas colon cancer patients had higher rates of consultations and Hb measurements. This study revealed a significant increase in healthcare seeking and diagnostic activity in general practice in the year prior to CRC diagnosis, which indicates the presence of a "diagnostic time window" and a potential for earlier diagnosis of CRC based on clinical signs and symptoms. © 2015 UICC.

Compulsive Cell Phone Use and History of Motor Vehicle Crash

PubMed Central

O’Connor, Stephen S.; Whitehill, Jennifer M.; King, Kevin M.; Kernic, Mary A.; Boyle, Linda Ng; Bresnahan, Brian; Mack, Christopher D.; Ebel, Beth E.

2013-01-01

Introduction Few studies have examined the psychological factors underlying the association between cell phone use and motor vehicle crash. We sought to examine the factor structure and convergent validity of a measure of problematic cell phone use and explore whether compulsive cell phone use is associated with a history of motor vehicle crash. Methods We recruited a sample of 383 undergraduate college students to complete an on-line assessment that included cell phone use and driving history. We explored the dimensionality of the Cell Phone Overuse Scale (CPOS) using factor analytic methods. Ordinary least squares regression models were used to examine associations between identified subscales and measures of impulsivity, alcohol use, and anxious relationship style to establish convergent validity. We used negative binomial regression models to investigate associations between the CPOS and motor vehicle crash incidence. Results We found the CPOS to be comprised of four subscales: anticipation, activity interfering, emotional reaction, and problem recognition. Each displayed significant associations with aspects of impulsivity, problematic alcohol use, and anxious relationship style characteristics. Only the anticipation subscale demonstrated statistically significant associations with reported motor vehicle crash incidence, controlling for clinical and demographic characteristics (RR 1.13, CI 1.01 to 1.26). For each one-point increase on the 6-point anticipation subscale, risk for previous motor vehicle crash increased by 13%. Conclusions Crash risk is strongly associated with heightened anticipation about incoming phone calls or messages. The mean score on the CPOS is associated with increased risk of motor vehicle crash but does not reach statistical significance. PMID:23910571

Evaluation of real-world mobility in age-related macular degeneration.

PubMed

Sengupta, Sabyasachi; Nguyen, Angeline M; van Landingham, Suzanne W; Solomon, Sharon D; Do, Diana V; Ferrucci, Luigi; Friedman, David S; Ramulu, Pradeep Y

2015-01-30

Previous research has suggested an association between poor vision and decreased mobility, including restricted levels of physical activity and travel away from home. We sought to determine the impact of age-related macular degeneration (AMD) on these measures of mobility. Fifty-seven AMD patients with bilateral, or severe unilateral, visual impairment were compared to 59 controls with normal vision. All study subjects were between the ages of 60 and 80. Subjects wore accelerometers and cellular network-based tracking devices over 7 days of normal activity. Number of steps taken, time spent in moderate-to-vigorous physical activity (MVPA), number of excursions from home, and time spent away from home were the primary outcome measures. In multivariate negative binomial regression models adjusted for age, gender, race, comorbidities, and education, AMD participants took fewer steps than controls (18% fewer steps per day, p = 0.01) and spent significantly less time in MVPA (35% fewer minutes, p < 0.001). In multivariate logistic regression models adjusting for age, sex, race, cognition, comorbidities, and grip strength, AMD subjects showed an increased likelihood of not leaving their home on a given day (odds ratio = 1.36, p = 0.04), but did not show a significant difference in the magnitude of time spent away from home (9% fewer minutes, p = 0.11). AMD patients with poorer vision engage in significantly less physical activity and take fewer excursions away from the home. Further studies identifying the factors mediating the relationship between vision loss and mobility are needed to better understand how to improve mobility among AMD patients.

Animal Ownership and Touching Enrich the Context of Social Contacts Relevant to the Spread of Human Infectious Diseases.

PubMed

Kifle, Yimer Wasihun; Goeyvaerts, Nele; Van Kerckhove, Kim; Willem, Lander; Kucharski, Adam; Faes, Christel; Leirs, Herwig; Hens, Niel; Beutels, Philippe

2015-01-01

Many human infectious diseases originate from animals or are transmitted through animal vectors. We aimed to identify factors that are predictive of ownership and touching of animals, assess whether animal ownership influences social contact behavior, and estimate the probability of a major zoonotic outbreak should a transmissible influenza-like pathogen be present in animals, all in the setting of a densely populated European country. A diary-based social contact survey (n = 1768) was conducted in Flanders, Belgium, from September 2010 until February 2011. Many participants touched pets (46%), poultry (2%) or livestock (2%) on a randomly assigned day, and a large proportion of participants owned such animals (51%, 15% and 5%, respectively). Logistic regression models indicated that larger households are more likely to own an animal and, unsurprisingly, that animal owners are more likely to touch animals. We observed a significant effect of age on animal ownership and touching. The total number of social contacts during a randomly assigned day was modeled using weighted-negative binomial regression. Apart from age, household size and day type (weekend versus weekday and regular versus holiday period), animal ownership was positively associated with the total number of social contacts during the weekend. Assuming that animal ownership and/or touching are at-risk events, we demonstrate a method to estimate the outbreak potential of zoonoses. We show that in Belgium animal-human interactions involving young children (0-9 years) and adults (25-54 years) have the highest potential to cause a major zoonotic outbreak.

The association between current unemployment and clinically determined poor oral health.

PubMed

Al-Sudani, Fouad Y H; Vehkalahti, Miira M; Suominen, Anna L

2015-08-01

The aim of this study was to assess whether current unemployment was associated with poor oral health and whether there was a difference in oral health according to the duration of the current unemployment. As part of the Health 2000 Survey in Finland (a nationwide comprehensive health examination survey), we used its data based on interviews, questionnaires, and clinical oral examinations of the 30- to 63-year-old respondents (n = 4773). Current employment status was measured in its dichotomous form, employed versus unemployed, and length of current unemployment was classified into four categories. We measured oral health in terms of numbers of missing teeth, of sound teeth, of filled teeth, of decayed teeth, and of teeth with deepened periodontal pockets (≥4 mm, ≥6 mm). Poisson regression models were fitted for all oral health outcomes except number of decayed teeth, for which negative binomial regression model was used. Oral health-related behaviors and sociodemographic and socioeconomic factors were added to the analyses. The unemployed subjects had higher numbers of missing teeth, of decayed teeth, and of teeth with periodontal pockets than the employed ones. The association remained consistent even after adjustments. Oral health-related behaviors seemed to mediate the association. We found no association between unemployment and number of sound teeth. Current long-term unemployment showed stronger association with poor oral health than short-term among women. The unemployed can be considered as a risk group for poor oral health. Oral healthcare should be reoriented toward those who are unemployed. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Animal Ownership and Touching Enrich the Context of Social Contacts Relevant to the Spread of Human Infectious Diseases

PubMed Central

Kifle, Yimer Wasihun; Goeyvaerts, Nele; Van Kerckhove, Kim; Willem, Lander; Faes, Christel; Leirs, Herwig; Hens, Niel; Beutels, Philippe

2015-01-01

Many human infectious diseases originate from animals or are transmitted through animal vectors. We aimed to identify factors that are predictive of ownership and touching of animals, assess whether animal ownership influences social contact behavior, and estimate the probability of a major zoonotic outbreak should a transmissible influenza-like pathogen be present in animals, all in the setting of a densely populated European country. A diary-based social contact survey (n = 1768) was conducted in Flanders, Belgium, from September 2010 until February 2011. Many participants touched pets (46%), poultry (2%) or livestock (2%) on a randomly assigned day, and a large proportion of participants owned such animals (51%, 15% and 5%, respectively). Logistic regression models indicated that larger households are more likely to own an animal and, unsurprisingly, that animal owners are more likely to touch animals. We observed a significant effect of age on animal ownership and touching. The total number of social contacts during a randomly assigned day was modeled using weighted-negative binomial regression. Apart from age, household size and day type (weekend versus weekday and regular versus holiday period), animal ownership was positively associated with the total number of social contacts during the weekend. Assuming that animal ownership and/or touching are at-risk events, we demonstrate a method to estimate the outbreak potential of zoonoses. We show that in Belgium animal-human interactions involving young children (0–9 years) and adults (25–54 years) have the highest potential to cause a major zoonotic outbreak. PMID:26193480

Drought impact functions as intermediate step towards drought damage assessment

NASA Astrophysics Data System (ADS)

Bachmair, Sophie; Svensson, Cecilia; Prosdocimi, Ilaria; Hannaford, Jamie; Helm Smith, Kelly; Svoboda, Mark; Stahl, Kerstin

2016-04-01

While damage or vulnerability functions for floods and seismic hazards have gained considerable attention, there is comparably little knowledge on drought damage or loss. On the one hand this is due to the complexity of the drought hazard affecting different domains of the hydrological cycle and different sectors of human activity. Hence, a single hazard indicator is likely not able to fully capture this multifaceted hazard. On the other hand, drought impacts are often non-structural and hard to quantify or monetize. Examples are impaired navigability of streams, restrictions on domestic water use, reduced hydropower production, reduced tree growth, and irreversible deterioration/loss of wetlands. Apart from reduced crop yield, data about drought damage or loss with adequate spatial and temporal resolution is scarce, making the development of drought damage functions difficult. As an intermediate step towards drought damage functions we exploit text-based reports on drought impacts from the European Drought Impact report Inventory and the US Drought Impact Reporter to derive surrogate information for drought damage or loss. First, text-based information on drought impacts is converted into timeseries of absence versus presence of impacts, or number of impact occurrences. Second, meaningful hydro-meteorological indicators characterizing drought intensity are identified. Third, different statistical models are tested as link functions relating drought hazard indicators with drought impacts: 1) logistic regression for drought impacts coded as binary response variable; and 2) mixture/hurdle models (zero-inflated/zero-altered negative binomial regression) and an ensemble regression tree approach for modeling the number of drought impact occurrences. Testing the predictability of (number of) drought impact occurrences based on cross-validation revealed a good agreement between observed and modeled (number of) impacts for regions at the scale of federal states or provinces with good data availability. Impact functions representing localized drought impacts are more challenging to construct given that less data is available, yet may provide information that more directly addresses stakeholders' needs. Overall, our study contributes insights into how drought intensity translates into ecological and socioeconomic impacts, and how such information may be used for enhancing drought monitoring and early warning.

Finite mixture modeling approach for developing crash modification factors in highway safety analysis.

PubMed

Park, Byung-Jung; Lord, Dominique; Wu, Lingtao

2016-10-28

This study aimed to investigate the relative performance of two models (negative binomial (NB) model and two-component finite mixture of negative binomial models (FMNB-2)) in terms of developing crash modification factors (CMFs). Crash data on rural multilane divided highways in California and Texas were modeled with the two models, and crash modification functions (CMFunctions) were derived. The resultant CMFunction estimated from the FMNB-2 model showed several good properties over that from the NB model. First, the safety effect of a covariate was better reflected by the CMFunction developed using the FMNB-2 model, since the model takes into account the differential responsiveness of crash frequency to the covariate. Second, the CMFunction derived from the FMNB-2 model is able to capture nonlinear relationships between covariate and safety. Finally, following the same concept as those for NB models, the combined CMFs of multiple treatments were estimated using the FMNB-2 model. The results indicated that they are not the simple multiplicative of single ones (i.e., their safety effects are not independent under FMNB-2 models). Adjustment Factors (AFs) were then developed. It is revealed that current Highway Safety Manual's method could over- or under-estimate the combined CMFs under particular combination of covariates. Safety analysts are encouraged to consider using the FMNB-2 models for developing CMFs and AFs. Copyright © 2016 Elsevier Ltd. 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)

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…

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.

The political ecology of disaster: an analysis of factors influencing U.S. tornado fatalities and injuries, 1998-2000.

PubMed

Donner, William R

2007-08-01

This study examines casualties from tornadoes in the United States between the years 1998 and 2000. A political model of human ecology (POET) was used to explore how the environment, technology, and social inequality influence rates of fatalities and injuries in two models. Data were drawn from four sources: John Hart's Severe Plot v2.0, National Weather Service (NWS) Warning Verification data, Storm Prediction Center (SPC) watch data, and tract-level census data. Negative binomial regression was used to analyze the causes of tornado fatalities and injuries. Independent variables (following POET) are classified in the following manner: population, organization, environment, and technology. Rural population, population density, and household size correspond to population; racial minorities and deprivation represent social organization; tornado area represents environment; and tornado watches and warnings, as well as mobile homes, correspond to technology. Findings suggest a strong relationship between the size of a tornado path and both fatalities and injuries, whereas other measures related to technology, population, and organization produce significant yet mixed results. Census tracts having larger populations of rural residents was, of the nonenvironmental factors, the most conclusive regarding its effects across the two models. The outcomes of analysis, although not entirely supportive of the model presented in this study, suggest to some degree that demographic and social factors play a role in vulnerability to tornadoes.

Who Visits a National Park and What do They Get Out of It?: A Joint Visitor Cluster Analysis and Travel Cost Model for Yellowstone National Park

NASA Astrophysics Data System (ADS)

Benson, Charles; Watson, Philip; Taylor, Garth; Cook, Philip; Hollenhorst, Steve

2013-10-01

Yellowstone National Park visitor data were obtained from a survey collected for the National Park Service by the Park Studies Unit at the University of Idaho. Travel cost models have been conducted for national parks in the United States; however, this study builds on these studies and investigates how benefits vary by types of visitors who participate in different activities while at the park. Visitor clusters were developed based on activities in which a visitor participated while at the park. The clusters were analyzed and then incorporated into a travel cost model to determine the economic value (consumer surplus) that the different visitor groups received from visiting the park. The model was estimated using a zero-truncated negative binomial regression corrected for endogenous stratification. The travel cost price variable was estimated using both 1/3 and 1/4 the wage rate to test for sensitivity to opportunity cost specification. The average benefit across all visitor cluster groups was estimated at between 235 and 276 per person per trip. However, per trip benefits varied substantially across clusters; from 90 to 103 for the "value picnickers," to 185-263 for the "backcountry enthusiasts," 189-278 for the "do it all adventurists," 204-303 for the "windshield tourists," and 323-714 for the "creature comfort" cluster group.

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

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.

Detection of Clostridium difficile infection clusters, using the temporal scan statistic, in a community hospital in southern Ontario, Canada, 2006-2011.

PubMed

Faires, Meredith C; Pearl, David L; Ciccotelli, William A; Berke, Olaf; Reid-Smith, Richard J; Weese, J Scott

2014-05-12

In hospitals, Clostridium difficile infection (CDI) surveillance relies on unvalidated guidelines or threshold criteria to identify outbreaks. This can result in false-positive and -negative cluster alarms. The application of statistical methods to identify and understand CDI clusters may be a useful alternative or complement to standard surveillance techniques. The objectives of this study were to investigate the utility of the temporal scan statistic for detecting CDI clusters and determine if there are significant differences in the rate of CDI cases by month, season, and year in a community hospital. Bacteriology reports of patients identified with a CDI from August 2006 to February 2011 were collected. For patients detected with CDI from March 2010 to February 2011, stool specimens were obtained. Clostridium difficile isolates were characterized by ribotyping and investigated for the presence of toxin genes by PCR. CDI clusters were investigated using a retrospective temporal scan test statistic. Statistically significant clusters were compared to known CDI outbreaks within the hospital. A negative binomial regression model was used to identify associations between year, season, month and the rate of CDI cases. Overall, 86 CDI cases were identified. Eighteen specimens were analyzed and nine ribotypes were classified with ribotype 027 (n = 6) the most prevalent. The temporal scan statistic identified significant CDI clusters at the hospital (n = 5), service (n = 6), and ward (n = 4) levels (P ≤ 0.05). Three clusters were concordant with the one C. difficile outbreak identified by hospital personnel. Two clusters were identified as potential outbreaks. The negative binomial model indicated years 2007-2010 (P ≤ 0.05) had decreased CDI rates compared to 2006 and spring had an increased CDI rate compared to the fall (P = 0.023). Application of the temporal scan statistic identified several clusters, including potential outbreaks not detected by hospital personnel. The identification of time periods with decreased or increased CDI rates may have been a result of specific hospital events. Understanding the clustering of CDIs can aid in the interpretation of surveillance data and lead to the development of better early detection systems.

Occupational injury among hospital patient-care workers: what is the association with workplace verbal abuse?

PubMed

Sabbath, Erika L; Hurtado, David A; Okechukwu, Cassandra A; Tamers, Sara L; Nelson, Candace; Kim, Seung-Sup; Wagner, Gregory; Sorenson, Glorian

2014-02-01

To test the association between workplace abuse exposure and injury risk among hospital workers. We hypothesized that exposed workers would have higher injury rates than unexposed workers. Survey of direct-care workers (n = 1,497) in two hospitals. Exposure to workplace abuse was assessed through self-report; occupational injury reports were extracted from employee records. We tested associations between non-physical workplace violence and injury using log-binomial regression and multilevel modeling. Adjusted prevalence ratio (PR) for injury associated with being yelled at was 1.52 (95% CI 1.19, 1.95); for experiencing hostile/offensive gestures 1.43 (1.11, 1.82); and for being sworn at 1.41 (1.09, 1.81). In analyses by injury subtypes, musculoskeletal injuries were more strongly associated with abuse than were acute traumatic injuries. Associations operated on group and individual levels and were most consistently associated with abuse perpetrated by patients. Exposure to workplace abuse may be a risk factor for injuries among hospital workers. © 2013 Wiley Periodicals, Inc.

Gasoline prices and their relationship to drunk-driving crashes.

PubMed

Chi, Guangqing; Zhou, Xuan; McClure, Timothy E; Gilbert, Paul A; Cosby, Arthur G; Zhang, Li; Robertson, Angela A; Levinson, David

2011-01-01

This study investigates the relationship between changing gasoline prices and drunk-driving crashes. Specifically, we examine the effects of gasoline prices on drunk-driving crashes in Mississippi by several crash types and demographic groups at the monthly level from 2004 to 2008, a period experiencing great fluctuation in gasoline prices. An exploratory visualization by graphs shows that higher gasoline prices are generally associated with fewer drunk-driving crashes. Higher gasoline prices depress drunk-driving crashes among young and adult drivers, among male and female drivers, and among white and black drivers. Results from negative binomial regression models show that when gas prices are higher, there are fewer drunk-driving crashes, particularly among property-damage-only crashes. When alcohol consumption levels are higher, there are more drunk-driving crashes, particularly fatal and injury crashes. The effects of gasoline prices and alcohol consumption are stronger on drunk-driving crashes than on all crashes. The findings do not vary much across different demographic groups. Overall, gasoline prices have greater effects on less severe crashes and alcohol consumption has greater effects on more severe crashes. Copyright © 2010 Elsevier Ltd. All rights reserved.

The relationship between gun ownership and firearm homicide rates in the United States, 1981-2010.

PubMed

Siegel, Michael; Ross, Craig S; King, Charles

2013-11-01

We examined the relationship between levels of household firearm ownership, as measured directly and by a proxy-the percentage of suicides committed with a firearm-and age-adjusted firearm homicide rates at the state level. We conducted a negative binomial regression analysis of panel data from the Centers for Disease Control and Prevention's Web-Based Injury Statistics Query and Reporting Systems database on gun ownership and firearm homicide rates across all 50 states during 1981 to 2010. We determined fixed effects for year, accounted for clustering within states with generalized estimating equations, and controlled for potential state-level confounders. Gun ownership was a significant predictor of firearm homicide rates (incidence rate ratio = 1.009; 95% confidence interval = 1.004, 1.014). This model indicated that for each percentage point increase in gun ownership, the firearm homicide rate increased by 0.9%. We observed a robust correlation between higher levels of gun ownership and higher firearm homicide rates. Although we could not determine causation, we found that states with higher rates of gun ownership had disproportionately large numbers of deaths from firearm-related homicides.

Correlates of health care utilization under targeted interventions: The case of female sex workers in Andhra Pradesh, India.

PubMed

Sharma, Varun; Suryawanshi, Dipak; Saggurti, Niranjan; Bharat, Shalini

2017-11-01

Accessibility and frequency of use of health care services among female sex workers (FSWs) are constrained by various factors. In this analysis, we examined the correlates of frequency of using health care services under targeted interventions among FSWs. A sample of FSWs (N = 1,973) was obtained from a second round (2012) of Behavioral Tracking Survey, conducted in five districts of Andhra Pradesh, a high-HIV-prevalence state in southern India. We used negative binomial regression models to analyze frequency of utilization of health care services among FSWs. Based on our analysis, we suggest that various predisposing and enabling factors were found to be significantly associated with the visit to NGO clinics for treatment of any health problem, any sexually transmitted infection symptom, and the number of condoms received from the peer worker or condom depot. We suggest the need for further research with respect to various correlates of frequency of using health care among FSWs to develop effective intervention strategies in countries that have high HIV prevalence among FSWs and targeted interventions need more diligent implementation to reach the unreached.

Work experience and gender differences in chronic disease risk in older Mexicans.

PubMed

Salinas, Jennifer J; Peek, M Kristen

2008-08-01

The purpose of this study is to examine the relationship between labor force participation and gender differences in the prevalence of arthritis, diabetes, and hypertension. The Mexican Health and Aging Survey (MHAS) data is nationally representative sample of older Mexicans 50 years and older. Binomial logistic regression models were performed to examine differences between older Mexican men and women in the prevalence of arthritis, diabetes, and hypertension. Interaction effects were also estimated between gender and occupation, length of time in the labor force, and pension eligibility. Older Mexican women have a significantly greater risk of having arthritis, diabetes, and hypertension. Findings from this study suggest that within the same occupational classification, women suffer from the damaging effects on health to a greater extent than men. Interaction effects show that women who work in services or in client's home are particularly susceptible to arthritis. Moreover, women who work in sales were at a significantly greater risk of hypertension than men. Older Mexican women are at greater risk of chronic disease and part of their vulnerability is a result of the type of work that they do.

Neighborhood characteristics contribute to urban alcohol availability: Accounting for race/ethnicity and social disorganization.

PubMed

Snowden, Aleksandra J

2016-01-01

This study examined the role that race/ethnicity and social disorganization play in alcohol availability in Milwaukee, Wisconsin, census block groups. This study estimated negative binomial regression models to examine separately the relationship between neighborhood racial/ethnic composition and social disorganization levels for (1) total, (2) on-premise, and (3) off-premise alcohol outlets. Results of this study suggest that proportion Hispanic was positively associated with total and with off-premise alcohol outlets. Second, proportion African American was negatively associated with on-premise alcohol outlets and positively associated with off-premise alcohol outlets. Proportion Asian was not associated with total, on-premise, or off-premise alcohol outlets. However, the effects of race/ethnicity on alcohol availability were either unrelated or negatively related to alcohol outlet availability once neighborhood social disorganization levels were taken into account, and social disorganization was positively and significantly associated with all alcohol outlet types. Neighborhood characteristics contribute to alcohol availability and must be considered in any efforts aimed toward prevention of alcohol-related negative health and social outcomes.

Utilization of emergency and hospital services among individuals in substance abuse treatment

PubMed Central

2014-01-01

Background To examine risk factors for use of hospital services among racial and ethnic minority clients in publicly funded substance abuse treatment in Los Angeles County, California. We explored cross-sectional annual data (2006 to 2009) from the Los Angeles County Participant Reporting System for adult participants (n = 73,251) who received services from treatment programs (n = 231). Methods This retrospective analysis of county admission data relied on hierarchical linear negative binomial regression models to explore number of hospital visits, accounting for clients nested in programs. Client data were collected during personal interviews at admission. Findings Our findings support previous work that noted increased use of emergency rooms among individuals suffering from mental health- and substance use-related issues and extend the knowledge base by highlighting other important features such as treatment need, i.e., residential compared to outpatient treatment. Conclusions These findings have implications for health care policy in terms of the need to increase prevention services and reduce costly hospitalization for a population at significant risk of co-occurring mental and physical disorders. PMID:24708866

Uber and Metropolitan Traffic Fatalities in the United States.

PubMed

Brazil, Noli; Kirk, David S

2016-08-01

Uber and similar rideshare services are rapidly dispersing in cities across the United States and beyond. Given the convenience and low cost, Uber has been characterized as a potential countermeasure for reducing the estimated 121 million episodes of drunk driving and the 10,000 resulting traffic fatalities that occur annually in the United States. We exploited differences in the timing of the deployment of Uber in US metropolitan counties from 2005 to 2014 to test the association between the availability of Uber's rideshare services and total, drunk driving-related, and weekend- and holiday-specific traffic fatalities in the 100 most populated metropolitan areas in the United States using negative binomial and Poisson regression models. We found that the deployment of Uber services in a given metropolitan county had no association with the number of subsequent traffic fatalities, whether measured in aggregate or specific to drunk-driving fatalities or fatalities during weekends and holidays. © The Author 2016. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Differences between seven measures of self-reported numbers of clients of female sex workers in southern India: implications for individual- and population-level analysis.

PubMed

Deering, Kathleen N; Vickerman, P; Pickles, M; Moses, S; Blanchard, J F; Ramesh, B M; Isac, S; Boily, M-C

2013-02-01

Quantifying sexual activity of sub-populations with high-risk sexual behaviour is important in understanding HIV epidemiology. This study examined inconsistency of seven outcomes measuring self-reported clients per month (CPM) of female sex workers (FSWs) in southern India and implications for individual/population-level analysis. Multivariate negative binomial regression was used to compare key social/environmental factors associated with each outcome. A transmission dynamics model was used to assess the impact of differences between outcomes on population-level FSW/client HIV prevalence. Outcomes based on 'clients per last working day' produced lower estimates than those based on 'clients per typical day'. Although the outcomes were strongly correlated, their averages differed by approximately two-fold (range 39.0-79.1 CPM). The CPM measure chosen did not greatly influence standard epidemiological 'risk factor' analysis. Differences across outcomes influenced HIV prevalence predictions. Due to this uncertainty, we recommend basing population-based estimates on the range of outcomes, particularly when assessing the impact of interventions.

Resources predicting positive and negative affect during the experience of stress: a study of older Asian Indian immigrants in the United States.

PubMed

Diwan, Sadhna; Jonnalagadda, Satya S; Balaswamy, Shantha

2004-10-01

Using the life stress model of psychological well-being, in this study we examined risks and resources predicting the occurrence of both positive and negative affect among older Asian Indian immigrants who experienced stressful life events. We collected data through a telephone survey of 226 respondents (aged 50 years and older) in the Southeastern United States. We used hierarchical, negative binomial regression analyses to examine correlates of positive and negative affect. Different coping resources influenced positive and negative affect when stressful life events were controlled for. Being female was a common risk factor for poorer positive and increased negative affect. Satisfaction with friendships and a cultural or ethnic identity that is either bicultural or more American were predictive of greater positive affect. Greater religiosity and increased mastery were resources predicting less negative affect. Cognitive and structural interventions that increase opportunities for social integration, increasing mastery, and addressing spiritual concerns are discussed as ways of coping with stress to improve the well-being of individuals in this immigrant community.

The employment of nurses in publicly funded substance abuse treatment programs.

PubMed

Knudsen, Hannah K; Abraham, Amanda J

2012-10-01

Little is known about the organizational and environmental factors associated with the employment of nurses in substance abuse treatment programs. Using data collected from the administrators of 250 publicly funded substance abuse treatment programs, this study examined the organizational and environmental correlates of nurse employment in these settings. Negative binomial regression models indicated that the number of nurses employed by treatment programs was positively associated with government ownership, location within a healthcare setting, and the availability of detoxification services. Outpatient-only programs employed fewer nurses than programs with inpatient/residential services. Two environmental factors were associated with nurse employment. Programs that more strongly endorsed a scale of financial barriers employed significantly fewer nurses, whereas programs indicating that funding from state contracts could be used to pay for healthcare providers employed significantly more nurses. These findings suggest that organizational decisions about employing nurses may reflect both the characteristics of the program and the funding environment. Future research should continue to examine the employment of nurses in substance abuse treatment settings, particularly given the shifting environment due to the implementation of healthcare reform.

Trends and correlates of child passenger restraint use in 6 Northwest tribes: the Native Children Always Ride Safe (Native CARS) project.

PubMed

Lapidus, Jodi A; Smith, Nicole Holdaway; Lutz, Tam; Ebel, Beth E

2013-02-01

We compared proportions of children properly restrained in vehicles in 6 Northwest American Indian tribes in 2003 and 2009, and evaluated risks for improper restraint. During spring 2009 we conducted a vehicle observation survey in Oregon, Washington, and Idaho tribal communities. We estimated the proportions of children riding properly restrained and evaluated correlates of improper restraint via log-binomial regression models for clustered data. We observed 1853 children aged 12 years and younger in 1207 vehicles; 49% rode properly restrained. More children aged 8 years and younger rode properly restrained in 2009 than 2003 (51% vs 29%; P < .001). Older booster seat-eligible children were least likely to ride properly restrained in 2009 (25%). American Indian children were more likely to ride improperly restrained than nonnative children in the same communities. Other risk factors included riding with an unrestrained or nonparent driver, riding where child passenger restraint laws were weaker than national guidelines, and taking a short trip. Although proper restraint has increased, it remains low. Tribe-initiated interventions to improve child passenger restraint use are under way.

Self-Efficacy as a Mediator of the Relationship Between the Perceived Food Environment and Healthy Eating in a Low Income Population in Los Angeles County.

PubMed

Gase, Lauren N; Glenn, Beth; Kuo, Tony

2016-04-01

While previous studies have described psychosocial and environmental factors that contribute to healthy eating, much remains unknown about the interactions between them. We assessed the relationship between the perceived food environment, self-efficacy and fruit and vegetable consumption, using data from a sample of racially diverse, low-income adult clientele of five public health centers in Los Angeles County (n = 1503). We constructed a negative binomial regression model to examine the association between perceived food environment and the number of fruits and vegetables consumed. For every one point increase on the perceived food environment scale, individuals ate about 5% more fruits and vegetables (95% CI 1.007, 1.089), controlling for other covariates. Self-efficacy was shown to be a significant mediator (mediated effect = 0.010; 95% CI 0.002, 0.020), accounting for 22.9% of the effect. Efforts to increase access to healthy options may not only improve eating behaviors, but also influence individuals' beliefs that they can eat healthfully.

Electronic fetal heart rate monitoring and its relationship to neonatal and infant mortality in the United States.

PubMed

Chen, Han-Yang; Chauhan, Suneet P; Ananth, Cande V; Vintzileos, Anthony M; Abuhamad, Alfred Z

2011-06-01

To examine the association between electronic fetal heart rate monitoring and neonatal and infant mortality, as well as neonatal morbidity. We used the United States 2004 linked birth and infant death data. Multivariable log-binomial regression models were fitted to estimate risk ratio for association between electronic fetal heart rate monitoring and mortality, while adjusting for potential confounders. In 2004, 89% of singleton pregnancies had electronic fetal heart rate monitoring. Electronic fetal heart rate monitoring was associated with significantly lower infant mortality (adjusted relative risk, 0.75); this was mainly driven by the lower risk of early neonatal mortality (adjusted relative risk, 0.50). In low-risk pregnancies, electronic fetal heart rate monitoring was associated with decreased risk for Apgar scores <4 at 5 minutes (relative risk, 0.54); in high-risk pregnancies, with decreased risk of neonatal seizures (relative risk, 0.65). In the United States, the use of electronic fetal heart rate monitoring was associated with a substantial decrease in early neonatal mortality and morbidity that lowered infant mortality. Copyright © 2011 Mosby, Inc. All rights reserved.

Faith-Based Hospitals and Variation in Psychiatric Inpatient Length of Stay in California, 2002-2011.

PubMed

Banta, Jim E; McKinney, Ogbochi

2016-06-01

We examined current treatment patterns at faith-based hospitals. Psychiatric discharges from all community-based hospitals in California were obtained for 2002-2011 and a Behavioral Model of Health Services Utilization approach used to study hospital religious affiliation and length of stay (LOS). During 10 years there were 1,976,893 psychiatric inpatient discharges, of which 14.3% were from faith-based nonprofit hospitals (eighteen Catholic, seven Seventh-day Adventist, and one Jewish hospital). Modest differences in patient characteristics and shorter LOS (7.5 vs. 8.3 days) were observed between faith-based and other hospitals. Multivariable negative binomial regression found shorter LOS at faith-based nonprofit hospitals (coefficient = -0.1169, p < 0.001, Wald χ (2) = 55) and greater LOS at all nonprofits (coefficient = 1.5909, p < 0.001, Wald χ (2) = 2755) as compared to local government-controlled hospitals. Faith-based hospitals provide a substantial and consistent amount of psychiatric care in California and may have slightly lower LOS after adjusting for patient and other hospital characteristics.

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.

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.

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…

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

Operating characteristics of full count and binomial sampling plans for green peach aphid (Hemiptera: Aphididae) in potato.

PubMed

Kabaluk, J Todd; Binns, Michael R; Vernon, Robert S

2006-06-01

Counts of green peach aphid, Myzus persicae (Sulzer) (Hemiptera: Aphididae), in potato, Solanum tuberosum L., fields were used to evaluate the performance of the sampling plan from a pest management company. The counts were further used to develop a binomial sampling method, and both full count and binomial plans were evaluated using operating characteristic curves. Taylor's power law provided a good fit of the data (r2 = 0.95), with the relationship between the variance (s2) and mean (m) as ln(s2) = 1.81(+/- 0.02) + 1.55(+/- 0.01) ln(m). A binomial sampling method was developed using the empirical model ln(m) = c + dln(-ln(1 - P(T))), to which the data fit well for tally numbers (T) of 0, 1, 3, 5, 7, and 10. Although T = 3 was considered the most reasonable given its operating characteristics and presumed ease of classification above or below critical densities (i.e., action thresholds) of one and 10 M. persicae per leaf, the full count method is shown to be superior. The mean number of sample sites per field visit by the pest management company was 42 +/- 19, with more than one-half (54%) of the field visits involving sampling 31-50 sample sites, which was acceptable in the context of operating characteristic curves for a critical density of 10 M. persicae per leaf. Based on operating characteristics, actual sample sizes used by the pest management company can be reduced by at least 50%, on average, for a critical density of 10 M. persicae per leaf. For a critical density of one M. persicae per leaf used to avert the spread of potato leaf roll virus, sample sizes from 50 to 100 were considered more suitable.

Novel formulation of the ℳ model through the Generalized-K distribution for atmospheric optical channels.

PubMed

Garrido-Balsells, José María; Jurado-Navas, Antonio; Paris, José Francisco; Castillo-Vazquez, Miguel; Puerta-Notario, Antonio

2015-03-09

In this paper, a novel and deeper physical interpretation on the recently published Málaga or ℳ statistical distribution is provided. This distribution, which is having a wide acceptance by the scientific community, models the optical irradiance scintillation induced by the atmospheric turbulence. Here, the analytical expressions previously published are modified in order to express them by a mixture of the known Generalized-K and discrete Binomial and Negative Binomial distributions. In particular, the probability density function (pdf) of the ℳ model is now obtained as a linear combination of these Generalized-K pdf, in which the coefficients depend directly on the parameters of the ℳ distribution. In this way, the Málaga model can be physically interpreted as a superposition of different optical sub-channels each of them described by the corresponding Generalized-K fading model and weighted by the ℳ dependent coefficients. The expressions here proposed are simpler than the equations of the original ℳ model and are validated by means of numerical simulations by generating ℳ -distributed random sequences and their associated histogram. This novel interpretation of the Málaga statistical distribution provides a valuable tool for analyzing the performance of atmospheric optical channels for every turbulence condition.

Optimization of finite difference forward modeling for elastic waves based on optimum combined window functions

NASA Astrophysics Data System (ADS)

Jian, Wang; Xiaohong, Meng; Hong, Liu; Wanqiu, Zheng; Yaning, Liu; Sheng, Gui; Zhiyang, Wang

2017-03-01

Full waveform inversion and reverse time migration are active research areas for seismic exploration. Forward modeling in the time domain determines the precision of the results, and numerical solutions of finite difference have been widely adopted as an important mathematical tool for forward modeling. In this article, the optimum combined of window functions was designed based on the finite difference operator using a truncated approximation of the spatial convolution series in pseudo-spectrum space, to normalize the outcomes of existing window functions for different orders. The proposed combined window functions not only inherit the characteristics of the various window functions, to provide better truncation results, but also control the truncation error of the finite difference operator manually and visually by adjusting the combinations and analyzing the characteristics of the main and side lobes of the amplitude response. Error level and elastic forward modeling under the proposed combined system were compared with outcomes from conventional window functions and modified binomial windows. Numerical dispersion is significantly suppressed, which is compared with modified binomial window function finite-difference and conventional finite-difference. Numerical simulation verifies the reliability of the proposed method.

Probabilistic assessment of precipitation-triggered landslides using historical records of landslide occurence, Seattle, Washington

USGS Publications Warehouse

Coe, J.A.; Michael, J.A.; Crovelli, R.A.; Savage, W.Z.; Laprade, W.T.; Nashem, W.D.

2004-01-01

Ninety years of historical landslide records were used as input to the Poisson and binomial probability models. Results from these models show that, for precipitation-triggered landslides, approximately 9 percent of the area of Seattle has annual exceedance probabilities of 1 percent or greater. Application of the Poisson model for estimating the future occurrence of individual landslides results in a worst-case scenario map, with a maximum annual exceedance probability of 25 percent on a hillslope near Duwamish Head in West Seattle. Application of the binomial model for estimating the future occurrence of a year with one or more landslides results in a map with a maximum annual exceedance probability of 17 percent (also near Duwamish Head). Slope and geology both play a role in localizing the occurrence of landslides in Seattle. A positive correlation exists between slope and mean exceedance probability, with probability tending to increase as slope increases. Sixty-four percent of all historical landslide locations are within 150 m (500 ft, horizontal distance) of the Esperance Sand/Lawton Clay contact, but within this zone, no positive or negative correlation exists between exceedance probability and distance to the contact.

Joint Analysis of Binomial and Continuous Traits with a Recursive Model: A Case Study Using Mortality and Litter Size of Pigs

PubMed Central

Varona, Luis; Sorensen, Daniel

2014-01-01

This work presents a model for the joint analysis of a binomial and a Gaussian trait using a recursive parametrization that leads to a computationally efficient implementation. The model is illustrated in an analysis of mortality and litter size in two breeds of Danish pigs, Landrace and Yorkshire. Available evidence suggests that mortality of piglets increased partly as a result of successful selection for total number of piglets born. In recent years there has been a need to decrease the incidence of mortality in pig-breeding programs. We report estimates of genetic variation at the level of the logit of the probability of mortality and quantify how it is affected by the size of the litter. Several models for mortality are considered and the best fits are obtained by postulating linear and cubic relationships between the logit of the probability of mortality and litter size, for Landrace and Yorkshire, respectively. An interpretation of how the presence of genetic variation affects the probability of mortality in the population is provided and we discuss and quantify the prospects of selecting for reduced mortality, without affecting litter size. PMID:24414548

[A study on the relationship between postmortem interval and the changes of DNA content in the kidney cellule of rat].

PubMed

Liu, L; Peng, D B; Liu, Y; Deng, W N; Liu, Y L; Li, J J

2001-05-01

To study changes of DNA content in the kidney cellule of rats and relationship with the postmortem interval. This experiment chose seven parameter of cell nuclear, including the area and integral optical density, determined the changes of DNA content in the kidney cellule of 15 rats at different intervals between 0 and 48 h postmortem with auto-TV-image system. The degradation rate of DNA in nuclear has a certainty relationship to early PMI(in 48 h) of rat, and get binomial regress equation. Determining the quantity of DNA in nuclear should be an objective and exact way to estimate the PMI.

Statistical Models for the Analysis of Zero-Inflated Pain Intensity Numeric Rating Scale Data.

PubMed

Goulet, Joseph L; Buta, Eugenia; Bathulapalli, Harini; Gueorguieva, Ralitza; Brandt, Cynthia A

2017-03-01

Pain intensity is often measured in clinical and research settings using the 0 to 10 numeric rating scale (NRS). NRS scores are recorded as discrete values, and in some samples they may display a high proportion of zeroes and a right-skewed distribution. Despite this, statistical methods for normally distributed data are frequently used in the analysis of NRS data. We present results from an observational cross-sectional study examining the association of NRS scores with patient characteristics using data collected from a large cohort of 18,935 veterans in Department of Veterans Affairs care diagnosed with a potentially painful musculoskeletal disorder. The mean (variance) NRS pain was 3.0 (7.5), and 34% of patients reported no pain (NRS = 0). We compared the following statistical models for analyzing NRS scores: linear regression, generalized linear models (Poisson and negative binomial), zero-inflated and hurdle models for data with an excess of zeroes, and a cumulative logit model for ordinal data. We examined model fit, interpretability of results, and whether conclusions about the predictor effects changed across models. In this study, models that accommodate zero inflation provided a better fit than the other models. These models should be considered for the analysis of NRS data with a large proportion of zeroes. We examined and analyzed pain data from a large cohort of veterans with musculoskeletal disorders. We found that many reported no current pain on the NRS on the diagnosis date. We present several alternative statistical methods for the analysis of pain intensity data with a large proportion of zeroes. Published by Elsevier Inc.

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.

Multi-level Bayesian safety analysis with unprocessed Automatic Vehicle Identification data for an urban expressway.

PubMed

Shi, Qi; Abdel-Aty, Mohamed; Yu, Rongjie

2016-03-01

In traffic safety studies, crash frequency modeling of total crashes is the cornerstone before proceeding to more detailed safety evaluation. The relationship between crash occurrence and factors such as traffic flow and roadway geometric characteristics has been extensively explored for a better understanding of crash mechanisms. In this study, a multi-level Bayesian framework has been developed in an effort to identify the crash contributing factors on an urban expressway in the Central Florida area. Two types of traffic data from the Automatic Vehicle Identification system, which are the processed data capped at speed limit and the unprocessed data retaining the original speed were incorporated in the analysis along with road geometric information. The model framework was proposed to account for the hierarchical data structure and the heterogeneity among the traffic and roadway geometric data. Multi-level and random parameters models were constructed and compared with the Negative Binomial model under the Bayesian inference framework. Results showed that the unprocessed traffic data was superior. Both multi-level models and random parameters models outperformed the Negative Binomial model and the models with random parameters achieved the best model fitting. The contributing factors identified imply that on the urban expressway lower speed and higher speed variation could significantly increase the crash likelihood. Other geometric factors were significant including auxiliary lanes and horizontal curvature. Copyright © 2015 Elsevier Ltd. All rights reserved.

Application of the Hyper-Poisson Generalized Linear Model for Analyzing Motor Vehicle Crashes.

PubMed

Khazraee, S Hadi; Sáez-Castillo, Antonio Jose; Geedipally, Srinivas Reddy; Lord, Dominique

2015-05-01

The hyper-Poisson distribution can handle both over- and underdispersion, and its generalized linear model formulation allows the dispersion of the distribution to be observation-specific and dependent on model covariates. This study's objective is to examine the potential applicability of a newly proposed generalized linear model framework for the hyper-Poisson distribution in analyzing motor vehicle crash count data. The hyper-Poisson generalized linear model was first fitted to intersection crash data from Toronto, characterized by overdispersion, and then to crash data from railway-highway crossings in Korea, characterized by underdispersion. The results of this study are promising. When fitted to the Toronto data set, the goodness-of-fit measures indicated that the hyper-Poisson model with a variable dispersion parameter provided a statistical fit as good as the traditional negative binomial model. The hyper-Poisson model was also successful in handling the underdispersed data from Korea; the model performed as well as the gamma probability model and the Conway-Maxwell-Poisson model previously developed for the same data set. The advantages of the hyper-Poisson model studied in this article are noteworthy. Unlike the negative binomial model, which has difficulties in handling underdispersed data, the hyper-Poisson model can handle both over- and underdispersed crash data. Although not a major issue for the Conway-Maxwell-Poisson model, the effect of each variable on the expected mean of crashes is easily interpretable in the case of this new model. © 2014 Society for Risk Analysis.

The Impact of a Pay-for-Performance Program on Central Line-Associated Blood Stream Infections in Pennsylvania.

PubMed

Bastian, Nathaniel D; Kang, Hyojung; Nembhard, Harriet B; Bloschichak, Andrew; Griffin, Paul M

2016-01-01

Healthcare associated infections have significantly contributed to the rising cost of hospital care in the United States. The implementation of pay-for-performance (P4P) programs has been one approach to improve quality at a reduced cost. We quantify the impact of Highmark's Quality Blue (QB) hospital P4P program on central line-associated blood stream infections (CLABSI) in Pennsylvania. The impact of years of participation in QB on CLABSI is also evaluated. Data from 149 Pennsylvania hospitals on CLABSI from 2008-2013 are used. Negative binomial regression and fixed effects panel regression are performed. Hospitals participating in QB have 0.727 times the CLABSI as those hospitals that do not participate. Hospitals participating for four or more years have on average 3.13 fewer CLABSI per year compared to those participating for less than four years. Highmark's P4P program has shown improved outcomes with regards to CLABSI, but further research is needed to determine if QB is cost effective.

Early-life mortality risks in opposite-sex and same-sex twins: a Danish cohort study of the twin testosterone transfer hypothesis

PubMed Central

Ahrenfeldt, Linda Juel; Larsen, Lisbeth Aagaard; Lindahl-Jacobsen, Rune; Skytthe, Axel; Hjelmborg, Jacob v.B.; Möller, Sören; Christensen, Kaare

2017-01-01

Purpose To investigate the twin testosterone transfer (TTT) hypothesis by comparing early-life mortality risks of opposite-sex (OS) and same-sex (SS) twins during the first 15 years of life. Methods We performed a population-based cohort study to compare mortality in OS and SS twins. We included 68,629 live-born Danish twins from 1973 to 2009 identified through the Danish Twin Registry and performed piecewise stratified Cox regression and log-binomial regression. Results Among 1933 deaths, we found significantly higher mortality for twin boys than for twin girls. For both sexes, OS twins had lower mortality than SS twins; the difference persisted for the first year of life for boys and for the first week of life for girls. Conclusions Although the mortality risk for OS boys was in the expected direction according to the TTT hypothesis, the results for OS girls pointed in the opposite direction, providing no clear evidence for the TTT hypothesis. PMID:28024904

[Effects of climate and grazing on the vegetation cover change in Xilinguole League of Inner Mongolia, North China].

PubMed

Wang, Hai-Mei; Li, Zheng-Hai; Wang, Zhen

2013-01-01

Based on the monthly temperature and precipitation data of 15 meteorological stations and the statistical data of livestock density in Xilinguole League in 1981-2007, and by using ArcGIS, this paper analyzed the spatial distribution of the climate aridity and livestock density in the League, and in combining with the ten-day data of the normalized difference vegetation index (NDVI) in 1981-2007, the driving factors of the vegetation cover change in the League were discussed. In the study period, there was a satisfactory linear regression relationship between the climate aridity and the vegetation coverage. The NDVI and the livestock density had a favorable binomial regression relationship. With the increase of NDVI, the livestock density increased first and decreased then. The vegetation coverage had a complex linear relationship with livestock density and climate aridity. The NDVI had a positive correlation with climate aridity, but a negative correlation with livestock density. Compared with livestock density, climate aridity had far greater effects on the NDVI.

Effect of a fall prevention program on balance maintenance using a quasi-experimental design in real-world settings.

PubMed

Robitaille, Yvonne; Fournier, Michel; Laforest, Sophie; Gauvin, Lise; Filiatrault, Johanne; Corriveau, Hélène

2012-08-01

To examine the effect of a fall prevention program offered under real-world conditions on balance maintenance several months after the program. To explore the program's impact on falls. A quasi-experimental study was conducted among community-dwelling seniors, with pre- and postintervention measures of balance performance and self-reported falls. Ten community-based organizations offered the intervention (98 participants) and 7 recruited participants to the study's control arm (102 participants). An earlier study examined balance immediately after the 12-week program. The present study focuses on the 12-month effect. Linear regression (balance) and negative binomial regression (falls) procedures were performed.falls. During the 12-month study period, experimental participants improved and maintained their balance as reflected by their scores on three performance tests. There was no evidence of an effect on falls.falls. Structured group exercise programs offered in community-based settings can maintain selected components of balance for several months after the program's end.

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

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.

Peak Weight and Height Velocity to Age 36 Months and Asthma Development: The Norwegian Mother and Child Cohort Study

PubMed Central

Magnus, Maria C.; Stigum, Hein; Håberg, Siri E.; Nafstad, Per; London, Stephanie J.; Nystad, Wenche

2015-01-01

Background The immediate postnatal period is the period of the fastest growth in the entire life span and a critical period for lung development. Therefore, it is interesting to examine the association between growth during this period and childhood respiratory disorders. Methods We examined the association of peak weight and height velocity to age 36 months with maternal report of current asthma at 36 months (n = 50,311), recurrent lower respiratory tract infections (LRTIs) by 36 months (n = 47,905) and current asthma at 7 years (n = 24,827) in the Norwegian Mother and Child Cohort Study. Peak weight and height velocity was calculated using the Reed1 model through multilevel mixed-effects linear regression. Multivariable log-binomial regression was used to calculate adjusted relative risks (adj.RR) and 95% confidence intervals (CI). We also conducted a sibling pair analysis using conditional logistic regression. Results Peak weight velocity was positively associated with current asthma at 36 months [adj.RR 1.22 (95%CI: 1.18, 1.26) per standard deviation (SD) increase], recurrent LRTIs by 36 months [adj.RR 1.14 (1.10, 1.19) per SD increase] and current asthma at 7 years [adj.RR 1.13 (95%CI: 1.07, 1.19) per SD increase]. Peak height velocity was not associated with any of the respiratory disorders. The positive association of peak weight velocity and asthma at 36 months remained in the sibling pair analysis. Conclusions Higher peak weight velocity, achieved during the immediate postnatal period, increased the risk of respiratory disorders. This might be explained by an influence on neonatal lung development, shared genetic/epigenetic mechanisms and/or environmental factors. PMID:25635872

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…

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.

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

A Methodology for Quantifying Certain Design Requirements During the Design Phase

NASA Technical Reports Server (NTRS)

Adams, Timothy; Rhodes, Russel

2005-01-01

A methodology for developing and balancing quantitative design requirements for safety, reliability, and maintainability has been proposed. Conceived as the basis of a more rational approach to the design of spacecraft, the methodology would also be applicable to the design of automobiles, washing machines, television receivers, or almost any other commercial product. Heretofore, it has been common practice to start by determining the requirements for reliability of elements of a spacecraft or other system to ensure a given design life for the system. Next, safety requirements are determined by assessing the total reliability of the system and adding redundant components and subsystems necessary to attain safety goals. As thus described, common practice leaves the maintainability burden to fall to chance; therefore, there is no control of recurring costs or of the responsiveness of the system. The means that have been used in assessing maintainability have been oriented toward determining the logistical sparing of components so that the components are available when needed. The process established for developing and balancing quantitative requirements for safety (S), reliability (R), and maintainability (M) derives and integrates NASA s top-level safety requirements and the controls needed to obtain program key objectives for safety and recurring cost (see figure). Being quantitative, the process conveniently uses common mathematical models. Even though the process is shown as being worked from the top down, it can also be worked from the bottom up. This process uses three math models: (1) the binomial distribution (greaterthan- or-equal-to case), (2) reliability for a series system, and (3) the Poisson distribution (less-than-or-equal-to case). The zero-fail case for the binomial distribution approximates the commonly known exponential distribution or "constant failure rate" distribution. Either model can be used. The binomial distribution was selected for modeling flexibility because it conveniently addresses both the zero-fail and failure cases. The failure case is typically used for unmanned spacecraft as with missiles.

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.

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.

The effectiveness of a monetary incentive offer on survey response rates and response completeness in a longitudinal study.

PubMed

Yu, Shengchao; Alper, Howard E; Nguyen, Angela-Maithy; Brackbill, Robert M; Turner, Lennon; Walker, Deborah J; Maslow, Carey B; Zweig, Kimberly C

2017-04-26

Achieving adequate response rates is an ongoing challenge for longitudinal studies. The World Trade Center Health Registry is a longitudinal health study that periodically surveys a cohort of ~71,000 people exposed to the 9/11 terrorist attacks in New York City. Since Wave 1, the Registry has conducted three follow-up surveys (Waves 2-4) every 3-4 years and utilized various strategies to increase survey participation. A promised monetary incentive was offered for the first time to survey non-respondents in the recent Wave 4 survey, conducted 13-14 years after 9/11. We evaluated the effectiveness of a monetary incentive in improving the response rate five months after survey launch, and assessed whether or not response completeness was compromised due to incentive use. The study compared the likelihood of returning a survey for those who received an incentive offer to those who did not, using logistic regression models. Among those who returned surveys, we also examined whether those receiving an incentive notification had higher rate of response completeness than those who did not, using negative binomial regression models and logistic regression models. We found that a $10 monetary incentive offer was effective in increasing Wave 4 response rates. Specifically, the $10 incentive offer was useful in encouraging initially reluctant participants to respond to the survey. The likelihood of returning a survey increased by 30% for those who received an incentive offer (AOR = 1.3, 95% CI: 1.1, 1.4), and the incentive increased the number of returned surveys by 18%. Moreover, our results did not reveal any significant differences on response completeness between those who received an incentive offer and those who did not. In the face of the growing challenge of maintaining a high response rate for the World Trade Center Health Registry follow-up surveys, this study showed the value of offering a monetary incentive as an additional refusal conversion strategy. Our findings also suggest that an incentive offer could be particularly useful near the end of data collection period when an immediate boost in response rate is needed.

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

Analysis of non-fatal and fatal injury rates for mine operator and contractor employees and the influence of work location.

PubMed

Karra, Vijia K

2005-01-01

Mining injury surveillance data are used as the basis for assessing the severity of injuries among operator and contractor employees in the underground and surface mining of various minerals. Injury rates during 1983-2002 derived from Mine Safety and Health Administration (MSHA) database are analyzed using the negative binomial regression model. The logarithmic mean injury rate is expressed as a linear function of seven indicator variables representing Non-Coal Contractor, Metal Operator, Non Metal Operator, Stone Operator, Sand and Gravel Operator, Coal Contractor, and Work Location, and a continuous variable, RelYear, representing the relative year starting with 1983 as the base year. Based on the model, the mean injury rate declined at a 1.69% annual rate, and the mean injury rate for work on the surface is 52.53% lower compared to the rate for work in the underground. With reference to the Coal Operator mean injury rate: the Non-Coal Contractor rate is 30.34% lower, the Metal Operator rate is 27.18% lower, the Non-Metal Operator rate is 37.51% lower, the Stone Operator rate is 23.44% lower, the Sand and Gravel Operator rate is 16.45% lower, and the Coal Contractor rate is 1.41% lower. Fatality rates during the same 20 year period are analyzed similarly using Poisson regression model. Based on this model, the mean fatality rate declined at a 3.17% annual rate, and the rate for work on the surface is 64.3% lower compared to the rate for work in the underground. With reference to the Coal Operator mean fatality rate: the Non-Coal Contractor rate is 234.81% higher, the Metal Operator rate is 5.79% lower, the Non-Metal Operator rate is 47.36% lower, the Stone Operator rate is 8.29% higher, the Sand and Gravel Operator rate is 60.32% higher, and the Coal Contractor rate is 129.54% higher.

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.

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

Urinary symptoms following external beam radiotherapy of the prostate: Dose-symptom correlates with multiple-event and event-count models.

PubMed

Yahya, Noorazrul; Ebert, Martin A; Bulsara, Max; House, Michael J; Kennedy, Angel; Joseph, David J; Denham, James W

2015-11-01

This study aimed to compare urinary dose-symptom correlates after external beam radiotherapy of the prostate using commonly utilised peak-symptom models to multiple-event and event-count models which account for repeated events. Urinary symptoms (dysuria, haematuria, incontinence and frequency) from 754 participants from TROG 03.04-RADAR trial were analysed. Relative (R1-R75 Gy) and absolute (A60-A75Gy) bladder dose-surface area receiving more than a threshold dose and equivalent uniform dose using exponent a (range: a ∈[1 … 100]) were derived. The dose-symptom correlates were analysed using; peak-symptom (logistic), multiple-event (generalised estimating equation) and event-count (negative binomial regression) models. Stronger dose-symptom correlates were found for incontinence and frequency using multiple-event and/or event-count models. For dysuria and haematuria, similar or better relationships were found using peak-symptom models. Dysuria, haematuria and high grade (⩾ 2) incontinence were associated to high dose (R61-R71 Gy). Frequency and low grade (⩾ 1) incontinence were associated to low and intermediate dose-surface parameters (R13-R41Gy). Frequency showed a parallel behaviour (a=1) while dysuria, haematuria and incontinence showed a more serial behaviour (a=4 to a ⩾ 100). Relative dose-surface showed stronger dose-symptom associations. For certain endpoints, the multiple-event and event-count models provide stronger correlates over peak-symptom models. Accounting for multiple events may be advantageous for a more complete understanding of urinary dose-symptom relationships. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

"Suicide shall cease to be a crime": suicide and undetermined death trends 1970-2000 before and after the decriminalization of suicide in Ireland 1993.

PubMed

Osman, Mugtaba; Parnell, Andrew C; Haley, Clifford

2017-02-01

Suicide is criminalized in more than 100 countries around the world. A dearth of research exists into the effect of suicide legislation on suicide rates and available statistics are mixed. This study investigates 10,353 suicide deaths in Ireland that took place between 1970 and 2000. Irish 1970-2000 annual suicide data were obtained from the Central Statistics Office and modelled via a negative binomial regression approach. We examined the effect of suicide legislation on different age groups and on both sexes. We used Bonferroni correction for multiple modelling. Statistical analysis was performed using the R statistical package version 3.1.2. The coefficient for the effect of suicide act on overall suicide deaths was -9.094 (95 % confidence interval (CI) -34.086 to 15.899), statistically non-significant (p = 0.476). The coefficient for the effect suicide act on undetermined deaths was statistically significant (p < 0.001) and was estimated to be -644.4 (95 % CI -818.6 to -469.9). The results of our study indicate that legalization of suicide is not associated with a significant increase in subsequent suicide deaths. However, undetermined death verdict rates have significantly dropped following legalization of suicide.

Maternal Language and Adverse Birth Outcomes in a Statewide Analysis

PubMed Central

Sentell, Tetine; Chang, Ann; Jun Ahn, Hyeong; Miyamura, Jill

2016-01-01

Background Limited English proficiency is associated with disparities across diverse health outcomes. However, evidence regarding adverse birth outcomes across languages is limited, particularly among US Asian and Pacific Islander populations. The study goal was to consider the relationship of maternal language to birth outcomes using statewide hospitalization data. Methods Detailed discharge data from Hawai‘i childbirth hospitalizations from 2012 (n=11,419) were compared by maternal language (English language or not) for adverse outcomes using descriptive and multivariable log-binomial regression models, controlling for race/ethnicity, age group, and payer. Results Ten percent of mothers spoke a language other than English; 93% of these spoke an Asian or Pacific Islander language. In multivariable models, compared to English speakers non-English speakers had significantly higher risk (adjusted relative risk [ARR]: 2.02; 95% Confidence Interval [CI]: 1.34–3.04) of obstetric trauma in vaginal deliveries without instrumentation. Some significant variation was seen by language for other birth outcomes, including an increased rate of primary Caesarean sections and vaginal births after Caesarean among non-English speakers. Conclusions Non-English speakers had approximately two times higher risk of having an obstetric trauma during a vaginal birth when other factors, including race/ethnicity, were controlled. Non-English speakers also had higher rates of potentially high-risk deliveries. PMID:26361937

Maternal language and adverse birth outcomes in a statewide analysis.

PubMed

Sentell, Tetine; Chang, Ann; Ahn, Hyeong Jun; Miyamura, Jill

2016-01-01

Limited English proficiency is associated with disparities across diverse health outcomes. However, evidence regarding adverse birth outcomes across languages is limited, particularly among U.S. Asian and Pacific Islander populations. The study goal was to consider the relationship of maternal language to birth outcomes using statewide hospitalization data. Detailed discharge data from Hawaii childbirth hospitalizations from 2012 (n = 11,419) were compared by maternal language (English language or not) for adverse outcomes using descriptive and multivariable log-binomial regression models, controlling for race/ethnicity, age group, and payer. Ten percent of mothers spoke a language other than English; 93% of these spoke an Asian or Pacific Islander language. In multivariable models, compared to English speakers, non-English speakers had significantly higher risk (adjusted relative risk [ARR]: 2.02; 95% confidence interval [CI]: 1.34-3.04) of obstetric trauma in vaginal deliveries without instrumentation. Some significant variation was seen by language for other birth outcomes, including an increased rate of primary Caesarean sections and vaginal births after Caesarean, among non-English speakers. Non-English speakers had approximately two times higher risk of having an obstetric trauma during a vaginal birth when other factors, including race/ethnicity, were controlled. Non-English speakers also had higher rates of potentially high-risk deliveries.

Research experiences and mentoring practices in selected east Asian graduate programs: predictors of research productivity among doctoral students in molecular biology.

PubMed

Ynalvez, Ruby; Garza-Gongora, Claudia; Ynalvez, Marcus Antonius; Hara, Noriko

2014-01-01

Although doctoral mentors recognize the benefits of providing quality advisement and close guidance, those of sharing project management responsibilities with mentees are still not well recognized. We observed that mentees, who have the opportunity to co-manage projects, generate more written output. Here we examine the link between research productivity, doctoral mentoring practices (DMP), and doctoral research experiences (DRE) of mentees in programs in the non-West. Inspired by previous findings that early career productivity is a strong predictor of later productivity, we examine the research productivity of 210 molecular biology doctoral students in selected programs in Japan, Singapore, and Taiwan. Using principal component (PC) analysis, we derive two sets of PCs: one set from 15 DMP and another set from 16 DRE items. We model research productivity using Poisson and negative-binomial regression models with these sets as predictors. Our findings suggest a need to re-think extant practices and to allocate resources toward professional career development in training future scientists. We contend that doctoral science training must not only be an occasion for future scientists to learn scientific and technical skills, but it must also be the opportunity to experience, to acquire, and to hone research management skills. © 2014 The International Union of Biochemistry and Molecular Biology.

Need for recovery from work and sleep-related complaints among nursing professionals.

PubMed

Silva-Costa, Aline; Griep, Rosane Harter; Fischer, Frida Marina; Rotenberg, Lúcia

2012-01-01

The concept of need for recovery from work (NFR) was deduced from the effort recuperation model. In this model work produces costs in terms of effort during the working day. When there is enough time and possibilities to recuperate, a worker will arrive at the next working day with no residual symptoms of previous effort. NFR evaluates work characteristics such as psychosocial demands, professional work hours or schedules. However, sleep may be an important part of the recovery process. The aim of the study was to test the association between sleep-related complaints and NFR. A cross-sectional study was carried out at three hospitals. All females nursing professionals engaged in assistance to patients were invited to participate (N = 1,307). Participants answered a questionnaire that included four sleep-related complaints (insomnia, unsatisfactory sleep, sleepiness during work hours and insufficient sleep), work characteristics and NRF scale. Binomial logistic regression analysis showed that all sleep-related complaints are associated with a high need for recovery from work. Those who reported insufficient sleep showed a greater chance of high need for recovery; OR=2.730 (CI 95% 2.074 - 3.593). These results corroborate the hypothesis that sleep is an important aspect of the recovery process and, therefore, should be thoroughly investigated.

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...

Estimating influenza and respiratory syncytial virus-associated mortality in Western Kenya using health and demographic surveillance system data, 2007-2013.

PubMed

Emukule, Gideon O; Spreeuwenberg, Peter; Chaves, Sandra S; Mott, Joshua A; Tempia, Stefano; Bigogo, Godfrey; Nyawanda, Bryan; Nyaguara, Amek; Widdowson, Marc-Alain; van der Velden, Koos; Paget, John W

2017-01-01

Influenza and respiratory syncytial virus (RSV) associated mortality has not been well-established in tropical Africa. We used the negative binomial regression method and the rate-difference method (i.e. deaths during low and high influenza/RSV activity months), to estimate excess mortality attributable to influenza and RSV using verbal autopsy data collected through a health and demographic surveillance system in Western Kenya, 2007-2013. Excess mortality rates were calculated for a) all-cause mortality, b) respiratory deaths (including pneumonia), c) HIV-related deaths, and d) pulmonary tuberculosis (TB) related deaths. Using the negative binomial regression method, the mean annual all-cause excess mortality rate associated with influenza and RSV was 14.1 (95% confidence interval [CI] 0.0-93.3) and 17.1 (95% CI 0.0-111.5) per 100,000 person-years (PY) respectively; and 10.5 (95% CI 0.0-28.5) and 7.3 (95% CI 0.0-27.3) per 100,000 PY for respiratory deaths, respectively. Highest mortality rates associated with influenza were among ≥50 years, particularly among persons with TB (41.6[95% CI 0.0-122.7]); and with RSV were among <5 years. Using the rate-difference method, the excess mortality rate for influenza and RSV was 44.8 (95% CI 36.8-54.4) and 19.7 (95% CI 14.7-26.5) per 100,000 PY, respectively, for all-cause deaths; and 9.6 (95% CI 6.3-14.7) and 6.6 (95% CI 3.9-11.0) per 100,000 PY, respectively, for respiratory deaths. Our study shows a substantial excess mortality associated with influenza and RSV in Western Kenya, especially among children <5 years and older persons with TB, supporting recommendations for influenza vaccination and efforts to develop RSV vaccines.

levels and sociodemographic correlates of accelerometer-based physical activity in Irish children: a cross-sectional study.

PubMed

Li, Xia; Kearney, Patricia M; Keane, Eimear; Harrington, Janas M; Fitzgerald, Anthony P

2017-06-01

The aim of this study was to explore levels and sociodemographic correlates of physical activity (PA) over 1 week using accelerometer data. Accelerometer data was collected over 1 week from 1075 8-11-year-old children in the cross-sectional Cork Children's Lifestyle Study. Threshold values were used to categorise activity intensity as sedentary, light, moderate or vigorous. Questionnaires collected data on demographic factors. Smoothed curves were used to display minute by minute variations. Binomial regression was used to identify factors correlated with the probability of meeting WHO 60 min moderate to vigorous PA guidelines. Overall, 830 children (mean (SD) age: 9.9(0.7) years, 56.3% boys) were included. From the binomial multiple regression analysis, boys were found more likely to meet guidelines (probability ratio 1.17, 95% CI 1.06 to 1.28) than girls. Older children were less likely to meet guidelines than younger children (probability ratio 0.91, CI 0.87 to 0.95). Normal weight children were more likely than overweight and obese children to meet guidelines (probability ratio 1.25, CI 1.16 to 1.34). Children in urban areas were more likely to meet guidelines than those in rural areas (probability ratio 1.19, CI 1.07 to 1.33). Longer daylight length days were associated with greater probability of meeting guidelines compared to shorter daylight length days. PA levels differed by individual factors including age, gender and weight status as well as by environmental factors including residence and daylight length. Less than one-quarter of children (26.8% boys, 16.2% girls) meet guidelines. Effective intervention policies are urgently needed to increase PA. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Effect of Breastfeeding Promotion on Early Childhood Caries and Breastfeeding Duration among 5 Year Old Children in Eastern Uganda: A Cluster Randomized Trial.

PubMed

Birungi, Nancy; Fadnes, Lars T; Okullo, Isaac; Kasangaki, Arabat; Nankabirwa, Victoria; Ndeezi, Grace; Tumwine, James K; Tylleskär, Thorkild; Lie, Stein Atle; Åstrøm, Anne Nordrehaug

2015-01-01

Although several studies have shown short term health benefits of exclusive breastfeeding (EBF), its long term consequences have not been studied extensively in low-income contexts. This study assessed the impact of an EBF promotion initiative for 6 months on early childhood caries (ECC) and breastfeeding duration in children aged 5 years in Mbale, Eastern Uganda. Participants were recruited from the Ugandan site of the PROMISE- EBF cluster randomised trial (ClinicalTrials.gov no: NCT00397150). A total of 765 pregnant women from 24 clusters were included in the ratio 1:1 to receive peer counselled promotion of EBF as the intervention or standard of care. At the 5 year follow-up, ECC was recorded under field conditions using the World Health Organization's decayed missing filled tooth (dmft) index. Adjusted negative binomial and linear regression were used in the analysis. Mean breastfeeding duration in the intervention and control groups (n=417) were 21.8 (CI 20.7-22.9) and 21.3(CI 20.7-21.9) months, respectively. The mean dmft was 1.5 (standard deviation [SD] 2.9) and 1.7 (SD 2.9) in the intervention and control groups, respectively. Corresponding prevalence estimates of ECC were 38% and 41%. Negative binomial regression analysis adjusted for cluster effects and loss-to-follow-up by inverse probability weights (IPW) showed an incidence-rate ratio (IRR) of 0.91 (95% CI 0.65-1.2). Comparing the effect of the trial arm on breastfeeding duration showed a difference in months of 0.48 (-0.72 to 1.7). PROMISE EBF trial did not impact on early childhood caries or breastfeeding duration at 5 years of age. This study contributes to the body of evidence that promotion of exclusive breastfeeding does not raise oral health concerns. However, the high burden of caries calls for efforts to improve the oral health condition in this setting. ClinicalTrials.gov NCT00397150.

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.

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.

The Protective Effects of Family Support on the Relationship between Official Intervention and General Delinquency across the Life Course

PubMed Central

Dong, Beidi; Krohn, Marvin D.

2016-01-01

Purpose Previous research on the labeling perspective has identified mediational processes and the long-term effects of official intervention in the life course. However, it is not yet clear what factors may moderate the relationship between labeling and subsequent offending. The current study integrates Cullen’s (1994) social support theory to examine how family social support conditions the criminogenic, stigmatizing effects of official intervention on delinquency and whether such protective effects vary by developmental stage. Methods Using longitudinal data from the Rochester Youth Development Study, we estimated negative binomial regression models to investigate the relationships between police arrest, family social support, and criminal offending during both adolescence and young adulthood. Results Police arrest is a significant predictor of self-reported delinquency in both the adolescent and adult models. Expressive family support exhibits main effects in the adolescent models; instrumental family support exhibits main effects at both developmental stages. Additionally, instrumental family support diminishes some of the predicted adverse effects of official intervention in adulthood. Conclusions Perception of family support can be critical in reducing general delinquency as well as buffering against the adverse effects of official intervention on subsequent offending. Policies and programs that work with families subsequent to a criminal justice intervention should emphasize the importance of providing a supportive environment for those who are labeled. PMID:28729962

Antibiotic resistance in hospitals: a ward-specific random effect model in a low antibiotic consumption environment.

PubMed

Aldrin, Magne; Raastad, Ragnhild; Tvete, Ingunn Fride; Berild, Dag; Frigessi, Arnoldo; Leegaard, Truls; Monnet, Dominique L; Walberg, Mette; Müller, Fredrik

2013-04-15

Association between previous antibiotic use and emergence of antibiotic resistance has been reported for several microorganisms. The relationship has been extensively studied, and although the causes of antibiotic resistance are multi-factorial, clear evidence of antibiotic use as a major risk factor exists. Most studies are carried out in countries with high consumption of antibiotics and corresponding high levels of antibiotic resistance, and currently, little is known whether and at what level the associations are detectable in a low antibiotic consumption environment. We conduct an ecological, retrospective study aimed at determining the impact of antibiotic consumption on antibiotic-resistant Pseudomonas aeruginosa in three hospitals in Norway, a country with low levels of antibiotic use. We construct a sophisticated statistical model to capture such low signals. To reduce noise, we conduct our study at hospital ward level. We propose a random effect Poisson or binomial regression model, with a reparametrisation that allows us to reduce the number of parameters. Inference is likelihood based. Through scenario simulation, we study the potential effects of reduced or increased antibiotic use. Results clearly indicate that the effects of consumption on resistance are present under conditions with relatively low use of antibiotic agents. This strengthens the recommendation on prudent use of antibiotics, even when consumption is relatively low. Copyright © 2012 John Wiley & Sons, Ltd.

The Association Between Neighborhood Poverty and HIV Diagnoses Among Males and Females in New York City, 2010-2011.

PubMed

Wiewel, Ellen W; Bocour, Angelica; Kersanske, Laura S; Bodach, Sara D; Xia, Qiang; Braunstein, Sarah L

2016-01-01

We assessed the association of neighborhood poverty with HIV diagnosis rates for males and females in New York City. We calculated annual HIV diagnosis rates by ZIP Code, sex, and neighborhood poverty level using 2010-2011 New York City (NYC) HIV surveillance data and data from the U.S. Census 2010 and American Community Survey 2007-2011. Neighborhood poverty levels were percentage of residents in a ZIP Code with incomes below the federal poverty threshold, categorized as 0%-<10% (low poverty), 10%-<20% (medium poverty), 20%-<30% (high poverty), and 30%-100% (very high poverty). We used sex-stratified negative binomial regression models to measure the association between neighborhood-level poverty and HIV diagnosis rates, controlling for neighborhood-level education, race/ethnicity, age, and percentage of men who have sex with men. In 2010-2011, 6,184 people were newly diagnosed with HIV. Median diagnosis rates per 100,000 population increased by neighborhood poverty level overall (13.7, 34.3, 50.6, and 75.6 for low-, medium-, high-, and very high-poverty ZIP Codes, respectively), for males, and for females. In regression models, higher neighborhood poverty remained associated with higher diagnosis rates among males (adjusted rate ratio [ARR] = 1.63, 95% confidence interval [CI] 1.34, 1.97) and females (ARR=2.14, 95% CI 1.46, 3.14) for very high- vs. low-poverty ZIP Codes. Living in very high- vs. low-poverty urban neighborhoods was associated with increased HIV diagnosis rates. After controlling for other factors, the association between poverty and diagnosis rates was stronger among females than among males. Alleviating poverty may help decrease HIV-related disparities.

Ethnic Disparities in Oral Health Related Quality of Life among Adults in London, England.

PubMed

Abdelrahim, R; Delgado-Angulo, E K; Gallagher, J E; Bernabé, E

2017-06-01

To explore ethnic disparities in oral health related quality of life (OHQoL) among adults, and the role that socioeconomic factors play in that association. Data from 705 adults from a socially deprived, ethnically diverse metropolitan area of London (England) were analysed for this study. Ethnicity was self-assigned based on the 2001 UK Census categories. OHQoL was measured using the Oral Health Impact Profile (OHIP-14), which provides information on the prevalence, extent and intensity of oral impacts on quality of life in the previous 12 months. Ethnic disparities were assessed in logistic regression models for prevalence of oral impacts and negative binomial regression models for extent and intensity of oral impacts. The prevalence of oral impacts was 12.7% (95% CI: 10.2-15.1) and the mean OHIP-14 extent and severity scores were 0.27 (95% CI: 0.20-0.34) and 4.19 (95% CI: 3.74-4.64), respectively. Black adults showed greater and Asian adults lower prevalence, extent and severity of oral impacts than White adults. However, significant differences were only found for the extent of oral impacts; Black adults reporting more and Asian adults fewer OHIP-14 items affected than their White counterparts. After adjustments for socioeconomic factors, Asian adults had significantly fewer OHIP-14 items affected than White adults (rate ratio: 0.28; 95%CI: 0.08-0.94). This study found disparities in OHQoL between the three main ethnic groups in South East London. Asian adults had better and Black adults had similar OHQoL than White adults after accounting for demographic and social factors. Copyright© 2017 Dennis Barber Ltd.

Angiogenic and inflammatory biomarkers in mid-pregnancy and small-for-gestational age outcomes in Tanzania

PubMed Central

DARLING, Anne Marie; MCDONALD, Chloe R.; CONROY, Andrea L.; HAYFORD, Kyla T.; RAJWANS, Nimerta; WANG, Molin; ABOUD, Said; URASSA, Willy S.; KAIN, Kevin C.; FAWZI, Wafaie W.

2014-01-01

OBJECTIVE To investigate the relationship between a panel of angiogenic and inflammatory biomarkers measured in mid-pregnancy and small-for-gestational age (SGA) outcomes in sub-Saharan Africa. STUDY DESIGN Concentrations of 18 angiogenic and inflammatory biomarkers were determined in 432 pregnant women in Dar es Salaam, Tanzania who participated in a trial examining the effect of multivitamins on pregnancy outcomes. Infants falling below the 10th percentile of birth weight for gestational age relative to the applied growth standards were considered SGA. Multivariate binomial regression models with the log link function were used to determine the relative risk of SGA associated with increasing quartiles of each biomarker. Stepwise cubic restricted splines were used to test for non-linearity of these associations. Receiver operating curves obtained from multivariate logistic regression models were used to assess the discriminatory capability of selected biomarkers. RESULTS A total of 60 participants (13.9%) gave birth to SGA infants. Compared to those in the first quartile, the risk of SGA was reduced among those in the fourth quartiles of VEGF-A (adjusted risk ratio (RR) 0.38, 95% Confidence Interval (CI), 0.19-0.74), PGF (adjusted RR 0.28, 95% CI, 0.12-0.61), sFlt-1 (adjusted RR 0.48, 95% CI, 0.23-1.01), MCP-1 (adjusted RR 0.48, 95% CI, 0.25-0.92), and Leptin (adjusted RR 0.46, 95% CI, 0.22-0.96) CONCLUSION Our findings provide evidence of altered angiogenic and inflammatory mediators, at mid-pregnancy, in women who went on to deliver small for gestational age infants. PMID:24881826

U.S. military service and the prevalence of metabolic syndrome: Findings from a cross-sectional analysis of the Cooper Center Longitudinal Study, 1979-2013.

PubMed

Janak, Jud C; Pérez, Adriana; Alamgir, Hasanat; Orman, Jean A; Cooper, Sharon P; Shuval, Kerem; DeFina, Laura; Barlow, Carolyn E; Gabriel, Kelley Pettee

2017-02-01

U.S. military service confers both health benefits and risks potentially associated with a clustering of cardiovascular risk factors called metabolic syndrome. However, the association between prior military service and metabolic syndrome has not sufficiently been examined. The purpose of the study was to compare the prevalence of metabolic syndrome by prior military service status. Among 42,370 men (887 with prior military service) examined from 1979 to 2013 at the Cooper Clinic (Dallas, TX), we used a cross-sectional study design to examine the association between military service and metabolic syndrome. First, an unadjusted log binomial regression model was performed by regressing the prevalence of metabolic syndrome on prior service. This was followed by performing Kleinbaum's modeling strategy for assessing confounding. The same methodology was used to explore the association between individual metabolic syndrome risk factors and prior service. Prior military service was not significantly associated with the prevalence of metabolic syndrome (PR=0.98, 0.89-1.07). None of the variables explored were identified as confounders. Participants with prior military service had lower prevalence of both elevated levels of triglycerides (PR=0.89, 0.80-0.99) and low levels of high-density lipoprotein-cholesterol (PR=0.78, 0.70-0.88). They had a higher prevalence of elevated resting systolic blood pressure (PR=1.23, 1.12-1.35). However, none of these associations were significant after adjusting for identified confounders: age; cardiorespiratory fitness; and exam year. Study findings indicate that military service was not independently associated with the prevalence of metabolic syndrome or its components. Future research is warranted longitudinally assessing the impact of military service on long-term outcomes. Copyright © 2016 Elsevier Inc. All rights reserved.

Male Sex Associated With Increased Risk of Neonatal Abstinence Syndrome.

PubMed

Charles, M Katherine; Cooper, William O; Jansson, Lauren M; Dudley, Judith; Slaughter, James C; Patrick, Stephen W

2017-06-01

Neonatal abstinence syndrome (NAS) is a postnatal opioid withdrawal syndrome. Factors associated with development of the syndrome are poorly understood; however, infant sex may influence the risk of NAS. Our objective was to determine if infant sex was associated with the development or severity of the syndrome in a large population-based cohort. This retrospective cohort study used vital statistics and prescription, outpatient, and inpatient administrative data for mothers and infants enrolled in the Tennessee Medicaid program between 2009 and 2011. Multivariable logistic regression models were used to evaluate the association between male sex and diagnosis of NAS, accounting for potential demographic and clinical confounders. NAS severity, as evidenced by hospital length of stay, was modeled by using negative binomial regression. Of 102 695 infants, 927 infants were diagnosed with NAS (484 male subjects and 443 female subjects). Adjustments were made for the following: maternal age, race, and education; maternal hepatitis C infection, anxiety, or depression; in utero exposure to selective serotonin reuptake inhibitors and cigarettes; infant birth weight, small for gestational age, and year; and the interaction between opioid type and opioid amount. Male infants were more likely than female infants to be diagnosed with NAS (adjusted odds ratio, 1.18 [95% confidence interval, 1.05-1.33]) and NAS requiring treatment (adjusted odds ratio, 1.24 [95% confidence interval, 1.04-1.47]). However, there was no sex-based difference in severity for those diagnosed with NAS. Treatment of NAS should be tailored to an infant's individual risk for the syndrome. Clinicians should be mindful that male sex is an important risk factor in the diagnosis of NAS. Copyright © 2017 by the American Academy of Pediatrics.

The accuracy of caries risk assessment in children attending South Australian School Dental Service: a longitudinal study

PubMed Central

Ha, Diep H; Spencer, A John; Slade, Gary D; Chartier, Andrew D

2014-01-01

Objectives To determine the accuracy of the caries risk assessment system and performance of clinicians in their attempts to predict caries for children during routine practice. Design Longitudinal study. Setting and participants Data on caries risk assessment conducted by clinicians during routine practice while providing care for children in the South Australian School Dental Service (SA SDS) were collected from electronic patient records. Baseline data on caries experience, clinicians’ ratings of caries risk status and child demographics were obtained for all SA SDS patients aged 5–15 years examined during 2002–2005. Outcome measure Children’s caries incidence rate, calculated using examination data after a follow-up period of 6–48 months from baseline, was used as the gold standard to compute the sensitivity (Se) and specificity (Sp) of clinicians’ baseline ratings of caries risk. Multivariate binomial regression models were used to evaluate effects of children's baseline characteristics on Se and Sp. Results A total of 133 clinicians rated caries risk status of 71 430 children during 2002–2005. The observed Se and Sp were 0.48 and 0.86, respectively (Se+Sp=1.34). Caries experience at baseline was the strongest factor influencing accuracy in multivariable regression model. Among children with no caries experience at baseline, overall accuracy (Se+Sp) was only 1.05, whereas it was 1.28 among children with at least one tooth surfaces with caries experience at baseline. Conclusions Clinicians’ accuracy in predicting caries risk during routine practice was similar to levels reported in research settings that simulated patient care. Accuracy was acceptable in children who had prior caries experience at the baseline examination, while it was poor among children with no caries experience. PMID:24477318

Work Productivity in Scleroderma – Analysis from the UCLA Scleroderma Quality of Life Study

PubMed Central

Singh, Manjit K.; Clements, Philip J.; Furst, Daniel E.; Maranian, Paul; Khanna, Dinesh

2011-01-01

Objective To examine the productivity of patients with scleroderma (SSc) both outside and within the home in a large observational cohort. Methods 162 patients completed the Work Productivity Survey. Patients indicated whether or not they were employed outside of the home, how many days/month they missed work (employment or household work) due to SSc and how many days/month productivity was decreased ≥ 50%. Patients also completed other patient-reported outcome measures. We developed binomial regression models to assess the predictors of days missed from work (paid employment or household activities). The covariates included: type of SSc, education, physician and patient global assessments, HAQ-DI, FACIT-Fatigue, and Center of Epidemiologic Studies Depression Scale – Short Form (CESD). Results The average age of patients was 51.8 years and 51% had limited SSc. Of 37% patients employed outside of the home, patients reported missing 2.6 days/month of work and had 2.5 days per month productivity reduced by half. Of the 102 patients who were not employed, 39.4% were unable to work due to their SSc. When we assessed patients for household activities (N = 162), patients missed an average of 8 days of housework/month and had productivity reduced by average of 6 days/month. In the regression models, patients with lower education and poor assessment of overall health by physician were more likely to miss work outside the home. Patients with limited SSc and high HAQ-DI were more likely to miss work at home. Conclusion SSc has a major impact on productivity at home and at work. Nearly 40% of patients reported disability due to their SSc. PMID:22012885

Indirect and direct costs of acute coronary syndromes with comorbid atrial fibrillation, heart failure, or both.

PubMed

Ghushchyan, Vahram; Nair, Kavita V; Page, Robert L

2015-01-01

The objective of this study was to determine the direct and indirect costs of acute coronary syndromes (ACS) alone and with common cardiovascular comorbidities. A retrospective analysis was conducted using the Medical Expenditure Panel Survey from 1998 to 2009. Four mutually exclusive cohorts were evaluated: ACS only, ACS with atrial fibrillation (AF), ACS with heart failure (HF), and ACS with both conditions. Direct costs were calculated for all-cause and cardiovascular-related health care resource utilization. Indirect costs were determined from productivity losses from missed days of work. Regression analysis was developed for each outcome controlling for age, US census region, insurance coverage, sex, race, ethnicity, education attainment, family income, and comorbidity burden. A negative binomial regression model was used for health care utilization variables. A Tobit model was utilized for health care costs and productivity loss variables. Total health care costs were greatest for those with ACS and both AF and HF ($38,484±5,191) followed by ACS with HF ($32,871±2,853), ACS with AF ($25,192±2,253), and ACS only ($17,954±563). Compared with the ACS only cohort, the mean all-cause adjusted health care costs associated with ACS with AF, ACS with HF, and ACS with AF and HF were $5,073 (95% confidence interval [CI] 719-9,427), $11,297 (95% CI 5,610-16,985), and $15,761 (95% CI 4,784-26,738) higher, respectively. Average wage losses associated with ACS with and without AF and/or HF amounted to $5,266 (95% CI -7,765, -2,767), when compared with patients without these conditions. ACS imposes a significant economic burden at both the individual and society level, particularly when with comorbid AF and HF.

The Association Between Neighborhood Poverty and HIV Diagnoses Among Males and Females in New York City, 2010–2011

PubMed Central

Bocour, Angelica; Kersanske, Laura S.; Bodach, Sara D.; Xia, Qiang; Braunstein, Sarah L.

2016-01-01

Objective We assessed the association of neighborhood poverty with HIV diagnosis rates for males and females in New York City. Methods We calculated annual HIV diagnosis rates by ZIP Code, sex, and neighborhood poverty level using 2010–2011 New York City (NYC) HIV surveillance data and data from the U.S. Census 2010 and American Community Survey 2007–2011. Neighborhood poverty levels were percentage of residents in a ZIP Code with incomes below the federal poverty threshold, categorized as 0%–<10% (low poverty), 10%–<20% (medium poverty), 20%–<30% (high poverty), and 30%–100% (very high poverty). We used sex-stratified negative binomial regression models to measure the association between neighborhood-level poverty and HIV diagnosis rates, controlling for neighborhood-level education, race/ethnicity, age, and percentage of men who have sex with men. Results In 2010–2011, 6,184 people were newly diagnosed with HIV. Median diagnosis rates per 100,000 population increased by neighborhood poverty level overall (13.7, 34.3, 50.6, and 75.6 for low-, medium-, high-, and very high-poverty ZIP Codes, respectively), for males, and for females. In regression models, higher neighborhood poverty remained associated with higher diagnosis rates among males (adjusted rate ratio [ARR] = 1.63, 95% confidence interval [CI] 1.34, 1.97) and females (ARR=2.14, 95% CI 1.46, 3.14) for very high- vs. low-poverty ZIP Codes. Conclusion Living in very high- vs. low-poverty urban neighborhoods was associated with increased HIV diagnosis rates. After controlling for other factors, the association between poverty and diagnosis rates was stronger among females than among males. Alleviating poverty may help decrease HIV-related disparities. PMID:26957664

Equity in health services use and intensity of use in Canada

PubMed Central

Asada, Yukiko; Kephart, George

2007-01-01

Background The Canadian health care system has striven to remove financial or other barriers to access to medically necessary health care services since the establishment of the Canada Health Act 20 years ago. Evidence has been conflicting as to what extent the Canadian health care system has met this goal of equitable access. The objective of this study was to examine whether and where socioeconomic inequities in health care utilization occur in Canada. Methods We used a nationally representative cross-sectional survey, the 2000/01 Canadian Community Health Survey, which provides a large sample size (about 110,000) and permits more comprehensive adjustment for need indicators than previous studies. We separately examined general practitioner, specialist, and hospital services using two-part hurdle models: use versus non-use by logistic regression, and the intensity of use among users by zero-truncated negative binomial regression. Results We found that lower income was associated with less contact with general practitioners, but among those who had contact, lower income and education were associated with greater intensity of use of general practitioners. Both lower income and education were associated with less contact with specialists, but there was no statistically significant relationship between these socioeconomic variables and intensity of specialist use among the users. Neither income nor education was statistically significantly associated with use or intensity of use of hospitals. Conclusion Our study unveiled possible socioeconomic inequities in the use of health care services in Canada. PMID:17349059