Sample records for random effects multinomial
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Liu, Xian; Engel, Charles C
2012-12-20
Researchers often encounter longitudinal health data characterized with three or more ordinal or nominal categories. Random-effects multinomial logit models are generally applied to account for potential lack of independence inherent in such clustered data. When parameter estimates are used to describe longitudinal processes, however, random effects, both between and within individuals, need to be retransformed for correctly predicting outcome probabilities. This study attempts to go beyond existing work by developing a retransformation method that derives longitudinal growth trajectories of unbiased health probabilities. We estimated variances of the predicted probabilities by using the delta method. Additionally, we transformed the covariates' regression coefficients on the multinomial logit function, not substantively meaningful, to the conditional effects on the predicted probabilities. The empirical illustration uses the longitudinal data from the Asset and Health Dynamics among the Oldest Old. Our analysis compared three sets of the predicted probabilities of three health states at six time points, obtained from, respectively, the retransformation method, the best linear unbiased prediction, and the fixed-effects approach. The results demonstrate that neglect of retransforming random errors in the random-effects multinomial logit model results in severely biased longitudinal trajectories of health probabilities as well as overestimated effects of covariates on the probabilities. Copyright © 2012 John Wiley & Sons, Ltd.
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An INAR(1) Negative Multinomial Regression Model for Longitudinal Count Data.
ERIC Educational Resources Information Center
Bockenholt, Ulf
1999-01-01
Discusses a regression model for the analysis of longitudinal count data in a panel study by adapting an integer-valued first-order autoregressive (INAR(1)) Poisson process to represent time-dependent correlation between counts. Derives a new negative multinomial distribution by combining INAR(1) representation with a random effects approach.…
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Ye, Xin; Garikapati, Venu M.; You, Daehyun; ...
2017-11-08
Most multinomial choice models (e.g., the multinomial logit model) adopted in practice assume an extreme-value Gumbel distribution for the random components (error terms) of utility functions. This distributional assumption offers a closed-form likelihood expression when the utility maximization principle is applied to model choice behaviors. As a result, model coefficients can be easily estimated using the standard maximum likelihood estimation method. However, maximum likelihood estimators are consistent and efficient only if distributional assumptions on the random error terms are valid. It is therefore critical to test the validity of underlying distributional assumptions on the error terms that form the basismore » of parameter estimation and policy evaluation. In this paper, a practical yet statistically rigorous method is proposed to test the validity of the distributional assumption on the random components of utility functions in both the multinomial logit (MNL) model and multiple discrete-continuous extreme value (MDCEV) model. Based on a semi-nonparametric approach, a closed-form likelihood function that nests the MNL or MDCEV model being tested is derived. The proposed method allows traditional likelihood ratio tests to be used to test violations of the standard Gumbel distribution assumption. Simulation experiments are conducted to demonstrate that the proposed test yields acceptable Type-I and Type-II error probabilities at commonly available sample sizes. The test is then applied to three real-world discrete and discrete-continuous choice models. For all three models, the proposed test rejects the validity of the standard Gumbel distribution in most utility functions, calling for the development of robust choice models that overcome adverse effects of violations of distributional assumptions on the error terms in random utility functions.« less
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Ye, Xin; Garikapati, Venu M.; You, Daehyun
Most multinomial choice models (e.g., the multinomial logit model) adopted in practice assume an extreme-value Gumbel distribution for the random components (error terms) of utility functions. This distributional assumption offers a closed-form likelihood expression when the utility maximization principle is applied to model choice behaviors. As a result, model coefficients can be easily estimated using the standard maximum likelihood estimation method. However, maximum likelihood estimators are consistent and efficient only if distributional assumptions on the random error terms are valid. It is therefore critical to test the validity of underlying distributional assumptions on the error terms that form the basismore » of parameter estimation and policy evaluation. In this paper, a practical yet statistically rigorous method is proposed to test the validity of the distributional assumption on the random components of utility functions in both the multinomial logit (MNL) model and multiple discrete-continuous extreme value (MDCEV) model. Based on a semi-nonparametric approach, a closed-form likelihood function that nests the MNL or MDCEV model being tested is derived. The proposed method allows traditional likelihood ratio tests to be used to test violations of the standard Gumbel distribution assumption. Simulation experiments are conducted to demonstrate that the proposed test yields acceptable Type-I and Type-II error probabilities at commonly available sample sizes. The test is then applied to three real-world discrete and discrete-continuous choice models. For all three models, the proposed test rejects the validity of the standard Gumbel distribution in most utility functions, calling for the development of robust choice models that overcome adverse effects of violations of distributional assumptions on the error terms in random utility functions.« less
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The Mixed Effects Trend Vector Model
ERIC Educational Resources Information Center
de Rooij, Mark; Schouteden, Martijn
2012-01-01
Maximum likelihood estimation of mixed effect baseline category logit models for multinomial longitudinal data can be prohibitive due to the integral dimension of the random effects distribution. We propose to use multidimensional unfolding methodology to reduce the dimensionality of the problem. As a by-product, readily interpretable graphical…
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NASA Astrophysics Data System (ADS)
Zeraatpisheh, Mojtaba; Ayoubi, Shamsollah; Jafari, Azam; Finke, Peter
2017-05-01
The efficiency of different digital and conventional soil mapping approaches to produce categorical maps of soil types is determined by cost, sample size, accuracy and the selected taxonomic level. The efficiency of digital and conventional soil mapping approaches was examined in the semi-arid region of Borujen, central Iran. This research aimed to (i) compare two digital soil mapping approaches including Multinomial logistic regression and random forest, with the conventional soil mapping approach at four soil taxonomic levels (order, suborder, great group and subgroup levels), (ii) validate the predicted soil maps by the same validation data set to determine the best method for producing the soil maps, and (iii) select the best soil taxonomic level by different approaches at three sample sizes (100, 80, and 60 point observations), in two scenarios with and without a geomorphology map as a spatial covariate. In most predicted maps, using both digital soil mapping approaches, the best results were obtained using the combination of terrain attributes and the geomorphology map, although differences between the scenarios with and without the geomorphology map were not significant. Employing the geomorphology map increased map purity and the Kappa index, and led to a decrease in the 'noisiness' of soil maps. Multinomial logistic regression had better performance at higher taxonomic levels (order and suborder levels); however, random forest showed better performance at lower taxonomic levels (great group and subgroup levels). Multinomial logistic regression was less sensitive than random forest to a decrease in the number of training observations. The conventional soil mapping method produced a map with larger minimum polygon size because of traditional cartographic criteria used to make the geological map 1:100,000 (on which the conventional soil mapping map was largely based). Likewise, conventional soil mapping map had also a larger average polygon size that resulted in a lower level of detail. Multinomial logistic regression at the order level (map purity of 0.80), random forest at the suborder (map purity of 0.72) and great group level (map purity of 0.60), and conventional soil mapping at the subgroup level (map purity of 0.48) produced the most accurate maps in the study area. The multinomial logistic regression method was identified as the most effective approach based on a combined index of map purity, map information content, and map production cost. The combined index also showed that smaller sample size led to a preference for the order level, while a larger sample size led to a preference for the great group level.
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A Dirichlet-Multinomial Bayes Classifier for Disease Diagnosis with Microbial Compositions.
Gao, Xiang; Lin, Huaiying; Dong, Qunfeng
2017-01-01
Dysbiosis of microbial communities is associated with various human diseases, raising the possibility of using microbial compositions as biomarkers for disease diagnosis. We have developed a Bayes classifier by modeling microbial compositions with Dirichlet-multinomial distributions, which are widely used to model multicategorical count data with extra variation. The parameters of the Dirichlet-multinomial distributions are estimated from training microbiome data sets based on maximum likelihood. The posterior probability of a microbiome sample belonging to a disease or healthy category is calculated based on Bayes' theorem, using the likelihood values computed from the estimated Dirichlet-multinomial distribution, as well as a prior probability estimated from the training microbiome data set or previously published information on disease prevalence. When tested on real-world microbiome data sets, our method, called DMBC (for Dirichlet-multinomial Bayes classifier), shows better classification accuracy than the only existing Bayesian microbiome classifier based on a Dirichlet-multinomial mixture model and the popular random forest method. The advantage of DMBC is its built-in automatic feature selection, capable of identifying a subset of microbial taxa with the best classification accuracy between different classes of samples based on cross-validation. This unique ability enables DMBC to maintain and even improve its accuracy at modeling species-level taxa. The R package for DMBC is freely available at https://github.com/qunfengdong/DMBC. IMPORTANCE By incorporating prior information on disease prevalence, Bayes classifiers have the potential to estimate disease probability better than other common machine-learning methods. Thus, it is important to develop Bayes classifiers specifically tailored for microbiome data. Our method shows higher classification accuracy than the only existing Bayesian classifier and the popular random forest method, and thus provides an alternative option for using microbial compositions for disease diagnosis.
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Estimation from incomplete multinomial data. Ph.D. Thesis - Harvard Univ.
NASA Technical Reports Server (NTRS)
Credeur, K. R.
1978-01-01
The vector of multinomial cell probabilities was estimated from incomplete data, incomplete in that it contains partially classified observations. Each such partially classified observation was observed to fall in one of two or more selected categories but was not classified further into a single category. The data were assumed to be incomplete at random. The estimation criterion was minimization of risk for quadratic loss. The estimators were the classical maximum likelihood estimate, the Bayesian posterior mode, and the posterior mean. An approximation was developed for the posterior mean. The Dirichlet, the conjugate prior for the multinomial distribution, was assumed for the prior distribution.
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Multinomial mixture model with heterogeneous classification probabilities
Holland, M.D.; Gray, B.R.
2011-01-01
Royle and Link (Ecology 86(9):2505-2512, 2005) proposed an analytical method that allowed estimation of multinomial distribution parameters and classification probabilities from categorical data measured with error. While useful, we demonstrate algebraically and by simulations that this method yields biased multinomial parameter estimates when the probabilities of correct category classifications vary among sampling units. We address this shortcoming by treating these probabilities as logit-normal random variables within a Bayesian framework. We use Markov chain Monte Carlo to compute Bayes estimates from a simulated sample from the posterior distribution. Based on simulations, this elaborated Royle-Link model yields nearly unbiased estimates of multinomial and correct classification probability estimates when classification probabilities are allowed to vary according to the normal distribution on the logit scale or according to the Beta distribution. The method is illustrated using categorical submersed aquatic vegetation data. ?? 2010 Springer Science+Business Media, LLC.
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Higgs, Megan D.; Link, William; White, Gary C.; Haroldson, Mark A.; Bjornlie, Daniel D.
2013-01-01
Mark-resight designs for estimation of population abundance are common and attractive to researchers. However, inference from such designs is very limited when faced with sparse data, either from a low number of marked animals, a low probability of detection, or both. In the Greater Yellowstone Ecosystem, yearly mark-resight data are collected for female grizzly bears with cubs-of-the-year (FCOY), and inference suffers from both limitations. To overcome difficulties due to sparseness, we assume homogeneity in sighting probabilities over 16 years of bi-annual aerial surveys. We model counts of marked and unmarked animals as multinomial random variables, using the capture frequencies of marked animals for inference about the latent multinomial frequencies for unmarked animals. We discuss undesirable behavior of the commonly used discrete uniform prior distribution on the population size parameter and provide OpenBUGS code for fitting such models. The application provides valuable insights into subtleties of implementing Bayesian inference for latent multinomial models. We tie the discussion to our application, though the insights are broadly useful for applications of the latent multinomial model.
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Sarma, Sisira; Simpson, Wayne
2007-12-01
Utilizing a unique longitudinal survey linked with home care use data, this paper analyzes the determinants of elderly living arrangements in Manitoba, Canada using a random effects multinomial logit model that accounts for unobserved individual heterogeneity. Because current home ownership is potentially endogenous in a living arrangements choice model, we use prior home ownership as an instrument. We also use prior home care use as an instrument for home care and use a random coefficient framework to account for unobserved health status. After controlling for relevant socio-demographic factors and accounting for unobserved individual heterogeneity, we find that home care and home ownership reduce the probability of living in a nursing home. Consistent with previous studies, we find that age is a strong predictor of nursing home entry. We also find that married people, those who have lived longer in the same community, and those who are healthy are more likely to live independently and less likely to be institutionalized or to cohabit with individuals other than their spouse.
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NASA Technical Reports Server (NTRS)
Jahshan, S. N.; Singleterry, R. C.
2001-01-01
The effect of random fuel redistribution on the eigenvalue of a one-speed reactor is investigated. An ensemble of such reactors that are identical to a homogeneous reference critical reactor except for the fissile isotope density distribution is constructed such that it meets a set of well-posed redistribution requirements. The average eigenvalue,
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NASA Astrophysics Data System (ADS)
Cao, Faxian; Yang, Zhijing; Ren, Jinchang; Ling, Wing-Kuen; Zhao, Huimin; Marshall, Stephen
2017-12-01
Although the sparse multinomial logistic regression (SMLR) has provided a useful tool for sparse classification, it suffers from inefficacy in dealing with high dimensional features and manually set initial regressor values. This has significantly constrained its applications for hyperspectral image (HSI) classification. In order to tackle these two drawbacks, an extreme sparse multinomial logistic regression (ESMLR) is proposed for effective classification of HSI. First, the HSI dataset is projected to a new feature space with randomly generated weight and bias. Second, an optimization model is established by the Lagrange multiplier method and the dual principle to automatically determine a good initial regressor for SMLR via minimizing the training error and the regressor value. Furthermore, the extended multi-attribute profiles (EMAPs) are utilized for extracting both the spectral and spatial features. A combinational linear multiple features learning (MFL) method is proposed to further enhance the features extracted by ESMLR and EMAPs. Finally, the logistic regression via the variable splitting and the augmented Lagrangian (LORSAL) is adopted in the proposed framework for reducing the computational time. Experiments are conducted on two well-known HSI datasets, namely the Indian Pines dataset and the Pavia University dataset, which have shown the fast and robust performance of the proposed ESMLR framework.
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ERIC Educational Resources Information Center
Hladky, Paul W.
2007-01-01
Random-climb models enable undergraduate chemistry students to visualize polymer molecules, quantify their configurational properties, and relate molecular structure to a variety of physical properties. The model could serve as an introduction to more elaborate models of polymer molecules and could help in learning topics such as lattice models of…
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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…
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Towards dropout training for convolutional neural networks.
Wu, Haibing; Gu, Xiaodong
2015-11-01
Recently, dropout has seen increasing use in deep learning. For deep convolutional neural networks, dropout is known to work well in fully-connected layers. However, its effect in convolutional and pooling layers is still not clear. This paper demonstrates that max-pooling dropout is equivalent to randomly picking activation based on a multinomial distribution at training time. In light of this insight, we advocate employing our proposed probabilistic weighted pooling, instead of commonly used max-pooling, to act as model averaging at test time. Empirical evidence validates the superiority of probabilistic weighted pooling. We also empirically show that the effect of convolutional dropout is not trivial, despite the dramatically reduced possibility of over-fitting due to the convolutional architecture. Elaborately designing dropout training simultaneously in max-pooling and fully-connected layers, we achieve state-of-the-art performance on MNIST, and very competitive results on CIFAR-10 and CIFAR-100, relative to other approaches without data augmentation. Finally, we compare max-pooling dropout and stochastic pooling, both of which introduce stochasticity based on multinomial distributions at pooling stage. Copyright © 2015 Elsevier Ltd. All rights reserved.
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2012-01-01
Background Identifying risk factors for Salmonella Enteritidis (SE) infections in Ontario will assist public health authorities to design effective control and prevention programs to reduce the burden of SE infections. Our research objective was to identify risk factors for acquiring SE infections with various phage types (PT) in Ontario, Canada. We hypothesized that certain PTs (e.g., PT8 and PT13a) have specific risk factors for infection. Methods Our study included endemic SE cases with various PTs whose isolates were submitted to the Public Health Laboratory-Toronto from January 20th to August 12th, 2011. Cases were interviewed using a standardized questionnaire that included questions pertaining to demographics, travel history, clinical symptoms, contact with animals, and food exposures. A multinomial logistic regression method using the Generalized Linear Latent and Mixed Model procedure and a case-case study design were used to identify risk factors for acquiring SE infections with various PTs in Ontario, Canada. In the multinomial logistic regression model, the outcome variable had three categories representing human infections caused by SE PT8, PT13a, and all other SE PTs (i.e., non-PT8/non-PT13a) as a referent category to which the other two categories were compared. Results In the multivariable model, SE PT8 was positively associated with contact with dogs (OR=2.17, 95% CI 1.01-4.68) and negatively associated with pepper consumption (OR=0.35, 95% CI 0.13-0.94), after adjusting for age categories and gender, and using exposure periods and health regions as random effects to account for clustering. Conclusions Our study findings offer interesting hypotheses about the role of phage type-specific risk factors. Multinomial logistic regression analysis and the case-case study approach are novel methodologies to evaluate associations among SE infections with different PTs and various risk factors. PMID:23057531
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Effects of ignoring baseline on modeling transitions from intact cognition to dementia.
Yu, Lei; Tyas, Suzanne L; Snowdon, David A; Kryscio, Richard J
2009-07-01
This paper evaluates the effect of ignoring baseline when modeling transitions from intact cognition to dementia with mild cognitive impairment (MCI) and global impairment (GI) as intervening cognitive states. Transitions among states are modeled by a discrete-time Markov chain having three transient (intact cognition, MCI, and GI) and two competing absorbing states (death and dementia). Transition probabilities depend on two covariates, age and the presence/absence of an apolipoprotein E-epsilon4 allele, through a multinomial logistic model with shared random effects. Results are illustrated with an application to the Nun Study, a cohort of 678 participants 75+ years of age at baseline and followed longitudinally with up to ten cognitive assessments per nun.
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Multidimensional Computerized Adaptive Testing for Indonesia Junior High School Biology
ERIC Educational Resources Information Center
Kuo, Bor-Chen; Daud, Muslem; Yang, Chih-Wei
2015-01-01
This paper describes a curriculum-based multidimensional computerized adaptive test that was developed for Indonesia junior high school Biology. In adherence to the Indonesian curriculum of different Biology dimensions, 300 items was constructed, and then tested to 2238 students. A multidimensional random coefficients multinomial logit model was…
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Burgette, Lane F; Reiter, Jerome P
2013-06-01
Multinomial outcomes with many levels can be challenging to model. Information typically accrues slowly with increasing sample size, yet the parameter space expands rapidly with additional covariates. Shrinking all regression parameters towards zero, as often done in models of continuous or binary response variables, is unsatisfactory, since setting parameters equal to zero in multinomial models does not necessarily imply "no effect." We propose an approach to modeling multinomial outcomes with many levels based on a Bayesian multinomial probit (MNP) model and a multiple shrinkage prior distribution for the regression parameters. The prior distribution encourages the MNP regression parameters to shrink toward a number of learned locations, thereby substantially reducing the dimension of the parameter space. Using simulated data, we compare the predictive performance of this model against two other recently-proposed methods for big multinomial models. The results suggest that the fully Bayesian, multiple shrinkage approach can outperform these other methods. We apply the multiple shrinkage MNP to simulating replacement values for areal identifiers, e.g., census tract indicators, in order to protect data confidentiality in public use datasets.
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Effects of ignoring baseline on modeling transitions from intact cognition to dementia
Yu, Lei; Tyas, Suzanne L.; Snowdon, David A.; Kryscio, Richard J.
2009-01-01
This paper evaluates the effect of ignoring baseline when modeling transitions from intact cognition to dementia with mild cognitive impairment (MCI) and global impairment (GI) as intervening cognitive states. Transitions among states are modeled by a discrete-time Markov chain having three transient (intact cognition, MCI, and GI) and two competing absorbing states (death and dementia). Transition probabilities depend on two covariates, age and the presence/absence of an apolipoprotein E-ε4 allele, through a multinomial logistic model with shared random effects. Results are illustrated with an application to the Nun Study, a cohort of 678 participants 75+ years of age at baseline and followed longitudinally with up to ten cognitive assessments per nun. PMID:20161282
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ERIC Educational Resources Information Center
Lee, John Chi-Kin; Zhang, Zhonghua; Yin, Hongbiao
2010-01-01
This article used the multidimensional random coefficients multinomial logit model to examine the construct validity and detect the substantial differential item functioning (DIF) of the Chinese version of motivated strategies for learning questionnaire (MSLQ-CV). A total of 1,354 Hong Kong junior high school students were administered the…
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Arrow, P; Klobas, E
2017-06-01
To compare changes in child dental anxiety after treatment for early childhood caries (ECC) using two treatment approaches. Children with ECC were randomized to test (atraumatic restorative treatment (ART)-based approach) or control (standard care approach) groups. Children aged 3 years or older completed a dental anxiety scale at baseline and follow up. Changes in child dental anxiety from baseline to follow up were tested using the chi-squared statistic, Wilcoxon rank sum test, McNemar's test and multinomial logistic regression. Two hundred and fifty-four children were randomized (N = 127 test, N = 127 control). At baseline, 193 children completed the dental anxiety scale, 211 at follow up and 170 completed the scale on both occasions. Children who were anxious at baseline (11%) were no longer anxious at follow up, and 11% non-anxious children became anxious. Multinomial logistic regression found each increment in the number of visits increased the odds of worsening dental anxiety (odds ratio (OR), 2.2; P < 0.05), whereas each increment in the number of treatments lowered the odds of worsening anxiety (OR, 0.50; P = 0.05). The ART-based approach to managing ECC resulted in similar levels of dental anxiety to the standard treatment approach and provides a valuable alternative approach to the management of ECC in a primary dental care setting. © 2016 Australian Dental Association.
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The analysis of the pilot's cognitive and decision processes
NASA Technical Reports Server (NTRS)
Curry, R. E.
1975-01-01
Articles are presented on pilot performance in zero-visibility precision approach, failure detection by pilots during automatic landing, experiments in pilot decision-making during simulated low visibility approaches, a multinomial maximum likelihood program, and a random search algorithm for laboratory computers. Other topics discussed include detection of system failures in multi-axis tasks and changes in pilot workload during an instrument landing.
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Neighborhood Structural Inequality, Collective Efficacy, and Sexual Risk Behavior among Urban Youth
BROWNING, CHRISTOPHER R.; BURRINGTON, LORI A.; LEVENTHAL, TAMA; BROOKS-GUNN, JEANNE
2011-01-01
We draw on collective efficacy theory to extend a contextual model of early adolescent sexual behavior. Specifically, we hypothesize that neighborhood structural disadvantage—as measured by levels of concentrated poverty, residential instability, and aspects of immigrant concentration—and diminished collective efficacy have consequences for the prevalence of early adolescent multiple sexual partnering. Findings from random effects multinomial logistic regression models of the number of sexual partners among a sample of youth, age 11 to 16, from the Project on Human Development in Chicago Neighborhoods (N = 768) reveal evidence of neighborhood effects on adolescent higher-risk sexual activity. Collective efficacy is negatively associated with having two or more sexual partners versus one (but not zero versus one) sexual partner. The effect of collective efficacy is dependent upon age: The regulatory effect of collective efficacy increases for older adolescents. PMID:18771063
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Lampoudi, Sotiria; Gillespie, Dan T; Petzold, Linda R
2009-03-07
The Inhomogeneous Stochastic Simulation Algorithm (ISSA) is a variant of the stochastic simulation algorithm in which the spatially inhomogeneous volume of the system is divided into homogeneous subvolumes, and the chemical reactions in those subvolumes are augmented by diffusive transfers of molecules between adjacent subvolumes. The ISSA can be prohibitively slow when the system is such that diffusive transfers occur much more frequently than chemical reactions. In this paper we present the Multinomial Simulation Algorithm (MSA), which is designed to, on the one hand, outperform the ISSA when diffusive transfer events outnumber reaction events, and on the other, to handle small reactant populations with greater accuracy than deterministic-stochastic hybrid algorithms. The MSA treats reactions in the usual ISSA fashion, but uses appropriately conditioned binomial random variables for representing the net numbers of molecules diffusing from any given subvolume to a neighbor within a prescribed distance. Simulation results illustrate the benefits of the algorithm.
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NASA Astrophysics Data System (ADS)
Lin, Yingzhi; Deng, Xiangzheng; Li, Xing; Ma, Enjun
2014-12-01
Spatially explicit simulation of land use change is the basis for estimating the effects of land use and cover change on energy fluxes, ecology and the environment. At the pixel level, logistic regression is one of the most common approaches used in spatially explicit land use allocation models to determine the relationship between land use and its causal factors in driving land use change, and thereby to evaluate land use suitability. However, these models have a drawback in that they do not determine/allocate land use based on the direct relationship between land use change and its driving factors. Consequently, a multinomial logistic regression method was introduced to address this flaw, and thereby, judge the suitability of a type of land use in any given pixel in a case study area of the Jiangxi Province, China. A comparison of the two regression methods indicated that the proportion of correctly allocated pixels using multinomial logistic regression was 92.98%, which was 8.47% higher than that obtained using logistic regression. Paired t-test results also showed that pixels were more clearly distinguished by multinomial logistic regression than by logistic regression. In conclusion, multinomial logistic regression is a more efficient and accurate method for the spatial allocation of land use changes. The application of this method in future land use change studies may improve the accuracy of predicting the effects of land use and cover change on energy fluxes, ecology, and environment.
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Latent spatial models and sampling design for landscape genetics
Hanks, Ephraim M.; Hooten, Mevin B.; Knick, Steven T.; Oyler-McCance, Sara J.; Fike, Jennifer A.; Cross, Todd B.; Schwartz, Michael K.
2016-01-01
We propose a spatially-explicit approach for modeling genetic variation across space and illustrate how this approach can be used to optimize spatial prediction and sampling design for landscape genetic data. We propose a multinomial data model for categorical microsatellite allele data commonly used in landscape genetic studies, and introduce a latent spatial random effect to allow for spatial correlation between genetic observations. We illustrate how modern dimension reduction approaches to spatial statistics can allow for efficient computation in landscape genetic statistical models covering large spatial domains. We apply our approach to propose a retrospective spatial sampling design for greater sage-grouse (Centrocercus urophasianus) population genetics in the western United States.
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Weather impacts on single-vehicle truck crash injury severity.
Naik, Bhaven; Tung, Li-Wei; Zhao, Shanshan; Khattak, Aemal J
2016-09-01
The focus of this paper is on illustrating the feasibility of aggregating data from disparate sources to investigate the relationship between single-vehicle truck crash injury severity and detailed weather conditions. Specifically, this paper presents: (a) a methodology that combines detailed 15-min weather station data with crash and roadway data, and (b) an empirical investigation of the effects of weather on crash-related injury severities of single-vehicle truck crashes. Random parameters ordinal and multinomial regression models were used to investigate crash injury severity under different weather conditions, taking into account the individual unobserved heterogeneity. The adopted methodology allowed consideration of environmental, roadway, and climate-related variables in single-vehicle truck crash injury severity. Results showed that wind speed, rain, humidity, and air temperature were linked with single-vehicle truck crash injury severity. Greater recorded wind speed added to the severity of injuries in single-vehicle truck crashes in general. Rain and warmer air temperatures were linked to more severe crash injuries in single-vehicle truck crashes while higher levels of humidity were linked to less severe injuries. Random parameters ordered logit and multinomial logit, respectively, revealed some individual heterogeneity in the data and showed that integrating comprehensive weather data with crash data provided useful insights into factors associated with single-vehicle truck crash injury severity. The research provided a practical method that combined comprehensive 15-min weather station data with crash and roadway data, thereby providing useful insights into crash injury severity of single-vehicle trucks. Those insights are useful for future truck driver educational programs and for truck safety in different weather conditions. Copyright © 2016 Elsevier Ltd and National Safety Council. All rights reserved.
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Classification of Effective Soil Depth by Using Multinomial Logistic Regression Analysis
NASA Astrophysics Data System (ADS)
Chang, C. H.; Chan, H. C.; Chen, B. A.
2016-12-01
Classification of effective soil depth is a task of determining the slopeland utilizable limitation in Taiwan. The "Slopeland Conservation and Utilization Act" categorizes the slopeland into agriculture and husbandry land, land suitable for forestry and land for enhanced conservation according to the factors including average slope, effective soil depth, soil erosion and parental rock. However, sit investigation of the effective soil depth requires a cost-effective field work. This research aimed to classify the effective soil depth by using multinomial logistic regression with the environmental factors. The Wen-Shui Watershed located at the central Taiwan was selected as the study areas. The analysis of multinomial logistic regression is performed by the assistance of a Geographic Information Systems (GIS). The effective soil depth was categorized into four levels including deeper, deep, shallow and shallower. The environmental factors of slope, aspect, digital elevation model (DEM), curvature and normalized difference vegetation index (NDVI) were selected for classifying the soil depth. An Error Matrix was then used to assess the model accuracy. The results showed an overall accuracy of 75%. At the end, a map of effective soil depth was produced to help planners and decision makers in determining the slopeland utilizable limitation in the study areas.
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Modeling Information Content Via Dirichlet-Multinomial Regression Analysis.
Ferrari, Alberto
2017-01-01
Shannon entropy is being increasingly used in biomedical research as an index of complexity and information content in sequences of symbols, e.g. languages, amino acid sequences, DNA methylation patterns and animal vocalizations. Yet, distributional properties of information entropy as a random variable have seldom been the object of study, leading to researchers mainly using linear models or simulation-based analytical approach to assess differences in information content, when entropy is measured repeatedly in different experimental conditions. Here a method to perform inference on entropy in such conditions is proposed. Building on results coming from studies in the field of Bayesian entropy estimation, a symmetric Dirichlet-multinomial regression model, able to deal efficiently with the issue of mean entropy estimation, is formulated. Through a simulation study the model is shown to outperform linear modeling in a vast range of scenarios and to have promising statistical properties. As a practical example, the method is applied to a data set coming from a real experiment on animal communication.
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A generalized nonlinear model-based mixed multinomial logit approach for crash data analysis.
Zeng, Ziqiang; Zhu, Wenbo; Ke, Ruimin; Ash, John; Wang, Yinhai; Xu, Jiuping; Xu, Xinxin
2017-02-01
The mixed multinomial logit (MNL) approach, which can account for unobserved heterogeneity, is a promising unordered model that has been employed in analyzing the effect of factors contributing to crash severity. However, its basic assumption of using a linear function to explore the relationship between the probability of crash severity and its contributing factors can be violated in reality. This paper develops a generalized nonlinear model-based mixed MNL approach which is capable of capturing non-monotonic relationships by developing nonlinear predictors for the contributing factors in the context of unobserved heterogeneity. The crash data on seven Interstate freeways in Washington between January 2011 and December 2014 are collected to develop the nonlinear predictors in the model. Thirteen contributing factors in terms of traffic characteristics, roadway geometric characteristics, and weather conditions are identified to have significant mixed (fixed or random) effects on the crash density in three crash severity levels: fatal, injury, and property damage only. The proposed model is compared with the standard mixed MNL model. The comparison results suggest a slight superiority of the new approach in terms of model fit measured by the Akaike Information Criterion (12.06 percent decrease) and Bayesian Information Criterion (9.11 percent decrease). The predicted crash densities for all three levels of crash severities of the new approach are also closer (on average) to the observations than the ones predicted by the standard mixed MNL model. Finally, the significance and impacts of the contributing factors are analyzed. Copyright © 2016 Elsevier Ltd. All rights reserved.
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An Empirical Bayes Estimate of Multinomial Probabilities.
1982-02-01
multinomial probabilities has been considered from a decision theoretic point of view by Steinhaus (1957), Trybula (1958) and Rutkowska (1977). In a recent...variate Rypergeometric and Multinomial Distributions," Zastosowania Matematyki, 16, 9-21. Steinhaus , H. (1957), "The Problem of Estimation." Annals of
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Modeling abundance using multinomial N-mixture models
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.
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Arsenic exposure and oral cavity lesions in Bangladesh.
Syed, Emdadul H; Melkonian, Stephanie; Poudel, Krishna C; Yasuoka, Junko; Otsuka, Keiko; Ahmed, Alauddin; Islam, Tariqul; Parvez, Faruque; Slavkovich, Vesna; Graziano, Joseph H; Ahsan, Habibul; Jimba, Masamine
2013-01-01
To evaluate the relationship between arsenic exposure and oral cavity lesions among an arsenic-exposed population in Bangladesh. We carried out an analysis utilizing the baseline data of the Health Effects of Arsenic Exposure Longitudinal Study, which is an ongoing population-based cohort study to investigate health outcomes associated with arsenic exposure via drinking water in Araihazar, Bangladesh. We used multinomial regression models to estimate the risk of oral cavity lesions. Participants with high urinary arsenic levels (286.1 to 5000.0 μg/g) were more likely to develop arsenical lesions of the gums (multinomial odds ratio = 2.90; 95% confidence interval, 1.11 to 7.54), and tongue (multinomial odds ratio = 2.79; 95% confidence interval, 1.51 to 5.15), compared with those with urinary arsenic levels of 7.0 to 134.0 μg/g. Higher level of arsenic exposure was positively associated with increased arsenical lesions of the gums and tongue.
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2012-01-01
Background A discrete choice experiment (DCE) is a preference survey which asks participants to make a choice among product portfolios comparing the key product characteristics by performing several choice tasks. Analyzing DCE data needs to account for within-participant correlation because choices from the same participant are likely to be similar. In this study, we empirically compared some commonly-used statistical methods for analyzing DCE data while accounting for within-participant correlation based on a survey of patient preference for colorectal cancer (CRC) screening tests conducted in Hamilton, Ontario, Canada in 2002. Methods A two-stage DCE design was used to investigate the impact of six attributes on participants' preferences for CRC screening test and willingness to undertake the test. We compared six models for clustered binary outcomes (logistic and probit regressions using cluster-robust standard error (SE), random-effects and generalized estimating equation approaches) and three models for clustered nominal outcomes (multinomial logistic and probit regressions with cluster-robust SE and random-effects multinomial logistic model). We also fitted a bivariate probit model with cluster-robust SE treating the choices from two stages as two correlated binary outcomes. The rank of relative importance between attributes and the estimates of β coefficient within attributes were used to assess the model robustness. Results In total 468 participants with each completing 10 choices were analyzed. Similar results were reported for the rank of relative importance and β coefficients across models for stage-one data on evaluating participants' preferences for the test. The six attributes ranked from high to low as follows: cost, specificity, process, sensitivity, preparation and pain. However, the results differed across models for stage-two data on evaluating participants' willingness to undertake the tests. Little within-patient correlation (ICC ≈ 0) was found in stage-one data, but substantial within-patient correlation existed (ICC = 0.659) in stage-two data. Conclusions When small clustering effect presented in DCE data, results remained robust across statistical models. However, results varied when larger clustering effect presented. Therefore, it is important to assess the robustness of the estimates via sensitivity analysis using different models for analyzing clustered data from DCE studies. PMID:22348526
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NASA Astrophysics Data System (ADS)
Elmore, K. L.
2016-12-01
The Metorological Phenomemna Identification NeartheGround (mPING) project is an example of a crowd-sourced, citizen science effort to gather data of sufficeint quality and quantity needed by new post processing methods that use machine learning. Transportation and infrastructure are particularly sensitive to precipitation type in winter weather. We extract attributes from operational numerical forecast models and use them in a random forest to generate forecast winter precipitation types. We find that random forests applied to forecast soundings are effective at generating skillful forecasts of surface ptype with consideralbly more skill than the current algorithms, especuially for ice pellets and freezing rain. We also find that three very different forecast models yuield similar overall results, showing that random forests are able to extract essentially equivalent information from different forecast models. We also show that the random forest for each model, and each profile type is unique to the particular forecast model and that the random forests developed using a particular model suffer significant degradation when given attributes derived from a different model. This implies that no single algorithm can perform well across all forecast models. Clearly, random forests extract information unavailable to "physically based" methods because the physical information in the models does not appear as we expect. One intersting result is that results from the classic "warm nose" sounding profile are, by far, the most sensitive to the particular forecast model, but this profile is also the one for which random forests are most skillful. Finally, a method for calibrarting probabilties for each different ptype using multinomial logistic regression is shown.
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Congdon, Peter
2010-01-01
Different indicators of morbidity for chronic disease may not necessarily be available at a disaggregated spatial scale (e.g., for small areas with populations under 10 thousand). Instead certain indicators may only be available at a more highly aggregated spatial scale; for example, deaths may be recorded for small areas, but disease prevalence only at a considerably higher spatial scale. Nevertheless prevalence estimates at small area level are important for assessing health need. An instance is provided by England where deaths and hospital admissions for coronary heart disease are available for small areas known as wards, but prevalence is only available for relatively large health authority areas. To estimate CHD prevalence at small area level in such a situation, a shared random effect method is proposed that pools information regarding spatial morbidity contrasts over different indicators (deaths, hospitalizations, prevalence). The shared random effect approach also incorporates differences between small areas in known risk factors (e.g., income, ethnic structure). A Poisson-multinomial equivalence may be used to ensure small area prevalence estimates sum to the known higher area total. An illustration is provided by data for London using hospital admissions and CHD deaths at ward level, together with CHD prevalence totals for considerably larger local health authority areas. The shared random effect involved a spatially correlated common factor, that accounts for clustering in latent risk factors, and also provides a summary measure of small area CHD morbidity.
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Congdon, Peter
2010-01-01
Different indicators of morbidity for chronic disease may not necessarily be available at a disaggregated spatial scale (e.g., for small areas with populations under 10 thousand). Instead certain indicators may only be available at a more highly aggregated spatial scale; for example, deaths may be recorded for small areas, but disease prevalence only at a considerably higher spatial scale. Nevertheless prevalence estimates at small area level are important for assessing health need. An instance is provided by England where deaths and hospital admissions for coronary heart disease are available for small areas known as wards, but prevalence is only available for relatively large health authority areas. To estimate CHD prevalence at small area level in such a situation, a shared random effect method is proposed that pools information regarding spatial morbidity contrasts over different indicators (deaths, hospitalizations, prevalence). The shared random effect approach also incorporates differences between small areas in known risk factors (e.g., income, ethnic structure). A Poisson-multinomial equivalence may be used to ensure small area prevalence estimates sum to the known higher area total. An illustration is provided by data for London using hospital admissions and CHD deaths at ward level, together with CHD prevalence totals for considerably larger local health authority areas. The shared random effect involved a spatially correlated common factor, that accounts for clustering in latent risk factors, and also provides a summary measure of small area CHD morbidity. PMID:20195439
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Pandis, Nikolaos; Polychronopoulou, Argy; Madianos, Phoebus; Makou, Margarita; Eliades, Theodore
2011-06-01
The objective of this article was to record reporting characteristics related to study quality of research published in major specialty dental journals with the highest impact factor (Journal of Endodontics, Journal of Oral and Maxillofacial Surgery, American Journal of Orthodontics and Dentofacial Orthopedics; Pediatric Dentistry, Journal of Clinical Periodontology, and International Journal of Prosthetic Dentistry). The included articles were classified into the following 3 broad subject categories: (1) cross-sectional (snap-shot), (2) observational, and (3) interventional. Multinomial logistic regression was conducted for effect estimation using the journal as the response and randomization, sample calculation, confounding discussed, multivariate analysis, effect measurement, and confidence intervals as the explanatory variables. The results showed that cross-sectional studies were the dominant design (55%), whereas observational investigations accounted for 13%, and interventions/clinical trials for 32%. Reporting on quality characteristics was low for all variables: random allocation (15%), sample size calculation (7%), confounding issues/possible confounders (38%), effect measurements (16%), and multivariate analysis (21%). Eighty-four percent of the published articles reported a statistically significant main finding and only 13% presented confidence intervals. The Journal of Clinical Periodontology showed the highest probability of including quality characteristics in reporting results among all dental journals. Copyright © 2011 Elsevier Inc. All rights reserved.
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Ardoino, Ilaria; Lanzoni, Monica; Marano, Giuseppe; Boracchi, Patrizia; Sagrini, Elisabetta; Gianstefani, Alice; Piscaglia, Fabio; Biganzoli, Elia M
2017-04-01
The interpretation of regression models results can often benefit from the generation of nomograms, 'user friendly' graphical devices especially useful for assisting the decision-making processes. However, in the case of multinomial regression models, whenever categorical responses with more than two classes are involved, nomograms cannot be drawn in the conventional way. Such a difficulty in managing and interpreting the outcome could often result in a limitation of the use of multinomial regression in decision-making support. In the present paper, we illustrate the derivation of a non-conventional nomogram for multinomial regression models, intended to overcome this issue. Although it may appear less straightforward at first sight, the proposed methodology allows an easy interpretation of the results of multinomial regression models and makes them more accessible for clinicians and general practitioners too. Development of prediction model based on multinomial logistic regression and of the pertinent graphical tool is illustrated by means of an example involving the prediction of the extent of liver fibrosis in hepatitis C patients by routinely available markers.
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Small individual loans and mental health: a randomized controlled trial among South African adults
Fernald, Lia CH; Hamad, Rita; Karlan, Dean; Ozer, Emily J; Zinman, Jonathan
2008-01-01
Background In the developing world, access to small, individual loans has been variously hailed as a poverty-alleviation tool – in the context of "microcredit" – but has also been criticized as "usury" and harmful to vulnerable borrowers. Prior studies have assessed effects of access to credit on traditional economic outcomes for poor borrowers, but effects on mental health have been largely ignored. Methods Applicants who had previously been rejected (n = 257) for a loan (200% annual percentage rate – APR) from a lender in South Africa were randomly assigned to a "second-look" that encouraged loan officers to approve their applications. This randomized encouragement resulted in 53% of applicants receiving a loan they otherwise would not have received. All subjects were assessed 6–12 months later with questions about demographics, socio-economic status, and two indicators of mental health: the Center for Epidemiologic Studies – Depression Scale (CES-D) and Cohen's Perceived Stress scale. Intent-to-treat analyses were calculated using multinomial probit regressions. Results Randomization into receiving a "second look" for access to credit increased perceived stress in the combined sample of women and men; the findings were stronger among men. Credit access was associated with reduced depressive symptoms in men, but not women. Conclusion Our findings suggest that a mechanism used to reduce the economic stress of extremely poor individuals can have mixed effects on their experiences of psychological stress and depressive symptomatology. Our data support the notion that mental health should be included as a measure of success (or failure) when examining potential tools for poverty alleviation. Further longitudinal research is needed in South Africa and other settings to understand how borrowing at high interest rates affects gender roles and daily life activities. CCT: ISRCTN 10734925 PMID:19087316
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Small individual loans and mental health: a randomized controlled trial among South African adults.
Fernald, Lia C H; Hamad, Rita; Karlan, Dean; Ozer, Emily J; Zinman, Jonathan
2008-12-16
In the developing world, access to small, individual loans has been variously hailed as a poverty-alleviation tool - in the context of "microcredit" - but has also been criticized as "usury" and harmful to vulnerable borrowers. Prior studies have assessed effects of access to credit on traditional economic outcomes for poor borrowers, but effects on mental health have been largely ignored. Applicants who had previously been rejected (n = 257) for a loan (200% annual percentage rate - APR) from a lender in South Africa were randomly assigned to a "second-look" that encouraged loan officers to approve their applications. This randomized encouragement resulted in 53% of applicants receiving a loan they otherwise would not have received. All subjects were assessed 6-12 months later with questions about demographics, socio-economic status, and two indicators of mental health: the Center for Epidemiologic Studies - Depression Scale (CES-D) and Cohen's Perceived Stress scale. Intent-to-treat analyses were calculated using multinomial probit regressions. Randomization into receiving a "second look" for access to credit increased perceived stress in the combined sample of women and men; the findings were stronger among men. Credit access was associated with reduced depressive symptoms in men, but not women. Our findings suggest that a mechanism used to reduce the economic stress of extremely poor individuals can have mixed effects on their experiences of psychological stress and depressive symptomatology. Our data support the notion that mental health should be included as a measure of success (or failure) when examining potential tools for poverty alleviation. Further longitudinal research is needed in South Africa and other settings to understand how borrowing at high interest rates affects gender roles and daily life activities. CCT: ISRCTN 10734925.
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What influences participation in genetic carrier testing? Results from a discrete choice experiment.
Hall, Jane; Fiebig, Denzil G; King, Madeleine T; Hossain, Ishrat; Louviere, Jordan J
2006-05-01
This study explores factors that influence participation in genetic testing programs and the acceptance of multiple tests. Tay Sachs and cystic fibrosis are both genetically determined recessive disorders with differing severity, treatment availability, and prevalence in different population groups. We used a discrete choice experiment with a general community and an Ashkenazi Jewish sample; data were analysed using multinomial logit with random coefficients. Although Jewish respondents were more likely to be tested, both groups seem to be making very similar tradeoffs across attributes when they make genetic testing choices.
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Hoppe, Fred M
2008-06-01
We show that the formula of Faà di Bruno for the derivative of a composite function gives, in special cases, the sampling distributions in population genetics that are due to Ewens and to Pitman. The composite function is the same in each case. Other sampling distributions also arise in this way, such as those arising from Dirichlet, multivariate hypergeometric, and multinomial models, special cases of which correspond to Bose-Einstein, Fermi-Dirac, and Maxwell-Boltzmann distributions in physics. Connections are made to compound sampling models.
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Landscape effects on diets of two canids in Northwestern Texas: A multinomial modeling approach
Lemons, P.R.; Sedinger, J.S.; Herzog, M.P.; Gipson, P.S.; Gilliland, R.L.
2010-01-01
Analyses of feces, stomach contents, and regurgitated pellets are common techniques for assessing diets of vertebrates and typically contain more than 1 food item per sampling unit. When analyzed, these individual food items have traditionally been treated as independent, which represents pseudoreplication. When food types are recorded as present or absent, these samples can be treated as multinomial vectors of food items, with each vector representing 1 realization of a possible diet. We suggest such data have a similar structure to capture histories for closed-capture, capturemarkrecapture data. To assess the effects of landscapes and presence of a potential competitor, we used closed-capture models implemented in program MARK into analyze diet data generated from feces of swift foxes (Vulpes velox) and coyotes (Canis latrans) in northwestern Texas. The best models of diet contained season and location for both swift foxes and coyotes, but year accounted for less variation, suggesting that landscape type is an important predictor of diets of both species. Models containing the effect of coyote reduction were not competitive (??QAICc 53.6685), consistent with the hypothesis that presence of coyotes did not influence diet of swift foxes. Our findings suggest that landscape type may have important influences on diets of both species. We believe that multinomial models represent an effective approach to assess hypotheses when diet studies have a data structure similar to ours. ?? 2010 American Society of Mammalogists.
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Ordinal probability effect measures for group comparisons in multinomial cumulative link models.
Agresti, Alan; Kateri, Maria
2017-03-01
We consider simple ordinal model-based probability effect measures for comparing distributions of two groups, adjusted for explanatory variables. An "ordinal superiority" measure summarizes the probability that an observation from one distribution falls above an independent observation from the other distribution, adjusted for explanatory variables in a model. The measure applies directly to normal linear models and to a normal latent variable model for ordinal response variables. It equals Φ(β/2) for the corresponding ordinal model that applies a probit link function to cumulative multinomial probabilities, for standard normal cdf Φ and effect β that is the coefficient of the group indicator variable. For the more general latent variable model for ordinal responses that corresponds to a linear model with other possible error distributions and corresponding link functions for cumulative multinomial probabilities, the ordinal superiority measure equals exp(β)/[1+exp(β)] with the log-log link and equals approximately exp(β/2)/[1+exp(β/2)] with the logit link, where β is the group effect. Another ordinal superiority measure generalizes the difference of proportions from binary to ordinal responses. We also present related measures directly for ordinal models for the observed response that need not assume corresponding latent response models. We present confidence intervals for the measures and illustrate with an example. © 2016, The International Biometric Society.
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Markov switching multinomial logit model: An application to accident-injury severities.
Malyshkina, Nataliya V; Mannering, Fred L
2009-07-01
In this study, two-state Markov switching multinomial logit models are proposed for statistical modeling of accident-injury severities. These models assume Markov switching over time between two unobserved states of roadway safety as a means of accounting for potential unobserved heterogeneity. The states are distinct in the sense that in different states accident-severity outcomes are generated by separate multinomial logit processes. To demonstrate the applicability of the approach, two-state Markov switching multinomial logit models are estimated for severity outcomes of accidents occurring on Indiana roads over a four-year time period. Bayesian inference methods and Markov Chain Monte Carlo (MCMC) simulations are used for model estimation. The estimated Markov switching models result in a superior statistical fit relative to the standard (single-state) multinomial logit models for a number of roadway classes and accident types. It is found that the more frequent state of roadway safety is correlated with better weather conditions and that the less frequent state is correlated with adverse weather conditions.
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Numeric score-based conditional and overall change-in-status indices for ordered categorical data.
Lyles, Robert H; Kupper, Lawrence L; Barnhart, Huiman X; Martin, Sandra L
2015-11-30
Planned interventions and/or natural conditions often effect change on an ordinal categorical outcome (e.g., symptom severity). In such scenarios, it is sometimes desirable to assign a priori scores to observed changes in status, typically giving higher weight to changes of greater magnitude. We define change indices for such data based upon a multinomial model for each row of a c × c table, where the rows represent the baseline status categories. We distinguish an index designed to assess conditional changes within each baseline category from two others designed to capture overall change. One of these overall indices measures expected change across a target population. The other is scaled to capture the proportion of total possible change in the direction indicated by the data, so that it ranges from -1 (when all subjects finish in the least favorable category) to +1 (when all finish in the most favorable category). The conditional assessment of change can be informative regardless of how subjects are sampled into the baseline categories. In contrast, the overall indices become relevant when subjects are randomly sampled at baseline from the target population of interest, or when the investigator is able to make certain assumptions about the baseline status distribution in that population. We use a Dirichlet-multinomial model to obtain Bayesian credible intervals for the conditional change index that exhibit favorable small-sample frequentist properties. Simulation studies illustrate the methods, and we apply them to examples involving changes in ordinal responses for studies of sleep deprivation and activities of daily living. Copyright © 2015 John Wiley & Sons, Ltd.
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Harrell-Williams, Leigh; Wolfe, Edward W
2014-01-01
Previous research has investigated the influence of sample size, model misspecification, test length, ability distribution offset, and generating model on the likelihood ratio difference test in applications of item response models. This study extended that research to the evaluation of dimensionality using the multidimensional random coefficients multinomial logit model (MRCMLM). Logistic regression analysis of simulated data reveal that sample size and test length have a large effect on the capacity of the LR difference test to correctly identify unidimensionality, with shorter tests and smaller sample sizes leading to smaller Type I error rates. Higher levels of simulated misfit resulted in fewer incorrect decisions than data with no or little misfit. However, Type I error rates indicate that the likelihood ratio difference test is not suitable under any of the simulated conditions for evaluating dimensionality in applications of the MRCMLM.
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Quality and provider choice: a multinomial logit-least-squares model with selectivity.
Haas-Wilson, D; Savoca, E
1990-01-01
A Federal Trade Commission survey of contact lens wearers is used to estimate a multinomial logit-least-squares model of the joint determination of provider choice and quality of care in the contact lens industry. The effect of personal and industry characteristics on a consumer's choice among three types of providers--opticians, ophthalmologists, and optometrists--is estimated via multinomial logit. The regression model of the quality of care has two features that distinguish it from previous work in the area. First, it uses an outcome rather than a structural or process measure of quality. Quality is measured as an index of the presence of seven potentially pathological eye conditions caused by poorly fitted lenses. Second, the model controls for possible selection bias that may arise from the fact that the sample observations on quality are generated by consumers' nonrandom choices of providers. The multinomial logit estimates of provider choice indicate that professional regulations limiting the commercial practices of optometrists shift demand for contact lens services away from optometrists toward ophthalmologists. Further, consumers are more likely to have their lenses fitted by opticians in states that require the licensing of opticians. The regression analysis of variations in quality across provider types shows a strong positive selection bias in the estimate of the quality of care received by consumers of ophthalmologists' services. Failure to control for this selection bias results in an overestimate of the quality of care provided by ophthalmologists. PMID:2312308
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Mollenhauer, Robert; Brewer, Shannon K.
2017-01-01
Failure to account for variable detection across survey conditions constrains progressive stream ecology and can lead to erroneous stream fish management and conservation decisions. In addition to variable detection’s confounding long-term stream fish population trends, reliable abundance estimates across a wide range of survey conditions are fundamental to establishing species–environment relationships. Despite major advancements in accounting for variable detection when surveying animal populations, these approaches remain largely ignored by stream fish scientists, and CPUE remains the most common metric used by researchers and managers. One notable advancement for addressing the challenges of variable detection is the multinomial N-mixture model. Multinomial N-mixture models use a flexible hierarchical framework to model the detection process across sites as a function of covariates; they also accommodate common fisheries survey methods, such as removal and capture–recapture. Effective monitoring of stream-dwelling Smallmouth Bass Micropterus dolomieu populations has long been challenging; therefore, our objective was to examine the use of multinomial N-mixture models to improve the applicability of electrofishing for estimating absolute abundance. We sampled Smallmouth Bass populations by using tow-barge electrofishing across a range of environmental conditions in streams of the Ozark Highlands ecoregion. Using an information-theoretic approach, we identified effort, water clarity, wetted channel width, and water depth as covariates that were related to variable Smallmouth Bass electrofishing detection. Smallmouth Bass abundance estimates derived from our top model consistently agreed with baseline estimates obtained via snorkel surveys. Additionally, confidence intervals from the multinomial N-mixture models were consistently more precise than those of unbiased Petersen capture–recapture estimates due to the dependency among data sets in the hierarchical framework. We demonstrate the application of this contemporary population estimation method to address a longstanding stream fish management issue. We also detail the advantages and trade-offs of hierarchical population estimation methods relative to CPUE and estimation methods that model each site separately.
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Fuzzy multinomial logistic regression analysis: A multi-objective programming approach
NASA Astrophysics Data System (ADS)
Abdalla, Hesham A.; El-Sayed, Amany A.; Hamed, Ramadan
2017-05-01
Parameter estimation for multinomial logistic regression is usually based on maximizing the likelihood function. For large well-balanced datasets, Maximum Likelihood (ML) estimation is a satisfactory approach. Unfortunately, ML can fail completely or at least produce poor results in terms of estimated probabilities and confidence intervals of parameters, specially for small datasets. In this study, a new approach based on fuzzy concepts is proposed to estimate parameters of the multinomial logistic regression. The study assumes that the parameters of multinomial logistic regression are fuzzy. Based on the extension principle stated by Zadeh and Bárdossy's proposition, a multi-objective programming approach is suggested to estimate these fuzzy parameters. A simulation study is used to evaluate the performance of the new approach versus Maximum likelihood (ML) approach. Results show that the new proposed model outperforms ML in cases of small datasets.
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A Comparison of Methods for Detecting Differential Distractor Functioning
ERIC Educational Resources Information Center
Koon, Sharon
2010-01-01
This study examined the effectiveness of the odds-ratio method (Penfield, 2008) and the multinomial logistic regression method (Kato, Moen, & Thurlow, 2009) for measuring differential distractor functioning (DDF) effects in comparison to the standardized distractor analysis approach (Schmitt & Bleistein, 1987). Students classified as participating…
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Classifying emotion in Twitter using Bayesian network
NASA Astrophysics Data System (ADS)
Surya Asriadie, Muhammad; Syahrul Mubarok, Mohamad; Adiwijaya
2018-03-01
Language is used to express not only facts, but also emotions. Emotions are noticeable from behavior up to the social media statuses written by a person. Analysis of emotions in a text is done in a variety of media such as Twitter. This paper studies classification of emotions on twitter using Bayesian network because of its ability to model uncertainty and relationships between features. The result is two models based on Bayesian network which are Full Bayesian Network (FBN) and Bayesian Network with Mood Indicator (BNM). FBN is a massive Bayesian network where each word is treated as a node. The study shows the method used to train FBN is not very effective to create the best model and performs worse compared to Naive Bayes. F1-score for FBN is 53.71%, while for Naive Bayes is 54.07%. BNM is proposed as an alternative method which is based on the improvement of Multinomial Naive Bayes and has much lower computational complexity compared to FBN. Even though it’s not better compared to FBN, the resulting model successfully improves the performance of Multinomial Naive Bayes. F1-Score for Multinomial Naive Bayes model is 51.49%, while for BNM is 52.14%.
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Verbal Ability and Persistent Offending: A Race-Specific Test of Moffitt's Theory
Bellair, Paul E.; McNulty, Thomas L.; Piquero, Alex R.
2014-01-01
Theoretical questions linger over the applicability of the verbal ability model to African Americans and the social control theory hypothesis that educational failure mediates the effect of verbal ability on offending patterns. Accordingly, this paper investigates whether verbal ability distinguishes between offending groups within the context of Moffitt's developmental taxonomy. Questions are addressed with longitudinal data spanning childhood through young-adulthood from an ongoing national panel, and multinomial and hierarchical Poisson models (over-dispersed). In multinomial models, low verbal ability predicts membership in a life-course-persistent-oriented group relative to an adolescent-limited-oriented group. Hierarchical models indicate that verbal ability is associated with arrest outcomes among White and African American subjects, with effects consistently operating through educational attainment (high school dropout). The results support Moffitt's hypothesis that verbal deficits distinguish adolescent-limited- and life-course-persistent-oriented groups within race as well as the social control model of verbal ability. PMID:26924885
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Draine; Greenwald; Banaji
1996-03-01
In the preceding article, Buchner and Wippich used a guessing-corrected, multinomial process-dissociation analysis to test whether a gender bias in fame judgments reported by Banaji and Greenwald (Journal of Personality and Social Psychology, 1995, 68, 181-198) was unconscious. In their two experiments, Buchner and Wippich found no evidence for unconscious mediation of this gender bias. Their conclusion can be questioned by noting that (a) the gender difference in familiarity of previously seen names that Buchner and Wippich modeled was different from the gender difference in criterion for fame judgments reported by Banaji and Greenwald, (b) the assumptions of Buchner and Wippich's multinomial model excluded processes that are plausibly involved in the fame judgment task, and (c) the constructs of Buchner and Wippich's model that corresponded most closely to Banaji and Greenwald's gender-bias interpretation were formulated so as to preclude the possibility of modeling that interpretation. Perhaps a more complex multinomial model can model the Banaji and Greenwald interpretation.
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Draine, S C; Greenwald, A G; Banaji, M R
1996-01-01
In the preceding article, Buchner and Wippich used a guessing-corrected, multinomial process-dissociation analysis to test whether a gender bias in fame judgements reported by Banaji and Greenwald (Journal of Personality and Social Psychology, 1995, 68, 181-198) was unconscious. In their two experiments, Buchner and Wippich found no evidence for unconscious mediation of this gender bias. Their conclusion can be questioned by noting that (a) the gender difference in familiarity of previously seen names that Buchner and Wippich modeled was different from the gender difference in criterion for fame judgements reported by Banaji and Greenwald, (b) the assumptions of Buchner and Wippich's multinomial model excluded processes that are plausibly involved in the fame judgement task, and (c) the constructs of Buchner and Wippich's model that corresponded most closely to Banaji and Greenwald's gender-bias interpretation were formulated so as to preclude the possibility of modeling that interpretation. Perhaps a more complex multinomial model can model the Banaji and Greenwald interpretation.
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Analysis of multinomial models with unknown index using data augmentation
Royle, J. Andrew; Dorazio, R.M.; Link, W.A.
2007-01-01
Multinomial models with unknown index ('sample size') arise in many practical settings. In practice, Bayesian analysis of such models has proved difficult because the dimension of the parameter space is not fixed, being in some cases a function of the unknown index. We describe a data augmentation approach to the analysis of this class of models that provides for a generic and efficient Bayesian implementation. Under this approach, the data are augmented with all-zero detection histories. The resulting augmented dataset is modeled as a zero-inflated version of the complete-data model where an estimable zero-inflation parameter takes the place of the unknown multinomial index. Interestingly, data augmentation can be justified as being equivalent to imposing a discrete uniform prior on the multinomial index. We provide three examples involving estimating the size of an animal population, estimating the number of diabetes cases in a population using the Rasch model, and the motivating example of estimating the number of species in an animal community with latent probabilities of species occurrence and detection.
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NASA Astrophysics Data System (ADS)
Madhu, B.; Ashok, N. C.; Balasubramanian, S.
2014-11-01
Multinomial logistic regression analysis was used to develop statistical model that can predict the probability of breast cancer in Southern Karnataka using the breast cancer occurrence data during 2007-2011. Independent socio-economic variables describing the breast cancer occurrence like age, education, occupation, parity, type of family, health insurance coverage, residential locality and socioeconomic status of each case was obtained. The models were developed as follows: i) Spatial visualization of the Urban- rural distribution of breast cancer cases that were obtained from the Bharat Hospital and Institute of Oncology. ii) Socio-economic risk factors describing the breast cancer occurrences were complied for each case. These data were then analysed using multinomial logistic regression analysis in a SPSS statistical software and relations between the occurrence of breast cancer across the socio-economic status and the influence of other socio-economic variables were evaluated and multinomial logistic regression models were constructed. iii) the model that best predicted the occurrence of breast cancer were identified. This multivariate logistic regression model has been entered into a geographic information system and maps showing the predicted probability of breast cancer occurrence in Southern Karnataka was created. This study demonstrates that Multinomial logistic regression is a valuable tool for developing models that predict the probability of breast cancer Occurrence in Southern Karnataka.
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Past epidemiologic studies suggest maternal ambient air pollution exposure during critical periods of the pregnancy is associated with fetal development. We introduce a multinomial probit model that allows for the joint identification of susceptible daily periods during the pregn...
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Pig Data and Bayesian Inference on Multinomial Probabilities
ERIC Educational Resources Information Center
Kern, John C.
2006-01-01
Bayesian inference on multinomial probabilities is conducted based on data collected from the game Pass the Pigs[R]. Prior information on these probabilities is readily available from the instruction manual, and is easily incorporated in a Dirichlet prior. Posterior analysis of the scoring probabilities quantifies the discrepancy between empirical…
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Ye, Xin; Pendyala, Ram M.; Zou, Yajie
2017-01-01
A semi-nonparametric generalized multinomial logit model, formulated using orthonormal Legendre polynomials to extend the standard Gumbel distribution, is presented in this paper. The resulting semi-nonparametric function can represent a probability density function for a large family of multimodal distributions. The model has a closed-form log-likelihood function that facilitates model estimation. The proposed method is applied to model commute mode choice among four alternatives (auto, transit, bicycle and walk) using travel behavior data from Argau, Switzerland. Comparisons between the multinomial logit model and the proposed semi-nonparametric model show that violations of the standard Gumbel distribution assumption lead to considerable inconsistency in parameter estimates and model inferences. PMID:29073152
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Wang, Ke; Ye, Xin; Pendyala, Ram M; Zou, Yajie
2017-01-01
A semi-nonparametric generalized multinomial logit model, formulated using orthonormal Legendre polynomials to extend the standard Gumbel distribution, is presented in this paper. The resulting semi-nonparametric function can represent a probability density function for a large family of multimodal distributions. The model has a closed-form log-likelihood function that facilitates model estimation. The proposed method is applied to model commute mode choice among four alternatives (auto, transit, bicycle and walk) using travel behavior data from Argau, Switzerland. Comparisons between the multinomial logit model and the proposed semi-nonparametric model show that violations of the standard Gumbel distribution assumption lead to considerable inconsistency in parameter estimates and model inferences.
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A General Family of Limited Information Goodness-of-Fit Statistics for Multinomial Data
ERIC Educational Resources Information Center
Joe, Harry; Maydeu-Olivares, Alberto
2010-01-01
Maydeu-Olivares and Joe (J. Am. Stat. Assoc. 100:1009-1020, "2005"; Psychometrika 71:713-732, "2006") introduced classes of chi-square tests for (sparse) multidimensional multinomial data based on low-order marginal proportions. Our extension provides general conditions under which quadratic forms in linear functions of cell residuals are…
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Hierarchical Multinomial Processing Tree Models: A Latent-Trait Approach
ERIC Educational Resources Information Center
Klauer, Karl Christoph
2010-01-01
Multinomial processing tree models are widely used in many areas of psychology. A hierarchical extension of the model class is proposed, using a multivariate normal distribution of person-level parameters with the mean and covariance matrix to be estimated from the data. The hierarchical model allows one to take variability between persons into…
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Institutional Climate and Student Departure: A Multinomial Multilevel Modeling Approach
ERIC Educational Resources Information Center
Yi, Pyong-sik
2008-01-01
This study applied a multinomial HOLM technique to examine the extent to which the institutional climate for diversity influences the different types of college student withdrawal, such as stop out, drop out, and transfer. Based on a reformulation of Tinto's model along with the conceptualization of institutional climate for diversity by Hurtado…
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ERIC Educational Resources Information Center
Anderson, Carolyn J.; Verkuilen, Jay; Peyton, Buddy L.
2010-01-01
Survey items with multiple response categories and multiple-choice test questions are ubiquitous in psychological and educational research. We illustrate the use of log-multiplicative association (LMA) models that are extensions of the well-known multinomial logistic regression model for multiple dependent outcome variables to reanalyze a set of…
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A Multinomial Model of Event-Based Prospective Memory
ERIC Educational Resources Information Center
Smith, Rebekah E.; Bayen, Ute J.
2004-01-01
Prospective memory is remembering to perform an action in the future. The authors introduce the 1st formal model of event-based prospective memory, namely, a multinomial model that includes 2 separate parameters related to prospective memory processes. The 1st measures preparatory attentional processes, and the 2nd measures retrospective memory…
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Behavioral and Emotional Strengths among Youth in Systems of Care and the Effect of Race/Ethnicity
ERIC Educational Resources Information Center
Barksdale, Crystal L.; Azur, Melissa; Daniels, Amy M.
2010-01-01
Behavioral and emotional strengths are important to consider when understanding youth mental health and treatment. This study examined the association between youth strengths and functional impairment and whether this association is modified by race/ethnicity. Multinomial logistic regression models were used to estimate the effects of strengths on…
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A frequent goal in ecology is to understand the relationships between biological communities and their environment. Anderson and McCardle (2001) provided a nonparametric method, known as Permanova, that is often used for this purpose. Permanova represents a significant advance,...
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Habers, G Esther A; Huber, Adam M; Mamyrova, Gulnara; Targoff, Ira N; O'Hanlon, Terrance P; Adams, Sharon; Pandey, Janardan P; Boonacker, Chantal; van Brussel, Marco; Miller, Frederick W; van Royen-Kerkhof, Annet; Rider, Lisa G
2016-03-01
To identify early factors associated with disease course in patients with juvenile idiopathic inflammatory myopathies (IIMs). Univariable and multivariable multinomial logistic regression analyses were performed in a large juvenile IIM registry (n = 365) and included demographic characteristics, early clinical features, serum muscle enzyme levels, myositis autoantibodies, environmental exposures, and immunogenetic polymorphisms. Multivariable associations with chronic or polycyclic courses compared to a monocyclic course included myositis-specific autoantibodies (multinomial odds ratio [OR] 4.2 and 2.8, respectively), myositis-associated autoantibodies (multinomial OR 4.8 and 3.5), and a documented infection within 6 months of illness onset (multinomial OR 2.5 and 4.7). A higher overall clinical symptom score at diagnosis was associated with chronic or monocyclic courses compared to a polycyclic course. Furthermore, severe illness onset was associated with a chronic course compared to monocyclic or polycyclic courses (multinomial OR 2.1 and 2.6, respectively), while anti-p155/140 autoantibodies were associated with chronic or polycyclic courses compared to a monocyclic course (multinomial OR 3.9 and 2.3, respectively). Additional univariable associations of a chronic course compared to a monocyclic course included photosensitivity, V-sign or shawl sign rashes, and cuticular overgrowth (OR 2.2-3.2). The mean ultraviolet index and highest ultraviolet index in the month before diagnosis were associated with a chronic course compared to a polycyclic course in boys (OR 1.5 and 1.3), while residing in the Northwest was less frequently associated with a chronic course (OR 0.2). Our findings indicate that myositis autoantibodies, in particular anti-p155/140, and a number of early clinical features and environmental exposures are associated with a chronic course in patients with juvenile IIM. These findings suggest that early factors, which are associated with poorer outcomes in juvenile IIM, can be identified. © 2016, American College of Rheumatology.
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A nonparametric multiple imputation approach for missing categorical data.
Zhou, Muhan; He, Yulei; Yu, Mandi; Hsu, Chiu-Hsieh
2017-06-06
Incomplete categorical variables with more than two categories are common in public health data. However, most of the existing missing-data methods do not use the information from nonresponse (missingness) probabilities. We propose a nearest-neighbour multiple imputation approach to impute a missing at random categorical outcome and to estimate the proportion of each category. The donor set for imputation is formed by measuring distances between each missing value with other non-missing values. The distance function is calculated based on a predictive score, which is derived from two working models: one fits a multinomial logistic regression for predicting the missing categorical outcome (the outcome model) and the other fits a logistic regression for predicting missingness probabilities (the missingness model). A weighting scheme is used to accommodate contributions from two working models when generating the predictive score. A missing value is imputed by randomly selecting one of the non-missing values with the smallest distances. We conduct a simulation to evaluate the performance of the proposed method and compare it with several alternative methods. A real-data application is also presented. The simulation study suggests that the proposed method performs well when missingness probabilities are not extreme under some misspecifications of the working models. However, the calibration estimator, which is also based on two working models, can be highly unstable when missingness probabilities for some observations are extremely high. In this scenario, the proposed method produces more stable and better estimates. In addition, proper weights need to be chosen to balance the contributions from the two working models and achieve optimal results for the proposed method. We conclude that the proposed multiple imputation method is a reasonable approach to dealing with missing categorical outcome data with more than two levels for assessing the distribution of the outcome. In terms of the choices for the working models, we suggest a multinomial logistic regression for predicting the missing outcome and a binary logistic regression for predicting the missingness probability.
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The empathy impulse: A multinomial model of intentional and unintentional empathy for pain.
Cameron, C Daryl; Spring, Victoria L; Todd, Andrew R
2017-04-01
Empathy for pain is often described as automatic. Here, we used implicit measurement and multinomial modeling to formally quantify unintentional empathy for pain: empathy that occurs despite intentions to the contrary. We developed the pain identification task (PIT), a sequential priming task wherein participants judge the painfulness of target experiences while trying to avoid the influence of prime experiences. Using multinomial modeling, we distinguished 3 component processes underlying PIT performance: empathy toward target stimuli (Intentional Empathy), empathy toward prime stimuli (Unintentional Empathy), and bias to judge target stimuli as painful (Response Bias). In Experiment 1, imposing a fast (vs. slow) response deadline uniquely reduced Intentional Empathy. In Experiment 2, inducing imagine-self (vs. imagine-other) perspective-taking uniquely increased Unintentional Empathy. In Experiment 3, Intentional and Unintentional Empathy were stronger toward targets with typical (vs. atypical) pain outcomes, suggesting that outcome information matters and that effects on the PIT are not reducible to affective priming. Typicality of pain outcomes more weakly affected task performance when target stimuli were merely categorized rather than judged for painfulness, suggesting that effects on the latter are not reducible to semantic priming. In Experiment 4, Unintentional Empathy was stronger for participants who engaged in costly donation to cancer charities, but this parameter was also high for those who donated to an objectively worse but socially more popular charity, suggesting that overly high empathy may facilitate maladaptive altruism. Theoretical and practical applications of our modeling approach for understanding variation in empathy are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
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Marcelino, José A P; Silva, Luís; Garcia, Patricia V; Weber, Everett; Soares, António O
2013-08-01
The aim of this study was to assess the impact of anthropogenic disturbance on the partitioning of plant communities (species spectra) across a landcover gradient of community types, categorizing species on the basis of their biogeographic, ecological, and conservation status. We tested a multinomial model to generate species spectra and monitor changes in plant assemblages as anthropogenic disturbance rise, as well as the usefulness of this method to assess the conservation value of a given community. Herbaceous and arborescent communities were sampled in five Azorean islands. Margins were also sampled to account for edge effects. Different multinomial models were applied to a data set of 348 plant species accounting for differences in parameter estimates among communities and/or islands. Different levels of anthropogenic disturbance produced measurable changes on species spectra. Introduced species proliferated and indigenous species declined, as anthropogenic disturbance and management intensity increased. Species assemblages of relevance other than economic (i.e., native, endemic, threatened species) were enclosed not only in natural habitats, but also in human managed arborescent habitats, which can positively contribute for the preservation of indigenous species outside remnants of natural areas, depending on management strategies. A significant presence of invasive species in margin transects of most community types will contribute to an increase in edge effect that might facilitate invasion. The multinomial model developed in this study was found to be a novel and expedient tool to characterize the species spectra at a given community and its use could be extrapolated for other assemblages or organisms, in order to evaluate and forecast the conservation value of a site.
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Composite Linear Models | Division of Cancer Prevention
By Stuart G. Baker The composite linear models software is a matrix approach to compute maximum likelihood estimates and asymptotic standard errors for models for incomplete multinomial data. It implements the method described in Baker SG. Composite linear models for incomplete multinomial data. Statistics in Medicine 1994;13:609-622. The software includes a library of thirty
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ERIC Educational Resources Information Center
Smith, Rebekah E.; Bayen, Ute J.
2006-01-01
Event-based prospective memory involves remembering to perform an action in response to a particular future event. Normal younger and older adults performed event-based prospective memory tasks in 2 experiments. The authors applied a formal multinomial processing tree model of prospective memory (Smith & Bayen, 2004) to disentangle age differences…
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Francis, Wendy S; Taylor, Randolph S; Gutiérrez, Marisela; Liaño, Mary K; Manzanera, Diana G; Penalver, Renee M
2018-05-19
Two experiments investigated how well bilinguals utilise long-standing semantic associations to encode and retrieve semantic clusters in verbal episodic memory. In Experiment 1, Spanish-English bilinguals (N = 128) studied and recalled word and picture sets. Word recall was equivalent in L1 and L2, picture recall was better in L1 than in L2, and the picture superiority effect was stronger in L1 than in L2. Semantic clustering in word and picture recall was equivalent in L1 and L2. In Experiment 2, Spanish-English bilinguals (N = 128) and English-speaking monolinguals (N = 128) studied and recalled word sequences that contained semantically related pairs. Data were analyzed using a multinomial processing tree approach, the pair-clustering model. Cluster formation was more likely for semantically organised than for randomly ordered word sequences. Probabilities of cluster formation, cluster retrieval, and retrieval of unclustered items did not differ across languages or language groups. Language proficiency has little if any impact on the utilisation of long-standing semantic associations, which are language-general.
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Emergency Department Use by Nursing Home Residents: Effect of Severity of Cognitive Impairment
ERIC Educational Resources Information Center
Stephens, Caroline E.; Newcomer, Robert; Blegen, Mary; Miller, Bruce; Harrington, Charlene
2012-01-01
Purpose: To examine the 1-year prevalence and risk of emergency department (ED) use and ambulatory care-sensitive (ACS) ED use by nursing home (NH) residents with different levels of severity of cognitive impairment (CI). Design and Methods: We used multinomial logistic regression to estimate the effect of CI severity on the odds of any ED visit…
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ERIC Educational Resources Information Center
Knackstedt, Kimberly M.; Leko, Melinda M.; Siuty, Molly Baustien
2018-01-01
In this study, the authors present findings from a survey of 577 secondary special educators in a large Midwestern state regarding their reading pre-service and in-service teacher preparation and its effect on teachers' sense of preparedness for teaching reading to adolescents with disabilities. Six models were fitted using multinomial logistic…
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Kimani-Murage, Elizabeth W; Kimiywe, Judith; Kabue, Mark; Wekesah, Frederick; Matiri, Evelyn; Muhia, Nelson; Wanjohi, Milka; Muriuki, Peterrock; Samburu, Betty; Kanyuira, James N; Young, Sera L; Griffiths, Paula L; Madise, Nyovani J; McGarvey, Stephen T
2015-09-28
Interventions promoting optimal infant and young child nutrition could prevent a fifth of under-5 deaths in countries with high mortality. Poor infant and young child feeding practices are widely documented in Kenya, with potential detrimental effects on child growth, health and survival. Effective strategies to improve these practices are needed. This study aims to pilot implementation of the Baby Friendly Community Initiative (BFCI), a global initiative aimed at promoting optimal infant and young child feeding practices, to determine its feasibility and effectiveness with regards to infant feeding practices, nutrition and health outcomes in a rural setting in Kenya. The study, employing a cluster-randomized trial design, will be conducted in rural Kenya. A total of 12 clusters, constituting community units within the government's Community Health Strategy, will be randomized, with half allocated to the intervention and the other half to the control arm. A total of 812 pregnant women and their respective children will be recruited into the study. The mother-child pairs will be followed up until the child is 6 months old. Recruitment will last approximately 1 year from January 2015, and the study will run for 3 years, from 2014 to 2016. The intervention will involve regular counseling and support of mothers by trained community health workers and health professionals on maternal, infant and young child nutrition. Regular assessment of knowledge, attitudes and practices on maternal, infant and young child nutrition will be done, coupled with assessment of nutritional status of the mother-child pairs and morbidity for the children. Statistical methods will include analysis of covariance, multinomial logistic regression and multilevel modeling. The study is funded by the NIH and USAID through the Program for Enhanced Research (PEER) Health. Findings from the study outlined in this protocol will inform potential feasibility and effectiveness of a community-based intervention aimed at promoting optimal breastfeeding and other infant feeding practices. The intervention, if proved feasible and effective, will inform policy and practice in Kenya and similar settings, particularly regarding implementation of the baby friendly community initiative. ISRCTN03467700 ; Date of Registration: 24 September 2014.
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Hu, Xisheng; Wu, Zhilong; Wu, Chengzhen; Ye, Limin; Lan, Chaofeng; Tang, Kun; Xu, Lu; Qiu, Rongzu
2016-09-15
Forest cover changes are of global concern due to their roles in global warming and biodiversity. However, many previous studies have ignored the fact that forest loss and forest gain are different processes that may respond to distinct factors by stressing forest loss more than gain or viewing forest cover change as a whole. It behooves us to carefully examine the patterns and drivers of the change by subdividing it into several categories. Our study includes areas of forest loss (4.8% of the study area), forest gain (1.3% of the study area) and forest loss and gain (2.0% of the study area) from 2000 to 2012 in Fujian Province, China. In the study area, approximately 65% and 90% of these changes occurred within 2000m of the nearest road and under road densities of 0.6km/km(2), respectively. We compared two sampling techniques (systematic sampling and random sampling) and four intensities for each technique to investigate the driving patterns underlying the changes using multinomial logistic regression. The results indicated the lack of pronounced differences in the regressions between the two sampling designs, although the sample size had a great impact on the regression outcome. The application of multi-model inference indicated that the low level road density had a negative significant association with forest loss and forest loss and gain, the expressway density had a positive significant impact on forest loss, and the road network was insignificantly related to forest gain. The model including socioeconomic and biophysical variables illuminated potentially different predictors of the different forest change categories. Moreover, the multiple comparisons tested by Fisher's least significant difference (LSD) were a good compensation for the multinomial logistic model to enrich the interpretation of the regression results. Copyright © 2016 Elsevier B.V. All rights reserved.
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University-Industry Linkages in Developing Countries: Perceived Effect on Innovation
ERIC Educational Resources Information Center
Vaaland, Terje I.; Ishengoma, Esther
2016-01-01
Purpose: The purpose of this paper is to assess the perceptions of both universities and the resource-extractive companies on the influence of university-industry linkages (UILs) on innovation in a developing country. Design/Methodology/Approach: A total of 404 respondents were interviewed. Descriptive analysis and multinomial logistic regression…
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Diversity and Educational Benefits: Moving Beyond Self-Reported Questionnaire Data
ERIC Educational Resources Information Center
Herzog, Serge
2007-01-01
Effects of ethnic/racial diversity among students and faculty on cognitive growth of undergraduate students are estimated via a series of hierarchical linear and multinomial logistic regression models. Using objective measures of compositional, curricular, and interactional diversity based on actuarial course enrollment records of over 6,000…
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ERIC Educational Resources Information Center
Boll, Christina; Leppin, Julian Sebastian; Schömann, Klaus
2016-01-01
Overeducation potentially signals a productivity loss. With Socio-Economic Panel data from 1984 to 2011 we identify drivers of educational mismatch for East and West medium and highly educated Germans. Addressing measurement error, state dependence and unobserved heterogeneity, we run dynamic mixed multinomial logit models for three different…
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Prediction of Nursing Workload in Hospital.
Fiebig, Madlen; Hunstein, Dirk; Bartholomeyczik, Sabine
2018-01-01
A dissertation project at the Witten/Herdecke University [1] is investigating which (nursing sensitive) patient characteristics are suitable for predicting a higher or lower degree of nursing workload. For this research project four predictive modelling methods were selected. In a first step, SUPPORT VECTOR MACHINE, RANDOM FOREST, and GRADIENT BOOSTING were used to identify potential predictors from the nursing sensitive patient characteristics. The results were compared via FEATURE IMPORTANCE. To predict nursing workload the predictors identified in step 1 were modelled using MULTINOMIAL LOGISTIC REGRESSION. First results from the data mining process will be presented. A prognostic determination of nursing workload can be used not only as a basis for human resource planning in hospital, but also to respond to health policy issues.
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The status of diabetes control in Kurdistan province, west of Iran.
Esmailnasab, Nader; Afkhamzadeh, Abdorrahim; Roshani, Daem; Moradi, Ghobad
2013-09-17
Based on some estimation more than two million peoples in Iran are affected by Type 2 diabetes. The present study was designed to evaluate the status of diabetes control among Type 2 diabetes patients in Kurdistan, west of Iran and its associated factors. In our cross sectional study conducted in 2010, 411 Type 2 diabetes patients were randomly recruited from Sanandaj, Capital of Kurdistan. Chi square test was used in univariate analysis to address the association between HgAlc and FBS status and other variables. The significant results from Univariate analysis were entered in multivariate analysis and multinomial logistic regression model. In 38% of patients, FBS was in normal range (70-130) and in 47% HgA1c was <7% which is normal range for HgA1c. In univariate analysis, FBS level was associated with educational levels (P=0.001), referral style (P=0.001), referral time (P=0.009), and insulin injection (P=0.016). In addition, HgA1c had a relationship with sex (P=0.023), age (P=0.035), education (P=0.001), referral style (P=0.001), and insulin injection (P=0.008). After using multinomial logistic regression for significant results of univariate analysis, it was found that FBS was significantly associated with referral style. In addition HgA1c was significantly associated with referral style and Insulin injection. Although some of patients were under the coverage of specialized cares, but their diabetes were not properly controlled.
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Fridell, Mats; Hesse, Morten; Jaeger, Mads Meier; Kühlhorn, Eckart
2008-06-01
Mixed findings have been made with regard to the long-term predictive validity of antisocial personality disorder (ASPD) on criminal behaviour in samples of substance abusers. A longitudinal record-linkage study of a cohort of 1052 drug abusers admitted 1977-1995 was undertaken. Subjects were recruited from a detoxification and short-term rehabilitation unit in Lund, Sweden, and followed through criminal justice registers from their first treatment episode to death or to the year 2004. In a ML multinomial random effects regression, subjects diagnosed with antisocial personality disorders were 2.16 times more likely to be charged with theft only (p<0.001), and 2.44 times more likely to be charged committing multiple types of crime during an observation year (p<0.001). The findings of the current study support the predictive validity of the DSM-III-R diagnosis of ASPD. ASPD should be taken seriously in drug abusers, and be targeted in treatment to prevent crime in society.
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Analyzing the severity of accidents on the German Autobahn.
Manner, Hans; Wünsch-Ziegler, Laura
2013-08-01
We study the severity of accidents on the German Autobahn in the state of North Rhine-Westphalia using data for the years 2009 until 2011. We use a multinomial logit model to identify statistically relevant factors explaining the severity of the most severe injury, which is classified into the four classes fatal, severe injury, light injury and property damage. Furthermore, to account for unobserved heterogeneity we use a random parameter model. We study the effect of a number of factors including traffic information, road conditions, type of accidents, speed limits, presence of intelligent traffic control systems, age and gender of the driver and location of the accident. Our findings are in line with studies in different settings and indicate that accidents during daylight and at interchanges or construction sites are less severe in general. Accidents caused by the collision with roadside objects, involving pedestrians and motorcycles, or caused by bad sight conditions tend to be more severe. We discuss the measures of the 2011 German traffic safety programm in the light of our results. Copyright © 2013 Elsevier Ltd. All rights reserved.
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2018-04-01
Reports an error in "The empathy impulse: A multinomial model of intentional and unintentional empathy for pain" by C. Daryl Cameron, Victoria L. Spring and Andrew R. Todd ( Emotion , 2017[Apr], Vol 17[3], 395-411). In this article, there was an error in the calculation of some of the effect sizes. The w effect size was manually computed incorrectly. The incorrect number of total observations was used, which affected the final effect size estimates. This computing error does not change any of the results or interpretations about model fit based on the G² statistic, or about significant differences across conditions in process parameters. Therefore, it does not change any of the hypothesis tests or conclusions. The w statistics for overall model fit should be .02 instead of .04 in Study 1, .01 instead of .02 in Study 2, .01 instead of .03 for the OIT in Study 3 (model fit for the PIT remains the same: .00), and .02 instead of .03 in Study 4. The corrected tables can be seen here: http://osf.io/qebku at the Open Science Framework site for the article. (The following abstract of the original article appeared in record 2017-01641-001.) Empathy for pain is often described as automatic. Here, we used implicit measurement and multinomial modeling to formally quantify unintentional empathy for pain: empathy that occurs despite intentions to the contrary. We developed the pain identification task (PIT), a sequential priming task wherein participants judge the painfulness of target experiences while trying to avoid the influence of prime experiences. Using multinomial modeling, we distinguished 3 component processes underlying PIT performance: empathy toward target stimuli (Intentional Empathy), empathy toward prime stimuli (Unintentional Empathy), and bias to judge target stimuli as painful (Response Bias). In Experiment 1, imposing a fast (vs. slow) response deadline uniquely reduced Intentional Empathy. In Experiment 2, inducing imagine-self (vs. imagine-other) perspective-taking uniquely increased Unintentional Empathy. In Experiment 3, Intentional and Unintentional Empathy were stronger toward targets with typical (vs. atypical) pain outcomes, suggesting that outcome information matters and that effects on the PIT are not reducible to affective priming. Typicality of pain outcomes more weakly affected task performance when target stimuli were merely categorized rather than judged for painfulness, suggesting that effects on the latter are not reducible to semantic priming. In Experiment 4, Unintentional Empathy was stronger for participants who engaged in costly donation to cancer charities, but this parameter was also high for those who donated to an objectively worse but socially more popular charity, suggesting that overly high empathy may facilitate maladaptive altruism. Theoretical and practical applications of our modeling approach for understanding variation in empathy are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
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Pharmacy customers' knowledge of side effects of purchased medicines in Mexico.
Wirtz, Veronika J; Taxis, Katja; Dreser, Anahi
2009-01-01
To analyse pharmacy customers' knowledge and information sources about side effects of medicines they purchased and factors associated with this knowledge. Cross-sectional survey and semi-structured interviews with customers of 52 randomly selected community pharmacies in Morelos state, Mexico. Customers were included if they were older than 18 years, bought at least one drug either with or without medical prescription, and agreed to take part in the survey. Data were analysed using a multinomial logistic regression model. A total of 1445 customers buying 1946 drugs were surveyed (age 42.9 +/- 15.7 years, 56.9% female); 627 (59%) of 1055 customers who purchased prescription-only medicines (POM) did so without a prescription. Of all customers interviewed, 172 (11.9%) affirmed that the bought medicine(s) could cause harm. Only half of those (87 or 6%) were able to identify correctly at least one side effect of the purchased medicines. The majority received the information about side effects from a physician. Customers in semirural areas knew less about side effects (odds ratio: 0.26; 95% CI: 0.11-0.61; P = 0.00); whereas customers buying medicines for chronic pain, hypertension or diabetes knew more (odds ratio 2.63; 95% CI: 1.44-4.80; P = 0.00). The overall majority of customers did not know that medicines they bought could be harmful. This is particularly alarming because they frequently used POM without consulting a physician.
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ERIC Educational Resources Information Center
Dube, Chad; Starns, Jeffrey J.; Rotello, Caren M.; Ratcliff, Roger
2012-01-01
A classic question in the recognition memory literature is whether retrieval is best described as a continuous-evidence process consistent with signal detection theory (SDT), or a threshold process consistent with many multinomial processing tree (MPT) models. Because receiver operating characteristics (ROCs) based on confidence ratings are…
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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…
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A Bayesian Multinomial Probit MODEL FOR THE ANALYSIS OF PANEL CHOICE DATA.
Fong, Duncan K H; Kim, Sunghoon; Chen, Zhe; DeSarbo, Wayne S
2016-03-01
A new Bayesian multinomial probit model is proposed for the analysis of panel choice data. Using a parameter expansion technique, we are able to devise a Markov Chain Monte Carlo algorithm to compute our Bayesian estimates efficiently. We also show that the proposed procedure enables the estimation of individual level coefficients for the single-period multinomial probit model even when the available prior information is vague. We apply our new procedure to consumer purchase data and reanalyze a well-known scanner panel dataset that reveals new substantive insights. In addition, we delineate a number of advantageous features of our proposed procedure over several benchmark models. Finally, through a simulation analysis employing a fractional factorial design, we demonstrate that the results from our proposed model are quite robust with respect to differing factors across various conditions.
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1987-07-01
multinomial distribution as a magazine exposure model. J. of Marketing Research . 21, 100-106. Lehmann, E.L. (1983). Theory of Point Estimation. John Wiley and... Marketing Research . 21, 89-99. V I flWflW WflW~WWMWSS tWN ,rw fl rwwrwwr-w~ w-. ~. - - -- .~ 4’.) ~a 4’ ., . ’-4. .4.: .4~ I .4. ~J3iAf a,’ -a’ 4
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Peng, Yong; Peng, Shuangling; Wang, Xinghua; Tan, Shiyang
2018-06-01
This study aims to identify the effects of characteristics of vehicle, roadway, driver, and environment on fatality of drivers in vehicle-fixed object accidents on expressways in Changsha-Zhuzhou-Xiangtan district of Hunan province in China by developing multinomial logistic regression models. For this purpose, 121 vehicle-fixed object accidents from 2011-2017 are included in the modeling process. First, descriptive statistical analysis is made to understand the main characteristics of the vehicle-fixed object crashes. Then, 19 explanatory variables are selected, and correlation analysis of each two variables is conducted to choose the variables to be concluded. Finally, five multinomial logistic regression models including different independent variables are compared, and the model with best fitting and prediction capability is chosen as the final model. The results showed that the turning direction in avoiding fixed objects raised the possibility that drivers would die. About 64% of drivers died in the accident were found being ejected out of the car, of which 50% did not use a seatbelt before the fatal accidents. Drivers are likely to die when they encounter bad weather on the expressway. Drivers with less than 10 years of driving experience are more likely to die in these accidents. Fatigue or distracted driving is also a significant factor in fatality of drivers. Findings from this research provide an insight into reducing fatality of drivers in vehicle-fixed object accidents.
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Design and analysis of simple choice surveys for natural resource management
Fieberg, John; Cornicelli, Louis; Fulton, David C.; Grund, Marrett D.
2010-01-01
We used a simple yet powerful method for judging public support for management actions from randomized surveys. We asked respondents to rank choices (representing management regulations under consideration) according to their preference, and we then used discrete choice models to estimate probability of choosing among options (conditional on the set of options presented to respondents). Because choices may share similar unmodeled characteristics, the multinomial logit model, commonly applied to discrete choice data, may not be appropriate. We introduced the nested logit model, which offers a simple approach for incorporating correlation among choices. This forced choice survey approach provides a useful method of gathering public input; it is relatively easy to apply in practice, and the data are likely to be more informative than asking constituents to rate attractiveness of each option separately.
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NASA Astrophysics Data System (ADS)
Dokuchaev, P. M.; Meshalkina, J. L.; Yaroslavtsev, A. M.
2018-01-01
Comparative analysis of soils geospatial modeling using multinomial logistic regression, decision trees, random forest, regression trees and support vector machines algorithms was conducted. The visual interpretation of the digital maps obtained and their comparison with the existing map, as well as the quantitative assessment of the individual soil groups detection overall accuracy and of the models kappa showed that multiple logistic regression, support vector method, and random forest models application with spatial prediction of the conditional soil groups distribution can be reliably used for mapping of the study area. It has shown the most accurate detection for sod-podzolics soils (Phaeozems Albic) lightly eroded and moderately eroded soils. In second place, according to the mean overall accuracy of the prediction, there are sod-podzolics soils - non-eroded and warp one, as well as sod-gley soils (Umbrisols Gleyic) and alluvial soils (Fluvisols Dystric, Umbric). Heavy eroded sod-podzolics and gray forest soils (Phaeozems Albic) were detected by methods of automatic classification worst of all.
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Parallel Algorithms for Switching Edges in Heterogeneous Graphs.
Bhuiyan, Hasanuzzaman; Khan, Maleq; Chen, Jiangzhuo; Marathe, Madhav
2017-06-01
An edge switch is an operation on a graph (or network) where two edges are selected randomly and one of their end vertices are swapped with each other. Edge switch operations have important applications in graph theory and network analysis, such as in generating random networks with a given degree sequence, modeling and analyzing dynamic networks, and in studying various dynamic phenomena over a network. The recent growth of real-world networks motivates the need for efficient parallel algorithms. The dependencies among successive edge switch operations and the requirement to keep the graph simple (i.e., no self-loops or parallel edges) as the edges are switched lead to significant challenges in designing a parallel algorithm. Addressing these challenges requires complex synchronization and communication among the processors leading to difficulties in achieving a good speedup by parallelization. In this paper, we present distributed memory parallel algorithms for switching edges in massive networks. These algorithms provide good speedup and scale well to a large number of processors. A harmonic mean speedup of 73.25 is achieved on eight different networks with 1024 processors. One of the steps in our edge switch algorithms requires the computation of multinomial random variables in parallel. This paper presents the first non-trivial parallel algorithm for the problem, achieving a speedup of 925 using 1024 processors.
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Parallel Algorithms for Switching Edges in Heterogeneous Graphs☆
Khan, Maleq; Chen, Jiangzhuo; Marathe, Madhav
2017-01-01
An edge switch is an operation on a graph (or network) where two edges are selected randomly and one of their end vertices are swapped with each other. Edge switch operations have important applications in graph theory and network analysis, such as in generating random networks with a given degree sequence, modeling and analyzing dynamic networks, and in studying various dynamic phenomena over a network. The recent growth of real-world networks motivates the need for efficient parallel algorithms. The dependencies among successive edge switch operations and the requirement to keep the graph simple (i.e., no self-loops or parallel edges) as the edges are switched lead to significant challenges in designing a parallel algorithm. Addressing these challenges requires complex synchronization and communication among the processors leading to difficulties in achieving a good speedup by parallelization. In this paper, we present distributed memory parallel algorithms for switching edges in massive networks. These algorithms provide good speedup and scale well to a large number of processors. A harmonic mean speedup of 73.25 is achieved on eight different networks with 1024 processors. One of the steps in our edge switch algorithms requires the computation of multinomial random variables in parallel. This paper presents the first non-trivial parallel algorithm for the problem, achieving a speedup of 925 using 1024 processors. PMID:28757680
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ERIC Educational Resources Information Center
Matjasko, Jennifer L.
2011-01-01
Based on the stage environment and the person environment fit perspectives, the current study examined the relation between school disciplinary policies and offending from adolescence into young adulthood. Using Waves I and III of the National Longitudinal Study of Adolescent Health (a.k.a., Add Health), hierarchical multinomial logistic…
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ERIC Educational Resources Information Center
Hilbig, Benjamin E.
2012-01-01
Extending the well-established negativity bias in human cognition to truth judgments, it was recently shown that negatively framed statistical statements are more likely to be considered true than formally equivalent statements framed positively. However, the underlying processes responsible for this effect are insufficiently understood.…
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Protein Multiplexed Immunoassay Analysis with R.
Breen, Edmond J
2017-01-01
Plasma samples from 177 control and type 2 diabetes patients collected at three Australian hospitals are screened for 14 analytes using six custom-made multiplex kits across 60 96-well plates. In total 354 samples were collected from the patients, representing one baseline and one end point sample from each patient. R methods and source code for analyzing the analyte fluorescence response obtained from these samples by Luminex Bio-Plex ® xMap multiplexed immunoassay technology are disclosed. Techniques and R procedures for reading Bio-Plex ® result files for statistical analysis and data visualization are also presented. The need for technical replicates and the number of technical replicates are addressed as well as plate layout design strategies. Multinomial regression is used to determine plate to sample covariate balance. Methods for matching clinical covariate information to Bio-Plex ® results and vice versa are given. As well as methods for measuring and inspecting the quality of the fluorescence responses are presented. Both fixed and mixed-effect approaches for immunoassay statistical differential analysis are presented and discussed. A random effect approach to outlier analysis and detection is also shown. The bioinformatics R methodology present here provides a foundation for rigorous and reproducible analysis of the fluorescence response obtained from multiplexed immunoassays.
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ERIC Educational Resources Information Center
Sigfusdottir, Inga-Dora; Silver, Eric
2009-01-01
This study examines the effects of negative life events on anger and depressed mood among a sample of 7,758 Icelandic adolescents, measured as part of the National Survey of Icelandic Adolescents (Thorlindsson, Sigfusdottir, Bernburg, & Halldorsson, 1998). Using multiple linear regression and multinomial logit regression, we find that (a)…
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ERIC Educational Resources Information Center
Toutkoushian, Robert K.; Hossler, Don; DesJardins, Stephen L.; McCall, Brian; Gonzalez Canche, Manuel S.
2015-01-01
Our study adds to prior work on Indiana's Twenty-first Century Scholars(TFCS) program by focusing on whether participating in--rather than completing--the program affects the likelihood of students going to college and where they initially enrolled. We first employ binary and multinomial logistic regression to obtain estimates of the impact of the…
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Sirichotiratana, Nithat; Yogi, Subash; Prutipinyo, Chardsumon
2013-08-30
This study was conducted during February-March 2012 to determine the perception and support regarding smoke-free policy among tourists at Suvarnabhumi International Airport, Bangkok, Thailand. In this cross-sectional study, 200 tourists (n = 200) were enrolled by convenience sampling and interviewed by structured questionnaire. Descriptive statistics, chi-square, and multinomial logistic regression were adopted in the study. Results revealed that half (50%) of the tourists were current smokers and 55% had visited Thailand twice or more. Three quarter (76%) of tourists indicated that they would visit Thailand again even if it had a 100% smoke-free regulation. Almost all (99%) of the tourists had supported for the smoke-free policy (partial ban and total ban), and current smokers had higher percentage of support than non-smokers. Two factors, current smoking status and knowledge level, were significantly associated with perception level. After analysis with Multinomial Logistic Regression, it was found that perception, country group, and presence of designated smoking room (DSR) were associated with smoke-free policy. Recommendation is that, at institution level effective monitoring system is needed at the airport. At policy level, the recommendation is that effective comprehensive policy needed to be emphasized to ensure smoke-free airport environment.
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A Bayesian hierarchical model for discrete choice data in health care.
Antonio, Anna Liza M; Weiss, Robert E; Saigal, Christopher S; Dahan, Ely; Crespi, Catherine M
2017-01-01
In discrete choice experiments, patients are presented with sets of health states described by various attributes and asked to make choices from among them. Discrete choice experiments allow health care researchers to study the preferences of individual patients by eliciting trade-offs between different aspects of health-related quality of life. However, many discrete choice experiments yield data with incomplete ranking information and sparsity due to the limited number of choice sets presented to each patient, making it challenging to estimate patient preferences. Moreover, methods to identify outliers in discrete choice data are lacking. We develop a Bayesian hierarchical random effects rank-ordered multinomial logit model for discrete choice data. Missing ranks are accounted for by marginalizing over all possible permutations of unranked alternatives to estimate individual patient preferences, which are modeled as a function of patient covariates. We provide a Bayesian version of relative attribute importance, and adapt the use of the conditional predictive ordinate to identify outlying choice sets and outlying individuals with unusual preferences compared to the population. The model is applied to data from a study using a discrete choice experiment to estimate individual patient preferences for health states related to prostate cancer treatment.
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[Depression Symptoms of Mothers and Fathers of Persons with Schizophrenia].
Alexandrowicz, Rainer W; König, Daniel; Unger, Annemarie; Klug, Günter; Soulier, Nathalie; Freidl, Marion; Friedrich, Fabian
2016-05-01
The purpose of the present study was to investigate if depression symptomatology of patients' parents is predicted by the symptoms of schizophrenia. 101 mothers and 101 fathers of the same patients suffering from schizophrenia were included into this study. Parents filled in the "Beck Depression Inventory". Patients were assessed by means of the "Positive and Negative Syndrome Scale". For statistical analyses a Multidimensional Random Coefficients Multinomial Logit Model was applied. We found a significant positive association between negative symptoms and depression severity of fathers and mothers. Further, a significant positive association between positive symptoms and depression severity of fathers, but not of mothers was found. Our results show that depression of mothers and of fathers is associated with symptoms of schizophrenia even when controlling for potential predictors. © Georg Thieme Verlag KG Stuttgart · New York.
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Determinants of financial performance of home-visit nursing agencies in Japan.
Fukui, Sakiko; Yoshiuchi, Kazuhiro; Fujita, Junko; Ikezaki, Sumie
2014-01-09
Japan has the highest aging population in the world and promotion of home health services is an urgent policy issue. As home-visit nursing plays a major role in home health services, the Japanese government began promotion of this activity in 1994. However, the scale of home-visit nursing agencies has remained small (the average numbers of nursing staff and other staff were 4.2 and 1.7, respectively, in 2011) and financial performance (profitability) is a concern in such small agencies. Additionally, the factors related to profitability in home-visit nursing agencies in Japan have not been examined multilaterally and in detail. Therefore, the purpose of the study was to examine the determinants of financial performance of home-visit nursing agencies. We performed a nationwide survey of 2,912 randomly selected home-visit nursing agencies in Japan. Multinomial logistic regression was used to clarify the determinants of profitability of the agency (profitable, stable or unprofitable) based on variables related to management of the agency (operating structure, management by a nurse manager, employment, patient utilization, quality control, regional cooperation, and financial condition). Among the selected home-visit nursing agencies, responses suitable for analysis were obtained from 1,340 (effective response rate, 46.0%). Multinomial logistic regression analysis showed that both profitability and unprofitability were related to multiple variables in management of the agency when compared to agencies with stable financial performance. These variables included the number of nursing staff/rehabilitation staff/patients, being owned by a hospital, the number of cooperative hospitals, home-death rate among terminal patients, controlling staff objectives by nurse managers, and income going to compensation. The results suggest that many variables in management of a home-visit nursing agency, including the operating structure of the agency, regional cooperation, staff employment, patient utilization, and quality control of care, have an influence in both profitable and unprofitable agencies. These findings indicate the importance of consideration of management issues in achieving stable financial performance in home-visit nursing agencies in Japan. The findings may also be useful in other countries with growing aging populations.
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Determinants of financial performance of home-visit nursing agencies in Japan
2014-01-01
Background Japan has the highest aging population in the world and promotion of home health services is an urgent policy issue. As home-visit nursing plays a major role in home health services, the Japanese government began promotion of this activity in 1994. However, the scale of home-visit nursing agencies has remained small (the average numbers of nursing staff and other staff were 4.2 and 1.7, respectively, in 2011) and financial performance (profitability) is a concern in such small agencies. Additionally, the factors related to profitability in home-visit nursing agencies in Japan have not been examined multilaterally and in detail. Therefore, the purpose of the study was to examine the determinants of financial performance of home-visit nursing agencies. Methods We performed a nationwide survey of 2,912 randomly selected home-visit nursing agencies in Japan. Multinomial logistic regression was used to clarify the determinants of profitability of the agency (profitable, stable or unprofitable) based on variables related to management of the agency (operating structure, management by a nurse manager, employment, patient utilization, quality control, regional cooperation, and financial condition). Results Among the selected home-visit nursing agencies, responses suitable for analysis were obtained from 1,340 (effective response rate, 46.0%). Multinomial logistic regression analysis showed that both profitability and unprofitability were related to multiple variables in management of the agency when compared to agencies with stable financial performance. These variables included the number of nursing staff/rehabilitation staff/patients, being owned by a hospital, the number of cooperative hospitals, home-death rate among terminal patients, controlling staff objectives by nurse managers, and income going to compensation. Conclusions The results suggest that many variables in management of a home-visit nursing agency, including the operating structure of the agency, regional cooperation, staff employment, patient utilization, and quality control of care, have an influence in both profitable and unprofitable agencies. These findings indicate the importance of consideration of management issues in achieving stable financial performance in home-visit nursing agencies in Japan. The findings may also be useful in other countries with growing aging populations. PMID:24400964
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Jack, Clifford R.; Wiste, Heather J.; Weigand, Stephen D.; Rocca, Walter A.; Knopman, David S.; Mielke, Michelle M.; Lowe, Val J.; Senjem, Matthew L.; Gunter, Jeffrey L.; Preboske, Gregory M.; Pankratz, Vernon S.; Vemuri, Prashanthi; Petersen, Ronald C.
2015-01-01
Summary Background As treatment of pre-clinical Alzheimer's disease (AD) becomes a focus of therapeutic intervention, observational research studies should recognize the overlap between imaging abnormalities associated with typical aging vs those associated with AD. Our objective was to characterize how typical aging and pre-clinical AD blend together with advancing age in terms of neurodegeneration and b-amyloidosis. Methods We measured age-specific frequencies of amyloidosis and neurodegeneration in 985 cognitively normal subjects age 50 to 89 from a population-based study of cognitive aging. Potential participants were randomly selected from the Olmsted County, Minnesota population by age- and sex-stratification and invited to participate in cognitive evaluations and undergo multimodality imaging. To be eligible for inclusion, subjects must have been judged clinically to have no cognitive impairment and have undergone amyloid PET, FDG PET and MRI. Imaging studies were obtained from March 2006 to December 2013. Amyloid positive/negative status (A+/A−) was determined by amyloid PET using Pittsburgh Compound B. Neurodegeneration positive/negative status (N+/N−) was determined by an AD-signature FDG PET measure and/or hippocampal volume on MRI. We labeled subjects positive or negative for neurodegeneration (FDG PET or MRI) or amyloidosis by using cutpoints defined such that 90% of 75 clinically diagnosed AD dementia subjects were categorized as abnormal. APOE genotype was assessed using DNA extracted from blood. Every individual was assigned to one of four groups: A−N−, A+N−, A−N+, or A+N+. Age specific frequencies of the 4 A/N groups were determined cross-sectionally using multinomial regression models. Associations with APOE ε4 and sex effects were evaluated by including these covariates in the multinomial models. Findings The population frequency of A−N− was 100% (n=985) at age 50 and declined thereafter. The frequency of A+N− increased to a maximum of 28% (95% CI, 24%-32%) at age 74 then decreased to 17% (95% CI, 11%-25%) by age 89. A−N+ increased from age 60 onward reaching a frequency of 24% (95% CI, 16%-34%) by age 89. A+N+ increased from age 65 onward reaching a frequency of 42% (95% CI, 31%-52%) by age 89. A+N− and A+N+ were more frequent in APOE ε4 carriers. A+N+ was more, and A+N− less frequent in men. Interpretation Accumulation of A/N imaging abnormalities is nearly inevitable by old age yet people are able to remain cognitively normal despite these abnormalities. . The multinomial models suggest the A/N frequency trends by age are modified by APOE ε4 , which increases risk for amyloidosis, and male sex, which increases risk for neurodegeneration. Changing A/N frequencies with age suggest that individuals may follow different pathophysiological sequences. Funding National Institute on Aging; Alexander Family Professorship of Alzheimer's Disease Research. PMID:25201514
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Multinomial logistic regression in workers' health
NASA Astrophysics Data System (ADS)
Grilo, Luís M.; Grilo, Helena L.; Gonçalves, Sónia P.; Junça, Ana
2017-11-01
In European countries, namely in Portugal, it is common to hear some people mentioning that they are exposed to excessive and continuous psychosocial stressors at work. This is increasing in diverse activity sectors, such as, the Services sector. A representative sample was collected from a Portuguese Services' organization, by applying a survey (internationally validated), which variables were measured in five ordered categories in Likert-type scale. A multinomial logistic regression model is used to estimate the probability of each category of the dependent variable general health perception where, among other independent variables, burnout appear as statistically significant.
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A computer program for estimation from incomplete multinomial data
NASA Technical Reports Server (NTRS)
Credeur, K. R.
1978-01-01
Coding is given for maximum likelihood and Bayesian estimation of the vector p of multinomial cell probabilities from incomplete data. Also included is coding to calculate and approximate elements of the posterior mean and covariance matrices. The program is written in FORTRAN 4 language for the Control Data CYBER 170 series digital computer system with network operating system (NOS) 1.1. The program requires approximately 44000 octal locations of core storage. A typical case requires from 72 seconds to 92 seconds on CYBER 175 depending on the value of the prior parameter.
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Categorical Data Analysis Using a Skewed Weibull Regression Model
NASA Astrophysics Data System (ADS)
Caron, Renault; Sinha, Debajyoti; Dey, Dipak; Polpo, Adriano
2018-03-01
In this paper, we present a Weibull link (skewed) model for categorical response data arising from binomial as well as multinomial model. We show that, for such types of categorical data, the most commonly used models (logit, probit and complementary log-log) can be obtained as limiting cases. We further compare the proposed model with some other asymmetrical models. The Bayesian as well as frequentist estimation procedures for binomial and multinomial data responses are presented in details. The analysis of two data sets to show the efficiency of the proposed model is performed.
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Silvis, Alexander; Ford, W. Mark; Britzke, Eric R.
2015-01-01
Bat day-roost selection often is described through comparisons of day-roosts with randomly selected, and assumed unused, trees. Relatively few studies, however, look at patterns of multi-year selection or compare day-roosts used across years. We explored day-roost selection using 2 years of roost selection data for female northern long-eared bats (Myotis septentrionalis) on the Fort Knox Military Reservation, Kentucky, USA. We compared characteristics of randomly selected non-roost trees and day-roosts using a multinomial logistic model and day-roost species selection using chi-squared tests. We found that factors differentiating day-roosts from non-roosts and day-roosts between years varied. Day-roosts differed from non-roosts in the first year of data in all measured factors, but only in size and decay stage in the second year. Between years, day-roosts differed in size and canopy position, but not decay stage. Day-roost species selection was non-random and did not differ between years. Although bats used multiple trees, our results suggest that there were additional unused trees that were suitable as roosts at any time. Day-roost selection pattern descriptions will be inadequate if based only on a single year of data, and inferences of roost selection based only on comparisons of roost to non-roosts should be limited.
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Silvis, Alexander; Ford, W. Mark; Britzke, Eric R.
2015-01-01
Bat day-roost selection often is described through comparisons of day-roosts with randomly selected, and assumed unused, trees. Relatively few studies, however, look at patterns of multi-year selection or compare day-roosts used across years. We explored day-roost selection using 2 years of roost selection data for female northern long-eared bats (Myotis septentrionalis) on the Fort Knox Military Reservation, Kentucky, USA. We compared characteristics of randomly selected non-roost trees and day-roosts using a multinomial logistic model and day-roost species selection using chi-squared tests. We found that factors differentiating day-roosts from non-roosts and day-roosts between years varied. Day-roosts differed from non-roosts in the first year of data in all measured factors, but only in size and decay stage in the second year. Between years, day-roosts differed in size and canopy position, but not decay stage. Day-roost species selection was non-random and did not differ between years. Although bats used multiple trees, our results suggest that there were additional unused trees that were suitable as roosts at any time. Day-roost selection pattern descriptions will be inadequate if based only on a single year of data, and inferences of roost selection based only on comparisons of roost to non-roosts should be limited.
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Utility-based designs for randomized comparative trials with categorical outcomes
Murray, Thomas A.; Thall, Peter F.; Yuan, Ying
2016-01-01
A general utility-based testing methodology for design and conduct of randomized comparative clinical trials with categorical outcomes is presented. Numerical utilities of all elementary events are elicited to quantify their desirabilities. These numerical values are used to map the categorical outcome probability vector of each treatment to a mean utility, which is used as a one-dimensional criterion for constructing comparative tests. Bayesian tests are presented, including fixed sample and group sequential procedures, assuming Dirichlet-multinomial models for the priors and likelihoods. Guidelines are provided for establishing priors, eliciting utilities, and specifying hypotheses. Efficient posterior computation is discussed, and algorithms are provided for jointly calibrating test cutoffs and sample size to control overall type I error and achieve specified power. Asymptotic approximations for the power curve are used to initialize the algorithms. The methodology is applied to re-design a completed trial that compared two chemotherapy regimens for chronic lymphocytic leukemia, in which an ordinal efficacy outcome was dichotomized and toxicity was ignored to construct the trial’s design. The Bayesian tests also are illustrated by several types of categorical outcomes arising in common clinical settings. Freely available computer software for implementation is provided. PMID:27189672
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Stimulus control and affect in dietary behaviours. An intensive longitudinal study.
Schüz, Benjamin; Bower, Jodie; Ferguson, Stuart G
2015-04-01
Dietary behaviours are substantially influenced by environmental and internal stimuli, such as mood, social situation, and food availability. However, little is known about the role of stimulus control for eating in non-clinical populations, and no studies so far have looked at eating and drinking behaviour simultaneously. 53 individuals from the general population took part in an intensive longitudinal study with repeated, real-time assessments of eating and drinking using Ecological Momentary Assessment. Eating was assessed as main meals and snacks, drinks assessments were separated along alcoholic and non-alcoholic drinks. Situational and internal stimuli were assessed during both eating and drinking events, and during randomly selected non-eating occasions. Hierarchical multinomial logistic random effects models were used to analyse data, comparing dietary events to non-eating occasions. Several situational and affective antecedents of dietary behaviours could be identified. Meals were significantly associated with having food available and observing others eat. Snacking was associated with negative affect, having food available, and observing others eat. Engaging in activities and being with others decreased the likelihood of eating behaviours. Non-alcoholic drinks were associated with observing others eat, and less activities and company. Alcoholic drinks were associated with less negative affect and arousal, and with observing others eat. RESULTS support the role of stimulus control in dietary behaviours, with support for both internal and external, in particular availability and social stimuli. The findings for negative affect support the idea of comfort eating, and results point to the formation of eating habits via cue-behaviour associations. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Milte, Rachel; Ratcliffe, Julie; Chen, Gang; Lancsar, Emily; Miller, Michelle; Crotty, Maria
2014-07-01
This exploratory study sought to investigate the effect of cognitive functioning on the consistency of individual responses to a discrete choice experiment (DCE) study conducted exclusively with older people. A DCE to investigate preferences for multidisciplinary rehabilitation was administered to a consenting sample of older patients (aged 65 years and older) after surgery to repair a fractured hip (N = 84). Conditional logit, mixed logit, heteroscedastic conditional logit, and generalized multinomial logit regression models were used to analyze the DCE data and to explore the relationship between the level of cognitive functioning (specifically the absence or presence of mild cognitive impairment as assessed by the Mini-Mental State Examination) and preference and scale heterogeneity. Both the heteroscedastic conditional logit and generalized multinomial logit models indicated that the presence of mild cognitive impairment did not have a significant effect on the consistency of responses to the DCE. This study provides important preliminary evidence relating to the effect of mild cognitive impairment on DCE responses for older people. It is important that further research be conducted in larger samples and more diverse populations to further substantiate the findings from this exploratory study and to assess the practicality and validity of the DCE approach with populations of older people. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
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Nazem-Zadeh, Mohammad-Reza; Elisevich, Kost V; Schwalb, Jason M; Bagher-Ebadian, Hassan; Mahmoudi, Fariborz; Soltanian-Zadeh, Hamid
2014-12-15
Multiple modalities are used in determining laterality in mesial temporal lobe epilepsy (mTLE). It is unclear how much different imaging modalities should be weighted in decision-making. The purpose of this study is to develop response-driven multimodal multinomial models for lateralization of epileptogenicity in mTLE patients based upon imaging features in order to maximize the accuracy of noninvasive studies. The volumes, means and standard deviations of FLAIR intensity and means of normalized ictal-interictal SPECT intensity of the left and right hippocampi were extracted from preoperative images of a retrospective cohort of 45 mTLE patients with Engel class I surgical outcomes, as well as images of a cohort of 20 control, nonepileptic subjects. Using multinomial logistic function regression, the parameters of various univariate and multivariate models were estimated. Based on the Bayesian model averaging (BMA) theorem, response models were developed as compositions of independent univariate models. A BMA model composed of posterior probabilities of univariate response models of hippocampal volumes, means and standard deviations of FLAIR intensity, and means of SPECT intensity with the estimated weighting coefficients of 0.28, 0.32, 0.09, and 0.31, respectively, as well as a multivariate response model incorporating all mentioned attributes, demonstrated complete reliability by achieving a probability of detection of one with no false alarms to establish proper laterality in all mTLE patients. The proposed multinomial multivariate response-driven model provides a reliable lateralization of mesial temporal epileptogenicity including those patients who require phase II assessment. Copyright © 2014 Elsevier B.V. All rights reserved.
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Rong, Hu; Nianhua, Xie; Jun, Xu; Lianguo, Ruan; Si, Wu; Sheng, Wei; Heng, Guo; Xia, Wang
2017-12-01
We aimed to explore the prevalence of and risk factors for depressive symptoms (DS) among people living with HIV/AIDS (PLWHA) receiving antiretroviral treatment (ART) in Wuhan, Hubei, China. A cross-sectional study evaluating adult PLWHA receiving ART in nine designated clinical hospitals was conducted from October to December 2015. The validated Beck Depression Inventory (BDI) was used to assess DS in eligible participants. Socio-demographical, epidemiological and clinical data were directly extracted from the case reporting database of the China HIV/AIDS Information Network. Multinomial regression analysis was used to explore the risk factors for DS. 394 participants were finally included in all analyses. 40.3% were found to have DS with 13.7% having mild DS and 26.6% having moderate to severe DS. The results of multinomial regression analysis suggested that being married or living with a partner, recent experience of ART-related side effects, and/or history of HCV infection were positively associated with mild DS, while increasing age was positively associated with moderate to severe DS.
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Body mass index and employment status: A new look.
Kinge, Jonas Minet
2016-09-01
Earlier literature has usually modelled the impact of obesity on employment status as a binary choice (employed, yes/no). I provide new evidence on the impact of obesity on employment status by treating the dependent variable as a as a multinomial choice variable. Using data from a representative English survey, with measured height and weight on parents and children, I define employment status as one of four: working; looking for paid work; permanently not working due to disability; and, looking after home or family. I use a multinomial logit model controlling for a set of covariates. I also run instrumental variable models, instrumenting for Body Mass Index (BMI) based on genetic variation in weight. I find that BMI and obesity significantly increase the probability of "not working due to disability". The results for the other employment outcomes are less clear. My findings also indicate that BMI affects employment through its effect on health. Factors other than health may be less important in explaining the impact of BMI/obesity on employment. Copyright © 2016 Elsevier B.V. All rights reserved.
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Mostafa, Kamal S M
2011-04-01
Malnutrition among under-five children is a chronic problem in developing countries. This study explores the socio-economic determinants of severe and moderate stunting among under-five children of rural Bangladesh. The study used data from the 2007 Bangladesh Demographic and Health Survey. Cross-sectional and multinomial logistic regression analyses were used to assess the effect of the socio-demographic variables on moderate and severe stunting over normal among the children. Findings revealed that over two-fifths of the children were stunted, of which 26.3% were moderately stunted and 15.1% were severely stunted. The multivariate multinomial logistic regression analysis yielded significantly increased risk of severe stunting (OR=2.53, 95% CI=1.34-4.79) and moderate stunting (OR=2.37, 95% CI=1.47-3.83) over normal among children with a thinner mother. Region, father's education, toilet facilities, child's age, birth order of children and wealth index were also important determinants of children's nutritional status. Development and poverty alleviation programmes should focus on the disadvantaged rural segments of people to improve their nutritional status.
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Soda intake and tobacco use among young adult bar patrons: A cross-sectional study in seven cities.
Kearns, Cristin E; Lisha, Nadra E; Ling, Pamela M
2018-06-01
Young adults are among the greatest consumers of sugar sweetened beverages, and they also have high smoking rates. However, few studies address the relationship between these risk behaviors; this study examined the relationship between soda consumption and smoking among young adult bar patrons, a high-risk understudied population. A cross-sectional survey of young adult bar patrons (between January 2014 and October 2015) was conducted using randomized time location sampling (N = 8712) in Albuquerque, NM, Los Angeles, CA Nashville, TN, Oklahoma City, OK, San Diego, CA, San Francisco, CA, and Tucson, AZ. The survey found the prevalences of daily regular soda intake ranged from 32% in San Diego to 51% in Oklahoma City and current smoking ranged from 36% in Los Angeles, CA to 49% in Albuquerque, NM. In multinomial multivariate models with no soda consumption as the reference group and controlling for demographics and location, non-daily (OR = 1.24, 95% CI = 1.05, 1.47) and daily smokers (OR = 1.34, 95% CI = 1.08, 1.66) were both more likely to drink regular soda compared to not drinking any soda. No effects were found for diet soda consumption. These linked risks suggest that comprehensive health promotion efforts to decrease sugar sweetened beverage consumption and tobacco use, among other risky behaviors, may be effective in this population.
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An in vitro investigation of pre-treatment effects before fissure sealing.
Bagheri, Mahshid; Pilecki, Peter; Sauro, Salvatore; Sherriff, Martyn; Watson, Timothy F; Hosey, Marie Therese
2017-11-01
Fissure sealants prevent occlusal caries in permanent molars. Enamel preparation methods are used before fissure sealing. To investigate effects of bioglass air-abrasion pre-treatment with and without an adhesive, on fissure enamel of permanent teeth, with respect to etchability, microleakage and microtensile bond strength. Half of the occlusal surfaces of 50 extracted premolars underwent bioglass air-abrasion. Dye was applied to the entire occlusal surface. Photographs were taken to score etched surface by dye uptake. Adhesive was applied to 25 of the bioglass-treated areas and all teeth were fissure sealed, sectioned, and evaluated using confocal microscopy. Buccal and lingual surfaces of a further eight premolars were acid-etched and randomly received: air-abrasion, adhesive, both, or none before sealant application for microtensile bond strength measurement in half of the samples immediately and half following 6 months of water immersion. Linear mixed models and multinomial logistic regression were used (P = 0.05). Bioglass air-abrasion significantly improved enamel etchability and reduced microleakage. The addition of an adhesive made no difference to either microleakage or microtensile bond strength. The combination of bioglass abrasion and adhesive led to more cohesive, rather than adhesive, failure. Bioglass air-abrasion improved enamel etchability and reduced microleakage irrespective of the adhesive use but neither pre-treatment affected the microtensile bond strength. © 2017 BSPD, IAPD and John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
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Mixture Model and MDSDCA for Textual Data
NASA Astrophysics Data System (ADS)
Allouti, Faryel; Nadif, Mohamed; Hoai An, Le Thi; Otjacques, Benoît
E-mailing has become an essential component of cooperation in business. Consequently, the large number of messages manually produced or automatically generated can rapidly cause information overflow for users. Many research projects have examined this issue but surprisingly few have tackled the problem of the files attached to e-mails that, in many cases, contain a substantial part of the semantics of the message. This paper considers this specific topic and focuses on the problem of clustering and visualization of attached files. Relying on the multinomial mixture model, we used the Classification EM algorithm (CEM) to cluster the set of files, and MDSDCA to visualize the obtained classes of documents. Like the Multidimensional Scaling method, the aim of the MDSDCA algorithm based on the Difference of Convex functions is to optimize the stress criterion. As MDSDCA is iterative, we propose an initialization approach to avoid starting with random values. Experiments are investigated using simulations and textual data.
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NASA Astrophysics Data System (ADS)
Nong, Yu; Du, Qingyun; Wang, Kun; Miao, Lei; Zhang, Weiwei
2008-10-01
Urban growth modeling, one of the most important aspects of land use and land cover change study, has attracted substantial attention because it helps to comprehend the mechanisms of land use change thus helps relevant policies made. This study applied multinomial logistic regression to model urban growth in the Jiayu county of Hubei province, China to discover the relationship between urban growth and the driving forces of which biophysical and social-economic factors are selected as independent variables. This type of regression is similar to binary logistic regression, but it is more general because the dependent variable is not restricted to two categories, as those previous studies did. The multinomial one can simulate the process of multiple land use competition between urban land, bare land, cultivated land and orchard land. Taking the land use type of Urban as reference category, parameters could be estimated with odds ratio. A probability map is generated from the model to predict where urban growth will occur as a result of the computation.
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Bivariate categorical data analysis using normal linear conditional multinomial probability model.
Sun, Bingrui; Sutradhar, Brajendra
2015-02-10
Bivariate multinomial data such as the left and right eyes retinopathy status data are analyzed either by using a joint bivariate probability model or by exploiting certain odds ratio-based association models. However, the joint bivariate probability model yields marginal probabilities, which are complicated functions of marginal and association parameters for both variables, and the odds ratio-based association model treats the odds ratios involved in the joint probabilities as 'working' parameters, which are consequently estimated through certain arbitrary 'working' regression models. Also, this later odds ratio-based model does not provide any easy interpretations of the correlations between two categorical variables. On the basis of pre-specified marginal probabilities, in this paper, we develop a bivariate normal type linear conditional multinomial probability model to understand the correlations between two categorical variables. The parameters involved in the model are consistently estimated using the optimal likelihood and generalized quasi-likelihood approaches. The proposed model and the inferences are illustrated through an intensive simulation study as well as an analysis of the well-known Wisconsin Diabetic Retinopathy status data. Copyright © 2014 John Wiley & Sons, Ltd.
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Sirichotiratana, Nithat; Yogi, Subash; Prutipinyo, Chardsumon
2013-01-01
This study was conducted during February-March 2012 to determine the perception and support regarding smoke-free policy among tourists at Suvarnabhumi International Airport, Bangkok, Thailand. In this cross-sectional study, 200 tourists (n = 200) were enrolled by convenience sampling and interviewed by structured questionnaire. Descriptive statistics, chi-square, and multinomial logistic regression were adopted in the study. Results revealed that half (50%) of the tourists were current smokers and 55% had visited Thailand twice or more. Three quarter (76%) of tourists indicated that they would visit Thailand again even if it had a 100% smoke-free regulation. Almost all (99%) of the tourists had supported for the smoke-free policy (partial ban and total ban), and current smokers had higher percentage of support than non-smokers. Two factors, current smoking status and knowledge level, were significantly associated with perception level. After analysis with Multinomial Logistic Regression, it was found that perception, country group, and presence of designated smoking room (DSR) were associated with smoke-free policy. Recommendation is that, at institution level effective monitoring system is needed at the airport. At policy level, the recommendation is that effective comprehensive policy needed to be emphasized to ensure smoke-free airport environment. PMID:23999549
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Ainsworth, Holly F; Unwin, Jennifer; Jamison, Deborah L; Cordell, Heather J
2011-01-01
Many complex genetic effects, including epigenetic effects, may be expected to operate via mechanisms in the inter-uterine environment. A popular design for the investigation of such effects, including effects of parent-of-origin (imprinting), maternal genotype, and maternal-fetal genotype interactions, is to collect DNA from affected offspring and their mothers (case/mother duos) and to compare with an appropriate control sample. An alternative design uses data from cases and both parents (case/parent trios) but does not require controls. In this study, we describe a novel implementation of a multinomial modeling approach that allows the estimation of such genetic effects using either case/mother duos or case/parent trios. We investigate the performance of our approach using computer simulations and explore the sample sizes and data structures required to provide high power for detection of effects and accurate estimation of the relative risks conferred. Through the incorporation of additional assumptions (such as Hardy-Weinberg equilibrium, random mating and known allele frequencies) and/or the incorporation of additional types of control sample (such as unrelated controls, controls and their mothers, or both parents of controls), we show that the (relative risk) parameters of interest are identifiable and well estimated. Nevertheless, parameter interpretation can be complex, as we illustrate by demonstrating the mathematical equivalence between various different parameterizations. Our approach scales up easily to allow the analysis of large-scale genome-wide association data, provided both mothers and affected offspring have been genotyped at all variants of interest. Genet. Epidemiol. 35:19–45, 2011. © 2010 Wiley-Liss, Inc. PMID:21181895
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Andreae, Michael H; Nair, Singh; Gabry, Jonah S; Goodrich, Ben; Hall, Charles; Shaparin, Naum
2017-11-01
We investigated if human reminder phone calls in the patient's preferred language increase adherence with scheduled appointments in an inner-city chronic pain clinic. We hypothesized that language and cultural incongruence is the underlying mechanism to explain poor attendance at clinic appointments in underserved Hispanic populations. Pragmatic randomized controlled clinical trial SETTING: Innercity academic chronic pain clinic with a diverse, predominantly African-American and Hispanic population PATIENTS: All (n=963) adult patients with a scheduled first appointment between October 2014 and October 2015 at the Montefiore Pain Center in the Bronx, New York were enrolled. Patients were randomized to receive a human reminder call in their preferred language before their appointment, or no contact. We recorded patients' demographic characteristics and as primary outcome attendance as scheduled, failure to attend and/or cancellation calls. We fit Bayesian and classical multinomial logistic regression models to test if the intervention improved adherence with scheduled appointments. Among the 953 predominantly African American and Hispanic/Latino patients, 475 patients were randomly selected to receive a language-congruent, human reminder call, while 478 were assigned to receive no prior contact, (after we excluded 10 patients, scheduled for repeat appointments). In the experimental group, 275 patients adhered to their scheduled appointment, while 84 cancelled and 116 failed to attend. In the control group, 249 patients adhered to their scheduled appointment, 31 cancelled and 198 failed to attend. Human phone reminders in the preferred language increased adherence (RR 1.89, CI95% [1.42, 1.42], (p<0.01). The intervention seemed particularly effective in Hispanic patients, supporting our hypothesis of cultural congruence as possible underlying mechanism. Human reminder phone calls prior in the patient's preferred language increased adherence with scheduled appointments. The intervention facilitated access to much needed care in an ethnically diverse, resource poor population, presumably by overcoming language barriers. Copyright © 2017 Elsevier Inc. All rights reserved.
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Soeun Ahn; Joseph E. de Steiguer; Raymond B. Palmquist; Thomas P. Holmes
2000-01-01
Global warming due to the enhanced greenhouse effect through human activities has become a major public policy issue in recent years. The present study focuses on the potential economic impact of climate change on recreational trout fishing in the Southern Appalachian Mountains of North Carolina. Significant reductions in trout habitat and/or populations are...
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Women's Contraceptive Preference-Use Mismatch
He, Katherine; Dalton, Vanessa K.; Zochowski, Melissa K.
2017-01-01
Abstract Background: Family planning research has not adequately addressed women's preferences for different contraceptive methods and whether women's contraceptive experiences match their preferences. Methods: Data were drawn from the Women's Healthcare Experiences and Preferences Study, an Internet survey of 1,078 women aged 18–55 randomly sampled from a national probability panel. Survey items assessed women's preferences for contraceptive methods, match between methods preferred and used, and perceived reasons for mismatch. We estimated predictors of contraceptive preference with multinomial logistic regression models. Results: Among women at risk for pregnancy who responded with their preferred method (n = 363), hormonal methods (non-LARC [long-acting reversible contraception]) were the most preferred method (34%), followed by no method (23%) and LARC (18%). Sociodemographic differences in contraception method preferences were noted (p-values <0.05), generally with minority, married, and older women having higher rates of preferring less effective methods, compared to their counterparts. Thirty-six percent of women reported preference-use mismatch, with the majority preferring more effective methods than those they were using. Rates of match between preferred and usual methods were highest for LARC (76%), hormonal (non-LARC) (65%), and no method (65%). The most common reasons for mismatch were cost/insurance (41%), lack of perceived/actual need (34%), and method-specific preference concerns (19%). Conclusion: While preference for effective contraception was common among this sample of women, we found substantial mismatch between preferred and usual methods, notably among women of lower socioeconomic status and women using less effective methods. Findings may have implications for patient-centered contraceptive interventions. PMID:27710196
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Honey, Garry D; O'loughlin, Chris; Turner, Danielle C; Pomarol-Clotet, Edith; Corlett, Philip R; Fletcher, Paul C
2006-02-01
Ketamine is increasingly used to model the cognitive deficits and symptoms of schizophrenia. We investigated the extent to which ketamine administration in healthy volunteers reproduces the deficits in episodic recognition memory and agency source monitoring reported in schizophrenia. Intravenous infusions of placebo or 100 ng/ml ketamine were administered to 12 healthy volunteers in a double-blind, placebo-controlled, randomized, within-subjects study. In response to presented words, the subject or experimenter performed a deep or shallow encoding task, providing a 2(drug) x 2(depth of processing) x 2(agency) factorial design. At test, subjects discriminated old/new words, and recalled the sources (task and agent). Data were analyzed using multinomial modelling to identify item recognition, source memory for agency and task, and guessing biases. Under ketamine, item recognition and cued recall of deeply encoded items were impaired, replicating previous findings. In contrast to schizophrenia, there was a reduced tendency to externalize agency source guessing biases under ketamine. While the recognition memory deficit observed with ketamine is consistent with previous work and with schizophrenia, the changes in source memory differ from those reported in schizophrenic patients. This difference may account for the pattern of psychopathology induced by ketamine.
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Tarkang, Elvis Enowbeyang
2014-01-01
Since learners in secondary schools fall within the age group hardest hit by HIV/AIDS, it is obvious that these learners might be at high risk of contracting HIV/AIDS. However, little has been explored on the perception of risk of contracting HIV among secondary school learners in Cameroon. This study aimed at examining the perception of risk of contracting HIV among secondary school learners in Mbonge subdivision of rural Cameroon using the Health Belief Model (HBM) as framework. A quantitative, correlational design was adopted, using a self-administered questionnaire to collect data from 210 female learners selected through disproportional, stratified, simple random sampling technique, from three participating senior secondary schools. Statistics were calculated using SPSS version 20 software program. Only 39.4% of the respondents perceived themselves to be at high risk of contracting HIV, though the majority, 54.0% were sexually active. Multinomial logistic regression analyses show that sexual risk behaviours (p=0.000) and the Integrated Value Mapping (IVM) of the perception components of the HBM are the most significant factors associated with perception of risk of contracting HIV at the level p<0.05. The findings of this study can play an instrumental role in the development of effective preventive and interventional messages for adolescents in Cameroon.
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Effects of public premiums on children's health insurance coverage: evidence from 1999 to 2003.
Kenney, Genevieve; Hadley, Jack; Blavin, Fredric
This study uses 2000 to 2004 Current Population Survey data to examine the effects of public premiums on the insurance coverage of children whose family incomes are between 100% and 300% of the federal poverty level. The analysis employs multinomial logistic models that control for factors other than premium costs. While the magnitude of the estimated effects varies across models, the results consistently indicate that raising public premiums reduces enrollment in public programs, with some children who forgo public coverage having private coverage instead and others being uninsured. The results indicate that public premiums have larger effects when applied to lower-income families.
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A measurement theory of illusory conjunctions.
Prinzmetal, William; Ivry, Richard B; Beck, Diane; Shimizu, Naomi
2002-04-01
Illusory conjunctions refer to the incorrect perceptual combination of correctly perceived features, such as color and shape. Research on the phenomenon has been hampered by the lack of a measurement theory that accounts for guessing features, as well as the incorrect combination of correctly perceived features. Recently, several investigators have suggested using multinomial models as a tool for measuring feature integration. The authors examined the adequacy of these models in 2 experiments by testing whether model parameters reflect changes in stimulus factors. In a third experiment, confidence ratings were used as a tool for testing the model. Multinomial models accurately reflected both variations in stimulus factors and observers' trial-by-trial confidence ratings.
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Tian, Xinyu; Wang, Xuefeng; Chen, Jun
2014-01-01
Classic multinomial logit model, commonly used in multiclass regression problem, is restricted to few predictors and does not take into account the relationship among variables. It has limited use for genomic data, where the number of genomic features far exceeds the sample size. Genomic features such as gene expressions are usually related by an underlying biological network. Efficient use of the network information is important to improve classification performance as well as the biological interpretability. We proposed a multinomial logit model that is capable of addressing both the high dimensionality of predictors and the underlying network information. Group lasso was used to induce model sparsity, and a network-constraint was imposed to induce the smoothness of the coefficients with respect to the underlying network structure. To deal with the non-smoothness of the objective function in optimization, we developed a proximal gradient algorithm for efficient computation. The proposed model was compared to models with no prior structure information in both simulations and a problem of cancer subtype prediction with real TCGA (the cancer genome atlas) gene expression data. The network-constrained mode outperformed the traditional ones in both cases.
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Elliston, Katherine G; Ferguson, Stuart G; Schüz, Natalie; Schüz, Benjamin
2017-04-01
Individual eating behavior is a risk factor for obesity and highly dependent on internal and external cues. Many studies also suggest that the food environment (i.e., food outlets) influences eating behavior. This study therefore examines the momentary food environment (at the time of eating) and the role of cues simultaneously in predicting everyday eating behavior in adults with overweight and obesity. Intensive longitudinal study using ecological momentary assessment (EMA) over 14 days in 51 adults with overweight and obesity (average body mass index = 30.77; SD = 4.85) with a total of 745 participant days of data. Multiple daily assessments of eating (meals, high- or low-energy snacks) and randomly timed assessments. Cues and the momentary food environment were assessed during both assessment types. Random effects multinomial logistic regression shows that both internal (affect) and external (food availability, social situation, observing others eat) cues were associated with increased likelihood of eating. The momentary food environment predicted meals and snacking on top of cues, with a higher likelihood of high-energy snacks when fast food restaurants were close by (odds ratio [OR] = 1.89, 95% confidence interval [CI] = 1.22, 2.93) and a higher likelihood of low-energy snacks in proximity to supermarkets (OR = 2.29, 95% CI = 1.38, 3.82). Real-time eating behavior, both in terms of main meals and snacks, is associated with internal and external cues in adults with overweight and obesity. In addition, perceptions of the momentary food environment influence eating choices, emphasizing the importance of an integrated perspective on eating behavior and obesity prevention. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
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Zemp, Roland; Tanadini, Matteo; Plüss, Stefan; Schnüriger, Karin; Singh, Navrag B; Taylor, William R; Lorenzetti, Silvio
2016-01-01
Occupational musculoskeletal disorders, particularly chronic low back pain (LBP), are ubiquitous due to prolonged static sitting or nonergonomic sitting positions. Therefore, the aim of this study was to develop an instrumented chair with force and acceleration sensors to determine the accuracy of automatically identifying the user's sitting position by applying five different machine learning methods (Support Vector Machines, Multinomial Regression, Boosting, Neural Networks, and Random Forest). Forty-one subjects were requested to sit four times in seven different prescribed sitting positions (total 1148 samples). Sixteen force sensor values and the backrest angle were used as the explanatory variables (features) for the classification. The different classification methods were compared by means of a Leave-One-Out cross-validation approach. The best performance was achieved using the Random Forest classification algorithm, producing a mean classification accuracy of 90.9% for subjects with which the algorithm was not familiar. The classification accuracy varied between 81% and 98% for the seven different sitting positions. The present study showed the possibility of accurately classifying different sitting positions by means of the introduced instrumented office chair combined with machine learning analyses. The use of such novel approaches for the accurate assessment of chair usage could offer insights into the relationships between sitting position, sitting behaviour, and the occurrence of musculoskeletal disorders.
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Wu, Qiong; Zhang, Guohui; Ci, Yusheng; Wu, Lina; Tarefder, Rafiqul A; Alcántara, Adélamar Dely
2016-05-18
Teenage drivers are more likely to be involved in severely incapacitating and fatal crashes compared to adult drivers. Moreover, because two thirds of urban vehicle miles traveled are on signal-controlled roadways, significant research efforts are needed to investigate intersection-related teenage driver injury severities and their contributing factors in terms of driver behavior, vehicle-infrastructure interactions, environmental characteristics, roadway geometric features, and traffic compositions. Therefore, this study aims to explore the characteristic differences between teenage and adult drivers in intersection-related crashes, identify the significant contributing attributes, and analyze their impacts on driver injury severities. Using crash data collected in New Mexico from 2010 to 2011, 2 multinomial logit regression models were developed to analyze injury severities for teenage and adult drivers, respectively. Elasticity analyses and transferability tests were conducted to better understand the quantitative impacts of these factors and the teenage driver injury severity model's generality. The results showed that although many of the same contributing factors were found to be significant in the both teenage and adult driver models, certain different attributes must be distinguished to specifically develop effective safety solutions for the 2 driver groups. The research findings are helpful to better understand teenage crash uniqueness and develop cost-effective solutions to reduce intersection-related teenage injury severities and facilitate driver injury mitigation research.
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NASA Astrophysics Data System (ADS)
Snedden, Gregg A.; Steyer, Gregory D.
2013-02-01
Understanding plant community zonation along estuarine stress gradients is critical for effective conservation and restoration of coastal wetland ecosystems. We related the presence of plant community types to estuarine hydrology at 173 sites across coastal Louisiana. Percent relative cover by species was assessed at each site near the end of the growing season in 2008, and hourly water level and salinity were recorded at each site Oct 2007-Sep 2008. Nine plant community types were delineated with k-means clustering, and indicator species were identified for each of the community types with indicator species analysis. An inverse relation between salinity and species diversity was observed. Canonical correspondence analysis (CCA) effectively segregated the sites across ordination space by community type, and indicated that salinity and tidal amplitude were both important drivers of vegetation composition. Multinomial logistic regression (MLR) and Akaike's Information Criterion (AIC) were used to predict the probability of occurrence of the nine vegetation communities as a function of salinity and tidal amplitude, and probability surfaces obtained from the MLR model corroborated the CCA results. The weighted kappa statistic, calculated from the confusion matrix of predicted versus actual community types, was 0.7 and indicated good agreement between observed community types and model predictions. Our results suggest that models based on a few key hydrologic variables can be valuable tools for predicting vegetation community development when restoring and managing coastal wetlands.
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Kawamura, Yoko
2012-01-01
This study examines the relationship between sex-related perceptions and engagement in sexual intercourse among adolescents in Japan who were heavy users of text massaging. Using the data from the 6th National Survey on Youth Sexual Behavior of 548 high school students who heavily use text messaging, multinomial logistic regression analyses on variables constructing sexual norms and gender-role attitudes were conducted to assess the relationship with sexual activity status as the first step. A backward stepwise elimination method of multinomial logistic regression was used as the second step at which variables for each set of two factors were tested, and as the third step at which variables of two factors were simultaneously tested. The study results showed that perceptions were related to engagement in sexual intercourse among adolescents who heavily used text messaging. In particular, those who perceived that sex is an act to be engaged in at an earlier stage of a relationship and that men have a stronger sex drive tended to be sexually active or have experienced sexual intercourse. These findings could be utilized to design more effective sexual health education messages for Japanese adolescents who are at an elevated risk.
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Xu, Yueqing; McNamara, Paul; Wu, Yanfang; Dong, Yue
2013-10-15
Arable land in China has been decreasing as a result of rapid population growth and economic development as well as urban expansion, especially in developed regions around cities where quality farmland quickly disappears. This paper analyzed changes in arable land utilization during 1993-2008 in the Pinggu district, Beijing, China, developed a multinomial logit (MNL) model to determine spatial driving factors influencing arable land-use change, and simulated arable land transition probabilities. Land-use maps, as well as social-economic and geographical data were used in the study. The results indicated that arable land decreased significantly between 1993 and 2008. Lost arable land shifted into orchard, forestland, settlement, and transportation land. Significant differences existed for arable land transitions among different landform areas. Slope, elevation, population density, urbanization rate, distance to settlements, and distance to roadways were strong drivers influencing arable land transition to other uses. The MNL model was proved effective for predicting transition probabilities in land use from arable land to other land-use types, thus can be used for scenario analysis to develop land-use policies and land-management measures in this metropolitan area. Copyright © 2013 Elsevier Ltd. All rights reserved.
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Thorn, Annabel S C; Gathercole, Susan E; Frankish, Clive R
2005-03-01
The impact of four long-term knowledge variables on serial recall accuracy was investigated. Serial recall was tested for high and low frequency words and high and low phonotactic frequency nonwords in 2 groups: monolingual English speakers and French-English bilinguals. For both groups the recall advantage for words over nonwords reflected more fully correct recalls with fewer recall attempts that consisted of fragments of the target memory items (one or two of the three target phonemes recalled correctly); completely incorrect recalls were equivalent for the 2 list types. However, word frequency (for both groups), nonword phonotactic frequency (for the monolingual group), and language familiarity all influenced the proportions of completely incorrect recalls that were made. These results are not consistent with the view that long-term knowledge influences on immediate recall accuracy can be exclusively attributed to a redintegration process of the type specified in multinomial processing tree model of immediate recall. The finding of a differential influence on completely incorrect recalls of these four long-term knowledge variables suggests instead that the beneficial effects of long-term knowledge on short-term recall accuracy are mediated by more than one mechanism.
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The development of response surface pathway design to reduce animal numbers in toxicity studies
2014-01-01
Background This study describes the development of Response Surface Pathway (RSP) design, assesses its performance and effectiveness in estimating LD50, and compares RSP with Up and Down Procedures (UDPs) and Random Walk (RW) design. Methods A basic 4-level RSP design was used on 36 male ICR mice given intraperitoneal doses of Yessotoxin. Simulations were performed to optimise the design. A k-adjustment factor was introduced to ensure coverage of the dose window and calculate the dose steps. Instead of using equal numbers of mice on all levels, the number of mice was increased at each design level. Additionally, the binomial outcome variable was changed to multinomial. The performance of the RSP designs and a comparison of UDPs and RW were assessed by simulations. The optimised 4-level RSP design was used on 24 female NMRI mice given Azaspiracid-1 intraperitoneally. Results The in vivo experiment with basic 4-level RSP design estimated the LD50 of Yessotoxin to be 463 μg/kgBW (95% CI: 383–535). By inclusion of the k-adjustment factor with equal or increasing numbers of mice on increasing dose levels, the estimate changed to 481 μg/kgBW (95% CI: 362–566) and 447 μg/kgBW (95% CI: 378–504 μg/kgBW), respectively. The optimised 4-level RSP estimated the LD50 to be 473 μg/kgBW (95% CI: 442–517). A similar increase in power was demonstrated using the optimised RSP design on real Azaspiracid-1 data. The simulations showed that the inclusion of the k-adjustment factor, reduction in sample size by increasing the number of mice on higher design levels and incorporation of a multinomial outcome gave estimates of the LD50 that were as good as those with the basic RSP design. Furthermore, optimised RSP design performed on just three levels reduced the number of animals from 36 to 15 without loss of information, when compared with the 4-level designs. Simulated comparison of the RSP design with UDPs and RW design demonstrated the superiority of RSP. Conclusion Optimised RSP design reduces the number of animals needed. The design converges rapidly on the area of interest and is at least as efficient as both the UDPs and RW design. PMID:24661560
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Sørensen, Sabrina Storgaard; Jensen, Morten Berg; Pedersen, Kjeld Møller; Ehlers, Lars
2018-02-01
To examine the heterogeneity in cost-effectiveness analyses of patient-tailored complex interventions. Latent class analysis (LCA) was performed on data from a randomized controlled trial evaluating a patient-tailored case management strategy for patients suffering from chronic obstructive pulmonary disease (COPD). LCA was conducted on detailed process variables representing service variation in the intervention group. Features of the identified latent classes were compared for consistency with baseline demographic, clinical, and economic characteristics for each class. Classes for the control group, corresponding to the identified latent classes for the intervention group, were identified using multinomial logistic regression. Cost-utility analyses were then conducted at the class level, and uncertainty surrounding the point estimates was assessed by probabilistic sensitivity analysis. The LCA identified three distinct classes: the psychologically care class, the extensive COPD care class, and the limited COPD care class. Patient baseline characteristics were in line with the features identified in the LCA. Evaluation of cost-effectiveness revealed highly disparate results, and case management for only the extensive COPD care class appeared cost-effective with an incremental cost-effectiveness ratio of £26,986 per quality-adjusted life-year gained using the threshold value set by the National Institute of Health and Care Excellence. Findings indicate that researchers evaluating patient-tailored complex interventions need to address both supply-side variation and demand-side heterogeneity to link findings with outcome. The article specifically proposes the use of LCA because it is believed to have the potential to enable more appropriate targeting of complex care strategies. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
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Li, Jie; Huang, Yuan-Guang; Ran, Mao-Sheng; Fan, Yu; Chen, Wen; Evans-Lacko, Sara; Thornicroft, Graham
2018-04-01
Comprehensive interventions including components of stigma and discrimination reduction in schizophrenia in low- and middle-income countries (LMICs) are lacking. We developed a community-based comprehensive intervention to evaluate its effects on clinical symptoms, social functioning, internalized stigma and discrimination among patients with schizophrenia. A randomized controlled trial including an intervention group (n = 169) and a control group (n = 158) was performed. The intervention group received comprehensive intervention (strategies against stigma and discrimination, psycho-education, social skills training and cognitive behavioral therapy) and the control group received face to face interview. Both lasted for nine months. Participants were measured at baseline, 6 months and 9 months using the Internalized Stigma of Mental Illness scale (ISMI), Discrimination and Stigma Scale (DISC-12), Global Assessment of Functioning (GAF), Schizophrenia Quality of Life Scale (SQLS), Self-Esteem Scale (SES), Brief Psychiatric Rating Scale (BPRS) and PANSS negative scale (PANSS-N). Insight and medication compliance were evaluated by senior psychiatrists. Data were analyzed by descriptive statistics, t-test, chi-square test or Fisher's exact test. Linear Mixed Models were used to show intervention effectiveness on scales. General Linear Mixed Models with multinomial logistic link function were used to assess the effectiveness on medication compliance and insight. We found a significant reduction on anticipated discrimination, BPRS and PANSS-N total scores, and an elevation on overcoming stigma and GAF in the intervention group after 9 months. These suggested the intervention may be effective in reducing anticipated discrimination, increasing skills overcoming stigma as well as improving clinical symptoms and social functioning in Chinese patients with schizophrenia. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
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Khosravi, Ahmad; Mohammadpoorasl, Asghar; Holakouie-Naieni, Kourosh; Mahmoodi, Mahmood; Pouyan, Ali Akbar; Mansournia, Mohammad Ali
2016-12-01
Identification of the causal impact of self-esteem on smoking stages faces seemingly insurmountable problems in observational data, where self-esteem is not manipulable by the researcher and cannot be assigned randomly. The aim of this study was to find out if weaker self-esteem in adolescence is a risk factor of cigarette smoking in a longitudinal study in Iran. In this longitudinal study, 4,853 students (14-18 years) completed a self-administered multiple-choice anonym questionnaire. The students were evaluated twice, 12 months apart. Students were matched based on coarsened exact matching on pretreatment variables, including age, gender, smoking stages at the first wave of study, socioeconomic status, general risk-taking behavior, having a smoker in the family, having a smoker friend, attitude toward smoking, and self-injury, to ensure statistically equivalent comparison groups. Self-esteem was measured using the Rosenberg 10-item questionnaire and were classified using a latent class analysis. After matching, the effect of self-esteem was evaluated using a multinomial logistic model. In the causal fitted model, for adolescents with weaker self-esteem relative to those with stronger self-esteem, the relative risk for experimenters and regular smokers relative to nonsmokers would be expected to increase by a factor of 2.2 (1.9-2.6) and 2.0 (1.5-2.6), respectively. Using a causal approach, our study indicates that low self-esteem is consistently associated with progression in cigarette smoking stages.
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Blake, Khandis R; Dixson, Barnaby J W; O'Dean, Siobhan M; Denson, Thomas F
2017-04-01
Several studies report that wearing red clothing enhances women's attractiveness and signals sexual proceptivity to men. The associated hypothesis that women will choose to wear red clothing when fertility is highest, however, has received mixed support from empirical studies. One possible cause of these mixed findings may be methodological. The current study aimed to replicate recent findings suggesting a positive association between hormonal profiles associated with high fertility (high estradiol to progesterone ratios) and the likelihood of wearing red. We compared the effect of the estradiol to progesterone ratio on the probability of wearing: red versus non-red (binary logistic regression); red versus neutral, black, blue, green, orange, multi-color, and gray (multinomial logistic regression); and each of these same colors in separate binary models (e.g., green versus non-green). Red versus non-red analyses showed a positive trend between a high estradiol to progesterone ratio and wearing red, but the effect only arose for younger women and was not robust across samples. We found no compelling evidence for ovarian hormones increasing the probability of wearing red in the other analyses. However, we did find that the probability of wearing neutral was positively associated with the estradiol to progesterone ratio, though the effect did not reach conventional levels of statistical significance. Findings suggest that although ovarian hormones may affect younger women's preference for red clothing under some conditions, the effect is not robust when differentiating amongst other colors of clothing. In addition, the effect of ovarian hormones on clothing color preference may not be specific to the color red. Copyright © 2017 Elsevier Inc. All rights reserved.
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The Effect of Task Duration on Event-Based Prospective Memory: A Multinomial Modeling Approach
Zhang, Hongxia; Tang, Weihai; Liu, Xiping
2017-01-01
Remembering to perform an action when a specific event occurs is referred to as Event-Based Prospective Memory (EBPM). This study investigated how EBPM performance is affected by task duration by having university students (n = 223) perform an EBPM task that was embedded within an ongoing computer-based color-matching task. For this experiment, we separated the overall task’s duration into the filler task duration and the ongoing task duration. The filler task duration is the length of time between the intention and the beginning of the ongoing task, and the ongoing task duration is the length of time between the beginning of the ongoing task and the appearance of the first Prospective Memory (PM) cue. The filler task duration and ongoing task duration were further divided into three levels: 3, 6, and 9 min. Two factors were then orthogonally manipulated between-subjects using a multinomial processing tree model to separate the effects of different task durations on the two EBPM components. A mediation model was then created to verify whether task duration influences EBPM via self-reminding or discrimination. The results reveal three points. (1) Lengthening the duration of ongoing tasks had a negative effect on EBPM performance while lengthening the duration of the filler task had no significant effect on it. (2) As the filler task was lengthened, both the prospective and retrospective components show a decreasing and then increasing trend. Also, when the ongoing task duration was lengthened, the prospective component decreased while the retrospective component significantly increased. (3) The mediating effect of discrimination between the task duration and EBPM performance was significant. We concluded that different task durations influence EBPM performance through different components with discrimination being the mediator between task duration and EBPM performance. PMID:29163277
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A simplified conjoint recognition paradigm for the measurement of gist and verbatim memory.
Stahl, Christoph; Klauer, Karl Christoph
2008-05-01
The distinction between verbatim and gist memory traces has furthered the understanding of numerous phenomena in various fields, such as false memory research, research on reasoning and decision making, and cognitive development. To measure verbatim and gist memory empirically, an experimental paradigm and multinomial measurement model has been proposed but rarely applied. In the present article, a simplified conjoint recognition paradigm and multinomial model is introduced and validated as a measurement tool for the separate assessment of verbatim and gist memory processes. A Bayesian metacognitive framework is applied to validate guessing processes. Extensions of the model toward incorporating the processes of phantom recollection and erroneous recollection rejection are discussed.
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optBINS: Optimal Binning for histograms
NASA Astrophysics Data System (ADS)
Knuth, Kevin H.
2018-03-01
optBINS (optimal binning) determines the optimal number of bins in a uniform bin-width histogram by deriving the posterior probability for the number of bins in a piecewise-constant density model after assigning a multinomial likelihood and a non-informative prior. The maximum of the posterior probability occurs at a point where the prior probability and the the joint likelihood are balanced. The interplay between these opposing factors effectively implements Occam's razor by selecting the most simple model that best describes the data.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd
Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test ofmore » the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake.« less
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NASA Astrophysics Data System (ADS)
Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd; Baharum, Adam
2015-10-01
Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test of the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake.
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Uncovering a latent multinomial: Analysis of mark-recapture data with misidentification
Link, W.A.; Yoshizaki, J.; Bailey, L.L.; Pollock, K.H.
2010-01-01
Natural tags based on DNA fingerprints or natural features of animals are now becoming very widely used in wildlife population biology. However, classic capture-recapture models do not allow for misidentification of animals which is a potentially very serious problem with natural tags. Statistical analysis of misidentification processes is extremely difficult using traditional likelihood methods but is easily handled using Bayesian methods. We present a general framework for Bayesian analysis of categorical data arising from a latent multinomial distribution. Although our work is motivated by a specific model for misidentification in closed population capture-recapture analyses, with crucial assumptions which may not always be appropriate, the methods we develop extend naturally to a variety of other models with similar structure. Suppose that observed frequencies f are a known linear transformation f = A???x of a latent multinomial variable x with cell probability vector ?? = ??(??). Given that full conditional distributions [?? | x] can be sampled, implementation of Gibbs sampling requires only that we can sample from the full conditional distribution [x | f, ??], which is made possible by knowledge of the null space of A???. We illustrate the approach using two data sets with individual misidentification, one simulated, the other summarizing recapture data for salamanders based on natural marks. ?? 2009, The International Biometric Society.
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Uncovering a Latent Multinomial: Analysis of Mark-Recapture Data with Misidentification
Link, W.A.; Yoshizaki, J.; Bailey, L.L.; Pollock, K.H.
2009-01-01
Natural tags based on DNA fingerprints or natural features of animals are now becoming very widely used in wildlife population biology. However, classic capture-recapture models do not allow for misidentification of animals which is a potentially very serious problem with natural tags. Statistical analysis of misidentification processes is extremely difficult using traditional likelihood methods but is easily handled using Bayesian methods. We present a general framework for Bayesian analysis of categorical data arising from a latent multinomial distribution. Although our work is motivated by a specific model for misidentification in closed population capture-recapture analyses, with crucial assumptions which may not always be appropriate, the methods we develop extend naturally to a variety of other models with similar structure. Suppose that observed frequencies f are a known linear transformation f=A'x of a latent multinomial variable x with cell probability vector pi= pi(theta). Given that full conditional distributions [theta | x] can be sampled, implementation of Gibbs sampling requires only that we can sample from the full conditional distribution [x | f, theta], which is made possible by knowledge of the null space of A'. We illustrate the approach using two data sets with individual misidentification, one simulated, the other summarizing recapture data for salamanders based on natural marks.
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Allelic variation contributes to bacterial host specificity
Yue, Min; Han, Xiangan; Masi, Leon De; ...
2015-10-30
Understanding the molecular parameters that regulate cross-species transmission and host adaptation of potential pathogens is crucial to control emerging infectious disease. Although microbial pathotype diversity is conventionally associated with gene gain or loss, the role of pathoadaptive nonsynonymous single-nucleotide polymorphisms (nsSNPs) has not been systematically evaluated. Here, our genome-wide analysis of core genes within Salmonella enterica serovar Typhimurium genomes reveals a high degree of allelic variation in surface-exposed molecules, including adhesins that promote host colonization. Subsequent multinomial logistic regression, MultiPhen and Random Forest analyses of known/suspected adhesins from 580 independent Typhimurium isolates identifies distinct host-specific nsSNP signatures. Moreover, population andmore » functional analyses of host-associated nsSNPs for FimH, the type 1 fimbrial adhesin, highlights the role of key allelic residues in host-specific adherence in vitro. In conclusion, together, our data provide the first concrete evidence that functional differences between allelic variants of bacterial proteins likely contribute to pathoadaption to diverse hosts.« less
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Foot placement during error and pedal applications in naturalistic driving.
Wu, Yuqing; Boyle, Linda Ng; McGehee, Daniel; Roe, Cheryl A; Ebe, Kazutoshi; Foley, James
2017-02-01
Data from a naturalistic driving study was used to examine foot placement during routine foot pedal movements and possible pedal misapplications. The study included four weeks of observations from 30 drivers, where pedal responses were recorded and categorized. The foot movements associated with pedal misapplications and errors were the focus of the analyses. A random forest algorithm was used to predict the pedal application types based the video observations, foot placements, drivers' characteristics, drivers' cognitive function levels and anthropometric measurements. A repeated multinomial logit model was then used to estimate the likelihood of the foot placement given various driver characteristics and driving scenarios. The findings showed that prior foot location, the drivers' seat position, and the drive sequence were all associated with incorrect foot placement during an event. The study showed that there is a potential to develop a driver assistance system that can reduce the likelihood of a pedal error. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Yeh, C-Y; Schafferer, C; Lee, J-M; Hsieh, C-J
2016-07-01
This study examines the impact on smokers' behaviour of a planned increase in the Health and Welfare Surcharge of Tobacco Products in Taiwan. This study used a structured questionnaire to perform telephone interviews. Stratified random sampling was applied to interview current smokers aged 18-65 years in Taiwan. Based on nationwide survey data of smokers' responses to future increases in cigarette prices, this study used multinomial logistic regression to perform its analyses. After the proposed increase in the Health and Welfare Surcharge of Tobacco Products, subsequent cigarette price increases would motivate nearly 30% of the smokers to adopt smoking-related changes and 10% to change to lower-priced brands. The study suggests that a large increase in the Health and Welfare Surcharge of Tobacco Products would lead to considerable changes in smoking behaviour, which in turn would increase cessation rate at the population level. Copyright © 2016 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.
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Li, Haitao; Sun, Ying; Qian, Dongfu
2016-11-30
Policy makers require information regarding performance of different primary care delivery models in managing hypertension, which can be helpful for better hypertension management. This study aims to compare continuity of care among hypertensive patients between Direct Management (DM) Model of community health centers (CHCs) in Wuhan and Loose Collaboration (LC) Model in Nanjing. A cross-sectional questionnaire survey was conducted. Four CHCs in each city were randomly selected as study settings. 386 patients in Nanjing and 396 in Wuhan completed face-to-face interview surveys and were included in the final analysis. The relational continuity and coordination continuity (including both information continuity and management continuity) were measured and analyzed. Binary or multinomial logistic regression models were used for comparison between the two cities. Participants from Nanjing had better relational continuity with primary care providers as compared with those from Wuhan, including more likely to be familiar with a CHC physician (OR = 2.762; 95%CI: 1.878 to 4.061), taken care of by the same CHC physician (OR = 1.846; 95%CI: 1.262 to 2.700), and known well by a CHC physician (OR = 1.762; 95%CI: 1.206 to 2.572). Multinomial logistic regression analyses showed there were significant differences between the two cities in reported frequency of communications between hospital and CHC physicians (P = 0.001), whether hospital and CHC physicians gave same treatment suggestions (P = 0.016), as well as how treatment strategy was formulated (P < 0.001). Participants in Wuhan were less likely than those in Nanjing to consider there was continuum regarding health services provided by hospital and CHC physicians (OR = 3.932; 95%CI: 2.394 to 6.459). Our study shows that continuity of care is better for LC Model in Nanjing than DM Model in Wuhan. Our study suggests there is room for improvement regarding relational and information continuity in both cities.
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A site specific model and analysis of the neutral somatic mutation rate in whole-genome cancer data.
Bertl, Johanna; Guo, Qianyun; Juul, Malene; Besenbacher, Søren; Nielsen, Morten Muhlig; Hornshøj, Henrik; Pedersen, Jakob Skou; Hobolth, Asger
2018-04-19
Detailed modelling of the neutral mutational process in cancer cells is crucial for identifying driver mutations and understanding the mutational mechanisms that act during cancer development. The neutral mutational process is very complex: whole-genome analyses have revealed that the mutation rate differs between cancer types, between patients and along the genome depending on the genetic and epigenetic context. Therefore, methods that predict the number of different types of mutations in regions or specific genomic elements must consider local genomic explanatory variables. A major drawback of most methods is the need to average the explanatory variables across the entire region or genomic element. This procedure is particularly problematic if the explanatory variable varies dramatically in the element under consideration. To take into account the fine scale of the explanatory variables, we model the probabilities of different types of mutations for each position in the genome by multinomial logistic regression. We analyse 505 cancer genomes from 14 different cancer types and compare the performance in predicting mutation rate for both regional based models and site-specific models. We show that for 1000 randomly selected genomic positions, the site-specific model predicts the mutation rate much better than regional based models. We use a forward selection procedure to identify the most important explanatory variables. The procedure identifies site-specific conservation (phyloP), replication timing, and expression level as the best predictors for the mutation rate. Finally, our model confirms and quantifies certain well-known mutational signatures. We find that our site-specific multinomial regression model outperforms the regional based models. The possibility of including genomic variables on different scales and patient specific variables makes it a versatile framework for studying different mutational mechanisms. Our model can serve as the neutral null model for the mutational process; regions that deviate from the null model are candidates for elements that drive cancer development.
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Multinomial Bayesian learning for modeling classical and nonclassical receptive field properties.
Hosoya, Haruo
2012-08-01
We study the interplay of Bayesian inference and natural image learning in a hierarchical vision system, in relation to the response properties of early visual cortex. We particularly focus on a Bayesian network with multinomial variables that can represent discrete feature spaces similar to hypercolumns combining minicolumns, enforce sparsity of activation to learn efficient representations, and explain divisive normalization. We demonstrate that maximal-likelihood learning using sampling-based Bayesian inference gives rise to classical receptive field properties similar to V1 simple cells and V2 cells, while inference performed on the trained network yields nonclassical context-dependent response properties such as cross-orientation suppression and filling in. Comparison with known physiological properties reveals some qualitative and quantitative similarities.
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Disentangling stereotype activation and stereotype application in the stereotype misperception task.
Krieglmeyer, Regina; Sherman, Jeffrey W
2012-08-01
When forming impressions about other people, stereotypes about the individual's social group often influence the resulting impression. At least 2 distinguishable processes underlie stereotypic impression formation: stereotype activation and stereotype application. Most previous research has used implicit measures to assess stereotype activation and explicit measures to assess stereotype application, which has several disadvantages. The authors propose a measure of stereotypic impression formation, the stereotype misperception task (SMT), together with a multinomial model that quantitatively disentangles the contributions of stereotype activation and application to responses in the SMT. The validity of the SMT and of the multinomial model was confirmed in 5 studies. The authors hope to advance research on stereotyping by providing a measurement tool that separates multiple processes underlying impression formation.
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Johnson, Kjell; Guo, Cen; Gosink, Mark; Wang, Vicky; Hauben, Manfred
2012-12-01
A principal objective of pharmacovigilance is to detect adverse drug reactions that are unknown or novel in terms of their clinical severity or frequency. One method is through inspection of spontaneous reporting system databases, which consist of millions of reports of patients experiencing adverse effects while taking one or more drugs. For such large databases, there is an increasing need for quantitative and automated screening tools to assist drug safety professionals in identifying drug-event combinations (DECs) worthy of further investigation. Existing algorithms can effectively identify problematic DECs when the frequencies are high. However these algorithms perform differently for low-frequency DECs. In this work, we provide a method based on the multinomial distribution that identifies signals of disproportionate reporting, especially for low-frequency combinations. In addition, we comprehensively compare the performance of commonly used algorithms with the new approach. Simulation results demonstrate the advantages of the proposed method, and analysis of the Adverse Event Reporting System data shows that the proposed method can help detect interesting signals. Furthermore, we suggest that these methods be used to identify DECs that occur significantly less frequently than expected, thus identifying potential alternative indications for these drugs. We provide an empirical example that demonstrates the importance of exploring underexpected DECs. Code to implement the proposed method is available in R on request from the corresponding authors. kjell@arboranalytics.com or Mark.M.Gosink@Pfizer.com Supplementary data are available at Bioinformatics online.
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Snedden, Gregg A.; Steyer, Gregory D.
2013-01-01
Understanding plant community zonation along estuarine stress gradients is critical for effective conservation and restoration of coastal wetland ecosystems. We related the presence of plant community types to estuarine hydrology at 173 sites across coastal Louisiana. Percent relative cover by species was assessed at each site near the end of the growing season in 2008, and hourly water level and salinity were recorded at each site Oct 2007–Sep 2008. Nine plant community types were delineated with k-means clustering, and indicator species were identified for each of the community types with indicator species analysis. An inverse relation between salinity and species diversity was observed. Canonical correspondence analysis (CCA) effectively segregated the sites across ordination space by community type, and indicated that salinity and tidal amplitude were both important drivers of vegetation composition. Multinomial logistic regression (MLR) and Akaike's Information Criterion (AIC) were used to predict the probability of occurrence of the nine vegetation communities as a function of salinity and tidal amplitude, and probability surfaces obtained from the MLR model corroborated the CCA results. The weighted kappa statistic, calculated from the confusion matrix of predicted versus actual community types, was 0.7 and indicated good agreement between observed community types and model predictions. Our results suggest that models based on a few key hydrologic variables can be valuable tools for predicting vegetation community development when restoring and managing coastal wetlands.
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Prevalence and associated factors of stress in the Malaysian Police Force.
Masilamani, Retneswari; Bulgiba, Awang; Chinna, Karuthan; Darus, Azlan; Isahak, Marzuki; Kandiben, Shathanapriya; Koh, David
2013-01-01
This study aims to determine the prevalence of stress and the associated socio-demographic and work factors among police personnel in Metropolitan Kuala Lumpur, Malaysia. A cross-sectional study was conducted in two randomly selected police districts in Kuala Lumpur from 2009 to 2011. A total of 579 police officers from 11 police stations and two headquarters participated in this study. The 21-item Depression, Anxiety and Stress questionnaire was used. Multinomial logistic regression analyses were carried out to examine the effect of socio-demographic and work factors on stress. The overall prevalence of stress was 38.8% (95% CI 34.2, 43.6) with 5.9% (3.9, 8.8), 14.9% (11.6, 18.8) and 18.0% (14.5, 22.2) for severe, moderate and mild stress, respectively. Inspectors were more likely to suffer from severe stress (aOR 10.68, 95% CI 3.51, 32.53) compared to junior officers. Those who complained that their salaries were not commensurate with their jobs were more likely to suffer from moderate levels of stress (aOR 2.73, 95% CI 1.43, 5.22) compared to those who were happy with their salaries. This study strengthens findings that police job is stressful. Special attention needs to be paid to Inspector-level ranks and the remuneration structure of police officers to address this issue. Copyright © 2013 Elsevier Inc. All rights reserved.
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Tarkang, Elvis Enowbeyang
2014-01-01
Introduction Since learners in secondary schools fall within the age group hardest hit by HIV/AIDS, it is obvious that these learners might be at high risk of contracting HIV/AIDS. However, little has been explored on the perception of risk of contracting HIV among secondary school learners in Cameroon. This study aimed at examining the perception of risk of contracting HIV among secondary school learners in Mbonge subdivision of rural Cameroon using the Health Belief Model (HBM) as framework. Methods A quantitative, correlational design was adopted, using a self-administered questionnaire to collect data from 210 female learners selected through disproportional, stratified, simple random sampling technique, from three participating senior secondary schools. Statistics were calculated using SPSS version 20 software program. Results Only 39.4% of the respondents perceived themselves to be at high risk of contracting HIV, though the majority, 54.0% were sexually active. Multinomial logistic regression analyses show that sexual risk behaviours (p=0.000) and the Integrated Value Mapping (IVM) of the perception components of the HBM are the most significant factors associated with perception of risk of contracting HIV at the level p<0.05. Conclusion The findings of this study can play an instrumental role in the development of effective preventive and interventional messages for adolescents in Cameroon. PMID:25309659
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Impact of smoking cessation aids and mass media among recent quitters.
Biener, Lois; Reimer, Rebecca L; Wakefield, Melanie; Szczypka, Glen; Rigotti, Nancy A; Connolly, Gregory
2006-03-01
Although studies have addressed the effectiveness of conventional smoking aids such as quit-smoking programs and pharmaceutical therapy, few studies have assessed their likely impact on cessation at the population level relative to the impact of mass media anti-tobacco advertisements. A random digit dial telephone survey of 6739 Massachusetts residents conducted in 2001-2002 yielded a subsample of 787 individuals who had quit-smoking within the past 2 years. Measures included the types of cessation aids used and perceptions of their helpfulness. Rates of population impact were estimated. Multinomial logistic regression determined the predictors of being helped by conventional aids, by TV advertisements only, or having no help. Analyses conducted in 2004-2005 showed that advertisements were the most frequently mentioned source of help among recent quitters. Older more dependent smokers were most likely to find conventional aids helpful. Younger respondents and those who had remained abstinent for more than 6 months were most likely to report being helped by TV ads. The most helpful ads were those that depicted illness due to smoking or provided inspirational quit tips. Anti-tobacco media campaigns are a vital component of the National Action Plan for Tobacco Cessation. It is essential that such a campaign be implemented, both to support the National Quit Line and to provide assistance to those smokers who find no other form of aid helpful.
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Casagrande, Gina; LeJeune, Jeffery; Belury, Martha A; Medeiros, Lydia C
2011-04-01
The Theory of Planned Behavior was used to determine if dietitians personal characteristics and beliefs about fresh vegetable food safety predict whether they currently teach, intend to teach, or neither currently teach nor intend to teach food safety information to their clients. Dietitians who participated in direct client education responded to this web-based survey (n=327). The survey evaluated three independent belief variables: Subjective Norm, Attitudes, and Perceived Behavioral Control. Spearman rho correlations were completed to determine variables that correlated best with current teaching behavior. Multinomial logistical regression was conducted to determine if the belief variables significantly predicted dietitians teaching behavior. Binary logistic regression was used to determine which independent variable was the better predictor of whether dietitians currently taught. Controlling for age, income, education, and gender, the multinomial logistical regression was significant. Perceived behavioral control was the best predictor of whether a dietitian currently taught fresh vegetable food safety. Factors affecting whether dietitians currently taught were confidence in fresh vegetable food safety knowledge, being socially influenced, and a positive attitude toward the teaching behavior. These results validate the importance of teaching food safety effectively and may be used to create more informed food safety curriculum for dietitians. Copyright © 2011 Elsevier Ltd. All rights reserved.
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Prospective memory after moderate-to-severe traumatic brain injury: a multinomial modeling approach.
Pavawalla, Shital P; Schmitter-Edgecombe, Maureen; Smith, Rebekah E
2012-01-01
Prospective memory (PM), which can be understood as the processes involved in realizing a delayed intention, is consistently found to be impaired after a traumatic brain injury (TBI). Although PM can be empirically dissociated from retrospective memory, it inherently involves both a prospective component (i.e., remembering that an action needs to be carried out) and retrospective components (i.e., remembering what action needs to be executed and when). This study utilized a multinomial processing tree model to disentangle the prospective (that) and retrospective recognition (when) components underlying PM after moderate-to-severe TBI. Seventeen participants with moderate to severe TBI and 17 age- and education-matched control participants completed an event-based PM task that was embedded within an ongoing computer-based color-matching task. The multinomial processing tree modeling approach revealed a significant group difference in the prospective component, indicating that the control participants allocated greater preparatory attentional resources to the PM task compared to the TBI participants. Participants in the TBI group were also found to be significantly more impaired than controls in the when aspect of the retrospective component. These findings indicated that the TBI participants had greater difficulty allocating the necessary preparatory attentional resources to the PM task and greater difficulty discriminating between PM targets and nontargets during task execution, despite demonstrating intact posttest recall and/or recognition of the PM tasks and targets.
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Nobre, Aline Araújo; Carvalho, Marilia Sá; Griep, Rosane Härter; Fonseca, Maria de Jesus Mendes da; Melo, Enirtes Caetano Prates; Santos, Itamar de Souza; Chor, Dora
2017-08-17
To compare two methodological approaches: the multinomial model and the zero-inflated gamma model, evaluating the factors associated with the practice and amount of time spent on leisure time physical activity. Data collected from 14,823 baseline participants in the Longitudinal Study of Adult Health (ELSA-Brasil - Estudo Longitudinal de Saúde do Adulto ) have been analysed. Regular leisure time physical activity has been measured using the leisure time physical activity module of the International Physical Activity Questionnaire. The explanatory variables considered were gender, age, education level, and annual per capita family income. The main advantage of the zero-inflated gamma model over the multinomial model is that it estimates mean time (minutes per week) spent on leisure time physical activity. For example, on average, men spent 28 minutes/week longer on leisure time physical activity than women did. The most sedentary groups were young women with low education level and income. The zero-inflated gamma model, which is rarely used in epidemiological studies, can give more appropriate answers in several situations. In our case, we have obtained important information on the main determinants of the duration of leisure time physical activity. This information can help guide efforts towards the most vulnerable groups since physical inactivity is associated with different diseases and even premature death.
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Ansari, Nabila; Young, Christopher J; Schlub, Timothy E; Dhillon, Haryana M; Solomon, Michael J
2015-12-01
Strong evidence supports the use of neoadjuvant radiotherapy in rectal cancer to improve local control. This randomised controlled trial aimed to determine the effect of clinical and non-clinical factors on decision making by colorectal surgeons in patients with rectal cancer. Two surveys comprising vignettes of alternating short (4) and long (12) cues identified previously as important in rectal cancer, were randomly assigned to all members of the CSSANZ. Respondents chose from three possible treatments: long course chemoradiotherapy (LC), short course radiotherapy (SC) or surgery alone to investigate the effects on surgeon decision and confidence in decisions. Choice data were analysed using multinomial logistic regression models. 106 of 165 (64%) surgeons responded. LC was the preferred treatment choice in 73% of vignettes. Surgeons were more likely to recommend LC over SC (OR 1.79) or surgery alone (OR 1.99) when presented with the shorter, four-cue scenarios. There was no significant difference in confidence in decisions made when surgeons were presented with long cue vignettes (P = 0.57). Significant effects on the choice between LC, SC and surgery alone were tumour stage (P < 0.001), nodal status (P < 0.001), tumour position in the rectum (P < 0.001) and the circumferential location of the tumour (P < 0.001). A T4 tumour was the factor most likely associated with a recommendation against surgery alone (OR 335.96) or SC (OR 61.73). This study shows that clinical factors exert the greatest influence on surgeon decision making, which follows a "fast and frugal" heuristic decision making model. Copyright © 2015 IJS Publishing Group Limited. Published by Elsevier Ltd. All rights reserved.
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Hoefman, Renske J; van Exel, Job; Brouwer, Werner B F
2017-04-01
Informal care is often not included in economic evaluations in healthcare, while the impact of caregiving can be relevant for cost-effectiveness recommendations from a societal perspective. The impact of informal care can be measured and valued with the CarerQol instrument, which measures the impact of informal care on seven important burden dimensions (CarerQol-7D) and values this in terms of general quality of life (CarerQol-VAS). The CarerQol can be included at the effect side of multi-criteria analyses of patient interventions or in cost-effectiveness or utility analysis of interventions targeted at caregivers. At present, utility scores based on relative utility weights for the CarerQol-7D are only available for the Netherlands. This study calculates CarerQol-7D tariffs for Australia, Germany, Sweden, UK, and US. Data were collected among the general population in Australia, Germany, Sweden, UK, and US by an Internet survey. Utility weights were collected with a discrete choice experiment with two unlabeled alternatives described in terms of the seven CarerQol-7D dimensions. An efficient experimental design with priors obtained from the Netherlands was used to create the choice sets. Data was analyzed with a panel mixed multinomial logit model with random parameters. In all five countries, the CarerQol-7D dimensions were significantly associated with the utility of informal care situations. Physical health problems were most strongly associated with the utility for informal care situations. The tariff was constructed by adding up the relative utility weights per category of all CarerQol-7D dimensions for each country separately. The CarerQol tariffs for Australia, Germany, Sweden, UK, and US facilitate the inclusion of informal care in economic evaluations.
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Castelló, Adela; Fernández de Larrea, Nerea; Martín, Vicente; Dávila-Batista, Verónica; Boldo, Elena; Guevara, Marcela; Moreno, Víctor; Castaño-Vinyals, Gemma; Gómez-Acebo, Inés; Fernández-Tardón, Guillermo; Peiró, Rosana; Olmedo-Requena, Rocío; Capelo, Rocio; Navarro, Carmen; Pacho-Valbuena, Silvino; Pérez-Gómez, Beatriz; Kogevinas, Manolis; Pollán, Marina; Aragonés, Nuria
2018-05-01
The influence of dietary habits on the development of gastric adenocarcinoma is not clear. The objective of the present study was to explore the association of three previously identified dietary patterns with gastric adenocarcinoma by sex, age, cancer site, and morphology. MCC-Spain is a multicase-control study that included 295 incident cases of gastric adenocarcinoma and 3040 controls. The association of the Western, Prudent, and Mediterranean dietary patterns-derived in another Spanish case-control study-with gastric adenocarcinoma was assessed using multivariable logistic regression models with random province-specific intercepts and considering a possible interaction with sex and age. Risk according to tumor site (cardia, non-cardia) and morphology (intestinal/diffuse) was evaluated using multinomial regression models. A high adherence to the Western pattern increased gastric adenocarcinoma risk [odds ratio fourth_vs._first_quartile (95% confidence interval), 2.09 (1.31; 3.33)] even at low levels [odds ratio second_vs._first_quartile (95% confidence interval), 1.63 (1.05; 2.52)]. High adherence to the Mediterranean dietary pattern could prevent gastric adenocarcinoma [odds ratio fourth_vs._first_quartile (95% confidence interval), 0.53 (0.34; 0.82)]. Although no significant heterogeneity of effects was observed, the harmful effect of the Western pattern was stronger among older participants and for non-cardia adenocarcinomas, whereas the protective effect of the Mediterranean pattern was only observed among younger participants and for non-cardia tumors. Decreasing the consumption of fatty and sugary products and of red and processed meat in favor of an increase in the intake of fruits, vegetables, legumes, olive oil, nuts, and fish might prevent gastric adenocarcinoma.
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van der Velden, Peter G; Pijnappel, Bas; van der Meulen, Erik
2018-02-01
Examine to what extent adults affected by recent potentially traumatic events (PTE) with different PTSD-symptom levels are more at risk for post-event loneliness than non-affected adults are in the same study period. We extracted data from the Dutch longitudinal LISS panel to measure pre-event loneliness (2011) and post-event loneliness (2013 and 2014), pre-event mental health problems (2011), PTE and PTSD symptoms (2012). This panel is based on a traditional random sample drawn from the population register by Statistics Netherlands. Results of the multinomial logistic regression analyses showed that affected adults with high levels of PTSD symptoms were more at risk for high levels of post-event loneliness than affected adults with very low PTSD-symptom levels and non-affected adults, while controlling for pre-event loneliness, pre-event mental health problems and demographics. However, affected adults with very low levels of PTSD symptoms compared to non-affected adults were less at risk for medium and high levels of post-event loneliness while controlling for the same variables. Yet, pre-event loneliness appeared to be the strongest independent predictor of loneliness at later stages: more than 80% with high pre-event levels had high post-event levels at both follow-ups. Remarkably, potentially traumatic events have depending on PTSD-symptom levels both negative and positive effects on post-event loneliness in favor of affected adults with very low PTSD symptoms levels. However, post-event levels at later stages are predominantly determined by pre-event loneliness levels.
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Regression Models For Multivariate Count Data
Zhang, Yiwen; Zhou, Hua; Zhou, Jin; Sun, Wei
2016-01-01
Data with multivariate count responses frequently occur in modern applications. The commonly used multinomial-logit model is limiting due to its restrictive mean-variance structure. For instance, analyzing count data from the recent RNA-seq technology by the multinomial-logit model leads to serious errors in hypothesis testing. The ubiquity of over-dispersion and complicated correlation structures among multivariate counts calls for more flexible regression models. In this article, we study some generalized linear models that incorporate various correlation structures among the counts. Current literature lacks a treatment of these models, partly due to the fact that they do not belong to the natural exponential family. We study the estimation, testing, and variable selection for these models in a unifying framework. The regression models are compared on both synthetic and real RNA-seq data. PMID:28348500
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Regression Models For Multivariate Count Data.
Zhang, Yiwen; Zhou, Hua; Zhou, Jin; Sun, Wei
2017-01-01
Data with multivariate count responses frequently occur in modern applications. The commonly used multinomial-logit model is limiting due to its restrictive mean-variance structure. For instance, analyzing count data from the recent RNA-seq technology by the multinomial-logit model leads to serious errors in hypothesis testing. The ubiquity of over-dispersion and complicated correlation structures among multivariate counts calls for more flexible regression models. In this article, we study some generalized linear models that incorporate various correlation structures among the counts. Current literature lacks a treatment of these models, partly due to the fact that they do not belong to the natural exponential family. We study the estimation, testing, and variable selection for these models in a unifying framework. The regression models are compared on both synthetic and real RNA-seq data.
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Olstad, Dana Lee; Crawford, David A; Abbott, Gavin; McNaughton, Sarah A; Le, Ha Nd; Ni Mhurchu, Cliona; Pollard, Christina; Ball, Kylie
2017-08-25
The impacts of supermarket-based nutrition promotion interventions might be overestimated if participants shift their proportionate food purchasing away from their usual stores. This study quantified whether participants who received price discounts on fruits and vegetables (FV) in the Supermarket Healthy Eating for Life (SHELf) randomized controlled trial (RCT) shifted their FV purchasing into study supermarkets during the intervention period. Participants were 642 females randomly assigned to a 1) skill-building (n = 160), 2) price reduction (n = 161), 3) combined skill-building and price reduction (n = 160), or 4) control (n = 161) group. Participants self-reported the proportion of FV purchased in study supermarkets at baseline, 3- and 6-months post-intervention. Fisher's exact and χ 2 tests assessed differences among groups in the proportion of FV purchased in study supermarkets at each time point. Multinomial logistic regression assessed differences among groups in the change in proportionate FV purchasing over time. Post-intervention, 49% of participants purchased ≥50% of their FV in study supermarkets. Compared to all other groups, the price reduction group was approximately twice as likely (RRR: 1.8-2.2) to have increased proportionate purchasing of FV in study supermarkets from baseline to post-intervention (p< 0.05). Participants who received price reductions on FV were approximately twice as likely to shift their FV purchasing from other stores into study supermarkets during the intervention period. Unless food purchasing data are available for all sources, differential changes in purchasing patterns can make it difficult to discern the true impacts of nutrition interventions. The SHELf trial is registered with Current Controlled Trials Registration ISRCTN39432901, Registered 30 June 2010, Retrospectively registered ( http://www.isrctn.com/ISRCTN39432901 ).
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Hossain, Monir; Wright, Steven; Petersen, Laura A
2002-04-01
One way to monitor patient access to emergent health care services is to use patient characteristics to predict arrival time at the hospital after onset of symptoms. This predicted arrival time can then be compared with actual arrival time to allow monitoring of access to services. Predicted arrival time could also be used to estimate potential effects of changes in health care service availability, such as closure of an emergency department or an acute care hospital. Our goal was to determine the best statistical method for prediction of arrival intervals for patients with acute myocardial infarction (AMI) symptoms. We compared the performance of multinomial logistic regression (MLR) and discriminant analysis (DA) models. Models for MLR and DA were developed using a dataset of 3,566 male veterans hospitalized with AMI in 81 VA Medical Centers in 1994-1995 throughout the United States. The dataset was randomly divided into a training set (n = 1,846) and a test set (n = 1,720). Arrival times were grouped into three intervals on the basis of treatment considerations: <6 hours, 6-12 hours, and >12 hours. One model for MLR and two models for DA were developed using the training dataset. One DA model had equal prior probabilities, and one DA model had proportional prior probabilities. Predictive performance of the models was compared using the test (n = 1,720) dataset. Using the test dataset, the proportions of patients in the three arrival time groups were 60.9% for <6 hours, 10.3% for 6-12 hours, and 28.8% for >12 hours after symptom onset. Whereas the overall predictive performance by MLR and DA with proportional priors was higher, the DA models with equal priors performed much better in the smaller groups. Correct classifications were 62.6% by MLR, 62.4% by DA using proportional prior probabilities, and 48.1% using equal prior probabilities of the groups. The misclassifications by MLR for the three groups were 9.5%, 100.0%, 74.2% for each time interval, respectively. Misclassifications by DA models were 9.8%, 100.0%, and 74.4% for the model with proportional priors and 47.6%, 79.5%, and 51.0% for the model with equal priors. The choice of MLR or DA with proportional priors, or DA with equal priors for monitoring time intervals of predicted hospital arrival time for a population should depend on the consequences of misclassification errors.
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Flynn, Terry N; Louviere, Jordan J; Marley, Anthony AJ; Coast, Joanna; Peters, Tim J
2008-01-01
Background Researchers are increasingly investigating the potential for ordinal tasks such as ranking and discrete choice experiments to estimate QALY health state values. However, the assumptions of random utility theory, which underpin the statistical models used to provide these estimates, have received insufficient attention. In particular, the assumptions made about the decisions between living states and the death state are not satisfied, at least for some people. Estimated values are likely to be incorrectly anchored with respect to death (zero) in such circumstances. Methods Data from the Investigating Choice Experiments for the preferences of older people CAPability instrument (ICECAP) valuation exercise were analysed. The values (previously anchored to the worst possible state) were rescaled using an ordinal model proposed previously to estimate QALY-like values. Bootstrapping was conducted to vary artificially the proportion of people who conformed to the conventional random utility model underpinning the analyses. Results Only 26% of respondents conformed unequivocally to the assumptions of conventional random utility theory. At least 14% of respondents unequivocally violated the assumptions. Varying the relative proportions of conforming respondents in sensitivity analyses led to large changes in the estimated QALY values, particularly for lower-valued states. As a result these values could be either positive (considered to be better than death) or negative (considered to be worse than death). Conclusion Use of a statistical model such as conditional (multinomial) regression to anchor quality of life values from ordinal data to death is inappropriate in the presence of respondents who do not conform to the assumptions of conventional random utility theory. This is clearest when estimating values for that group of respondents observed in valuation samples who refuse to consider any living state to be worse than death: in such circumstances the model cannot be estimated. Only a valuation task requiring respondents to make choices in which both length and quality of life vary can produce estimates that properly reflect the preferences of all respondents. PMID:18945358
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Zimprich, Daniel; Wolf, Tabea
2018-06-20
In many studies of autobiographical memory, participants are asked to generate more than one autobiographical memory. The resulting data then have a hierarchical or multilevel structure, in the sense that the autobiographical memories (Level 1) generated by the same person (Level 2) tend to be more similar. Transferred to an analysis of the reminiscence bump in autobiographical memory, at Level 1 the prediction of whether an autobiographical memory will fall within the reminiscence bump is based on the characteristics of that memory. At Level 2, the prediction of whether an individual will report more autobiographical memories that fall in the reminiscence bump is based on the characteristics of the individual. We suggest a multilevel multinomial model that allows for analyzing whether an autobiographical memory falls in the reminiscence bump at both levels of analysis simultaneously. The data come from 100 older participants who reported up to 33 autobiographical memories. Our results showed that about 12% of the total variance was between persons (Level 2). Moreover, at Level 1, memories of first-time experiences were more likely to fall in the reminiscence bump than were emotionally more positive memories. At Level 2, persons who reported more emotionally positive memories tended to report fewer memories from the life period after the reminiscence bump. In addition, cross-level interactions showed that the effects at Level 1 partly depended on the Level 2 effects. We discuss possible extensions of the model we present and the meaning of our findings for two prominent explanatory approaches to the reminiscence bump, as well as future directions.
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Women's health in a rural community in Kerala, India: do caste and socioeconomic position matter?
Mohindra, K S; Haddad, Slim; Narayana, D
2006-01-01
Objectives To examine the social patterning of women's self‐reported health status in India and the validity of the two hypotheses: (1) low caste and lower socioeconomic position is associated with worse reported health status, and (2) associations between socioeconomic position and reported health status vary across castes. Design Cross‐sectional household survey, age‐adjusted percentages and odds ratios, and multilevel multinomial logistic regression models were used for analysis. Setting A panchayat (territorial decentralised unit) in Kerala, India, in 2003. Participants 4196 non‐elderly women. Outcome measures Self‐perceived health status and reported limitations in activities in daily living. Results Women from lower castes (scheduled castes/scheduled tribes (SC/ST) and other backward castes (OBC) reported a higher prevalence of poor health than women from forward castes. Socioeconomic inequalities were observed in health regardless of the indicators, education, women's employment status or household landholdings. The multilevel multinomial models indicate that the associations between socioeconomic indicators and health vary across caste. Among SC/ST and OBC women, the influence of socioeconomic variables led to a “magnifying” effect, whereas among forward caste women, a “buffering” effect was found. Among lower caste women, the associations between socioeconomic factors and self‐assessed health are graded; the associations are strongest when comparing the lowest and highest ratings of health. Conclusions Even in a relatively egalitarian state in India, there are caste and socioeconomic inequalities in women's health. Implementing interventions that concomitantly deal with caste and socioeconomic disparities will likely produce more equitable results than targeting either type of inequality in isolation. PMID:17108296
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Prevalence and Determinants of Secondhand Smoke Exposure Among Women in Bangladesh, 2011
Minnwegen, Martina; Kaneider, Ulrike; Kraemer, Alexander; Khan, Md. Mobarak Hossain
2015-01-01
Background and Objectives: The population of Bangladesh is highly susceptible to secondhand smoke (SHS) exposure due to high smoking rates and low awareness about the harmful effects of SHS. This study aims to determine the prevalence of SHS exposure and highlight the essential determinants in developing successful strategies to prevent adverse health effects in Bangladesh. Methods: The analysis is based on the Bangladesh Demographic Health Survey 2011, in which 17,749 women in the reproductive age group (12–49 years) were included. The information regarding SHS exposure at home was derived from the question: “How often does anyone smoke inside your house?” The variable was recoded into 3 groups: daily exposure, low exposure (exposed weekly, monthly, or less than monthly), and no SHS exposure. We performed descriptive and bivariable analyses and multinomial logistic regression. Results: A total of 46.7% of the women reported high exposure to SHS at home. According to the multinomial logistic regression model, relatively lower education and lower wealth index were significantly associated with daily SHS exposure at home. The exposure differed significantly between the divisions of Bangladesh. Having children at home (vs. not) and being Islamic (compared to other religious affiliations) were protective factors. Conclusions: The study indicates that women from socioeconomically disadvantaged households are more likely to experience daily exposure to SHS at home. Therefore, especially these groups have to be targeted to reduce tobacco consumption. In addition to aspects of legislation, future strategies need to focus educational aspects to improve the population’s health status in Bangladesh. PMID:25125322
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Discrete post-processing of total cloud cover ensemble forecasts
NASA Astrophysics Data System (ADS)
Hemri, Stephan; Haiden, Thomas; Pappenberger, Florian
2017-04-01
This contribution presents an approach to post-process ensemble forecasts for the discrete and bounded weather variable of total cloud cover. Two methods for discrete statistical post-processing of ensemble predictions are tested. The first approach is based on multinomial logistic regression, the second involves a proportional odds logistic regression model. Applying them to total cloud cover raw ensemble forecasts from the European Centre for Medium-Range Weather Forecasts improves forecast skill significantly. Based on station-wise post-processing of raw ensemble total cloud cover forecasts for a global set of 3330 stations over the period from 2007 to early 2014, the more parsimonious proportional odds logistic regression model proved to slightly outperform the multinomial logistic regression model. Reference Hemri, S., Haiden, T., & Pappenberger, F. (2016). Discrete post-processing of total cloud cover ensemble forecasts. Monthly Weather Review 144, 2565-2577.
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Emotionally enhanced memory for negatively arousing words: storage or retrieval advantage?
Nadarevic, Lena
2017-12-01
People typically remember emotionally negative words better than neutral words. Two experiments are reported that investigate whether emotionally enhanced memory (EEM) for negatively arousing words is based on a storage or retrieval advantage. Participants studied non-word-word pairs that either involved negatively arousing or neutral target words. Memory for these target words was tested by means of a recognition test and a cued-recall test. Data were analysed with a multinomial model that allows the disentanglement of storage and retrieval processes in the present recognition-then-cued-recall paradigm. In both experiments the multinomial analyses revealed no storage differences between negatively arousing and neutral words but a clear retrieval advantage for negatively arousing words in the cued-recall test. These findings suggest that EEM for negatively arousing words is driven by associative processes.
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Chaibub Neto, Elias
2015-01-01
In this paper we propose a vectorized implementation of the non-parametric bootstrap for statistics based on sample moments. Basically, we adopt the multinomial sampling formulation of the non-parametric bootstrap, and compute bootstrap replications of sample moment statistics by simply weighting the observed data according to multinomial counts instead of evaluating the statistic on a resampled version of the observed data. Using this formulation we can generate a matrix of bootstrap weights and compute the entire vector of bootstrap replications with a few matrix multiplications. Vectorization is particularly important for matrix-oriented programming languages such as R, where matrix/vector calculations tend to be faster than scalar operations implemented in a loop. We illustrate the application of the vectorized implementation in real and simulated data sets, when bootstrapping Pearson’s sample correlation coefficient, and compared its performance against two state-of-the-art R implementations of the non-parametric bootstrap, as well as a straightforward one based on a for loop. Our investigations spanned varying sample sizes and number of bootstrap replications. The vectorized bootstrap compared favorably against the state-of-the-art implementations in all cases tested, and was remarkably/considerably faster for small/moderate sample sizes. The same results were observed in the comparison with the straightforward implementation, except for large sample sizes, where the vectorized bootstrap was slightly slower than the straightforward implementation due to increased time expenditures in the generation of weight matrices via multinomial sampling. PMID:26125965
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Yu, Peng; Shaw, Chad A
2014-06-01
The Dirichlet-multinomial (DMN) distribution is a fundamental model for multicategory count data with overdispersion. This distribution has many uses in bioinformatics including applications to metagenomics data, transctriptomics and alternative splicing. The DMN distribution reduces to the multinomial distribution when the overdispersion parameter ψ is 0. Unfortunately, numerical computation of the DMN log-likelihood function by conventional methods results in instability in the neighborhood of [Formula: see text]. An alternative formulation circumvents this instability, but it leads to long runtimes that make it impractical for large count data common in bioinformatics. We have developed a new method for computation of the DMN log-likelihood to solve the instability problem without incurring long runtimes. The new approach is composed of a novel formula and an algorithm to extend its applicability. Our numerical experiments show that this new method both improves the accuracy of log-likelihood evaluation and the runtime by several orders of magnitude, especially in high-count data situations that are common in deep sequencing data. Using real metagenomic data, our method achieves manyfold runtime improvement. Our method increases the feasibility of using the DMN distribution to model many high-throughput problems in bioinformatics. We have included in our work an R package giving access to this method and a vingette applying this approach to metagenomic data. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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Factors Associated with Substance Use in Adolescents with Eating Disorders
Mann, Andrea P; Accurso, Erin C.; Stiles-Shields, Colleen; Capra, Lauren; Labuschagne, Zandre; Karnik, Niranjan S.; Grange, Daniel Le
2014-01-01
Purpose To examine the prevalence and potential risk factors associated with substance use in adolescents with eating disorders (EDs). Methods This cross-sectional study included 290 adolescents, ages 12 –18 years, who presented for an initial ED evaluation at The Eating Disorders Program at The University of Chicago Medicine (UCM) between 2001 and 2012. Several factors, including DSM-5 diagnosis, diagnostic scores, and demographic characteristics were examined. Multinomial logistic regression was used to test associations between several factors and patterns of drug use for alcohol, cannabis, tobacco, and any substance. Results Lifetime prevalence of any substance use was found to be 24.6% in those with anorexia nervosa (AN), 48.7% in bulimia nervosa (BN), and 28.6% in eating disorder not otherwise specified (EDNOS). Regular substance use (monthly, daily, and bingeing behaviors) or a substance use disorder (SUD) was found in 27.9% of all patients. Older age was the only factor associated with regular use of any substance in the final multinomial model. Older age and non-White race was associated with greater alcohol and cannabis use. Although binge-purge frequency and BN diagnosis were associated with regular substance use in bivariate analyses, gender, race and age were more robustly associated with substance use in the final multinomial models. Conclusions Co-morbid substance use in adolescents with EDs is an important issue. Interventions targeting high-risk groups reporting regular substance use or SUDs are needed. PMID:24656448
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Bayesian multinomial probit modeling of daily windows of ...
Past epidemiologic studies suggest maternal ambient air pollution exposure during critical periods of the pregnancy is associated with fetal development. We introduce a multinomial probit model that allows for the joint identification of susceptible daily periods during the pregnancy for 12 individual types of CHDs with respect to maternal PM2.5 exposure. We apply the model to a dataset of mothers from the National Birth Defect Prevention Study where daily PM2.5 exposures from weeks 2-8 of pregnancy are assigned (specific to each location and pregnancy date) using predictions from the downscaler pollution model. Results are compared to an aggregated exposure model which defines exposure as the average value over pregnancy weeks 2-8. Increased PM2.5 exposure during pregnancy days 53 and 50-51 for pulmonary valve stenosis and tetralogy of Fallot, respectively, are associated with an increased probability of development of each CHD. The largest estimated effect is seen for atrioventricular septal defects on pregnancy day 14. The aggregated exposure model fails to identify any significant windows of susceptibility during pregnancy weeks 2-8 for the considered CHDs. Considering daily PM2.5 exposures in a new modeling framework revealed positive associations for defects that the standard aggregated exposure model was unable to identify. Disclaimer: The views expressed in this manuscript are those of the authors and do not necessarily represent the views or policie
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Physical victimization, gender identity and suicide risk among transgender men and women.
Barboza, Gia Elise; Dominguez, Silvia; Chance, Elena
2016-12-01
We investigated whether being attacked physically due to one's gender identity or expression was associated with suicide risk among trans men and women living in Virginia. The sample consisted of 350 transgender men and women who participated in the Virginia Transgender Health Initiative Survey (THIS). Multivariate multinomial logistic regression was used to explore the competing outcomes associated with suicidal risk. Thirty-seven percent of trans men and women experienced at least one physical attack since the age of 13. On average, individuals experienced 3.97 (SD = 2.86) physical attacks; among these about half were attributed to one's gender identity or expression (mean = 2.08, SD = 1.96). In the multivariate multinomial regression, compared to those with no risk, being physically attacked increased the odds of both attempting and contemplating suicide regardless of gender attribution. Nevertheless, the relative impact of physical victimization on suicidal behavior was higher among those who were targeted on the basis of their gender identity or expression. Finally, no significant association was found between multiple measures of institutional discrimination and suicide risk once discriminatory and non-discriminatory physical victimization was taken into account. Trans men and women experience high levels of physical abuse and face multiple forms of discrimination. They are also at an increased risk for suicidal tendencies. Interventions that help transindividuals cope with discrimination and physical victimization simultaneously may be more effective in saving lives.
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Disentangling WTP per QALY data: different analytical approaches, different answers.
Gyrd-Hansen, Dorte; Kjaer, Trine
2012-03-01
A large random sample of the Danish general population was asked to value health improvements by way of both the time trade-off elicitation technique and willingness-to-pay (WTP) using contingent valuation methods. The data demonstrate a high degree of heterogeneity across respondents in their relative valuations on the two scales. This has implications for data analysis. We show that the estimates of WTP per QALY are highly sensitive to the analytical strategy. For both open-ended and dichotomous choice data we demonstrate that choice of aggregated approach (ratios of means) or disaggregated approach (means of ratios) affects estimates markedly as does the interpretation of the constant term (which allows for disproportionality across the two scales) in the regression analyses. We propose that future research should focus on why some respondents are unwilling to trade on the time trade-off scale, on how to interpret the constant value in the regression analyses, and on how best to capture the heterogeneity in preference structures when applying mixed multinomial logit. Copyright © 2011 John Wiley & Sons, Ltd.
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Williams, David R.
2009-01-01
Objectives. We examined whether perceived chronic discrimination was related to excess body fat accumulation in a random, multiethnic, population-based sample of US adults. Methods. We used multivariate multinomial logistic regression and logistic regression analyses to examine the relationship between interpersonal experiences of perceived chronic discrimination and body mass index and high-risk waist circumference. Results. Consistent with other studies, our analyses showed that perceived unfair treatment was associated with increased abdominal obesity. Compared with Irish, Jewish, Polish, and Italian Whites who did not experience perceived chronic discrimination, Irish, Jewish, Polish, and Italian Whites who perceived chronic discrimination were 2 to 6 times more likely to have a high-risk waist circumference. No significant relationship between perceived discrimination and the obesity measures was found among the other Whites, Blacks, or Hispanics. Conclusions. These findings are not completely unsupported. White ethnic groups including Polish, Italians, Jews, and Irish have historically been discriminated against in the United States, and other recent research suggests that they experience higher levels of perceived discrimination than do other Whites and that these experiences adversely affect their health. PMID:18923119
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NASA Astrophysics Data System (ADS)
Han, Xiaopeng; Huang, Xin; Li, Jiayi; Li, Yansheng; Yang, Michael Ying; Gong, Jianya
2018-04-01
In recent years, the availability of high-resolution imagery has enabled more detailed observation of the Earth. However, it is imperative to simultaneously achieve accurate interpretation and preserve the spatial details for the classification of such high-resolution data. To this aim, we propose the edge-preservation multi-classifier relearning framework (EMRF). This multi-classifier framework is made up of support vector machine (SVM), random forest (RF), and sparse multinomial logistic regression via variable splitting and augmented Lagrangian (LORSAL) classifiers, considering their complementary characteristics. To better characterize complex scenes of remote sensing images, relearning based on landscape metrics is proposed, which iteratively quantizes both the landscape composition and spatial configuration by the use of the initial classification results. In addition, a novel tri-training strategy is proposed to solve the over-smoothing effect of relearning by means of automatic selection of training samples with low classification certainties, which always distribute in or near the edge areas. Finally, EMRF flexibly combines the strengths of relearning and tri-training via the classification certainties calculated by the probabilistic output of the respective classifiers. It should be noted that, in order to achieve an unbiased evaluation, we assessed the classification accuracy of the proposed framework using both edge and non-edge test samples. The experimental results obtained with four multispectral high-resolution images confirm the efficacy of the proposed framework, in terms of both edge and non-edge accuracy.
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An application of the SF-6D to create heath values in Portuguese working age adults.
Ferreira, Lara Noronha; Ferreira, Pedro Lopes; Pereira, Luís Nobre; Brazier, John
2008-01-01
This study describes the health-related quality of life (HRQOL) of the Portuguese working age population and investigates sociodemographic differences. Subjects randomly selected from the working age population (n=2,459) were assessed using the SF-36v2 and converted into the preference-based SF-6D. The mean SF-6D utility value was 0.70 (range 0.63-0.73). The mean utility value was lower for the lower educational level than for the highest. Women, people living in rural areas and older adults reported lower levels of utility values. Non-parametric tests showed that health utility values were significantly related to employment; unskilled manual workers reported utility values lower than non-manual workers. For different diseases, mean utility values ranged from 0.58 (sexual diseases) to 0.66 (hepatic conditions). Cluster analysis was adopted to classify individuals into three groups according to their answers to the SF-6D dimensions. Multinomial logit regression was used to detect sociodemographic characteristics affecting the probability of following each cluster pattern. This study yielded normative data by age and gender for the SF-6D. The authors conclude that SF-6D is an effective tool for measuring HRQOL in the community so that different population groups can be compared. The preference-based measure used seems to discriminate adequately across sociodemographic differences. These results allow a better understanding of the impact of sociodemographic variables on the burden of illness perception.
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Association between Adverse Life Events and Addictive Behaviors among Male and Female Adolescents
Lee, Grace P.; Storr, Carla L.; Ialongo, Nicholas S.; Martins, Silvia S.
2012-01-01
Background Adverse life events have been associated with gambling and substance use as they can serve as forms of escapism. Involvement in gambling and substance use can also place individuals in adversely stressful situations. Objectives To explore potential male-female differences in the association between addictive behavior and adverse life events among an urban cohort of adolescents. Methods The study sample comprised of 515 adolescent participants in a randomized prevention trial. With self-reported data, four addictive behavior groups were created: Non-Substance Users and Non-Gamblers, Substance Users Only, Gamblers Only, and Substance Users and Gamblers. Multinomial logistic regression analyses with interaction terms of sex and adverse life events were conducted. Results Adverse life events and engaging in at least one addictive behavior were common for both sexes. Substance Users and Gamblers had more than twice the likelihood of Non-Substance Users and Non-Gamblers to experience any event as well as events of various domains (i.e., relationship, violence, and instability). Neither relationship nor instability events’ associations with the co-occurrence of substance use and gambling significantly differed between sexes. Conversely, females exposed to violence events were significantly more likely than similarly exposed males to report the co-occurrence of substance use and gambling. Conclusion Findings from the current study prompt future studies to devote more attention to the development of effective programs that teach adaptive coping strategies to adolescents, particularly to females upon exposure to violence. PMID:23082829
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Association between adverse life events and addictive behaviors among male and female adolescents.
Lee, Grace P; Storr, Carla L; Ialongo, Nicholas S; Martins, Silvia S
2012-01-01
Adverse life events have been associated with gambling and substance use as they can serve as forms of escapism. Involvement in gambling and substance use can also place individuals in adversely stressful situations. To explore potential male-female differences in the association between addictive behavior and adverse life events among an urban cohort of adolescents. The study sample comprised of 515 adolescent participants in a randomized prevention trial. With self-reported data, four addictive behavior groups were created: nonsubstance users and nongamblers, substance users only, gamblers only, and substance users and gamblers. Multinomial logistic regression analyses with interaction terms of sex and adverse life events were conducted. Adverse life events and engaging in at least one addictive behavior were common for both sexes. Substance users and gamblers had more than twice the likelihood of nonsubstance users and nongamblers to experience any event as well as events of various domains (ie, relationship, violence, and instability). Neither relationship nor instability events' associations with the co-occurrence of substance use and gambling significantly differed between sexes. Conversely, females exposed to violence events were significantly more likely than similarly exposed males to report the co-occurrence of substance use and gambling. Findings from the current study prompt future studies to devote more attention to the development of effective programs that teach adaptive coping strategies to adolescents, particularly to females upon exposure to violence. Copyright © American Academy of Addiction Psychiatry.
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Pulse pileup statistics for energy discriminating photon counting x-ray detectors
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Adam S.; Harrison, Daniel; Lobastov, Vladimir
Purpose: Energy discriminating photon counting x-ray detectors can be subject to a wide range of flux rates if applied in clinical settings. Even when the incident rate is a small fraction of the detector's maximum periodic rate N{sub 0}, pulse pileup leads to count rate losses and spectral distortion. Although the deterministic effects can be corrected, the detrimental effect of pileup on image noise is not well understood and may limit the performance of photon counting systems. Therefore, the authors devise a method to determine the detector count statistics and imaging performance. Methods: The detector count statistics are derived analyticallymore » for an idealized pileup model with delta pulses of a nonparalyzable detector. These statistics are then used to compute the performance (e.g., contrast-to-noise ratio) for both single material and material decomposition contrast detection tasks via the Cramer-Rao lower bound (CRLB) as a function of the detector input count rate. With more realistic unipolar and bipolar pulse pileup models of a nonparalyzable detector, the imaging task performance is determined by Monte Carlo simulations and also approximated by a multinomial method based solely on the mean detected output spectrum. Photon counting performance at different count rates is compared with ideal energy integration, which is unaffected by count rate. Results: The authors found that an ideal photon counting detector with perfect energy resolution outperforms energy integration for our contrast detection tasks, but when the input count rate exceeds 20%N{sub 0}, many of these benefits disappear. The benefit with iodine contrast falls rapidly with increased count rate while water contrast is not as sensitive to count rates. The performance with a delta pulse model is overoptimistic when compared to the more realistic bipolar pulse model. The multinomial approximation predicts imaging performance very close to the prediction from Monte Carlo simulations. The monoenergetic image with maximum contrast-to-noise ratio from dual energy imaging with ideal photon counting is only slightly better than with dual kVp energy integration, and with a bipolar pulse model, energy integration outperforms photon counting for this particular metric because of the count rate losses. However, the material resolving capability of photon counting can be superior to energy integration with dual kVp even in the presence of pileup because of the energy information available to photon counting. Conclusions: A computationally efficient multinomial approximation of the count statistics that is based on the mean output spectrum can accurately predict imaging performance. This enables photon counting system designers to directly relate the effect of pileup to its impact on imaging statistics and how to best take advantage of the benefits of energy discriminating photon counting detectors, such as material separation with spectral imaging.« less
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Lucini, Filipe R; S Fogliatto, Flavio; C da Silveira, Giovani J; L Neyeloff, Jeruza; Anzanello, Michel J; de S Kuchenbecker, Ricardo; D Schaan, Beatriz
2017-04-01
Emergency department (ED) overcrowding is a serious issue for hospitals. Early information on short-term inward bed demand from patients receiving care at the ED may reduce the overcrowding problem, and optimize the use of hospital resources. In this study, we use text mining methods to process data from early ED patient records using the SOAP framework, and predict future hospitalizations and discharges. We try different approaches for pre-processing of text records and to predict hospitalization. Sets-of-words are obtained via binary representation, term frequency, and term frequency-inverse document frequency. Unigrams, bigrams and trigrams are tested for feature formation. Feature selection is based on χ 2 and F-score metrics. In the prediction module, eight text mining methods are tested: Decision Tree, Random Forest, Extremely Randomized Tree, AdaBoost, Logistic Regression, Multinomial Naïve Bayes, Support Vector Machine (Kernel linear) and Nu-Support Vector Machine (Kernel linear). Prediction performance is evaluated by F1-scores. Precision and Recall values are also informed for all text mining methods tested. Nu-Support Vector Machine was the text mining method with the best overall performance. Its average F1-score in predicting hospitalization was 77.70%, with a standard deviation (SD) of 0.66%. The method could be used to manage daily routines in EDs such as capacity planning and resource allocation. Text mining could provide valuable information and facilitate decision-making by inward bed management teams. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.
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NASA Astrophysics Data System (ADS)
Al-Mudhafar, W. J.
2013-12-01
Precisely prediction of rock facies leads to adequate reservoir characterization by improving the porosity-permeability relationships to estimate the properties in non-cored intervals. It also helps to accurately identify the spatial facies distribution to perform an accurate reservoir model for optimal future reservoir performance. In this paper, the facies estimation has been done through Multinomial logistic regression (MLR) with respect to the well logs and core data in a well in upper sandstone formation of South Rumaila oil field. The entire independent variables are gamma rays, formation density, water saturation, shale volume, log porosity, core porosity, and core permeability. Firstly, Robust Sequential Imputation Algorithm has been considered to impute the missing data. This algorithm starts from a complete subset of the dataset and estimates sequentially the missing values in an incomplete observation by minimizing the determinant of the covariance of the augmented data matrix. Then, the observation is added to the complete data matrix and the algorithm continues with the next observation with missing values. The MLR has been chosen to estimate the maximum likelihood and minimize the standard error for the nonlinear relationships between facies & core and log data. The MLR is used to predict the probabilities of the different possible facies given each independent variable by constructing a linear predictor function having a set of weights that are linearly combined with the independent variables by using a dot product. Beta distribution of facies has been considered as prior knowledge and the resulted predicted probability (posterior) has been estimated from MLR based on Baye's theorem that represents the relationship between predicted probability (posterior) with the conditional probability and the prior knowledge. To assess the statistical accuracy of the model, the bootstrap should be carried out to estimate extra-sample prediction error by randomly drawing datasets with replacement from the training data. Each sample has the same size of the original training set and it can be conducted N times to produce N bootstrap datasets to re-fit the model accordingly to decrease the squared difference between the estimated and observed categorical variables (facies) leading to decrease the degree of uncertainty.
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The Spacetime Between Einstein and Kaluza-Klein: Further Explorations
NASA Astrophysics Data System (ADS)
Vuille, Chris
2017-01-01
Tensor multinomials can be used to create a generalization of Einstein's general relativity that in a mathematical sense falls between Einstein's original theory in four dimensions and the Kaluza-Klein theory in five dimensions. In the extended theory there are only four physical dimensions, but the tensor multinomials are expanded operators that can accommodate other forces of nature. The equivalent Ricci tensor of this geometry yields vacuum general relativity and electromagnetism, as well as a Klein-Gordon-like quantum scalar field. With a generalization of the stress-energy tensor, an exact solution for a plane-symmetric dust can be found where the scalar portion of the field drives early universe inflation, levels off for a period, then causes a later continued universal acceleration, a possible geometric mechanism for the inflaton or dark energy. Some new explorations of the equations, the problems, and possibilities will be presented and discussed.
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Identification of nonclassical properties of light with multiplexing layouts
NASA Astrophysics Data System (ADS)
Sperling, J.; Eckstein, A.; Clements, W. R.; Moore, M.; Renema, J. J.; Kolthammer, W. S.; Nam, S. W.; Lita, A.; Gerrits, T.; Walmsley, I. A.; Agarwal, G. S.; Vogel, W.
2017-07-01
In Sperling et al. [Phys. Rev. Lett. 118, 163602 (2017), 10.1103/PhysRevLett.118.163602], we introduced and applied a detector-independent method to uncover nonclassicality. Here, we extend those techniques and give more details on the performed analysis. We derive a general theory of the positive-operator-valued measure that describes multiplexing layouts with arbitrary detectors. From the resulting quantum version of a multinomial statistics, we infer nonclassicality probes based on a matrix of normally ordered moments. We discuss these criteria and apply the theory to our data which are measured with superconducting transition-edge sensors. Our experiment produces heralded multiphoton states from a parametric down-conversion light source. We show that the known notions of sub-Poisson and sub-binomial light can be deduced from our general approach, and we establish the concept of sub-multinomial light, which is shown to outperform the former two concepts of nonclassicality for our data.
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Identification of nonclassical properties of light with multiplexing layouts
Sperling, J.; Eckstein, A.; Clements, W. R.; Moore, M.; Renema, J. J.; Kolthammer, W. S.; Nam, S. W.; Lita, A.; Gerrits, T.; Walmsley, I. A.; Agarwal, G. S.; Vogel, W.
2018-01-01
In Sperling et al. [Phys. Rev. Lett. 118, 163602 (2017)], we introduced and applied a detector-independent method to uncover nonclassicality. Here, we extend those techniques and give more details on the performed analysis. We derive a general theory of the positive-operator-valued measure that describes multiplexing layouts with arbitrary detectors. From the resulting quantum version of a multinomial statistics, we infer nonclassicality probes based on a matrix of normally ordered moments. We discuss these criteria and apply the theory to our data which are measured with superconducting transition-edge sensors. Our experiment produces heralded multiphoton states from a parametric down-conversion light source. We show that the known notions of sub-Poisson and sub-binomial light can be deduced from our general approach, and we establish the concept of sub-multinomial light, which is shown to outperform the former two concepts of nonclassicality for our data. PMID:29670949
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Li, Juntao; Wang, Yanyan; Jiang, Tao; Xiao, Huimin; Song, Xuekun
2018-05-09
Diagnosing acute leukemia is the necessary prerequisite to treating it. Multi-classification on the gene expression data of acute leukemia is help for diagnosing it which contains B-cell acute lymphoblastic leukemia (BALL), T-cell acute lymphoblastic leukemia (TALL) and acute myeloid leukemia (AML). However, selecting cancer-causing genes is a challenging problem in performing multi-classification. In this paper, weighted gene co-expression networks are employed to divide the genes into groups. Based on the dividing groups, a new regularized multinomial regression with overlapping group lasso penalty (MROGL) has been presented to simultaneously perform multi-classification and select gene groups. By implementing this method on three-class acute leukemia data, the grouped genes which work synergistically are identified, and the overlapped genes shared by different groups are also highlighted. Moreover, MROGL outperforms other five methods on multi-classification accuracy. Copyright © 2017. Published by Elsevier B.V.
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MPTinR: analysis of multinomial processing tree models in R.
Singmann, Henrik; Kellen, David
2013-06-01
We introduce MPTinR, a software package developed for the analysis of multinomial processing tree (MPT) models. MPT models represent a prominent class of cognitive measurement models for categorical data with applications in a wide variety of fields. MPTinR is the first software for the analysis of MPT models in the statistical programming language R, providing a modeling framework that is more flexible than standalone software packages. MPTinR also introduces important features such as (1) the ability to calculate the Fisher information approximation measure of model complexity for MPT models, (2) the ability to fit models for categorical data outside the MPT model class, such as signal detection models, (3) a function for model selection across a set of nested and nonnested candidate models (using several model selection indices), and (4) multicore fitting. MPTinR is available from the Comprehensive R Archive Network at http://cran.r-project.org/web/packages/MPTinR/ .
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El Hajj, Maguy Saffouh; Kheir, Nadir; Al Mulla, Ahmad Mohd; Shami, Rula; Fanous, Nadia; Mahfoud, Ziyad R
2017-02-20
Cigarette smoking is one of the major preventable causes of death and diseases in Qatar. The study objective was to test the effect of a structured smoking cessation program delivered by trained pharmacists on smoking cessation rates in Qatar. A prospective randomized controlled trial was conducted in eight ambulatory pharmacies in Qatar. Eligible participants were smokers 18 years and older who smoked one or more cigarettes daily for 7 days, were motivated to quit, able to communicate in Arabic or English, and attend the program sessions. Intervention group participants met with the pharmacists four times at 2 to 4 week intervals. Participants in the control group received unstructured brief smoking cessation counseling. The primary study outcome was self-reported continuous abstinence at 12 months. Analysis was made utilizing data from only those who responded and also using intent-to-treat principle. A multinomial logistic regression model was fitted to assess the predictors of smoking at 12 months. Analysis was conducted using IBM-SPSS® version 23 and STATA® version 12. A total of 314 smokers were randomized into two groups: intervention (n = 167) and control (n = 147). Smoking cessation rates were higher in the intervention group at 12 months; however this difference was not statistically significant (23.9% vs. 16.9% p = 0.257). Similar results were observed but with smaller differences in the intent to treat analysis (12.6% vs. 9.5%, p = 0.391). Nevertheless, the daily number of cigarettes smoked for those who relapsed was significantly lower (by 4.7 and 5.6 cigarettes at 3 and 6 months respectively) in the intervention group as compared to the control group (p = 0.041 and p = 0.018 respectively). At 12 months, the difference was 3.2 cigarettes in favor of the intervention group but was not statistically significant (p = 0.246). Years of smoking and daily number of cigarettes were the only predictors of smoking as opposed to quitting at 12 months (p = 0.005; p = 0.027 respectively). There was no statistically significant difference in the smoking cessation rate at 12 months between the groups. However, the smoking cessation program led to higher (albeit non-significant) smoking cessation rates compared with usual care. More research should be conducted to identify factors that might improve abstinence. Clinical Trials NCT02123329 . Registration date 20 April 2014.
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Leclerc, Bernard-Simon; Dunnigan, Lise; Côté, Harold; Zunzunegui, Maria-Victoria; Hagan, Louise; Morin, Diane
2003-01-01
Objective To validate users' perception of nurses' recommendations to look for another health resource among clients seeking teleadvice. To analyze the effects of different users' and call characteristics on the incorrectness of the self-report. Data Sources/Study Setting This study is a secondary analysis of data obtained from 4,696 randomly selected participants in a survey conducted in 1997 among users of Info-Santé CLSC, a no-charge telenursing health-line service (THLS) available all over the province of Québec. Study Design/Data Collection Self-reported advice from follow-up survey phone interviews, conducted within 48 to 120 hours after the participant's call, were compared to the data consigned by the nurse in the computerized call record. Covariables concerned characteristics of callers, context of the calls, and satisfaction about the nurses' intervention. Association between these variables and inaccurate reports was identified using multinomial logistic regression analyses. Principal Findings Advice to consult were recorded by the nurse in 42 percent of cases, whereas 39 percent of callers stated they had received one. Overall disagreement between the two sources is 27 percent (12 percent by false positive and 15 percent by false negative) and kappa is 0.45. Characteristics such as living alone (adjusted OR=2.5), calls relating to psychological problems (OR=2.8), perceived seriousness (OR=∼2.6), as well as others, were associated with inaccurate reports. Conclusions Telephone health-line providers should be aware that many callers appear to interpret advice to seek additional health care differently than intended. Our findings suggest the need for continuing quality control interventions to reduce miscommunication, insure better understanding of advice by callers, and contribute to more effective service. PMID:12785568
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Kalus, Stefanie; Kneib, Thomas; Steiger, Axel; Holsboer, Florian; Yassouridis, Alexander
2009-04-01
The human sleep process shows dynamic alterations during the night. Methods are needed to examine whether and to what extent such alterations are affected by internal, possibly time-dependent, factors, such as endocrine activity. In an observational study, we examined simultaneously sleep EEG and nocturnal levels of renin, growth hormone (GH), and cortisol (between 2300 and 0700) in 47 healthy volunteers comprising 24 women (41.67 +/- 2.93 yr of age) and 23 men (37.26 +/- 2.85 yr of age). Hormone concentrations were measured every 20 min. Conventional sleep stage scoring at 30-s intervals was applied. Semiparametric multinomial logit models are used to study and quantify possible time-dependent hormone effects on sleep stage transition courses. Results show that increased cortisol levels decrease the probability of transition from rapid-eye-movement (REM) sleep to wakefulness (WAKE) and increase the probability of transition from REM to non-REM (NREM) sleep, irrespective of the time in the night. Via the model selection criterion Akaike's information criterion, it was found that all considered hormone effects on transition probabilities with the initial state WAKE change with time. Similarly, transition from slow-wave sleep (SWS) to light sleep (LS) is affected by a "hormone-time" interaction for cortisol and renin, but not GH. For example, there is a considerable increase in the probability of SWS-LS transition toward the end of the night, when cortisol concentrations are very high. In summary, alterations in human sleep possess dynamic forms and are partially influenced by the endocrine activity of certain hormones. Statistical methods, such as semiparametric multinomial and time-dependent logit regression, can offer ambitious ways to investigate and estimate the association intensities between the nonstationary sleep changes and the time-dependent endocrine activities.
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Quaife, Matthew; Eakle, Robyn; Cabrera Escobar, Maria A; Vickerman, Peter; Kilbourne-Brook, Maggie; Mvundura, Mercy; Delany-Moretlwe, Sinead; Terris-Prestholt, Fern
2018-01-01
The development of antiretroviral (ARV)-based prevention products has the potential to substantially change the HIV prevention landscape; yet, little is known about how appealing these products will be outside of clinical trials, as compared with the existing options. We conducted a discrete choice experiment (DCE) to measure preferences for 5 new products among 4 important populations in the HIV response: adult men and women in the general population (aged 18 to 49 y), adolescent girls (aged 16 to 17 y), and self-identifying female sex workers (aged 18 to 49 y). We interviewed 661 self-reported HIV-negative participants in peri-urban South Africa, who were asked to choose between 3 unique, hypothetical products over 10 choice sets. Data were analyzed using multinomial, latent class and mixed multinomial logit models. HIV protection was the most important attribute to respondents; however, results indicate significant demand among all groups for multipurpose prevention products that offer protection from HIV infection, other STIs, and unwanted pregnancy. All groups demonstrated a strong preference for long-lasting injectable products. There was substantial heterogeneity in preferences within and across population groups. Hypothetical DCE data may not mirror real-world choices, and products will have more attributes in reality than represented in choice tasks. Background data on participants, including sensitive areas of HIV status and condom use, was self-reported. These results suggest that stimulating demand for new HIV prevention products may require a more a nuanced approach than simply developing highly effective products. No single product is likely to be equally attractive or acceptable across different groups. This study strengthens the call for effective and attractive multipurpose prevention products to be deployed as part of a comprehensive combination prevention strategy.
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OPTIMAL DESIGN FOR MULTINOMIAL CHOICE EXPERIMENTS. (R827987)
The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...
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Mabuza, Majola L; Ortmann, Gerald F; Wale, Edilegnaw; Mutenje, Munyaradzi J
2016-01-01
The aim of this article was to investigate the food (in)security effect of household income generated from major economic activities in rural Swaziland. From a sample of 979 households, the results of a multinomial treatment regression model indicated that gender of household head, labor endowment, education, size of arable land, and location significantly influenced the households' choice of primary economic activity. Further results suggested that off-farm-income-dependent households were less likely to be food insecure when compared with on-farm-income-dependent households. However, on-farm-income-dependent households had a better food security status than their counterparts who depended on remittances and nonfarm economic activities.
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Cerri, Karin H; Knapp, Martin; Fernandez, Jose-Luis
2014-09-01
The College Voor Zorgverzekeringen (CVZ) provides guidance to the Dutch healthcare system on funding and use of new pharmaceutical technologies. This study examined the impact of evidence, process and context factors on CVZ decisions in 2004-2009. A data set of CVZ decisions pertaining to pharmaceutical technologies was created, including 29 variables extracted from published information. A three-category outcome variable was used, defined as the decision to 'recommend', 'restrict' or 'not recommend' a technology. Technologies included in list 1A/1B or on the expensive drug list were considered recommended; those included in list 2 or for which patient co-payment is required were considered restricted; technologies not included on any reimbursement list were classified as 'not recommended'. Using multinomial logistic regression, the relative contribution of explanatory variables on CVZ decisions was assessed. In all, 244 technology appraisals (256 technologies) were analysed, with 51%, of technologies recommended, 33% restricted and 16% not recommended by CVZ for funding. The multinomial model showed significant associations (p ≤ 0.10) between CVZ outcome and several variables, including: (1) use of an active comparator and demonstration of statistical superiority of the primary endpoint in clinical trials, (2) pharmaceutical budget impact associated with introduction of the technology, (3) therapeutic indication and (4) prevalence of the target population. Results confirm the value of a comprehensive and multivariate approach to understanding CVZ decision-making.
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Lee, Jaeyoung; Yasmin, Shamsunnahar; Eluru, Naveen; Abdel-Aty, Mohamed; Cai, Qing
2018-02-01
In traffic safety literature, crash frequency variables are analyzed using univariate count models or multivariate count models. In this study, we propose an alternative approach to modeling multiple crash frequency dependent variables. Instead of modeling the frequency of crashes we propose to analyze the proportion of crashes by vehicle type. A flexible mixed multinomial logit fractional split model is employed for analyzing the proportions of crashes by vehicle type at the macro-level. In this model, the proportion allocated to an alternative is probabilistically determined based on the alternative propensity as well as the propensity of all other alternatives. Thus, exogenous variables directly affect all alternatives. The approach is well suited to accommodate for large number of alternatives without a sizable increase in computational burden. The model was estimated using crash data at Traffic Analysis Zone (TAZ) level from Florida. The modeling results clearly illustrate the applicability of the proposed framework for crash proportion analysis. Further, the Excess Predicted Proportion (EPP)-a screening performance measure analogous to Highway Safety Manual (HSM), Excess Predicted Average Crash Frequency is proposed for hot zone identification. Using EPP, a statewide screening exercise by the various vehicle types considered in our analysis was undertaken. The screening results revealed that the spatial pattern of hot zones is substantially different across the various vehicle types considered. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Hajdarbegovic, E; Blom, H; Verkouteren, J A C; Hofman, A; Hollestein, L M; Nijsten, T
2016-07-01
Epidermal barrier impairment and an altered immune system in atopic dermatitis (AD) may predispose to ultraviolet-induced DNA damage. To study the association between AD and actinic keratosis (AK) in a population-based cross-sectional study. AD was defined by modified criteria of the U.K. working party's diagnostic criteria. AKs were diagnosed by physicians during a full-body skin examination, and keratinocyte cancers were identified via linkage to the national pathology database. The results were analysed in adjusted multivariable and multinomial models. A lower proportion of subjects with AD had AKs than those without AD: 16% vs. 24%, P = 0·002; unadjusted odds ratio (OR) 0·60, 95% confidence interval (CI) 0·42-0·83; adjusted OR 0·74, 95% CI 0·51-1·05; fully adjusted OR 0·69, 95% CI 0·47-1·07. In a multinomial model patients with AD were less likely to have ≥ 10 AKs (adjusted OR 0·28, 95% CI 0·09-0·90). No effect of AD on basal cell carcinoma or squamous cell carcinoma was found: adjusted OR 0·71, 95% CI 0·41-1·24 and adjusted OR 1·54, 95% CI 0·66-3·62, respectively. AD in community-dwelling patients is not associated with AK. © 2016 British Association of Dermatologists.
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Semiparametric Thurstonian Models for Recurrent Choices: A Bayesian Analysis
ERIC Educational Resources Information Center
Ansari, Asim; Iyengar, Raghuram
2006-01-01
We develop semiparametric Bayesian Thurstonian models for analyzing repeated choice decisions involving multinomial, multivariate binary or multivariate ordinal data. Our modeling framework has multiple components that together yield considerable flexibility in modeling preference utilities, cross-sectional heterogeneity and parameter-driven…
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Estimation of Multinomial Probabilities.
1978-11-01
1971) and Alam (1978) have shown that the maximum likelihood estimator is admissible with respect to the quadratic loss. Steinhaus (1957) and Trybula...appear). Johnson, B. Mck. (1971). On admissible estimators for certain fixed sample binomial populations. Ann. Math. Statist. 92, 1579-1587. Steinhaus , H
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Social factors, weight perception, and weight control practices among adolescents in Mexico.
Bojorquez, Ietza; Villatoro, Jorge; Delgadillo, Marlene; Fleiz, Clara; Fregoso, Diana; Unikel, Claudia
2018-06-01
We evaluated the association of social factors and weight control practices in adolescents, and the mediation of this association by weight perception, in a national survey of students in Mexico ( n = 28,266). We employed multinomial and Poisson regression models and Sobel's test to assess mediation. Students whose mothers had a higher level of education were more likely to perceive themselves as overweight and also to engage in weight control practices. After adjusting for body weight perception, the effect of maternal education on weight control practices remained significant. Mediation tests were significant for boys and non-significant for girls.
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Sensitivity of Raman spectroscopy to normal patient variability
NASA Astrophysics Data System (ADS)
Vargis, Elizabeth; Byrd, Teresa; Logan, Quinisha; Khabele, Dineo; Mahadevan-Jansen, Anita
2011-11-01
Many groups have used Raman spectroscopy for diagnosing cervical dysplasia; however, there have been few studies looking at the effect of normal physiological variations on Raman spectra. We assess four patient variables that may affect normal Raman spectra: Race/ethnicity, body mass index (BMI), parity, and socioeconomic status. Raman spectra were acquired from a diverse population of 75 patients undergoing routine screening for cervical dysplasia. Classification of Raman spectra from patients with a normal cervix is performed using sparse multinomial logistic regression (SMLR) to determine if any of these variables has a significant effect. Results suggest that BMI and parity have the greatest impact, whereas race/ethnicity and socioeconomic status have a limited effect. Incorporating BMI and obstetric history into classification algorithms may increase sensitivity and specificity rates of disease classification using Raman spectroscopy. Studies are underway to assess the effect of these variables on disease.
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Positive and negative generation effects in source monitoring.
Riefer, David M; Chien, Yuchin; Reimer, Jason F
2007-10-01
Research is mixed as to whether self-generation improves memory for the source of information. We propose the hypothesis that positive generation effects (better source memory for self-generated information) occur in reality-monitoring paradigms, while negative generation effects (better source memory for externally presented information) tend to occur in external source-monitoring paradigms. This hypothesis was tested in an experiment in which participants read or generated words, followed by a memory test for the source of each word (read or generated) and the word's colour. Meiser and Bröder's (2002) multinomial model for crossed source dimensions was used to analyse the data, showing that source memory for generation (reality monitoring) was superior for the generated words, while source memory for word colour (external source monitoring) was superior for the read words. The model also revealed the influence of strong response biases in the data, demonstrating the usefulness of formal modelling when examining generation effects in source monitoring.
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Wiener, R Constance; Vohra, Rini; Sambamoorthi, Usha; Madhavan, S Suresh
2016-12-01
Objective The purpose of this study is to examine the burdens of caregivers on perception of the need and receipt of preventive dental care for a subset of children with special health care needs-children with Autism Spectrum disorder, developmental disability and/or mental health conditions (CASD/DD/MHC). Methods The authors used the 2009-2010 National Survey of CSHCN. The survey included questions addressing preventive dental care and caregivers' financial, employment, and time-related burdens. The associations of these burdens on perceptions and receipt of preventive dental care use were analyzed with bivariate Chi square analyses and multinomial logistic regressions for CASD/DD/MHC (N = 16,323). Results Overall, 16.3 % of CASD/DD/MHC had an unmet preventive dental care need. There were 40.0 % of caregivers who reported financial burden, 20.3 % who reported employment burden, and 10.8 % who reported time burden. A higher percentage of caregivers with financial burden, employment burden, and time-related burden reported that their CASD/DD/MHC did not receive needed preventive dental care (14.1, 16.5, 17.7 % respectively) compared to caregivers without financial, employment, or time burdens (9.0, 9.6 %, 11.0 % respectively). Caregivers with financial burden (adjusted multinomial odds ratio, 1.38 [95 % CI 1.02, 1.86] and employment burden (adjusted multinomial odds ratio, 1.45 [95 % CI 1.02, 2.06] were more likely to report that their child did not receive preventive dental care despite perceived need compared to caregivers without financial or employment burdens. Conclusions for practice Unmet needs for preventive dental care were associated with employment and financial burdens of the caregivers of CASD/DD/MHC.
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Vohra, Rini; Sambamoorthi, Usha; Madhavan, S. Suresh
2016-01-01
Objective The purpose of this study is to examine the burdens of caregivers on one perception of the need and receipt of preventive dental care for a subset of children with special health care needs—children with Autism Spectrum disorder, developmental disability and/or mental health conditions (CASD/DD/MHC). Methods The authors used the 2009–2010 National Survey of CSHCN. The survey included questions addressing preventive dental care and caregivers’ financial, employment, and time-related burdens. The associations of these burdens on perceptions and receipt of preventive dental care use were analyzed with bivariate Chi square analyses and multinomial logistic regressions for CASD/DD/MHC (N=16,323). Results Overall, 16.3% of CASD/DD/MHC had an unmet preventive dental care need. There were 40.0% of caregivers who reported financial burden, 20.3% who reported employment burden, and 10.8% who reported time burden. A higher percentage of caregivers with financial burden, employment burden, and time-related burden reported that their CASD/DD/MHC did not receive needed preventive dental care (14.1 %, 16.5%, 17.7% respectively) compared to caregivers without financial, employment, or time burdens (9.0%, 9.6%, 11.0% respectively). Caregivers with financial burden (adjusted multinomial odds ratio, 1.38 [95%CI: 1.02, 1.86]) and employment burden (adjusted multinomial odds ratio, 1.45 [95%CI: 1.02, 2.06]) were more likely to report that their child did not receive preventive dental care despite perceived need compared to caregivers without financial or employment burdens. Conclusions for practice Unmet needs for preventive dental care were associated with employment and financial burdens of the caregivers of CASD/DD/MHC. PMID:27465058
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Chronic disease prevalence among elderly Saudi men.
Saquib, Nazmus; Saquib, Juliann; Alhadlag, Abdulrahman; Albakour, Mohamad Anas; Aljumah, Bader; Sughayyir, Mohammed; Alhomidan, Ziad; Alminderej, Omar; Aljaser, Mohamed; Al-Mazrou, Abdulrahman
2017-01-01
Saudi demographic composition has changed because of increased life expectancy and decreased fertility rates. Little data are available about health conditions among older adults in Saudi Arabia, who are expected to represent 20% of the population by 2050. The study aim was to assess the prevalence and risk factors for chronic conditions among older Saudi men. The sample pertained to 400 men (age ≥55 years) from Buraidah, Al-Qassim. Research assistants recruited participants in all the mosques from the randomly selected neighborhoods (16 of 95). They administered a structured questionnaire that assessed self-reported disease history (heart disease, hypertension, diabetes, asthma, gastric/peptic ulcer, and cancer), and medication use; participants' height, weight, blood pressure, and random blood glucose (glucometer) were measured. Multinomial logistic regressions were employed to assess correlates of number of chronic diseases. The mean and standard deviation for age and body mass index (BMI) were 63.0 ± 7.5 years and 28.9 ± 4.8 (kg/m 2 ), respectively. 78% (77.8%) were overweight or obese, 35.0% were employed, 54.5% walked daily, 9.3% were current smokers, and 85.0% belonged to the middle class. The prevalence of hypertension, diabetes, heart disease, asthma, ulcer, and cancer were: 71.3% 27.3%, 16.4%, 9.7%, 8.9%, and 2.0%, respectively. Of the participants, 31.0% had one, 34.5% had two or more, and 34.5% did not have any chronic diseases. The likelihood of chronic diseases increased with increased age, higher BMI, and current smoking. The chronic disease prevalence among the Saudi elderly men is substantial.
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Trajectories of suicidal ideation over 6 months among 482 outpatients with bipolar disorder.
Köhler-Forsberg, Ole; Madsen, Trine; Behrendt-Møller, Ida; Sylvia, Louisa; Bowden, Charles L; Gao, Keming; Bobo, William V; Trivedi, Madhukar H; Calabrese, Joseph R; Thase, Michael; Shelton, Richard C; McInnis, Melvin; Tohen, Mauricio; Ketter, Terence A; Friedman, Edward S; Deckersbach, Thilo; McElroy, Susan L; Reilly-Harrington, Noreen A; Nierenberg, Andrew A
2017-12-01
Suicidal ideation occurs frequently among individuals with bipolar disorder; however, its course and persistence over time remains unclear. We aimed to investigate 6-months trajectories of suicidal ideation among adults with bipolar disorder. The Bipolar CHOICE study randomized 482 outpatients with bipolar disorder to 6 months of lithium- or quetiapine-based treatment including other psychotropic medications as clinically indicated. Participants were asked at 9 visits about suicidal ideation using the Concise Health Risk Tracking scale. We performed latent Growth Mixture Modelling analysis to empirically identify trajectories of suicidal ideation. Multinomial logistic regression analyses were applied to estimate associations between trajectories and potential predictors. We identified four distinct trajectories. The Moderate-Stable group represented 11.1% and was characterized by constant suicidal ideation. The Moderate-Unstable group included 2.9% with persistent thoughts about suicide with a more fluctuating course. The third (Persistent-low, 20.8%) and fourth group (Persistent-very-low, 65.1%) were characterized by low levels of suicidal ideation. Higher depression scores and previous suicide attempts (non-significant trend) predicted membership of the Moderate-Stable group, whereas randomized treatment did not. No specific treatments against suicidal ideation were included and suicidal thoughts may persist for several years. More than one in ten adult outpatients with bipolar disorder had moderately increased suicidal ideation throughout 6 months of pharmacotherapy. The identified predictors may help clinicians to identify those with additional need for treatment against suicidal thoughts and future studies need to investigate whether targeted treatment (pharmacological and non-pharmacological) may improve the course of persistent suicidal ideation. Copyright © 2017 Elsevier B.V. All rights reserved.
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Graffelman, Jan; Sánchez, Milagros; Cook, Samantha; Moreno, Victor
2013-01-01
In genetic association studies, tests for Hardy-Weinberg proportions are often employed as a quality control checking procedure. Missing genotypes are typically discarded prior to testing. In this paper we show that inference for Hardy-Weinberg proportions can be biased when missing values are discarded. We propose to use multiple imputation of missing values in order to improve inference for Hardy-Weinberg proportions. For imputation we employ a multinomial logit model that uses information from allele intensities and/or neighbouring markers. Analysis of an empirical data set of single nucleotide polymorphisms possibly related to colon cancer reveals that missing genotypes are not missing completely at random. Deviation from Hardy-Weinberg proportions is mostly due to a lack of heterozygotes. Inbreeding coefficients estimated by multiple imputation of the missings are typically lowered with respect to inbreeding coefficients estimated by discarding the missings. Accounting for missings by multiple imputation qualitatively changed the results of 10 to 17% of the statistical tests performed. Estimates of inbreeding coefficients obtained by multiple imputation showed high correlation with estimates obtained by single imputation using an external reference panel. Our conclusion is that imputation of missing data leads to improved statistical inference for Hardy-Weinberg proportions.
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Roberts, Michaela; Hanley, Nick; Cresswell, Will
2017-09-15
While ecological links between ecosystems have been long recognised, management rarely crosses ecosystem boundaries. Coral reefs are susceptible to damage through terrestrial run-off, and failing to account for this within management threatens reef protection. In order to quantify the extent to that coral reef users are willing to support management actions to improve ecosystem quality, we conducted a choice experiment with SCUBA divers on the island of Bonaire, Caribbean Netherlands. Specifically, we estimated their willingness to pay to reduce terrestrial overgrazing as a means to improve reef health. Willingness to pay was estimated using the multinomial, random parameter and latent class logit models. Willingness to pay for improvements to reef quality was positive for the majority of respondents. Estimates from the latent class model determined willingness to pay for reef improvements of between $31.17 - $413.18/year, dependent on class membership. This represents a significant source of funding for terrestrial conservation, and illustrates the potential for user fees to be applied across ecosystem boundaries. We argue that such across-ecosystem-boundary funding mechanisms are an important avenue for future investigation in many connected systems. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Exploring Sampling in the Detection of Multicategory EEG Signals
Siuly, Siuly; Kabir, Enamul; Wang, Hua; Zhang, Yanchun
2015-01-01
The paper presents a structure based on samplings and machine leaning techniques for the detection of multicategory EEG signals where random sampling (RS) and optimal allocation sampling (OS) are explored. In the proposed framework, before using the RS and OS scheme, the entire EEG signals of each class are partitioned into several groups based on a particular time period. The RS and OS schemes are used in order to have representative observations from each group of each category of EEG data. Then all of the selected samples by the RS from the groups of each category are combined in a one set named RS set. In the similar way, for the OS scheme, an OS set is obtained. Then eleven statistical features are extracted from the RS and OS set, separately. Finally this study employs three well-known classifiers: k-nearest neighbor (k-NN), multinomial logistic regression with a ridge estimator (MLR), and support vector machine (SVM) to evaluate the performance for the RS and OS feature set. The experimental outcomes demonstrate that the RS scheme well represents the EEG signals and the k-NN with the RS is the optimum choice for detection of multicategory EEG signals. PMID:25977705
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Risk Factors Associated with Peer Victimization and Bystander Behaviors among Adolescent Students.
Huang, Zepeng; Liu, Zhenni; Liu, Xiangxiang; Lv, Laiwen; Zhang, Yan; Ou, Limin; Li, Liping
2016-07-27
Despite the prevalence of the phenomena of peer victimization and bystander behaviors, little data has generated to describe their relationships and risk factors. In this paper, a self-administered survey using a cross-sectional cluster-random sampling method in a sample of 5450 participants (2734 girls and 2716 boys) between 4th and 11th grades was conducted at six schools (two primary schools and four middle schools) located in Shantou, China. Self-reported peer victimization, bystander behaviors and information regarding parents' risky behaviors and individual behavioral factors were collected. Multinomial logistic regression analysis was applied to evaluate risk factors affecting peer victimization and bystander behaviors. The results indicated that urban participants were more likely to become bullying victims but less likely to become passive bystanders. Contrarily, bullying victimization was related to the increasing of passive bystander behaviors. Father drinking and mother smoking as independent factors were risk factors for peer victimization. Participants who were smoking or drinking had a tendency to be involved in both peer victimization and passive bystander behaviors. This study suggested that bystander behaviors, victims' and parents' educations play a more important role in peer victimization than previously thought.
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Contributions of sociodemographic factors to criminal behavior
Mundia, Lawrence; Matzin, Rohani; Mahalle, Salwa; Hamid, Malai Hayati; Osman, Ratna Suriani
2016-01-01
We explored the extent to which prisoner sociodemographic variables (age, education, marital status, employment, and whether their parents were married or not) influenced offending in 64 randomly selected Brunei inmates, comprising both sexes. A quantitative field survey design ideal for the type of participants used in a prison context was employed to investigate the problem. Hierarchical multiple regression analysis with backward elimination identified prisoner marital status and age groups as significantly related to offending. Furthermore, hierarchical multinomial logistic regression analysis with backward elimination indicated that prisoners’ age, primary level education, marital status, employment status, and parental marital status as significantly related to stealing offenses with high odds ratios. All 29 nonrecidivists were false negatives and predicted to reoffend upon release. Similarly, all 33 recidivists were projected to reoffend after release. Hierarchical binary logistic regression analysis revealed age groups (24–29 years and 30–35 years), employed prisoner, and primary level education as variables with high likelihood trends for reoffending. The results suggested that prisoner interventions (educational, counseling, and psychotherapy) in Brunei should treat not only antisocial personality, psychopathy, and mental health problems but also sociodemographic factors. The study generated offending patterns, trends, and norms that may inform subsequent investigations on Brunei prisoners. PMID:27382342
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An introduction to multidimensional measurement using Rasch models.
Briggs, Derek C; Wilson, Mark
2003-01-01
The act of constructing a measure requires a number of important assumptions. Principle among these assumptions is that the construct is unidimensional. In practice there are many instances when the assumption of unidimensionality does not hold, and where the application of a multidimensional measurement model is both technically appropriate and substantively advantageous. In this paper we illustrate the usefulness of a multidimensional approach to measurement with the Multidimensional Random Coefficient Multinomial Logit (MRCML) model, an extension of the unidimensional Rasch model. An empirical example is taken from a collection of embedded assessments administered to 541 students enrolled in middle school science classes with a hands-on science curriculum. Student achievement on these assessments are multidimensional in nature, but can also be treated as consecutive unidimensional estimates, or as is most common, as a composite unidimensional estimate. Structural parameters are estimated for each model using ConQuest, and model fit is compared. Student achievement in science is also compared across models. The multidimensional approach has the best fit to the data, and provides more reliable estimates of student achievement than under the consecutive unidimensional approach. Finally, at an interpretational level, the multidimensional approach may well provide richer information to the classroom teacher about the nature of student achievement.
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Social branding to decrease smoking among young adults in bars.
Ling, Pamela M; Lee, Youn Ok; Hong, Juliette; Neilands, Torsten B; Jordan, Jeffrey W; Glantz, Stanton A
2014-04-01
We evaluated a Social Branding antitobacco intervention for "hipster" young adults that was implemented between 2008 and 2011 in San Diego, California. We conducted repeated cross-sectional surveys of random samples of young adults going to bars at baseline and over a 3-year follow-up. We used multinomial logistic regression to evaluate changes in daily smoking, nondaily smoking, and binge drinking, controlling for demographic characteristics, alcohol use, advertising receptivity, trend sensitivity, and tobacco-related attitudes. During the intervention, current (past 30 day) smoking decreased from 57% (baseline) to 48% (at follow-up 3; P = .002), and daily smoking decreased from 22% to 15% (P < .001). There were significant interactions between hipster affiliation and alcohol use on smoking. Among hipster binge drinkers, the odds of daily smoking (odds ratio [OR] = 0.44; 95% confidence interval [CI] = 0.30, 0.63) and nondaily smoking (OR = 0.57; 95% CI = 0.42, 0.77) decreased significantly at follow-up 3. Binge drinking also decreased significantly at follow-up 3 (OR = 0.64; 95% CI = 0.53, 0.78). Social Branding campaigns are a promising strategy to decrease smoking in young adult bar patrons.
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Cwik, Jan C; Papen, Fabienne; Lemke, Jan-Erik; Margraf, Jürgen
2016-01-01
This study examines the utility of checklists in attaining more accurate diagnoses in the context of diagnostic decision-making for mental disorders. The study also aimed to replicate results from a meta-analysis indicating that there is no association between patients' gender and misdiagnoses. To this end, 475 psychotherapists were asked to judge three case vignettes describing patients with Major Depressive Disorder (MDD), Generalized Anxiety Disorder, and Borderline Personality Disorder. Therapists were randomly assigned to experimental conditions in a 2 (diagnostic method: with using diagnostic checklists vs. without using diagnostic checklists) × 2 (gender: male vs. female case vignettes) between-subjects design. Multinomial logistic and linear regression analyses were used to examine the association between the usage of diagnostic checklists as well as patients' gender and diagnostic decisions. The results showed that when checklists were used, fewer incorrect co-morbid diagnoses were made, but clinicians were less likely to diagnose MDD even when the criteria were met. Additionally, checklists improved therapists' confidence with diagnostic decisions, but were not associated with estimations of patients' characteristics. As expected, there were no significant associations between gender and diagnostic decisions.
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Panwar, Bharat; Raghava, Gajendra P S
2015-04-01
The RNA-protein interactions play a diverse role in the cells, thus identification of RNA-protein interface is essential for the biologist to understand their function. In the past, several methods have been developed for predicting RNA interacting residues in proteins, but limited efforts have been made for the identification of protein-interacting nucleotides in RNAs. In order to discriminate protein-interacting and non-interacting nucleotides, we used various classifiers (NaiveBayes, NaiveBayesMultinomial, BayesNet, ComplementNaiveBayes, MultilayerPerceptron, J48, SMO, RandomForest, SMO and SVM(light)) for prediction model development using various features and achieved highest 83.92% sensitivity, 84.82 specificity, 84.62% accuracy and 0.62 Matthew's correlation coefficient by SVM(light) based models. We observed that certain tri-nucleotides like ACA, ACC, AGA, CAC, CCA, GAG, UGA, and UUU preferred in protein-interaction. All the models have been developed using a non-redundant dataset and are evaluated using five-fold cross validation technique. A web-server called RNApin has been developed for the scientific community (http://crdd.osdd.net/raghava/rnapin/). Copyright © 2015 Elsevier Inc. All rights reserved.
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Statistical Development and Application of Cultural Consensus Theory
2012-03-31
Bulletin & Review , 17, 275-286. Schmittmann, V.D., Dolan, C.V., Raijmakers, M.E.J., and Batchelder, W.H. (2010). Parameter identification in...Wu, H., Myung, J.I., and Batchelder, W.H. (2010). Minimum description length model selection of multinomial processing tree models. Psychonomic
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Sinaiko, Anna D
2011-04-01
To assess how quality information from multiple sources and financial incentives affect consumer choice of physicians in tiered physician networks. Survey of a stratified random sample of Massachusetts state employees. Respondents were assigned a hypothetical structure with differential copayments for "Tier 1" (preferred) and "Tier 2" (nonpreferred) physicians. Half of respondents were told they needed to select a cardiologist, and half were told they needed to select a dermatologist. Patients were asked whether they would choose a Tier 1 doctor, a Tier 2 doctor, or had no preference in a case where they had no further quality information, a case where a family member or friend recommended a Tier 2 doctor, and a case where their personal physician recommended a Tier 2 doctor. The effects of copayments, recommendations, physician specialty, and patient characteristics on the reported probability of selecting a Tier 1 doctor are analyzed using multinomial logit and logistic regression. Relative to a case where there is no copayment differential between tiers, copayment differences of U.S.$10-U.S.$35 increase the number of respondents indicating they would select a Tier 1 physician by 3.5-11.7 percent. Simulations suggest copayments must exceed U.S.$300 to counteract the recommendation for a lower tiered physician from friends, family, or a referring physician. Sensitivity to the copayments varied with physician specialty. Tiered provider networks with these copayment levels appear to have limited influence on physician choice when contradicted by other trusted sources. Consumers' response likely varies with physician specialty. © Health Research and Educational Trust.
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Cadavid-Betancur, David A; Ospina, Marta C; Hincapié-Palacio, Doracelly; Bernal-Restrepo, Luz M; Buitrago-Giraldo, Seti; Perez-Toro, Olga; Santacruz-Sanmartín, Eduardo; Lenis-Ballesteros, Viviana; Almanza-Payares, Rita; Díaz, Francisco J
2017-09-05
The seroprevalence of hepatitis B (HB) and of potentially associated factors in Medellin, Colombia, were investigated 17years after the start of universal vaccination. Biological and sociodemographic data from a population survey with a multistage random sampling were analyzed in 6-64year old individuals. HB surface antigen, total HB core antibodies and HB surface antibodies, and in some cases IgM antibodies to HB core antigen, were tested in 2077 samples. Factors potentially associated with and natural, and vaccine immunity relative to susceptibility (absence of any marker) were analyzed using a multinomial logistic regression. The prevalence of serological patterns was: chronic infection 0.20% (95% CI 0.11-0.71), vaccine immunity 25.10% (95% CI 21.72-28.83) and natural immunity 2.60% (95% CI 1.80-3.74). No markers were detected in 71.30% (95% CI 67.70-74.83) of the individuals and evidence of recent infection was not detected. Relative to the absence of markers, natural immunity was potentially associated with age (6-17years and 41-64years) and sleeping less than 6 hours, while vaccine immunity was associated with age (6-17years), reporting vaccination against HB, belonging to high socioeconomic strata, home ownership and being obese, after adjusting for other variables. These results may be a population effect of mass vaccination. It is recommended to complete the vaccination schedule and to study in detail, persistence of antibodies and the role of obesity and socioeconomic strata in the vaccine immunity. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Weaver, Emma R. N.; Agius, Paul A.; Veale, Hilary; Dorning, Karl; Hlang, Thein T.; Aung, Poe P.; Fowkes, Freya J. I.; Hellard, Margaret E.
2016-01-01
Gastrointestinal diseases are major contributors to mortality among children globally, causing one in 10 child deaths. Although most deaths are in children aged ≤ 5 years, the burden of disease in school-aged children is still considerable and contributes to high rates of school absenteeism. This study investigates behavioral and structural risk factors associated with diarrhea and/or vomiting among schoolchildren in Myanmar. Cross-sectional data from a school-based multistage cluster sample of grade 4 and 5 students were analyzed to explore water, sanitation, and hygiene (WASH) facilities and hygiene-related practices of students in monastic schools in Myanmar. The outcome of interest was student self-reported diarrhea and/or vomiting in the past week. Random effects multinomial logistic regression models were used to explore correlates at the student and school level. A total of 2,082 students from 116 schools across eight states/regions were included. Of these, 11% (223) self-reported at least one episode of diarrhea only, 12% (253) at least one episode of vomiting only, and 12% (244) diarrhea and vomiting in the past week. Independent risk factors associated with the outcome included poor availability of handwash stations, no access to a septic tank toilet, inconsistent toilet use, and lower student grade. These findings highlight the importance of having an adequate number of handwash stations for students, the provision of septic tank toilets, and consistent toilet use. Future WASH programs need to target not only the provision of these WASH facilities but also their utilization, particularly among younger school-aged children. PMID:27325805
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Factors associated with disordered gambling in Finland
2013-01-01
Background The purpose of this study was to compare the socio-demographic characteristics of non-problem gamblers, problem gamblers and pathological gamblers, to investigate the association between gambling related factors and perceived health and well-being among the three subgroups of gamblers, and to analyse simultaneously socio-demographic characteristics, gambling related factors and perceived health and well-being and the severity of disordered gambling (problem gamblers and pathological gamblers). Methods The data were collected through a nationwide telephone survey in 2011. Participants were selected through a random population sample of 15-74-year-old Finns. From that sample, persons with any past-year gambling involvement (N = 3451) were selected for a subsample for the descriptive and inferential analysis in the present paper. Gambling was assessed using the South Oaks Gambling Screen. Statistical significance was determined by chi-squared tests. The odds ratio and effect size were computed by using multivariate-adjusted multinomial logistic regression analysis. Results The most significant socio-demographic characteristics (male gender, young age, education ≤12 years), gambling related factors (slot machine gambling, internet gambling) and perceived health and well-being (feeling lonely, smoking daily, risky alcohol consumption, mental health problems) explained 22.9 per cent of the variation in the severity of disordered gambling. Conclusion Male gender and loneliness were found to be associated with problem gambling in particular, along with smoking and risky alcohol consumption. Mental health problems and risky alcohol consumption were associated with pathological gambling. These identified associations between disordered gambling, mental health problems and risky alcohol consumption should be taken into consideration when implementing screenings of disordered gambling. PMID:23816162
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Aging, subjective experience, and cognitive control: dramatic false remembering by older adults.
Jacoby, Larry L; Bishara, Anthony J; Hessels, Sandra; Toth, Jeffrey P
2005-05-01
Recent research suggests that older adults are more susceptible to interference effects than are young adults; however, that research has failed to equate differences in original learning. In 4 experiments, the authors show that older adults are more susceptible to interference effects produced by a misleading prime. Even when original learning was equated, older adults were 10 times as likely to falsely remember misleading information and were much less likely to increase their accuracy by opting not to answer under conditions of free responding. The results are well described by a multinomial model that postulates multiple modes of cognitive control. According to that model, older adults are likely to be captured by misleading information, a form of goal neglect or deficit in inhibitory functions. Copyright 2005 APA, all rights reserved.
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Hooman, A.; Mohammadzadeh, M
Some medical and epidemiological surveys have been designed to predict a nominal response variable with several levels. With regard to the type of pregnancy there are four possible states: wanted, unwanted by wife, unwanted by husband and unwanted by couple. In this paper, we have predicted the type of pregnancy, as well as the factors influencing it using three different models and comparing them. Regarding the type of pregnancy with several levels, we developed a multinomial logistic regression, a neural network and a flexible discrimination based on the data and compared their results using tow statistical indices: Surface under curvemore » (ROC) and kappa coefficient. Based on these tow indices, flexible discrimination proved to be a better fit for prediction on data in comparison to other methods. When the relations among variables are complex, one can use flexible discrimination instead of multinomial logistic regression and neural network to predict the nominal response variables with several levels in order to gain more accurate predictions.« less
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Polcicová, Gabriela; Tino, Peter
2004-01-01
We introduce topographic versions of two latent class models (LCM) for collaborative filtering. Latent classes are topologically organized on a square grid. Topographic organization of latent classes makes orientation in rating/preference patterns captured by the latent classes easier and more systematic. The variation in film rating patterns is modelled by multinomial and binomial distributions with varying independence assumptions. In the first stage of topographic LCM construction, self-organizing maps with neural field organized according to the LCM topology are employed. We apply our system to a large collection of user ratings for films. The system can provide useful visualization plots unveiling user preference patterns buried in the data, without loosing potential to be a good recommender model. It appears that multinomial distribution is most adequate if the model is regularized by tight grid topologies. Since we deal with probabilistic models of the data, we can readily use tools from probability and information theories to interpret and visualize information extracted by our system.
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A multilevel model for comorbid outcomes: obesity and diabetes in the US.
Congdon, Peter
2010-02-01
Multilevel models are overwhelmingly applied to single health outcomes, but when two or more health conditions are closely related, it is important that contextual variation in their joint prevalence (e.g., variations over different geographic settings) is considered. A multinomial multilevel logit regression approach for analysing joint prevalence is proposed here that includes subject level risk factors (e.g., age, race, education) while also taking account of geographic context. Data from a US population health survey (the 2007 Behavioral Risk Factor Surveillance System or BRFSS) are used to illustrate the method, with a six category multinomial outcome defined by diabetic status and weight category (obese, overweight, normal). The influence of geographic context is partly represented by known geographic variables (e.g., county poverty), and partly by a model for latent area influences. In particular, a shared latent variable (common factor) approach is proposed to measure the impact of unobserved area influences on joint weight and diabetes status, with the latent variable being spatially structured to reflect geographic clustering in risk.
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Compensation of hospital-based physicians.
Steinwald, B
1983-01-01
This study is concerned with methods of compensating hospital-based physicians (HBPs) in five medical specialties: anesthesiology, pathology, radiology, cardiology, and emergency medicine. Data on 2232 nonfederal, short-term general hospitals came from a mail questionnaire survey conducted in Fall 1979. The data indicate that numerous compensation methods exist but these methods, without much loss of precision, can be reduced to salary, percentage of department revenue, and fee-for-service. When HBPs are compensated by salary or percentage methods, most patient billing is conducted by the hospital. In contrast, most fee-for-service HBPs bill their patients directly. Determinants of HBP compensation methods are investigated via multinomial logit analysis. This analysis indicates that choice of HBP compensation methods are investigated via multinomial logit analysis. This analysis indicates that choice of HBP compensation methods is sensitive to a number of hospital characteristics and attributes of both the hospital and physicians' services markets. The empirical findings are discussed in light of past conceptual and empirical research on physician compensation, and current policy issues in the health services sector. PMID:6841112
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Predictors of Early Termination in a University Counseling Training Clinic
ERIC Educational Resources Information Center
Lampropoulos, Georgios K.; Schneider, Mercedes K.; Spengler, Paul M.
2009-01-01
Despite the existence of counseling dropout research, there are limited predictive data for counseling in training clinics. Potential predictor variables were investigated in this archival study of 380 client files in a university counseling training clinic. Multinomial logistic regression, predictive discriminant analysis, and classification and…
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Understanding Civic Identity in College
ERIC Educational Resources Information Center
Weerts, David J.; Cabrera, Alberto F.
2015-01-01
Past literature has examined ways in which college students adopt civic identities. However, little is known about characteristics of students that vary in their expression of these identities. Drawing on data from American College Testing (ACT), this study employs multinomial logistic regression to understand attributes of students who vary in…
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Evaluating the Locational Attributes of Education Management Organizations (EMOs)
ERIC Educational Resources Information Center
Gulosino, Charisse; Miron, Gary
2017-01-01
This study uses logistic and multinomial logistic regression models to analyze neighborhood factors affecting EMO (Education Management Organization)-operated schools' locational attributes (using census tracts) in 41 states for the 2014-2015 school year. Our research combines market-based school reform, institutional theory, and resource…
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Intergroup Relations and Predictors of Immigrant Experience
ERIC Educational Resources Information Center
Danso, Kofi; Lum, Terry
2013-01-01
Using survey data from 1,036 participants, which included 4 immigrant groups, we examined the factors that influence immigrants' experiences as they interact with nonimmigrant Americans. Logistic and multinomial regression results indicate that non-European immigrants were more likely to report negative experiences with Americans. The odds of…
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The Role of Predictor Courses and Teams on Individual Student Success
ERIC Educational Resources Information Center
Baker-Eveleth, Lori Jo; O'Neill, Michele; Sisodiya, Sanjay R.
2014-01-01
Research suggests that diverse environments enhance conscious modes of thought, resulting in greater intellectual engagement and active thinking. Ordinal and multinomial logistic regression results indicate that accounting courses and business law classes are useful predictors of subsequent performance. Odds ratio estimates indicate that students…
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Choice-Based Segmentation as an Enrollment Management Tool
ERIC Educational Resources Information Center
Young, Mark R.
2002-01-01
This article presents an approach to enrollment management based on target marketing strategies developed from a choice-based segmentation methodology. Students are classified into "switchable" or "non-switchable" segments based on their probability of selecting specific majors. A modified multinomial logit choice model is used to identify…
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Caregivers' Retirement Congruency: A Case for Caregiver Support
ERIC Educational Resources Information Center
Humble, Aine M.; Keefe, Janice M.; Auton, Greg M.
2012-01-01
Using the concept of "retirement congruency" (RC), which takes into account greater variation in retirement decisions (low, moderate, or high RC) than a dichotomous conceptualization (forced versus chosen), multinomial logistic regression was conducted on a sample of caregivers from the 2002 Canadian General Social Survey who were…
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Depta, Adam; Jewczak, Maciej; Skura-Madziała, Anna
2017-10-01
The quality of life (QoL) experienced by cancer patients depends both on their state of health and on sociodemographic factors. Tumours in the head and neck region have a particularly adverse effect on patients psychologically and on their social functioning. The study involved 121 patients receiving radiotherapy treatment for head and neck cancers. They included 72 urban and 49 rural residents. QoL was assessed using the questionnaires EORTC-QLQ-C30 and QLQ-H&N35. The data were analysed using statistical methods: a χ 2 test for independence and a multinomial logit model. The evaluation of QoL showed a strong, statistically significant, positive dependence on state of health, and a weak dependence on sociodemographic factors and place of residence. Evaluations of financial situation and living conditions were similar for rural and urban residents. Patients from urban areas had the greatest anxiety about deterioration of their state of health. Rural respondents were more often anxious about a worsening of their financial situation, and expressed a fear of loneliness. Studying the QoL of patients with head and neck cancer provides information concerning the areas in which the disease inhibits their lives, and the extent to which it does so. It indicates conditions for the adaptation of treatment and care methods in the healthcare system which might improve the QoL of such patients. A multinomial logit model identifies the factors determining the patients' health assessment and defines the probable values of such assessment.
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do Nascimento, Carla Ferreira; Duarte, Yeda Aparecida Oliveira; Lebrão, Maria Lúcia; Chiavegatto Filho, Alexandre Dias Porto
To analyze a representative sample of older individuals of São Paulo, Brazil, according to outdoor fallers, indoor fallers and non-fallers, and to identify biological and socioeconomic (individual and contextual) factors associated with the occurrence and place of falls. A cross-sectional study was conducted using data (n = 1345) from the 2010 wave of the Health, Wellbeing and Aging (SABE) Study, a representative sample of older residents (60 years and older) of São Paulo, Brazil. Multinomial logistic analysis was performed to identify individual factors associated with the occurrence and place of falls, and multilevel multinomial analysis to identify contextual effects (green areas, violence, presence of slums and income inequality). 29% had a fall in the last 12 months, with 59% occurring in indoor spaces. Individuals who had outdoor falls were overall not statistically different from non-fallers; on the other hand, those who had the last fall indoor had worse health status. Moderate homicide rate was a factor associated with increased presence of indoor falls, compared with non-fallers. Our results describe the importance of falls, a common problem in active and community-dwelling older adults of São Paulo, Brazil. Transforming outdoor spaces into walk-friendly areas is essential to allow socialization and autonomy with safety. Creating strategies that take into account the most vulnerable populations, as those who live in violent areas and the oldest older adults, will be a growing challenge among developing countries. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
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Shah, Gulzar H; Badana, Adrian N S; Robb, Claire; Livingood, William C
2016-01-01
Local health departments (LHDs) are striving to meet public health needs within their jurisdictions, amidst fiscal restraints and complex dynamic environment. Resource sharing across jurisdictions is a critical opportunity for LHDs to continue to enhance effectiveness and increase efficiency. This research examines the extent of cross-jurisdictional resource sharing among LHDs, the programmatic areas and organizational functions for which LHDs share resources, and LHD characteristics associated with resource sharing. Data from the National Association of County & City Health Officials' 2013 National Profile of LHDs were used. Descriptive statistics and multinomial logistic regression were performed for the 5 implementation-oriented outcome variables of interest, with 3 levels of implementation. More than 54% of LHDs shared resources such as funding, staff, or equipment with 1 or more other LHDs on a continuous, recurring basis. Results from the multinomial regression analysis indicate that economies of scale (population size and metropolitan status) had significant positive influences (at P ≤ .05) on resource sharing. Engagement in accreditation, community health assessment, community health improvement planning, quality improvement, and use of the Community Guide were associated with lower levels of engagement in resource sharing. Doctoral degree of the top executive and having 1 or more local boards of health carried a positive influence on resource sharing. Cross-jurisdictional resource sharing is a viable and commonly used process to overcome the challenges of new and emerging public health problems within the constraints of restricted budgets. LHDs, particularly smaller LHDs with limited resources, should consider increased resource sharing to address emerging challenges.
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Hassali, Mohamed Azmi; Mohamad Yahaya, Abdul Haniff; Shafie, Asrul Akmal; Saleem, Fahad; Chua, Gin Nie; Aljadhey, Hisham
2013-01-01
Objective The study aims to evaluate the predictors of non-prescription medicine purchasing patterns among pharmacy patrons in Malaysia. Methods A cross-sectional nationwide study was undertaken in 2011 in sixty randomly selected community pharmacies across 14 Malaysian states. A pharmacy exit survey was conducted over a 6-month period across Malaysia. A one-stage random cluster sampling technique was employed as there was no national sampling framework available for conducting this survey. Face-to-face interviews using a validated and pre-tested questionnaire were conducted by trained data collectors. The non-prescription medicine purchasing pattern was explored and analysed descriptively. Chi-square/Fisher exact test was used to determine the association between study variables. Multinomial logistic regression analysis was used to determine the predictors of type of non-prescription medicine purchased. Results A total of 2729 pharmacy patrons agreed to participate in 60 selected pharmacy outlets. A total of 3462 non-prescription medicine were purchased during the study period with an average of 1.3 medicines per participant. Most of the non-prescription medicine purchased was meant for alimentary tract and metabolism (31.8%), followed by respiratory system (19.4%) and musculoskeletal system (15.8%) usage. Factors found to be associated with the choice of non-prescription medicine purchased were age group [χ2 = 170.75, (df = 57), p<0.01], locality [χ2 = 48.16, (df = 19), p<0.01], gender [χ2 = 32.93, (df = 13), p = 0.002], ethnic group [χ2 = 118.89, (df = 39), p<0.01] and type of occupation [χ2 = 222.434, (df = 117), p<0.01]. Non-prescription medicine purchased defined about 20% of the variance in the combination of predictors such as locality, gender, age, ethnicity, type of occupation and household income. Conclusion The predictors for selection of non-prescription medicine were locality (urban or rural), gender, age, ethnicity, type of occupation and household income per month. Future studies need to explore the safety and effectiveness of using these non-prescription medicines. PMID:23573195
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Race and Unemployment: Labor Market Experiences of Black and White Men, 1968-1988.
ERIC Educational Resources Information Center
Wilson, Franklin D.; And Others
1995-01-01
Estimation of multinomial logistic regression models on a sample of unemployed workers suggested that persistently higher black unemployment is due to differential access to employment opportunities by region, occupational placement, labor market segmentation, and discrimination. The racial gap in unemployment is greatest for college-educated…
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Test Design Project: Studies in Test Adequacy. Annual Report.
ERIC Educational Resources Information Center
Wilcox, Rand R.
These studies in test adequacy focus on two problems: procedures for estimating reliability, and techniques for identifying ineffective distractors. Fourteen papers are presented on recent advances in measuring achievement (a response to Molenaar); "an extension of the Dirichlet-multinomial model that allows true score and guessing to be…
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ERIC Educational Resources Information Center
Grinstead, Mary L.; Mauldin, Teresa; Sabia, Joseph J.; Koonce, Joan; Palmer, Lance
2011-01-01
Using microdata from the American Dream Demonstration, the current study examines factors associated with savings and savings goal achievement (indicated by a matched withdrawal) among participants of individual development account (IDA) programs. Multinomial logit results show that hours of participation in financial education programs, higher…
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Predicting the Frequency of Senior Center Attendance.
ERIC Educational Resources Information Center
Miner, Sonia; And Others
1993-01-01
Used data from 1984 Supplement on Aging of the National Health Interview Survey to examine frequency of senior center attendance. Estimated multinomial logistic regression model to distinguish between persons who rarely, sometimes, and frequently attend. Found that more frequent users are older. Greater frequency was associated with lower income…
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Support vector machines classifiers of physical activities in preschoolers
USDA-ARS?s Scientific Manuscript database
The goal of this study is to develop, test, and compare multinomial logistic regression (MLR) and support vector machines (SVM) in classifying preschool-aged children physical activity data acquired from an accelerometer. In this study, 69 children aged 3-5 years old were asked to participate in a s...
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An Investigation of the Representativeness Heuristic: The Case of a Multiple Choice Exam
ERIC Educational Resources Information Center
Chernoff, Egan J.; Mamolo, Ami; Zazkis, Rina
2016-01-01
By focusing on a particular alteration of the comparative likelihood task, this study contributes to research on teachers' understanding of probability. Our novel task presented prospective teachers with multinomial, contextualized sequences and asked them to identify which was least likely. Results demonstrate that determinants of…
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ERIC Educational Resources Information Center
Idsoe, Thormod; Dyregrov, Atle; Idsoe, Ella Cosmovici
2012-01-01
PTSD symptoms related to school bullying have rarely been investigated, and never in national samples. We used data from a national survey to investigate this among students from grades 8 and 9 (n = 963). The prevalence estimates of exposure to bullying were within the range of earlier research findings. Multinomial logistic regression showed that…
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Poverty and Material Hardship in Grandparent-Headed Households
ERIC Educational Resources Information Center
Baker, Lindsey A.; Mutchler, Jan E.
2010-01-01
Using the 2001 Survey of Income and Program Participation, the current study examines poverty and material hardship among children living in 3-generation (n = 486), skipped-generation (n = 238), single-parent (n = 2,076), and 2-parent (n = 6,061) households. Multinomial and logistic regression models indicated that children living in…
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Victimization and Health Risk Factors among Weapon-Carrying Youth
ERIC Educational Resources Information Center
Stayton, Catherine; McVeigh, Katharine H.; Olson, E. Carolyn; Perkins, Krystal; Kerker, Bonnie D.
2011-01-01
Objective: To compare health risks of 2 subgroups of weapon carriers: victimized and nonvictimized youth. Methods: 2003-2007 NYC Youth Risk Behavior Surveys were analyzed using bivariate analyses and multinomial logistic regression. Results: Among NYC teens, 7.5% reported weapon carrying without victimization; 6.9% reported it with victimization.…
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In-State Tuition Policies for Undocumented Youth
ERIC Educational Resources Information Center
Vargas, Edward D.
2011-01-01
This article is an investigation into why U.S. states have enacted, banned, or continued with the status quo regarding in-state tuition policies for unauthorized youth. Using data from multiple government and nonprofit sources, a series of multinomial logistic regressions are estimated to explain the determinants of state behavior across the…
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Badve, Sunil V; Zhang, Lei; Coombes, Jeff S; Pascoe, Elaine M; Cass, Alan; Clarke, Philip; Ferrari, Paolo; McDonald, Stephen P; Morrish, Alicia T; Pedagogos, Eugenie; Perkovic, Vlado; Reidlinger, Donna; Scaria, Anish; Walker, Rowan; Vergara, Liza A; Hawley, Carmel M; Johnson, David W
2015-01-01
Erythropoiesis stimulating agent (ESA)-resistant anemia is common in chronic kidney disease (CKD). To evaluate the determinants of severity of ESA resistance in patients with CKD and primary ESA-resistance. Secondary analysis of a randomized controlled trial (the Handling Erythropoietin Resistance with Oxpentifylline, HERO). 53 adult patients with CKD stage 4 or 5 and primary ESA-resistant anemia (hemoglobin ≤120 g/L, ESA resistance index [ERI] ≥1.0 IU/kg/week/gHb for erythropoietin or ≥0.005 μg/kg/week/gHb for darbepoeitin, no cause for ESA-resistance identified). Iron studies, parathyroid hormone, albumin, liver enzymes, phosphate or markers of oxidative stress and inflammation. Participants were divided into tertiles of ERI. Multinomial logistic regression was used to analyse the determinants of ERI tertiles. All patients, except one, were receiving dialysis for end-stage kidney disease. The mean ± SD ERI values in the low (n = 18), medium (n = 18) and high (n = 17) ERI tertiles were 1.4 ± 0.3, 2.3 ± 0.2 and 3.5 ± 0.8 IU/kg/week/gHb, respectively (P < 0.001). There were no significant differences observed in age, gender, ethnicity, cause of kidney disease, diabetes, iron studies, parathyroid hormone, albumin, liver enzymes, phosphate or markers of oxidative stress and inflammation between the ERI tertiles. The median [inter-quartile range] serum alkaline phosphatase concentrations in the low, medium and high ERI tertiles were 89 [64,121], 99 [76,134 and 148 [87,175] U/L, respectively (P = 0.054). There was a weak but statistically significant association between ERI and serum alkaline phosphatase (R(2) = 0.06, P = 0.03). Using multinomial logistic regression, the risk of being in the high ERI tertile relative to the low ERI tertile increased with increasing serum alkaline phosphatase levels (P = 0.02). No other variables were significantly associated with ERI. Small sample size; bone-specific alkaline phosphatase, other markers of bone turnover and bone biopsies not evaluated. Serum alkaline phosphatase was associated with severity of ESA resistance in ESA-resistant patients with CKD. Large prospective studies are required to confirm this association. ( Australian New Zealand Clinical Trials Registry 12608000199314).
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Sikder, Shegufta S; Labrique, Alain B; Craig, Ian M; Wakil, Mohammad Abdul; Shamim, Abu Ahmed; Ali, Hasmot; Mehra, Sucheta; Wu, Lee; Shaikh, Saijuddin; West, Keith P; Christian, Parul
2015-04-18
In communities with low rates of institutional delivery, little data exist on care-seeking behavior for potentially life-threatening obstetric complications. In this analysis, we sought to describe care-seeking patterns for self-reported complications and near misses in rural Bangladesh and to identify factors associated with care seeking for these conditions. Utilizing data from a community-randomized controlled trial enrolling 42,214 pregnant women between 2007 and 2011, we used multivariable multinomial logistic regression to explore the association of demographic and socioeconomic factors, perceived need, and service availability with care seeking for obstetric complications or near misses. We also used multivariable multinomial logistic regression to analyze the factors associated with care seeking by type of obstetric complication (eclampsia, sepsis, hemorrhage, and obstructed labor). Out of 9,576 women with data on care seeking for obstetric complications, 77% sought any care, with 29% (n = 2,150) visiting at least one formal provider and 70% (n = 5,149) visiting informal providers only. The proportion of women seeking at least one formal provider was highest among women reporting eclampsia (57%), followed by hemorrhage (28%), obstructed labor (22%), and sepsis (17%) (p < 0.001). In multivariable analyses, socioeconomic factors such as living in a household from the highest wealth quartile (Relative Risk Ratio of 1.49; 95% CI of [1.33-1.73]), women's literacy (RRR of 1.21; 95% CI of [1.05-1.42]), and women's employment (RRR of 1.10; 95% CI of [1.01-1.18]) were significantly associated with care seeking from formal providers. Service factors including living less than 10 kilometers from a health facility (RRR of 1.16; 95% CI of [1.05-1.28]) and facility availability of comprehensive obstetric services (RRR of 1.25; 95% CI of 1.04-1.36) were also significantly associated with seeking care from formal providers. While the majority of women reporting obstetric complications sought care, less than a third visited health facilities. Improvements in socioeconomic factors such as maternal literacy, coupled with improved geographic access and service availability, may increase care seeking from formal facilities. Enhancing community awareness on symptoms of hemorrhage, sepsis, and obstructed labor and their consequences may promote care seeking for obstetric complications in rural Bangladesh. NCT00860470 .
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ERIC Educational Resources Information Center
Morgan, Paul L.; Li, Hui; Cook, Michael; Farkas, George; Hillemeier, Marianne M.; Lin, Yu-chu
2016-01-01
We sought to identify which kindergarten children are simultaneously at risk of moderate or severe symptomatology in both attention-deficit/hyperactivity disorder (ADHD) and conduct disorder (CD) as adolescents. These risk factor estimates have not been previously available. We conducted multinomial logistic regression analyses of multiinformant…
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A Simplified Conjoint Recognition Paradigm for the Measurement of Gist and Verbatim Memory
ERIC Educational Resources Information Center
Stahl, Christoph; Klauer, Karl Christoph
2008-01-01
The distinction between verbatim and gist memory traces has furthered the understanding of numerous phenomena in various fields, such as false memory research, research on reasoning and decision making, and cognitive development. To measure verbatim and gist memory empirically, an experimental paradigm and multinomial measurement model has been…
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Foreign Diploma versus Immigrant Background: Determinants of Labour Market Success or Failure?
ERIC Educational Resources Information Center
Storen, Liv Anne; Wiers-Jenssen, Jannecke
2010-01-01
This article compares the labour market situation of graduates with different types of international background. The authors look at four groups of graduates: immigrants and ethnic Norwegians graduated in Norway and immigrants and ethnic Norwegians graduated abroad. By employing multinomial logistic regression analyses the authors find that ethnic…
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Motivations and Benefits for Attaining HR Certifications
ERIC Educational Resources Information Center
Lester, Scott W.; Dwyer, Dale J.
2012-01-01
Purpose: The aim of this paper is to examine the motivations and benefits for pursuing or not pursuing the PHR and SPHR. Design/methodology/approach: Using a sample of 1,862 participants, the study used multinomial logistic and hierarchical linear regression to test six hypotheses. Findings: Participants pursuing SPHR were more likely to report…
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Latent spatial models and sampling design for landscape genetics
Ephraim M. Hanks; Melvin B. Hooten; Steven T. Knick; Sara J. Oyler-McCance; Jennifer A. Fike; Todd B. Cross; Michael K. Schwartz
2016-01-01
We propose a spatially-explicit approach for modeling genetic variation across space and illustrate how this approach can be used to optimize spatial prediction and sampling design for landscape genetic data. We propose a multinomial data model for categorical microsatellite allele data commonly used in landscape genetic studies, and introduce a latent spatial...
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2012-11-01
use in this work the variational approximation algo- rithm implemented and distributed by Pr . Blei1. Each learned multinomial distribution φk is tra...4,111,240 newswire articles collected from four distinct international sources including the New York Times (Graff and Cieri, 2003). The New York Times
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Early Family Formation among White, Black, and Mexican American Women
ERIC Educational Resources Information Center
Landale, Nancy S.; Schoen, Robert; Daniels, Kimberly
2010-01-01
Using data from Waves I and III of Add Health, this study examines early family formation among 6,144 White, Black, and Mexican American women. Drawing on cultural and structural perspectives, models of the first and second family transitions (cohabitation, marriage, or childbearing) are estimated using discrete-time multinomial logistic…
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ERIC Educational Resources Information Center
Winfield, Evelyn B.; Whaley, Arthur L.
2005-01-01
The present study examined relationship status, psychological orientation toward sexual risk taking, and other characteristics as potential correlates of risky sexual behavior in a sample of 223 heterosexual African American college students. Risky sexual behavior was investigated as a multinomial variable (i.e., abstinence, consistent condom use,…
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School Climate: The Controllable and the Uncontrollable
ERIC Educational Resources Information Center
Sulak, Tracey N.
2018-01-01
A positive school climate impacts students by promoting positive relations among students, staff and faculty of the school. The current study used latent class analysis and multinomial regression with R3STEP to analyse patterns of negative behaviours in schools and test the association of these patterns with structural variables like school size,…
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Bayesian Network Meta-Analysis for Unordered Categorical Outcomes with Incomplete Data
ERIC Educational Resources Information Center
Schmid, Christopher H.; Trikalinos, Thomas A.; Olkin, Ingram
2014-01-01
We develop a Bayesian multinomial network meta-analysis model for unordered (nominal) categorical outcomes that allows for partially observed data in which exact event counts may not be known for each category. This model properly accounts for correlations of counts in mutually exclusive categories and enables proper comparison and ranking of…
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Using Computational Text Classification for Qualitative Research and Evaluation in Extension
ERIC Educational Resources Information Center
Smith, Justin G.; Tissing, Reid
2018-01-01
This article introduces a process for computational text classification that can be used in a variety of qualitative research and evaluation settings. The process leverages supervised machine learning based on an implementation of a multinomial Bayesian classifier. Applied to a community of inquiry framework, the algorithm was used to identify…
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An Analysis of Losses to the Southern Commercial Timberland Base
Ian A. Munn; David Cleaves
1998-01-01
Demographic and physical factors influencing the conversion of commercial timberland iu the south to non-forestry uses between the last two Forest Inventory Analysis (FIA) surveys were investigated. GIS techniques linked Census data and FIA plot level data. Multinomial logit regression identified factors associated with losses to the timberland base. Conversion to...
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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…
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Application of a Multidimensional Nested Logit Model to Multiple-Choice Test Items
ERIC Educational Resources Information Center
Bolt, Daniel M.; Wollack, James A.; Suh, Youngsuk
2012-01-01
Nested logit models have been presented as an alternative to multinomial logistic models for multiple-choice test items (Suh and Bolt in "Psychometrika" 75:454-473, 2010) and possess a mathematical structure that naturally lends itself to evaluating the incremental information provided by attending to distractor selection in scoring. One potential…
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Two-Phase Item Selection Procedure for Flexible Content Balancing in CAT
ERIC Educational Resources Information Center
Cheng, Ying; Chang, Hua-Hua; Yi, Qing
2007-01-01
Content balancing is an important issue in the design and implementation of computerized adaptive testing (CAT). Content-balancing techniques that have been applied in fixed content balancing, where the number of items from each content area is fixed, include constrained CAT (CCAT), the modified multinomial model (MMM), modified constrained CAT…
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Caste, Class, and Urbanization: The Shaping of Religious Community in Contemporary India
ERIC Educational Resources Information Center
Stroope, Samuel
2012-01-01
Building on the implications of qualitative work from India and urbanism theories, I aim to understand whether religious bonding social capital in contemporary India increases with greater urbanization and whether such increases are moderated by caste or social class position. Results from multinomial logistic regression on 1,417 Hindu respondents…
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American Youths' Access to Substance Abuse Treatment: Does Type of Treatment Facility Matter?
ERIC Educational Resources Information Center
Lo, Celia C.; Cheng, Tyrone C.
2013-01-01
Using data from the 2007 National Survey on Drug Use and Health, this study examines whether several social exclusion and psychological factors affect adolescents' receipt of substance abuse treatment. Multinomial logistic regression techniques were used to analyze data. The study asked how the specified factors provide pathways to receipt of…
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Primary Factors Related to Multiple Placements for Children in Out-of-Home Care
ERIC Educational Resources Information Center
Eggertsen, Lars
2008-01-01
Using an ecological framework, this study identified which factors related to out-of-home placements significantly influenced multiple placements for children in Utah during 2000, 2001, and 2002. Multinomial logistic regression statistical procedures and a geographical information system (GIS) were used to analyze the data. The final model…
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Institutional Discharges and Subsequent Shelter Use among Unaccompanied Adults in New York City
ERIC Educational Resources Information Center
Metraux, Stephen; Byrne, Thomas; Culhane, Dennis P.
2010-01-01
This study empirically examines the link between homelessness and discharges from other institutions. An administrative record match was undertaken to determine rates of discharge from institutional care for 9,247 unaccompanied adult shelter users in New York City. Cluster analysis and multinomial logistic regression analysis was then used to…
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ERIC Educational Resources Information Center
Street, Nathan Lee
2017-01-01
Teacher value-added measures (VAM) are designed to provide information regarding teachers' causal impact on the academic growth of students while controlling for exogenous variables. While some researchers contend VAMs successfully and authentically measure teacher causality on learning, others suggest VAMs cannot adequately control for exogenous…
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Profiles of Supportive Alumni: Donors, Volunteers, and Those Who "Do It All"
ERIC Educational Resources Information Center
Weerts, David J.; Ronca, Justin M.
2007-01-01
In the competitive marketplace of higher education, college and university alumni are increasingly called on to support their institutions in multiple ways: political advocacy, volunteerism, and charitable giving. Drawing on alumni survey data gathered from a large research extensive university, we employ a multinomial logistic regression model to…
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ERIC Educational Resources Information Center
Zwick, Rebecca; Lenaburg, Lubella
2009-01-01
In certain data analyses (e.g., multiple discriminant analysis and multinomial log-linear modeling), classification decisions are made based on the estimated posterior probabilities that individuals belong to each of several distinct categories. In the Bayesian network literature, this type of classification is often accomplished by assigning…
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John Hogland; Nedret Billor; Nathaniel Anderson
2013-01-01
Discriminant analysis, referred to as maximum likelihood classification within popular remote sensing software packages, is a common supervised technique used by analysts. Polytomous logistic regression (PLR), also referred to as multinomial logistic regression, is an alternative classification approach that is less restrictive, more flexible, and easy to interpret. To...
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Impact of Perceived Risk and Friend Influence on Alcohol and Marijuana Use among Students
ERIC Educational Resources Information Center
Merianos, Ashley L.; Rosen, Brittany L.; Montgomery, LaTrice; Barry, Adam E.; Smith, Matthew Lee
2017-01-01
We performed a secondary analysis of Adolescent Health Risk Behavior Survey data (N=937), examining associations between lifetime alcohol and marijuana use with intrapersonal (i.e., risk perceptions) and interpersonal (e.g., peer approval and behavior) factors. Multinomial and binary logistic regression analyses contend students reporting lifetime…
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ERIC Educational Resources Information Center
Saltonstall, Margot
2013-01-01
This study seeks to advance and expand research on college student success. Using multinomial logistic regression analysis, the study investigates the contribution of psychosocial variables above and beyond traditional achievement and demographic measures to predicting first-semester college grade point average (GPA). It also investigates if…
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New machine-learning algorithms for prediction of Parkinson's disease
NASA Astrophysics Data System (ADS)
Mandal, Indrajit; Sairam, N.
2014-03-01
This article presents an enhanced prediction accuracy of diagnosis of Parkinson's disease (PD) to prevent the delay and misdiagnosis of patients using the proposed robust inference system. New machine-learning methods are proposed and performance comparisons are based on specificity, sensitivity, accuracy and other measurable parameters. The robust methods of treating Parkinson's disease (PD) includes sparse multinomial logistic regression, rotation forest ensemble with support vector machines and principal components analysis, artificial neural networks, boosting methods. A new ensemble method comprising of the Bayesian network optimised by Tabu search algorithm as classifier and Haar wavelets as projection filter is used for relevant feature selection and ranking. The highest accuracy obtained by linear logistic regression and sparse multinomial logistic regression is 100% and sensitivity, specificity of 0.983 and 0.996, respectively. All the experiments are conducted over 95% and 99% confidence levels and establish the results with corrected t-tests. This work shows a high degree of advancement in software reliability and quality of the computer-aided diagnosis system and experimentally shows best results with supportive statistical inference.
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Profiles of internalizing and externalizing symptoms associated with bullying victimization.
Eastman, Meridith; Foshee, Vangie; Ennett, Susan; Sotres-Alvarez, Daniela; Reyes, H Luz McNaughton; Faris, Robert; North, Kari
2018-06-01
This study identified profiles of internalizing (anxiety and depression) and externalizing (delinquency and violence against peers) symptoms among bullying victims and examined associations between bullying victimization characteristics and profile membership. The sample consisted of 1196 bullying victims in grades 8-10 (M age = 14.4, SD = 1.01) who participated in The Context Study in three North Carolina counties in Fall 2003. Five profiles were identified using latent profile analysis: an asymptomatic profile and four profiles capturing combinations of internalizing and externalizing symptoms. Associations between bullying characteristics and membership in symptom profiles were tested using multinomial logistic regression. More frequent victimization increased odds of membership in the two high internalizing profiles compared to the asymptomatic profile. Across all multinomial logistic regression models, when the high internalizing, high externalizing profile was the reference category, adolescents who received any type of bullying (direct, indirect, or dual) were more likely to be in this category than any others. Copyright © 2018 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.
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A Multilevel Model for Comorbid Outcomes: Obesity and Diabetes in the US
Congdon, Peter
2010-01-01
Multilevel models are overwhelmingly applied to single health outcomes, but when two or more health conditions are closely related, it is important that contextual variation in their joint prevalence (e.g., variations over different geographic settings) is considered. A multinomial multilevel logit regression approach for analysing joint prevalence is proposed here that includes subject level risk factors (e.g., age, race, education) while also taking account of geographic context. Data from a US population health survey (the 2007 Behavioral Risk Factor Surveillance System or BRFSS) are used to illustrate the method, with a six category multinomial outcome defined by diabetic status and weight category (obese, overweight, normal). The influence of geographic context is partly represented by known geographic variables (e.g., county poverty), and partly by a model for latent area influences. In particular, a shared latent variable (common factor) approach is proposed to measure the impact of unobserved area influences on joint weight and diabetes status, with the latent variable being spatially structured to reflect geographic clustering in risk. PMID:20616977
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Sampaolo, Letizia; Tommaso, Giulia; Gherardi, Bianca; Carrozzi, Giuliano; Freni Sterrantino, Anna; Ottone, Marta; Goldoni, Carlo Alberto; Bertozzi, Nicoletta; Scaringi, Meri; Bolognesi, Lara; Masocco, Maria; Salmaso, Stefania; Lauriola, Paolo
2017-01-01
"OBJECTIVES: to identify groups of people in relation to the perception of environmental risk and to assess the main characteristics using data collected in the environmental module of the surveillance network Italian Behavioral Risk Factor Surveillance System (PASSI). perceptive profiles were identified using a latent class analysis; later they were included as outcome in multinomial logistic regression models to assess the association between environmental risk perception and demographic, health, socio-economic and behavioural variables. the latent class analysis allowed to split the sample in "worried", "indifferent", and "positive" people. The multinomial logistic regression model showed that the "worried" profile typically includes people of Italian nationality, living in highly urbanized areas, with a high level of education, and with economic difficulties; they pay special attention to their own health and fitness, but they have a negative perception of their own psychophysical state. the application of advanced statistical analysis enable to appraise PASSI data in order to characterize the perception of environmental risk, making the planning of interventions related to risk communication possible. ".
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NASA Astrophysics Data System (ADS)
Zhu, Wei; Timmermans, Harry
2011-06-01
Models of geographical choice behavior have been dominantly based on rational choice models, which assume that decision makers are utility-maximizers. Rational choice models may be less appropriate as behavioral models when modeling decisions in complex environments in which decision makers may simplify the decision problem using heuristics. Pedestrian behavior in shopping streets is an example. We therefore propose a modeling framework for pedestrian shopping behavior incorporating principles of bounded rationality. We extend three classical heuristic rules (conjunctive, disjunctive and lexicographic rule) by introducing threshold heterogeneity. The proposed models are implemented using data on pedestrian behavior in Wang Fujing Street, the city center of Beijing, China. The models are estimated and compared with multinomial logit models and mixed logit models. Results show that the heuristic models are the best for all the decisions that are modeled. Validation tests are carried out through multi-agent simulation by comparing simulated spatio-temporal agent behavior with the observed pedestrian behavior. The predictions of heuristic models are slightly better than those of the multinomial logit models.
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A general equation to obtain multiple cut-off scores on a test from multinomial logistic regression.
Bersabé, Rosa; Rivas, Teresa
2010-05-01
The authors derive a general equation to compute multiple cut-offs on a total test score in order to classify individuals into more than two ordinal categories. The equation is derived from the multinomial logistic regression (MLR) model, which is an extension of the binary logistic regression (BLR) model to accommodate polytomous outcome variables. From this analytical procedure, cut-off scores are established at the test score (the predictor variable) at which an individual is as likely to be in category j as in category j+1 of an ordinal outcome variable. The application of the complete procedure is illustrated by an example with data from an actual study on eating disorders. In this example, two cut-off scores on the Eating Attitudes Test (EAT-26) scores are obtained in order to classify individuals into three ordinal categories: asymptomatic, symptomatic and eating disorder. Diagnoses were made from the responses to a self-report (Q-EDD) that operationalises DSM-IV criteria for eating disorders. Alternatives to the MLR model to set multiple cut-off scores are discussed.
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A general class of multinomial mixture models for anuran calling survey data
Royle, J. Andrew; Link, W.A.
2005-01-01
We propose a general framework for modeling anuran abundance using data collected from commonly used calling surveys. The data generated from calling surveys are indices of calling intensity (vocalization of males) that do not have a precise link to actual population size and are sensitive to factors that influence anuran behavior. We formulate a model for calling-index data in terms of the maximum potential calling index that could be observed at a site (the 'latent abundance class'), given its underlying breeding population, and we focus attention on estimating the distribution of this latent abundance class. A critical consideration in estimating the latent structure is imperfect detection, which causes the observed abundance index to be less than or equal to the latent abundance class. We specify a multinomial sampling model for the observed abundance index that is conditional on the latent abundance class. Estimation of the latent abundance class distribution is based on the marginal likelihood of the index data, having integrated over the latent class distribution. We apply the proposed modeling framework to data collected as part of the North American Amphibian Monitoring Program (NAAMP).
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Modeling health survey data with excessive zero and K responses.
Lin, Ting Hsiang; Tsai, Min-Hsiao
2013-04-30
Zero-inflated Poisson regression is a popular tool used to analyze data with excessive zeros. Although much work has already been performed to fit zero-inflated data, most models heavily depend on special features of the individual data. To be specific, this means that there is a sizable group of respondents who endorse the same answers making the data have peaks. In this paper, we propose a new model with the flexibility to model excessive counts other than zero, and the model is a mixture of multinomial logistic and Poisson regression, in which the multinomial logistic component models the occurrence of excessive counts, including zeros, K (where K is a positive integer) and all other values. The Poisson regression component models the counts that are assumed to follow a Poisson distribution. Two examples are provided to illustrate our models when the data have counts containing many ones and sixes. As a result, the zero-inflated and K-inflated models exhibit a better fit than the zero-inflated Poisson and standard Poisson regressions. Copyright © 2012 John Wiley & Sons, Ltd.
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Predictors of Start of Different Antidepressants in Patient Charts among Patients with Depression
Kim, Hyungjin Myra; Zivin, Kara; Choe, Hae Mi; Stano, Clare M.; Ganoczy, Dara; Walters, Heather; Valenstein, Marcia
2016-01-01
Background In usual psychiatric care, antidepressant treatments are selected based on physician and patient preferences rather than being randomly allocated, resulting in spurious associations between these treatments and outcome studies. Objectives To identify factors recorded in electronic medical chart progress notes predictive of antidepressant selection among patients who had received a depression diagnosis. Methods This retrospective study sample consisted of 556 randomly selected Veterans Health Administration (VHA) patients diagnosed with depression from April 1, 1999 to September 30, 2004, stratified by the antidepressant agent, geographic region, gender, and year of depression cohort entry. Predictors were obtained from administrative data, and additional variables were abstracted from electronic medical chart notes in the year prior to the start of the antidepressant in five categories: clinical symptoms and diagnoses, substance use, life stressors, behavioral/ideation measures (e.g., suicide attempts), and treatments received. Multinomial logistic regression analysis was used to assess the predictors associated with different antidepressant prescribing, and adjusted relative risk ratios (RRR) are reported. Results Of the administrative data-based variables, gender, age, illicit drug abuse or dependence, and number of psychiatric medications in prior year were significantly associated with antidepressant selection. After adjusting for administrative data-based variables, sleep problems (RRR = 2.47) or marital issues (RRR = 2.64) identified in the charts were significantly associated with prescribing mirtazapine rather than sertraline; however, no other chart-based variables showed a significant association or an association with a large magnitude. Conclusion Some chart data-based variables were predictive of antidepressant selection, but we neither found many nor found them highly predictive of antidepressant selection in patients treated for depression. PMID:25943003
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Effect of finite particle number sampling on baryon number fluctuations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Steinheimer, Jan; Koch, Volker
The effects of finite particle number sampling on the net baryon number cumulants, extracted from fluid dynamical simulations, are studied. The commonly used finite particle number sampling procedure introduces an additional Poissonian (or multinomial if global baryon number conservation is enforced) contribution which increases the extracted moments of the baryon number distribution. If this procedure is applied to a fluctuating fluid dynamics framework, one severely overestimates the actual cumulants. We show that the sampling of so-called test particles suppresses the additional contribution to the moments by at least one power of the number of test particles. We demonstrate this methodmore » in a numerical fluid dynamics simulation that includes the effects of spinodal decomposition due to a first-order phase transition. Furthermore, in the limit where antibaryons can be ignored, we derive analytic formulas which capture exactly the effect of particle sampling on the baryon number cumulants. These formulas may be used to test the various numerical particle sampling algorithms.« less
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Effect of finite particle number sampling on baryon number fluctuations
Steinheimer, Jan; Koch, Volker
2017-09-28
The effects of finite particle number sampling on the net baryon number cumulants, extracted from fluid dynamical simulations, are studied. The commonly used finite particle number sampling procedure introduces an additional Poissonian (or multinomial if global baryon number conservation is enforced) contribution which increases the extracted moments of the baryon number distribution. If this procedure is applied to a fluctuating fluid dynamics framework, one severely overestimates the actual cumulants. We show that the sampling of so-called test particles suppresses the additional contribution to the moments by at least one power of the number of test particles. We demonstrate this methodmore » in a numerical fluid dynamics simulation that includes the effects of spinodal decomposition due to a first-order phase transition. Furthermore, in the limit where antibaryons can be ignored, we derive analytic formulas which capture exactly the effect of particle sampling on the baryon number cumulants. These formulas may be used to test the various numerical particle sampling algorithms.« less
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Budd, Kristen M; Mancini, Christina
2017-09-01
In the United States, electronic monitoring (EM) and global positioning systems (GPS) are new applications that are used to extensively monitor and track convicted sex offenders. What is unclear though are public perceptions of this strategy. This research examines public perceptions of a national sample of Americans on the use of GPS/EM with convicted sex offenders as a method to reduce their sexual recidivism. Using a multinomial regression model, we analyze the effects of sex offender myths and parental status on public perceptions that sex offender GPS/EM is very effective in reducing sexual recidivism. Findings suggest that public perceptions of effectiveness are partially driven by myths and also that parents are unsure of this strategy. The analysis contributes to the growing body of knowledge on public perceptions of GPS/EM to manage sex offenders in communities. Implications of the study and areas for future research are discussed in light of the findings.
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Dietary Fiber Intake Is Inversely Associated with Periodontal Disease among US Adults.
Nielsen, Samara Joy; Trak-Fellermeier, Maria Angelica; Joshipura, Kaumudi; Dye, Bruce A
2016-12-01
Approximately 47% of adults in the United States have periodontal disease. Dietary guidelines recommend a diet providing adequate fiber. Healthier dietary habits, particularly an increased fiber intake, may contribute to periodontal disease prevention. Our objective was to evaluate the relation of dietary fiber intake and its sources with periodontal disease in the US adult population (≥30 y of age). Data from 6052 adults participating in NHANES 2009-2012 were used. Periodontal disease was defined (according to the CDC/American Academy of Periodontology) as severe, moderate, mild, and none. Intake was assessed by 24-h dietary recalls. The relation between periodontal disease and dietary fiber, whole-grain, and fruit and vegetable intakes were evaluated by using multivariate models, adjusting for sociodemographic characteristics and dentition status. In the multivariate logistic model, the lowest quartile of dietary fiber was associated with moderate-severe periodontitis (compared with mild-none) compared with the highest dietary fiber intake quartile (OR: 1.30; 95% CI: 1.00, 1.69). In the multivariate multinomial logistic model, intake in the lowest quartile of dietary fiber was associated with higher severity of periodontitis than dietary fiber intake in the highest quartile (OR: 1.27; 95% CI: 1.00, 1.62). In the adjusted logistic model, whole-grain intake was not associated with moderate-severe periodontitis. However, in the adjusted multinomial logistic model, adults consuming whole grains in the lowest quartile were more likely to have more severe periodontal disease than were adults consuming whole grains in the highest quartile (OR: 1.32; 95% CI: 1.08, 1.62). In fully adjusted logistic and multinomial logistic models, fruit and vegetable intake was not significantly associated with periodontitis. We found an inverse relation between dietary fiber intake and periodontal disease among US adults ≥30 y old. Periodontal disease was associated with low whole-grain intake but not with low fruit and vegetable intake. © 2016 American Society for Nutrition.
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Weaver, Emma R N; Agius, Paul A; Veale, Hilary; Dorning, Karl; Hlang, Thein T; Aung, Poe P; Fowkes, Freya J I; Hellard, Margaret E
2016-08-03
Gastrointestinal diseases are major contributors to mortality among children globally, causing one in 10 child deaths. Although most deaths are in children aged ≤ 5 years, the burden of disease in school-aged children is still considerable and contributes to high rates of school absenteeism. This study investigates behavioral and structural risk factors associated with diarrhea and/or vomiting among schoolchildren in Myanmar. Cross-sectional data from a school-based multistage cluster sample of grade 4 and 5 students were analyzed to explore water, sanitation, and hygiene (WASH) facilities and hygiene-related practices of students in monastic schools in Myanmar. The outcome of interest was student self-reported diarrhea and/or vomiting in the past week. Random effects multinomial logistic regression models were used to explore correlates at the student and school level. A total of 2,082 students from 116 schools across eight states/regions were included. Of these, 11% (223) self-reported at least one episode of diarrhea only, 12% (253) at least one episode of vomiting only, and 12% (244) diarrhea and vomiting in the past week. Independent risk factors associated with the outcome included poor availability of handwash stations, no access to a septic tank toilet, inconsistent toilet use, and lower student grade. These findings highlight the importance of having an adequate number of handwash stations for students, the provision of septic tank toilets, and consistent toilet use. Future WASH programs need to target not only the provision of these WASH facilities but also their utilization, particularly among younger school-aged children. © The American Society of Tropical Medicine and Hygiene.
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Obesity and the burden of health risks among the elderly in Ghana: A population study.
Boateng, Godfred O; Adams, Ellis A; Odei Boateng, Mavis; Luginaah, Isaac N; Taabazuing, Mary-Margaret
2017-01-01
The causes and health risks associated with obesity in young people have been extensively documented, but elderly obesity is less well understood, especially in sub-Saharan Africa. This study examines the relationship between obesity and the risk of chronic diseases, cognitive impairment, and functional disability among the elderly in Ghana. It highlights the social and cultural dimensions of elderly obesity and discusses the implications of related health risks using a socio-ecological model. We used data from wave 1 of the Ghana Study on Global Ageing and Adult Health (SAGE) survey-2007/8, with a restricted sample of 2,091 for those 65 years and older. Using random effects multinomial, ordered, and binary logit models, we examined the relationship between obesity and the risk of stage 1 and stage 2 hypertension, arthritis, difficulties with recall and learning new tasks, and deficiencies with activities of daily living and instrumental activities of daily living. Elderly Ghanaians who were overweight and obese had a higher risk of stage 1 and stage 2 hypertension, and were more likely to be diagnosed with arthritis and report severe deficiencies with instrumental activities of daily living. Those who were underweight were 1.71 times more likely to report severe difficulties with activities of daily living. A sub analysis using waist circumference as a measure of body fat showed elderly females with abdominal adiposity were relatively more likely to have stage 2 hypertension. These findings call for urgent policy initiatives geared towards reducing obesity among working adults given the potentially detrimental consequences in late adulthood. Future research should explore the gendered pathways leading to health disadvantages among Ghanaian women in late adulthood.
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Enns, Sylvia Claassen; Perotta, Bruno; Paro, Helena B; Gannam, Silmar; Peleias, Munique; Mayer, Fernanda Brenneisen; Santos, Itamar Souza; Menezes, Marta; Senger, Maria Helena; Barelli, Cristiane; Silveira, Paulo S P; Martins, Milton A; Zen Tempski, Patricia
2016-03-01
To assess perceptions of educational environment of students from 22 Brazilian medical schools and to study the association between these perceptions and quality of life (QoL) measures. The authors performed a multicenter study (August 2011 to August 2012), examining students' views both of (1) educational environment using the Dundee Ready Education Environment Measure (DREEM) and (2) QoL using the World Health Organization Quality of Life Assessment, abbreviated version (WHOQOL-BREF). They also examined students' self-assessment of their overall QoL and medical-school-related QoL (MSQoL). The authors classified participants' perceptions into four quartiles according to DREEM total score, overall QoL, and MSQoL. Of 1,650 randomly selected students, 1,350 (81.8%) completed the study. The mean total DREEM score was 119.4 (standard deviation = 27.1). Higher total DREEM scores were associated with higher overall QoL and MSQoL scores (P < .001 for all comparisons) and younger ages (P < .001). Mean overall QoL scores were higher than MSQoL scores (mean difference, 1.35; 95% confidence interval [CI] 1.28-1.43; P < .001). Multinomial regression models showed significant dose-response patterns: Higher DREEM quartile scores were associated with better QoL. The psychological health domain of WHOQOL-BREF was most closely associated with DREEM scores (odds ratio 4.70; 95% CI = 3.80-5.81). The authors observed a positive association between QoL measures and DREEM scores. This association had a dose-response effect, independent of age, sex, and year of medical training, showing that educational environment appears to be an important moderator of medical student QoL.
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Comparison of four statistical and machine learning methods for crash severity prediction.
Iranitalab, Amirfarrokh; Khattak, Aemal
2017-11-01
Crash severity prediction models enable different agencies to predict the severity of a reported crash with unknown severity or the severity of crashes that may be expected to occur sometime in the future. This paper had three main objectives: comparison of the performance of four statistical and machine learning methods including Multinomial Logit (MNL), Nearest Neighbor Classification (NNC), Support Vector Machines (SVM) and Random Forests (RF), in predicting traffic crash severity; developing a crash costs-based approach for comparison of crash severity prediction methods; and investigating the effects of data clustering methods comprising K-means Clustering (KC) and Latent Class Clustering (LCC), on the performance of crash severity prediction models. The 2012-2015 reported crash data from Nebraska, United States was obtained and two-vehicle crashes were extracted as the analysis data. The dataset was split into training/estimation (2012-2014) and validation (2015) subsets. The four prediction methods were trained/estimated using the training/estimation dataset and the correct prediction rates for each crash severity level, overall correct prediction rate and a proposed crash costs-based accuracy measure were obtained for the validation dataset. The correct prediction rates and the proposed approach showed NNC had the best prediction performance in overall and in more severe crashes. RF and SVM had the next two sufficient performances and MNL was the weakest method. Data clustering did not affect the prediction results of SVM, but KC improved the prediction performance of MNL, NNC and RF, while LCC caused improvement in MNL and RF but weakened the performance of NNC. Overall correct prediction rate had almost the exact opposite results compared to the proposed approach, showing that neglecting the crash costs can lead to misjudgment in choosing the right prediction method. Copyright © 2017 Elsevier Ltd. All rights reserved.
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Maziak, W; Ward, K D; Eissenberg, T
2004-10-05
To evaluate factors related to level of narghile (waterpipe) use as a first step towards modeling tobacco dependence among narghile users. Cross sectional survey done in 2003 using interviewer-administered anonymous questionnaires. Cafes/restaurants serving narghiles in Aleppo, Syria. Narghile smokers (161 men and 107 women; mean age, 30.1 +/- 10.2, 161; age range, 18-68 years; response rate, 95.3%) randomly selected from the 17 cafes/restaurants sampled. Frequency of narghile use (daily, weekly, monthly) was assessed as a function of several factors potentially indicative of dependence, including situational characteristics (where, when, and with whom smoking occurs; seasonality of use, and sharing of narghile), attitudes, and experience with quitting narghile use, escalation of use over time, future intentions regarding use, perception of being "hooked" on narghile, and cognitions/behaviors engaged in to support use (carrying one's own narghile; think of narghile when it is not available; considering narghile for selection of cafes/restaurants). Frequency of narghile use was strongly correlated with participant's subjective judgment of how hooked they are on narghile (coefficient, 0.5). Predictors of narghile use frequency according to multinomial logistic regression were: male gender, smoking mainly alone versus with others; smoking mainly at home versus outside; smoking more frequently since initiation, being hooked on narghile, carrying narghile, and considering it for cafe/restaurant choice. Our data reveal two main domains of a tobacco dependence syndrome likely to be relevant to narghile; the first reflects the effects of nicotine contained in narghile tobacco, and is not very different from what is seen with other tobacco products, and the second is unique to narghile and is related mainly to its social dimension, with more intensive smokers showing an increasingly individual pattern of narghile smoking.
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Finbråten, Hanne Søberg; Pettersen, Kjell Sverre; Wilde-Larsson, Bodil; Nordström, Gun; Trollvik, Anne; Guttersrud, Øystein
2017-11-01
To validate the European Health Literacy Survey Questionnaire (HLS-EU-Q47) in people with type 2 diabetes mellitus. The HLS-EU-Q47 latent variable is outlined in a framework with four cognitive domains integrated in three health domains, implying 12 theoretically defined subscales. Valid and reliable health literacy measurers are crucial to effectively adapt health communication and education to individuals and groups of patients. Cross-sectional study applying confirmatory latent trait analyses. Using a paper-and-pencil self-administered approach, 388 adults responded in March 2015. The data were analysed using the Rasch methodology and confirmatory factor analysis. Response violation (response dependency) and trait violation (multidimensionality) of local independence were identified. Fitting the "multidimensional random coefficients multinomial logit" model, 1-, 3- and 12-dimensional Rasch models were applied and compared. Poor model fit and differential item functioning were present in some items, and several subscales suffered from poor targeting and low reliability. Despite multidimensional data, we did not observe any unordered response categories. Interpreting the domains as distinct but related latent dimensions, the data fit a 12-dimensional Rasch model and a 12-factor confirmatory factor model best. Therefore, the analyses did not support the estimation of one overall "health literacy score." To support the plausibility of claims based on the HLS-EU score(s), we suggest: removing the health care aspect to reduce the magnitude of multidimensionality; rejecting redundant items to avoid response dependency; adding "harder" items and applying a six-point rating scale to improve subscale targeting and reliability; and revising items to improve model fit and avoid bias owing to person factors. © 2017 John Wiley & Sons Ltd.
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Neighborhood fast food availability and fast food consumption.
Oexle, Nathalie; Barnes, Timothy L; Blake, Christine E; Bell, Bethany A; Liese, Angela D
2015-09-01
Recent nutritional and public health research has focused on how the availability of various types of food in a person's immediate area or neighborhood influences his or her food choices and eating habits. It has been theorized that people living in areas with a wealth of unhealthy fast-food options may show higher levels of fast-food consumption, a factor that often coincides with being overweight or obese. However, measuring food availability in a particular area is difficult to achieve consistently: there may be differences in the strict physical locations of food options as compared to how individuals perceive their personal food availability, and various studies may use either one or both of these measures. The aim of this study was to evaluate the association between weekly fast-food consumption and both a person's perceived availability of fast-food and an objective measure of fast-food presence - Geographic Information Systems (GIS) - within that person's neighborhood. A randomly selected population-based sample of eight counties in South Carolina was used to conduct a cross-sectional telephone survey assessing self-report fast-food consumption and perceived availability of fast food. GIS was used to determine the actual number of fast-food outlets within each participant's neighborhood. Using multinomial logistic regression analyses, we found that neither perceived availability nor GIS-based presence of fast-food was significantly associated with weekly fast-food consumption. Our findings indicate that availability might not be the dominant factor influencing fast-food consumption. We recommend using subjective availability measures and considering individual characteristics that could influence both perceived availability of fast food and its impact on fast-food consumption. If replicated, our findings suggest that interventions aimed at reducing fast-food consumption by limiting neighborhood fast-food availability might not be completely effective. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Online, Interactive Option Grid Patient Decision Aids and their Effect on User Preferences.
Scalia, Peter; Durand, Marie-Anne; Kremer, Jan; Faber, Marjan; Elwyn, Glyn
2018-01-01
Randomized trials have shown that patient decision aids can modify users' preferred healthcare options, but research has yet to identify the attributes embedded in these tools that cause preferences to shift. The aim of this study was to investigate people's preferences as they used decision aids for 5 health decisions and, for each of the following: 1) determine if using the interactive Option Grid led to a pre-post shift in preferences; 2) determine which frequently asked questions (FAQs) led to preference shifts; 3) determine the FAQs that were rated as the most important as users compared options. Interactive Option Grid decision aids enable users to view attributes of available treatment or screening options, rate their importance, and specify their preferred options before and after decision aid use. The McNemar-Bowker paired test was used to compare stated pre-post preferences. Multinomial logistic regressions were conducted to investigate possible associations between covariates and preference shifts. Overall, 626 users completed the 5 most-used tools: 1) Amniocentesis test: yes or no? ( n = 73); 2) Angina: treatment options ( n = 88); 3) Breast cancer: surgical options ( n = 265); 4) Prostate Specific Antigen (PSA) test: yes or no? ( n = 82); 5) Statins for heart disease risk: yes or no? ( n = 118). The breast cancer, PSA, and statins Option Grid decision aids generated significant preference shifts. Generally, users shifted their preference when presented with the description of the available treatment options, and the risk associated with each option. The use of decision aids for some, but not all health decisions, was accompanied by a shift in user preferences. Users typically valued information associated with risks, and chose more risk averse options after completing the interactive tool.
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Lope, Virginia; García-Esquinas, Esther; Ruiz-Dominguez, José Manuel; LLorca, Javier; Jiménez-Moleón, José Juan; Ruiz-Cerdá, José L; Alguacil, Juan; Tardón, Adonina; Dierssen-Sotos, Trinidad; Tabernero, Ángel; Mengual, Lourdes; Kogevinas, Manolis; Aragonés, Nuria; Castaño-Vinyals, Gemma; Pollán, Marina; Pérez-Gómez, Beatriz
2016-08-01
In utero and early-life exposures are suspected to modulate the risk of prostate cancer. This study examines the influence of certain perinatal and childhood-related factors on prostate cancer risk overall and by Gleason score at biopsy. MCC-Spain is a multicase-control study where 1088 histologically-confirmed incident prostate cancer cases (aged 42-85years) and 1345 population-based controls (aged 38-85years), frequency matched by age and province of recruitment, were recruited in 7 Spanish provinces. Self-reported perinatal and childhood-related characteristics were directly surveyed by trained staff. The association with prostate cancer risk, globally and according to Gleason score at biopsy, was evaluated using logistic and multinomial regression mixed models, adjusting for age, family history of prostate cancer, educational level and body mass index one year before the interview, and including the province as a random effect term. Most perinatal factors were not related to prostate cancer risk, with the exception of middle-high socioeconomic level at birth (OR for high grade tumors=1.36; 95%CI=1.09-1.68). Regarding puberty, risk rose by 6% for each year of delayed onset (OR=1.06; 95%CI=1.01-1.10; p trend=0.016), with a clear excess of risk in men who reached puberty after age 15 (OR:1.35; 95%CI=1.08-1.68). A borderline significant positive association with prepubertal height was also observed (p trend=0.094). Some exposures experienced in utero and during adolescence, when the prostate is still maturing, might be relevant for prostate cancer risk in adulthood. Copyright © 2016 Elsevier Ltd. All rights reserved.
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Hall, Kelli Stidham; Moreau, Caroline; Trussell, James; Barber, Jennifer
2013-08-01
We prospectively examined the influence of young women's depression and psychological stress symptoms on their weekly contraceptive method use. We examined data from 689 women ages 18-20 years participating in a longitudinal cohort study. Women completed 8,877 weekly journals over the first year, which assessed reproductive, relationship, and health information. We focused on baseline depression (Center for Epidemiologic Studies-Depression Scale) and stress (Perceived Stress Scale) symptoms and weekly contraceptive method use. Analyses used multivariate random effects and multinomial logistic regression. Approximately one quarter of women exhibited moderate/severe depression (27%) and stress (25%) symptoms at baseline. Contraception was not used in 10% of weekly journals, whereas coital and noncoital methods were used in 42% and 48% of weeks, respectively. In adjusted models, women with moderate/severe stress symptoms had more than twice the odds of contraception nonuse than women without stress (odds ratio [OR] 2.23, confidence interval [CI] 1.02-4.89, p = .04). Additionally, women with moderate/severe depression (RR .52, CI .40-.68, p < .001) and stress (relative risk [RR] .75, CI .58-.96, p = .02) symptoms had lower relative risks of using long-acting methods than oral contraceptives (OCs; reference category). Women with stress symptoms also had higher relative risks of using condoms (RR 1.17, CI 1.00-1.34, p = .02) and withdrawal (RR 1.29, CI 1.10-1.51, p = .001) than OCs. The relative risk of dual versus single method use was also lower for women with stress symptoms. Women's psychological symptoms predicted their weekly contraceptive nonuse and use of less effective methods. Further research can determine the influence of dynamic psychological symptoms on contraceptive choices and failures over time. Copyright © 2013 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.
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Wielaard, Ilse; Hoyer, Mathijs; Rhebergen, Didi; Stek, Max L; Comijs, Hannie C
2018-03-01
Childhood abuse makes people vulnerable to developing depression, even in late life. Psychosocial factors that are common in late life, such as loneliness or lack of a partner, may explain this association. Our aim was to investigate whether the association between childhood abuse and depression in older adults can be explained by psychosocial factors. Cross-sectional data were derived from the Netherlands Study of Depression in Older Persons (aged 60-93), including 132 without lifetime depression, 242 persons with an early-onset depression (<60 years), and 125 with a late-onset (≥60 years) depression. Childhood abuse (yes/no) and a frequency-based childhood abuse index were included. Multinomial regression and multivariable mediation analyses were used to examine the association between childhood abuse and the onset of depression, and the influence of loneliness, social network, and partner status. Multinomial regression analyses showed a significant association between childhood abuse and the childhood abuse index with early- and late-onset depression. Multivariable mediation analyses showed that the association between childhood abuse and early-onset depression was partly mediated by social network size and loneliness. This was particularly present for emotional neglect and psychological abuse, but not for physical and sexual abuse. No psychosocial mediators were found for the association between childhood abuse and late-onset depression. A smaller social network and feelings of loneliness mediate the association between childhood abuse and early-onset depression in older adults. Our findings show the importance of detecting childhood abuse as well as the age at depression onset and mapping of relevant psychosocial factors in the treatment of late-life depression. Copyright © 2018 John Wiley & Sons, Ltd.
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Jewczak, Maciej; Skura-Madziała, Anna
2017-01-01
Introduction The quality of life (QoL) experienced by cancer patients depends both on their state of health and on sociodemographic factors. Tumours in the head and neck region have a particularly adverse effect on patients psychologically and on their social functioning. Material and methods The study involved 121 patients receiving radiotherapy treatment for head and neck cancers. They included 72 urban and 49 rural residents. QoL was assessed using the questionnaires EORTC-QLQ-C30 and QLQ-H&N35. The data were analysed using statistical methods: a χ2 test for independence and a multinomial logit model. Results The evaluation of QoL showed a strong, statistically significant, positive dependence on state of health, and a weak dependence on sociodemographic factors and place of residence. Evaluations of financial situation and living conditions were similar for rural and urban residents. Patients from urban areas had the greatest anxiety about deterioration of their state of health. Rural respondents were more often anxious about a worsening of their financial situation, and expressed a fear of loneliness. Conclusions Studying the QoL of patients with head and neck cancer provides information concerning the areas in which the disease inhibits their lives, and the extent to which it does so. It indicates conditions for the adaptation of treatment and care methods in the healthcare system which might improve the QoL of such patients. A multinomial logit model identifies the factors determining the patients’ health assessment and defines the probable values of such assessment. PMID:29181080
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Khatab, Khaled; Adegboye, Oyelola; Mohammed, Taofeeq Ibn
2016-01-01
Globally, the burden of mortality in children, especially in poor developing countries, is alarming and has precipitated concern and calls for concerted efforts in combating such health problems. Examples of diseases that contribute to this burden of mortality include diarrhoea, cough, fever, and the overlap between these illnesses, causing childhood morbidity and mortality. To gain insight into these health issues, we employed the 2008 Demographic and Health Survey Data of Egypt, which recorded details from 10,872 children under five. This data focused on the demographic and socio-economic characteristics of household members. We applied a Bayesian multinomial model to assess the area-specific spatial effects and risk factors of co-morbidity of fever, diarrhoea and cough for children under the age of five. The results showed that children under 20 months of age were more likely to have the three diseases (OR: 6.8; 95% CI: 4.6-10.2) than children between 20 and 40 months (OR: 2.14; 95% CI: 1.38-3.3). In multivariate Bayesian geo-additive models, the children of mothers who were over 20 years of age were more likely to have only cough (OR: 1.2; 95% CI: 0.9-1.5) and only fever (OR: 1.2; 95% CI: 0.91-1.51) compared with their counterparts. Spatial results showed that the North-eastern region of Egypt has a higher incidence than most of other regions. This study showed geographic patterns of Egyptian governorates in the combined prevalence of morbidity among Egyptian children. It is obvious that the Nile Delta, Upper Egypt, and south-eastern Egypt have high rates of diseases and are more affected. Therefore, more attention is needed in these areas.
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Using a multinomial tree model for detecting mixtures in perceptual detection
Chechile, Richard A.
2014-01-01
In the area of memory research there have been two rival approaches for memory measurement—signal detection theory (SDT) and multinomial processing trees (MPT). Both approaches provide measures for the quality of the memory representation, and both approaches provide for corrections for response bias. In recent years there has been a strong case advanced for the MPT approach because of the finding of stochastic mixtures on both target-present and target-absent tests. In this paper a case is made that perceptual detection, like memory recognition, involves a mixture of processes that are readily represented as a MPT model. The Chechile (2004) 6P memory measurement model is modified in order to apply to the case of perceptual detection. This new MPT model is called the Perceptual Detection (PD) model. The properties of the PD model are developed, and the model is applied to some existing data of a radiologist examining CT scans. The PD model brings out novel features that were absent from a standard SDT analysis. Also the topic of optimal parameter estimation on an individual-observer basis is explored with Monte Carlo simulations. These simulations reveal that the mean of the Bayesian posterior distribution is a more accurate estimator than the corresponding maximum likelihood estimator (MLE). Monte Carlo simulations also indicate that model estimates based on only the data from an individual observer can be improved upon (in the sense of being more accurate) by an adjustment that takes into account the parameter estimate based on the data pooled across all the observers. The adjustment of the estimate for an individual is discussed as an analogous statistical effect to the improvement over the individual MLE demonstrated by the James–Stein shrinkage estimator in the case of the multiple-group normal model. PMID:25018741
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Rivera, Echo A; Kubiak, Sheryl P; Bybee, Deborah
2014-12-01
Research on women's aggression typically focuses on relational aggression. However, the study of violence must include multiple forms of violence such as aggression against partners and non-partner others, while also considering victimization experiences by partners and non-partners. The focus of this study is the multiple experiences of violence (perpetration and victimization) of women who are incarcerated. Incarcerated women are likely to experience higher rates of both than women in community settings, but most will be released in a brief period of time. Using a random sample (N = 580) we conducted cluster analyses to identify five patterns of women's aggression. Clusters varied depending on the target/s of aggression (i.e., partner and/or others), and type of aggression (i.e., physical and/or intimidation). Multinomial logistic regression was performed to determine the relationship between women's membership in a perpetration cluster and their victimization. Victimization history was related to an increased risk of perpetrating aggression, and varied depending on the target and type of aggression. Our findings provide support that research and interventions addressing women's use of aggression must also address their victimization history. Furthermore, results indicate that for some women, aggression towards partners and others is related. Future research should investigate multiple forms of aggression.
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Vegetarian Diet and Cardiometabolic Risk among Asian Indians in the United States.
Misra, Ranjita; Balagopal, Padmini; Raj, Sudha; Patel, Thakor G
2018-01-01
Research studies have shown that plant-based diets confer cardiovascular and metabolic health benefits. Asian Indians (AIs) in the US (who have often followed plant-based diets) have elevated risk for chronic diseases such as diabetes, metabolic syndrome, and obesity suggesting ethnic vulnerability that imply genetic and/or lifestyle causative links. This study explored the association between this ethnic group and diabetes, obesity, and metabolic syndrome after controlling for demographics, acculturation, family history of diabetes, and lifestyle and clinical risk factors. The sample comprised of 1038 randomly selected adult AIs in seven US sites. Prevalence and metabolic syndrome was estimated, and obesity was calculated using the WHO Asian criteria. Multivariate analysis included multinomial logistic regression. The mean age and length of residency in the US were 47 and 18.5 years, respectively. The majority of respondents were vegetarians (62%) and educated. A vegetarian lifestyle was associated with females, food label users, respondents with poor/fair current health status, less acculturated, and those who reported their diet had not changed after coming to the US. Vegetarian status was a protective factor and lowered the risk for diabetes but not for metabolic syndrome and obesity in the regression model. Results provide a firm basis for educational programs.
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Social Branding to Decrease Smoking Among Young Adults in Bars
Lee, Youn Ok; Hong, Juliette; Neilands, Torsten B.; Jordan, Jeffrey W.; Glantz, Stanton A.
2014-01-01
Objectives. We evaluated a Social Branding antitobacco intervention for “hipster” young adults that was implemented between 2008 and 2011 in San Diego, California. Methods. We conducted repeated cross-sectional surveys of random samples of young adults going to bars at baseline and over a 3-year follow-up. We used multinomial logistic regression to evaluate changes in daily smoking, nondaily smoking, and binge drinking, controlling for demographic characteristics, alcohol use, advertising receptivity, trend sensitivity, and tobacco-related attitudes. Results. During the intervention, current (past 30 day) smoking decreased from 57% (baseline) to 48% (at follow-up 3; P = .002), and daily smoking decreased from 22% to 15% (P < .001). There were significant interactions between hipster affiliation and alcohol use on smoking. Among hipster binge drinkers, the odds of daily smoking (odds ratio [OR] = 0.44; 95% confidence interval [CI] = 0.30, 0.63) and nondaily smoking (OR = 0.57; 95% CI = 0.42, 0.77) decreased significantly at follow-up 3. Binge drinking also decreased significantly at follow-up 3 (OR = 0.64; 95% CI = 0.53, 0.78). Conclusions. Social Branding campaigns are a promising strategy to decrease smoking in young adult bar patrons. PMID:24524502
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Vegetarian Diet and Cardiometabolic Risk among Asian Indians in the United States
Balagopal, Padmini; Patel, Thakor G.
2018-01-01
Research studies have shown that plant-based diets confer cardiovascular and metabolic health benefits. Asian Indians (AIs) in the US (who have often followed plant-based diets) have elevated risk for chronic diseases such as diabetes, metabolic syndrome, and obesity suggesting ethnic vulnerability that imply genetic and/or lifestyle causative links. This study explored the association between this ethnic group and diabetes, obesity, and metabolic syndrome after controlling for demographics, acculturation, family history of diabetes, and lifestyle and clinical risk factors. The sample comprised of 1038 randomly selected adult AIs in seven US sites. Prevalence and metabolic syndrome was estimated, and obesity was calculated using the WHO Asian criteria. Multivariate analysis included multinomial logistic regression. The mean age and length of residency in the US were 47 and 18.5 years, respectively. The majority of respondents were vegetarians (62%) and educated. A vegetarian lifestyle was associated with females, food label users, respondents with poor/fair current health status, less acculturated, and those who reported their diet had not changed after coming to the US. Vegetarian status was a protective factor and lowered the risk for diabetes but not for metabolic syndrome and obesity in the regression model. Results provide a firm basis for educational programs. PMID:29670913
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Depression after Exposure to Stressful Events: Lessons Learned from the SARS Epidemic
Liu, Xinhua; Kakade, Meghana; Fuller, Cordelia J.; Fan, Bin; Fang, Yunyun; Kong, Junhui; Guan, Zhiqiang; Wu, Ping
2011-01-01
Aim To examine, among hospital employees exposed to an outbreak of severe acute respiratory syndrome (SARS), post-outbreak levels of depressive symptoms, and the relationship between those depressive symptom levels and the types of outbreak event exposures experienced. Methods In 2006, randomly selected employees (n = 549) of a hospital in Beijing were surveyed concerning their exposures to the city’s 2003 SARS outbreak, and the ways in which the outbreak had affected their mental health. Subjects were assessed on sociodemographic factors, on types of exposure to the outbreak, and on symptoms of post-traumatic stress disorder (PTSD) and depression. Results The results of multinomial regression analyses showed that, with other relevant factors controlled for, being single, having been quarantined during the outbreak, having been exposed to other traumatic events prior to SARS, and perceived SARS-related risk level during the outbreak were found to increase the odds of having a high level of depressive symptoms three years later. Altruistic acceptance of risk during the outbreak was found to decrease the odds of high post-outbreak depressive symptom levels. Conclusions Policy makers and mental health professionals working to prepare for potential disease outbreaks should be aware that the experience of being quarantined can, in some cases, lead to long-term adverse mental health consequences. PMID:21489421
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Stability and change in fertility preferences among young women in Malawi.
Sennott, Christie; Yeatman, Sara
2012-03-01
Although studies have demonstrated change in fertility preferences over time, there is a lack of definitive knowledge about the level and direction of change among individuals, especially young and unmarried women. Furthermore, little is known about the factors associated with changes in fertility preferences over time. The analysis uses the first five waves of data from a longitudinal study of a random sample of women aged 15-25 in southern Malawi. The data were collected four months apart over an 18-month period, between June 2009 and December 2010. Multinomial logit regression models were used to calculate relative risk ratios and identify associations between four categories of life events-reproductive, relationship, health and economic-and shifts in fertility timing preferences. In each four-month period, more than half of the women reported changes in the desired timing of their next birth, and delays and accelerations in timing desires were common. Several life events, including having a child, entering a serious relationship and changes in household finances were associated with changes in the level and direction of fertility preference. Shifts in fertility timing preferences often occur in response to changes in life circumstances. Understanding the reasons for these shifts may aid family planning providers in meeting women's contraceptive needs.
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[TOBACCO CONSUMPTION AMONG ADULTS IN MONTERREY: RELATION TO EXERCISE REGULARLY AND FAMILY].
Ruiz-Juan, Francisco; Isorna-Folgar, Manuel; Ruiz-Risueño, Jorge; Vaquero-Cristóbal, Raquel
2015-08-01
determine the relationship among tobacco consumption, physical activity, sociodemographic variables and family behaviours in Mexican adults. 978 Mexican adults (483 males and 495 females) were interviewed by a random routes questionnaire. Multinomial logistic regression was used to calculate odds ratio (OR) and confidence interval (CI = 95%). men have a high risk factor of tobacco comsumption in frequency and/or amount. 18 to 45 years-old is the age range with high probability of tobacco comsumption, while the more age, the less comsumption. The tobacco consumption risk is significantly low in people who have less that a primary education. Participants who have never done physical exercise have a low possibility of tobacco consumption, while the consumption is high in the group of people who have abandoned physical activity. The family context is a risk factor of tobacco consumption in frequency. About alcohol consumption, it was found that people who drink alcohol have a high probability of smoke. tobacco consumption at high frequencies and amounts and physical activity are inversely relationship. It has been also detected a direct relationship between the frequency and the amount of tobacco and alcohol consumptions; and between the frequency and the amount of tobacco consumption and the family in the tobacco consumption. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.
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Honarmand, Marieh; Farhadmollashahi, Leila; Bekyghasemi, Mahmoud
2013-01-01
Smokeless tobacco consumption is one of the causes of oral cancer. The aim of this study was to determine the prevalence of smokeless tobacco consumption among male students of Zahedan universities and associated factors in 2012. In this cross-sectional study, 431 students were selected from the universities of Zahedan using multi-stage random cluster sampling. The data collection tool was a questionnaire including questions about demographic information, history of smokeless tobacco consumption, and awareness of smokeless tobacco hazards. Data were analyzed by SPSS19 using Chi-square test and multinomial logistic regression, with p<0.05 considered significant. At the time of conducting this study, 102 students (23.7%) had already consumed smokeless tobacco and 49 students (11.4%) were current users (consuming at least once in 30 days before the study). There was a significant relationship between history of smokeless tobacco consumption, university/college, place of living, mean GPA, and mother's education level (p<0.05). Also there was a significant association between knowledge and prevalence of smokeless tobacco use (p<0.001). There is a relatively high prevalence of smokeless tobacco consumption among the male students of universities of Zahedan, which shows the need to emphasize the provision and implementation of prevention programs in universities.
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Levin, A; Rahman, M A; Quayyum, Z; Routh, S; Barkat-e-Khuda
2001-01-01
This paper seeks to investigate the determinants of child health care seeking behaviours in rural Bangladesh. In particular, the effects of income, women's access to income, and the prices of obtaining child health care are examined. Data on the use of child curative care were collected in two rural areas of Bangladesh--Abhoynagar Thana of Jessore District and Mirsarai Thana of Chittagong District--in March 1997. In estimating the use of child curative care, the nested multinomial logit specification was used. The results of the analysis indicate that a woman's involvement in a credit union or income generation affected the likelihood that curative child care was used. Household wealth decreased the likelihood that the child had an illness episode and affected the likelihood that curative child care was sought. Among facility characteristics, travel time was statistically significant and was negatively associated with the use of a provider.
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Ahn, Jae Joon; Kim, Young Min; Yoo, Keunje; Park, Joonhong; Oh, Kyong Joo
2012-11-01
For groundwater conservation and management, it is important to accurately assess groundwater pollution vulnerability. This study proposed an integrated model using ridge regression and a genetic algorithm (GA) to effectively select the major hydro-geological parameters influencing groundwater pollution vulnerability in an aquifer. The GA-Ridge regression method determined that depth to water, net recharge, topography, and the impact of vadose zone media were the hydro-geological parameters that influenced trichloroethene pollution vulnerability in a Korean aquifer. When using these selected hydro-geological parameters, the accuracy was improved for various statistical nonlinear and artificial intelligence (AI) techniques, such as multinomial logistic regression, decision trees, artificial neural networks, and case-based reasoning. These results provide a proof of concept that the GA-Ridge regression is effective at determining influential hydro-geological parameters for the pollution vulnerability of an aquifer, and in turn, improves the AI performance in assessing groundwater pollution vulnerability.
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ERIC Educational Resources Information Center
Lubbers, Marcel; Jaspers, Eva; Ultee, Wout
2009-01-01
Two years after the legalization of same-sex marriages in the Netherlands, 65% of the Dutch population largely or completely disagrees with the statement "gay marriage should be abolished." This article shows, by way of multinomial logistic regression analysis of survey data, which socializing agents influence one's attitude toward…
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Large Sample Confidence Limits for Goodman and Kruskal's Proportional Prediction Measure TAU-b
ERIC Educational Resources Information Center
Berry, Kenneth J.; Mielke, Paul W.
1976-01-01
A Fortran Extended program which computes Goodman and Kruskal's Tau-b, its asymmetrical counterpart, Tau-a, and three sets of confidence limits for each coefficient under full multinomial and proportional stratified sampling is presented. A correction of an error in the calculation of the large sample standard error of Tau-b is discussed.…
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ERIC Educational Resources Information Center
Grinshteyn, Erin; Yang, Y. T.
2017-01-01
Background: We examined the relationship between exposure to electronic bullying and absenteeism as a result of being afraid. Methods: This multivariate, multinomial regression analysis of the 2013 Youth Risk Behavior Survey data assessed the association between experiencing electronic bullying in the past year and how often students were absent…
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ERIC Educational Resources Information Center
Ansara, Donna L.; Hindin, Michelle J.
2009-01-01
This study uses data from the 2002 Cebu Longitudinal Health and Nutrition Survey to examine the prevalence of and factors associated with intimate partner violence perpetration by husbands and wives in Cebu, Philippines. Multinomial logistic regression was used to identify the factors associated with wife-only, husband-only, and reciprocal…
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ERIC Educational Resources Information Center
Arria, Amelia M.; Garnier-Dykstra, Laura M.; Caldeira, Kimberly M.; Vincent, Kathryn B.; O'Grady, Kevin E.; Wish, Eric D.
2011-01-01
Objective: To investigate the possible association between untreated ADHD symptoms (as measured by the Adult ADHD Self-Report Scale) and persistent nonmedical use of prescription stimulants. Method: Multinomial regression modeling was used to compare ADHD symptoms among three groups of college students enrolled in a longitudinal study over 4…
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A Multinomial Model for Identifying Significant Pure-Tone Threshold Shifts
ERIC Educational Resources Information Center
Schlauch, Robert S.; Carney, Edward
2007-01-01
Purpose: Significant threshold differences on retest for pure-tone audiometry are often evaluated by application of ad hoc rules, such as a shift in a pure-tone average or in 2 adjacent frequencies that exceeds a predefined amount. Rules that are so derived do not consider the probability of observing a particular audiogram. Methods: A general…
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A Multilevel Study of Students' Motivations of Studying Accounting: Implications for Employers
ERIC Educational Resources Information Center
Law, Philip; Yuen, Desmond
2012-01-01
Purpose: The purpose of this study is to examine the influence of factors affecting students' choice of accounting as a study major in Hong Kong. Design/methodology/approach: Multinomial logistic regression and Hierarchical Generalized Linear Modeling (HGLM) are used to analyze the survey data for the level one and level two data, which is the…
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ERIC Educational Resources Information Center
Veldkamp, Bernard P.; van der Linden, Wim J.
2008-01-01
In most operational computerized adaptive testing (CAT) programs, the Sympson-Hetter (SH) method is used to control the exposure of the items. Several modifications and improvements of the original method have been proposed. The Stocking and Lewis (1998) version of the method uses a multinomial experiment to select items. For severely constrained…
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Belonging to and Exclusion from the Peer Group in Schools: Influences on Adolescents' Moral Choices
ERIC Educational Resources Information Center
Feigenberg, Luba Falk; King, Melissa Steel; Barr, Dennis J.; Selman, Robert L.
2008-01-01
This paper reports on a mixed methods study of adolescents' responses to case material about social exclusion. First, a qualitative coding method is presented that describes the way adolescents choose and justify strategies to negotiate such situations. The responses were then analysed quantitatively using chi square tests and multinomial logistic…
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Religiosity Profiles of American Youth in Relation to Substance Use, Violence, and Delinquency
ERIC Educational Resources Information Center
Salas-Wright, Christopher P.; Vaughn, Michael G.; Hodge, David R.; Perron, Brian E.
2012-01-01
Relatively little is known in terms of the relationship between religiosity profiles and adolescents' involvement in substance use, violence, and delinquency. Using a diverse sample of 17,705 (49 % female) adolescents from the 2008 National Survey on Drug Use and Health, latent profile analysis and multinomial regression are employed to examine…
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ERIC Educational Resources Information Center
Jee, Rebecca Y.
2015-01-01
Voxy, an English-language-learning company, has developed a custom, in-house proficiency exam, the Voxy Proficiency Assessment (VPA), which is given to all learners at the beginning and end of their courses. Using Multinomial Logistic Regression (MLR), the impact of covariates, such as total learning activities completed and total number of…
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Woo-Yong Hyun; Robert B. Ditton
2007-01-01
The concept of recreation substitutability has been a continuing research topic for outdoor recreation researchers. This study explores the relationships among variables regarding the willingness to substitute one location for another location. The objectives of the study are 1) to ascertain and predict the extent to which saltwater anglers were willing to substitute...
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School Exits in the Milwaukee Parental Choice Program: Evidence of a Marketplace?
ERIC Educational Resources Information Center
Ford, Michael
2011-01-01
This article examines whether the large number of school exits from the Milwaukee school voucher program is evidence of a marketplace. Two logistic regression and multinomial logistic regression models tested the relation between the inability to draw large numbers of voucher students and the ability for a private school to remain viable. Data on…
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So Close, yet So Far Away: Early vs. Late Dropouts
ERIC Educational Resources Information Center
Ma, Yanli; Cragg, Kristina M.
2013-01-01
While some students drop out early in their academic career, others drop out close to completion. What similarities and differences exist between these early and late dropouts? Using a sample 3,520 first-time, full-time (FTFT) students seeking a bachelor's degree at a state university, this study employs multinomial logistic regression to model…
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ERIC Educational Resources Information Center
Roessler, Richard T.; Neath, Jeanne; McMahon, Brian T.; Rumrill, Phillip D.
2007-01-01
Single-predictor and stepwise multinomial logistic regression analyses and an external validation were completed on 3,082 allegations of employment discrimination by adults with multiple sclerosis. Women filed two thirds of the allegations, and individuals between 31 and 50 made the vast majority of discrimination charges (73%). Allegations…
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A Multinomial Logit Model of Attrition that Distinguishes between Stopout and Dropout Behavior
ERIC Educational Resources Information Center
Stratton, Leslie S.; O'Toole, Dennis M.; Wetzel, James N.
2004-01-01
College attrition rates are of substantial concern to policy makers and economists interested in educational attainment and earnings opportunities. This is not surprising since nationwide, almost one-third of all first-time college students fail to return for their sophomore year. There exists a substantial body of literature seeking to model this…
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ERIC Educational Resources Information Center
Sciarra, Daniel T.; Seirup, Holly J.; Sposato, Elizabeth
2016-01-01
This study investigated factors from high school that might predict college persistence. The sample consisted of 7,271 participants in three waves of data collection (2002, 2004 and 2006) who participated in the Educational Longitudinal Study (ELS; U.S. Department of Education, 2008). A multinomial logistic regression mode was employed to…
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USDA-ARS?s Scientific Manuscript database
Small, coded, pill-sized tracers embedded in grain are proposed as a method for grain traceability. A sampling process for a grain traceability system was designed and investigated by applying probability statistics using a science-based sampling approach to collect an adequate number of tracers fo...
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A Multinomial Logit Approach to Estimating Regional Inventories by Product Class
Lawrence Teeter; Xiaoping Zhou
1998-01-01
Current timber inventory projections generally lack information on inventory by product classes. Most models available for inventory projection and linked to supply analyses are limited to projecting aggregate softwood and hardwood. The objective of this research is to develop a methodology to distribute the volume on each FIA survey plot to product classes and...
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ERIC Educational Resources Information Center
Albaqshi, Amani Mohammed H.
2017-01-01
Functional Data Analysis (FDA) has attracted substantial attention for the last two decades. Within FDA, classifying curves into two or more categories is consistently of interest to scientists, but multi-class prediction within FDA is challenged in that most classification tools have been limited to binary response applications. The functional…
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Sendi, Pedram; Brouwer, Werner B F; Bucher, Heiner C; Weber, Rainer; Battegay, Manuel
2007-06-01
Time is a limited resource and individuals have to decide how many hours they should allocate to work and to leisure activities. Differences in wage rate or availability of non-labour income (financial support from families and savings) may influence how individuals allocate their time between work and leisure. An increase in wage rate may induce income effects (leisure time demanded increases) and substitution effects (leisure time demanded decreases) whereas an increase in non-labour income only induces income effects. We explored the effects of differences in wage rate and non-labour income on the allocation of time in HIV-infected patients. Patients enrolled in the Swiss HIV Cohort Study (SHCS) provided information on their time allocation, i.e. number of hours worked in 1998. A multinomial logistic regression model was used to test for income and substitution effects. Our results indicate that (i) the allocation of time in HIV-infected patients does not differ with level of education (i.e., wage rate), and that (ii) availability of non-labour income induces income effects, i.e. individuals demand more leisure time.
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The effects of mandatory health insurance on equity in access to outpatient care in Indonesia.
Hidayat, Budi; Thabrany, Hasbullah; Dong, Hengjin; Sauerborn, Rainer
2004-09-01
This paper examines the effects of mandatory health insurance on access and equity in access to public and private outpatient care in Indonesia. Data from the second round of the 1997 Indonesian Family Life Survey were used. We adopted the concentration index as a measure of equity, and this was calculated from actual data and from predicted probability of outpatient-care use saved from a multinomial logit regression. The study found that a mandatory insurance scheme for civil servants (Askes) had a strongly positive impact on access to public outpatient care, while a mandatory insurance scheme for private employees (Jamsostek) had a positive impact on access to both public and private outpatient care. The greatest effects of Jamsostek were observed amongst poor beneficiaries. A substantial increase in access will be gained by expanding insurance to the whole population. However, neither Askes nor Jamsostek had a positive impact on equity. Policy implications are discussed.
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ERIC Educational Resources Information Center
Obidzinski, Michal; Nieznanski, Marek
2017-01-01
The presented research was conducted in order to investigate the connections between developmental dyslexia and the functioning of verbatim and gist memory traces--assumed in the fuzzy-trace theory. The participants were 71 high school students (33 with dyslexia and 38 without learning difficulties). The modified procedure and multinomial model of…
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Comparative Evaluation of Two Methods to Estimate Natural Gas Production in Texas
2003-01-01
This report describes an evaluation conducted by the Energy Information Administration (EIA) in August 2003 of two methods that estimate natural gas production in Texas. The first method (parametric method) was used by EIA from February through August 2003 and the second method (multinomial method) replaced it starting in September 2003, based on the results of this evaluation.
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An Exploration of Teacher Attrition and Mobility in High Poverty Racially Segregated Schools
ERIC Educational Resources Information Center
Djonko-Moore, Cara M.
2016-01-01
The purpose of this study was to examine the mobility (movement to a new school) and attrition (quitting teaching) patterns of teachers in high poverty, racially segregated (HPRS) schools in the US. Using 2007-9 survey data from the National Center for Education Statistics, a multi-level multinomial logistic regression was performed to examine the…
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ERIC Educational Resources Information Center
Haataja, Anne; Ahtola, Annarilla; Poskiparta, Elisa; Salmivalli, Christina
2015-01-01
The present study provides a person-centered view on teachers' adherence to the KiVa antibullying curriculum over a school year. Factor mixture modeling was used to examine how teachers (N = 282) differed in their implementation profiles and multinomial logistic regression was used to identify factors related to these profiles. On the basis of…
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A Typology of Work-Family Arrangements among Dual-Earner Couples in Norway
ERIC Educational Resources Information Center
Kitterod, Ragni Hege; Lappegard, Trude
2012-01-01
A symmetrical family model of two workers or caregivers is a political goal in many western European countries. We explore how common this family type is in Norway, a country with high gender-equality ambitions, by using a multinomial latent class model to develop a typology of dual-earner couples with children based on the partners' allocations…
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ERIC Educational Resources Information Center
Jowett, Tim; Harraway, John; Lovelock, Brent; Skeaff, Sheila; Slooten, Liz; Strack, Mick; Shephard, Kerry
2014-01-01
Higher education is increasingly interested in its impact on the sustainability attributes of its students, so we wanted to explore how our students' environmental concern changed during their higher education experiences. We used the Revised New Ecological Paradigm Scale (NEP) with 505 students and developed and tested a multinomial…
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ERIC Educational Resources Information Center
Hansen, Mark; Cai, Li; Monroe, Scott; Li, Zhen
2014-01-01
It is a well-known problem in testing the fit of models to multinomial data that the full underlying contingency table will inevitably be sparse for tests of reasonable length and for realistic sample sizes. Under such conditions, full-information test statistics such as Pearson's X[superscript 2]?? and the likelihood ratio statistic…
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ERIC Educational Resources Information Center
Dixon, Pauline; Humble, Steve
2017-01-01
This research set out to investigate how, in a post-conflict area, parental preferences and household characteristics affect school choice for their children. A multinomial logit is used to model the relationship between education preferences and the selection of schools for 954 households in Freetown and neighboring districts, Western Area,…
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DOE Office of Scientific and Technical Information (OSTI.GOV)
Ryding, Kristen E.; Skalski, John R.
1999-06-01
The purpose of this report is to illustrate the development of a stochastic model using coded wire-tag (CWT) release and age-at-return data, in order to regress first year ocean survival probabilities against coastal ocean conditions and climate covariates.
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Frndak, Seth E; Smerbeck, Audrey M; Irwin, Lauren N; Drake, Allison S; Kordovski, Victoria M; Kunker, Katrina A; Khan, Anjum L; Benedict, Ralph H B
2016-10-01
We endeavored to clarify how distinct co-occurring symptoms relate to the presence of negative work events in employed multiple sclerosis (MS) patients. Latent profile analysis (LPA) was utilized to elucidate common disability patterns by isolating patient subpopulations. Samples of 272 employed MS patients and 209 healthy controls (HC) were administered neuroperformance tests of ambulation, hand dexterity, processing speed, and memory. Regression-based norms were created from the HC sample. LPA identified latent profiles using the regression-based z-scores. Finally, multinomial logistic regression tested for negative work event differences among the latent profiles. Four profiles were identified via LPA: a common profile (55%) characterized by slightly below average performance in all domains, a broadly low-performing profile (18%), a poor motor abilities profile with average cognition (17%), and a generally high-functioning profile (9%). Multinomial regression analysis revealed that the uniformly low-performing profile demonstrated a higher likelihood of reported negative work events. Employed MS patients with co-occurring motor, memory and processing speed impairments were most likely to report a negative work event, classifying them as uniquely at risk for job loss.
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Factors associated with happiness in the elderly persons living in the community.
Luchesi, Bruna Moretti; de Oliveira, Nathalia Alves; de Morais, Daiene; de Paula Pessoa, Rebeca Mendes; Pavarini, Sofia Cristina I; Chagas, Marcos Hortes N
2018-01-01
The aim of the present study was to evaluate factors associated with happiness in a sample of Brazilian older adults. A study was conducted with 263 elderly people in the area of coverage of a family health unit located in the state of São Paulo, Brazil. The Subjective Happiness Scale was used to measure happiness, the final score of which determined one of three outcomes: not happy, intermediate, and happy. Disability, sociodemographic characteristics, and psychological, cognitive, and physical factors were considered for the multinomial logistic regression analysis. Statistically significant differences were found among the three groups regarding satisfaction with life, disability, social phobia, anxiety, depression, and frailty (p≤0.05). In the multinomial regression analysis, being "not happy" was significantly associated with satisfaction with life (RRR: 0.53), depression (RRR: 1.46), social phobia (RRR: 1.24), and age (RRR: 1.06). The present findings indicate that psychological factors and age influence the levels of happiness in older adults living in the community. Furthermore, better screening, diagnosis, and treatment of mental health disorders could increase the feeling of happiness among older adults. Copyright © 2017 Elsevier B.V. All rights reserved.
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Zhang, Yongsheng; Wei, Heng; Zheng, Kangning
2017-01-01
Considering that metro network expansion brings us with more alternative routes, it is attractive to integrate the impacts of routes set and the interdependency among alternative routes on route choice probability into route choice modeling. Therefore, the formulation, estimation and application of a constrained multinomial probit (CMNP) route choice model in the metro network are carried out in this paper. The utility function is formulated as three components: the compensatory component is a function of influencing factors; the non-compensatory component measures the impacts of routes set on utility; following a multivariate normal distribution, the covariance of error component is structured into three parts, representing the correlation among routes, the transfer variance of route, and the unobserved variance respectively. Considering multidimensional integrals of the multivariate normal probability density function, the CMNP model is rewritten as Hierarchical Bayes formula and M-H sampling algorithm based Monte Carlo Markov Chain approach is constructed to estimate all parameters. Based on Guangzhou Metro data, reliable estimation results are gained. Furthermore, the proposed CMNP model also shows a good forecasting performance for the route choice probabilities calculation and a good application performance for transfer flow volume prediction. PMID:28591188
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Model-based Clustering of Categorical Time Series with Multinomial Logit Classification
NASA Astrophysics Data System (ADS)
Frühwirth-Schnatter, Sylvia; Pamminger, Christoph; Winter-Ebmer, Rudolf; Weber, Andrea
2010-09-01
A common problem in many areas of applied statistics is to identify groups of similar time series in a panel of time series. However, distance-based clustering methods cannot easily be extended to time series data, where an appropriate distance-measure is rather difficult to define, particularly for discrete-valued time series. Markov chain clustering, proposed by Pamminger and Frühwirth-Schnatter [6], is an approach for clustering discrete-valued time series obtained by observing a categorical variable with several states. This model-based clustering method is based on finite mixtures of first-order time-homogeneous Markov chain models. In order to further explain group membership we present an extension to the approach of Pamminger and Frühwirth-Schnatter [6] by formulating a probabilistic model for the latent group indicators within the Bayesian classification rule by using a multinomial logit model. The parameters are estimated for a fixed number of clusters within a Bayesian framework using an Markov chain Monte Carlo (MCMC) sampling scheme representing a (full) Gibbs-type sampler which involves only draws from standard distributions. Finally, an application to a panel of Austrian wage mobility data is presented which leads to an interesting segmentation of the Austrian labour market.
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Evaluating the Relationship between Productivity and Quality in Emergency Departments
Bastian, Nathaniel D.; Riordan, John P.
2017-01-01
Background In the United States, emergency departments (EDs) are constantly pressured to improve operational efficiency and quality in order to gain financial benefits and maintain a positive reputation. Objectives The first objective is to evaluate how efficiently EDs transform their input resources into quality outputs. The second objective is to investigate the relationship between the efficiency and quality performance of EDs and the factors affecting this relationship. Methods Using two data sources, we develop a data envelopment analysis (DEA) model to evaluate the relative efficiency of EDs. Based on the DEA result, we performed multinomial logistic regression to investigate the relationship between ED efficiency and quality performance. Results The DEA results indicated that the main source of inefficiencies was working hours of technicians. The multinomial logistic regression result indicated that the number of electrocardiograms and X-ray procedures conducted in the ED and the length of stay were significantly associated with the trade-offs between relative efficiency and quality. Structural ED characteristics did not influence the relationship between efficiency and quality. Conclusions Depending on the structural and operational characteristics of EDs, different factors can affect the relationship between efficiency and quality. PMID:29065673
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2013-01-01
Background Nutrition in the first 1,000 days of life (during pregnancy and the first two years) is critical for child growth and survival. Poor maternal, infant and young child nutrition (MIYCN) practices are widely documented in Kenya, with potential detrimental effects on child growth and survival. This is particularly a problem in slums, where most urban residents live. For example, exclusive breastfeeding for the first six months is only about two per cent. Innovative strategies to reach slum residents are therefore needed. Strategies like the Baby Friendly Hospital Initiative have proven effective in some settings but their effectiveness in resource-limited settings, including slums where many women do not deliver in hospital, is questionable. We propose to test the effectiveness of a home-based intervention on infant feeding practices, nutrition and health outcomes of infants born in two slums in Nairobi, Kenya. Methods/Design The study, employing a cluster-randomised study design, will be conducted in two slums in Nairobi: Korogocho and Viwandani where 14 community units (defined by the Government’s health care system) will form the unit of randomization. A total of 780 pregnant women and their respective child will be recruited into the study. The mother-child pair will be followed up until the child is one year old. Recruitment will last approximately one year and three months from September 2012 to December 2013. The mothers will receive regular, personalised, home-based counselling by trained Community Health Workers on MIYCN. Regular assessment of knowledge, attitudes and practices on MIYCN will be done, coupled with assessments of nutritional status of the mother-child pairs and diarrhea morbidity for the children. Statistical methods will include analysis of covariance and multinomial logistic regression. Additionally, cost-effectiveness analysis will be done. The study is funded by the Wellcome Trust and will run from March 2012 to February 2015. Discussion Interventions aimed at promoting optimal breastfeeding and complementary feeding practices are considered to have high impact and could prevent a fifth of the under-five deaths in countries with high mortality rates. This study will inform policy and practice in Kenya and similar settings regarding delivery mechanisms for such high-impact interventions, particularly among urban poor populations. Trial registration ISRCTN83692672 PMID:24370263
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Juon, Hee-Soon; Strong, Carol; Kim, Frederic; Park, Eunmi; Lee, Sunmin
2016-01-01
This study aimed to evaluate the effect of a lay health worker (LHW) telephone intervention on completing a series of hepatitis B virus (HBV) vaccinations among foreign-born Asian Americans in the Baltimore-Washington Metropolitan area. During the period of April 2013 and March 2014, we recruited Asian Americans who were 18 years of age and older in the community-based organizations. Of the 645 eligible participants, 600 (201 Chinese, 198 Korean, 201 Vietnamese) completed a pretest survey and received hepatitis B screening. Based on the screening results, we conducted a randomized controlled trial among those unprotected (HBsAg-/HBsAB-) by assigning them either to an intervention group (n = 124) or control group (n = 108). The intervention group received a list of resources by mails for where to get free vaccinations as well as reminder calls for vaccinations from trained LHWs, while the control group received only list of resources by mail. Seven months after mailing the HBV screening results, trained LHWs followed up with all participants by phone to ask how many of the recommended series of 3 vaccinations they had received: none, 1 or 2, or all 3 (complete). Their self-reported vaccinations were verified with the medical records. Multinomial logistic regressions were used to examine the effect of the LHW intervention. Process evaluation was conducted by asking study participants in the intervention group to evaluate the performance of the LHWs. After seven months, those in the intervention group were more likely to have 1 or more vaccines than the control group, compared to the no vaccination group (OR = 3.04, 95% CI, 1.16, 8.00). Also, those in the intervention group were more likely to complete a series of vaccinations than the control group, compared to the no vaccination group (OR = 7.29, 95% CI 3.39, 15.67). The most important barrier preventing them from seeking hepatitis B vaccinations was lack of time to get the vaccination. The most important promoters to getting vaccinations, among those who had vaccinations (n = 89), were our intervention program (70.8%) and self-motivation (49.4%). The majority of participants in the intervention group received the phone calls from LHWs (93%) and almost all of them got the reminder to receive vaccines (98%). The LHW intervention was successful at increasing HBV vaccinations rates among foreign-born Asian Americans. This study suggests that this culturally integrated intervention program may be useful for reducing liver cancer disparities from chronic HBV infection in high risk Asian Americans. ClinicalTrials.gov NCT02760537.
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Examining the association between race, ethnicity, and health status: do assets matter?
Boyas, Javier; Shobe, Marcia A; Hannam, Holly M
2009-10-01
The current study employs data from the 2004 Immigration and Intergenerational Mobility in Metropolitan Los Angeles (IIMMLA) study to examine the degree to which observed differences in self-reported health status between African Americans, Asians, Latinos, and non-Hispanic Whites in the United States can be attributed to differences in various indicators of socioeconomic status. Results of the multinomial logistic regression techniques suggest that socioeconomic indicators had varying significant effects in predicting self-reported health status among all racial and ethnic groups. Among African Americans, homeownership, income, and age played a significant role. Among Asian Americans, only income and age significantly predicted health status. Among Latinos, income, having a checking account, and age significantly shaped health status, while education, age, and homeownership significantly predicted health status among non-Hispanic Whites.
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Ecstasy Use and Suicidal Behavior Among Adolescents: Findings from a National Survey
Kim, Jueun; Fan, Bin; Liu, Xinhua; Kerner, Nancy; Wu, Ping
2011-01-01
This study examines the relationship between ecstasy use and suicidal behaviors among adolescents in the United States. Data from the adolescent subsample (ages 12–17, N=19,301) of the 2000 NHSDA were used in the analyses. Information on adolescent substance use, suicidal behaviors and related socio-demographic, family and individual factors was obtained in the survey. The rate of past year suicide attempt among adolescents with lifetime ecstasy use was almost double that of adolescents who had used other drugs only, and nine times that of adolescents with no history of illicit drug use. In multinomial logistic regression analyses, controlling for related factors, the effect of ecstasy use remained significant. Adolescent ecstasy users may require enhanced suicide prevention and intervention efforts. PMID:21631573
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Women's labor force participation in later life: the effects of early work and family experiences.
Pienta, A M; Burr, J A; Mutchler, J E
1994-09-01
The purpose of this study was to develop and evaluate a model of labor force participation among a group of older women in the United States. A comprehensive measure of women's combined work and family experiences across the adult life course was created. Employing data from the 1984 Survey of Income and Program Participation, we applied multinomial logistic regression techniques to examine the association between work-family experiences and later life labor supply. Our findings generally support an attachment hypothesis, showing that women who were the most work-oriented throughout the life course were more likely than women who experienced family-related spells of nonlabor-market activity to participate in the labor force, either full-time or part-time, later in life.
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Ma, Ke-Zong M; Norton, Edward C; Lee, Shoou-Yih D
2010-01-01
Objective To test the hypothesis that declining fertility would affect the number of cesarean sections (c-sections) on maternal demand, but not medically indicated c-sections. Data Sources The 1996–2004 National Health Insurance Research Database in Taiwan for all singleton deliveries. Study Design Retrospective population-based, longitudinal study. Estimation was performed using multinomial probit models. Principal Findings Results revealed that declining fertility had a significant positive effect on the probability of having a c-section on maternal request but not medically indicated c-section. Conclusions Our findings offer a precautionary note to countries experiencing a fertility decline. Policies to contain the rise of c-sections should understand the role of women's preferences, especially regarding cesarean deliveries on maternal request. PMID:20545781
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NASA Astrophysics Data System (ADS)
Laudan, Jonas; Rözer, Viktor; Sieg, Tobias; Vogel, Kristin; Thieken, Annegret H.
2017-12-01
Flash floods are caused by intense rainfall events and represent an insufficiently understood phenomenon in Germany. As a result of higher precipitation intensities, flash floods might occur more frequently in future. In combination with changing land use patterns and urbanisation, damage mitigation, insurance and risk management in flash-flood-prone regions are becoming increasingly important. However, a better understanding of damage caused by flash floods requires ex post collection of relevant but yet sparsely available information for research. At the end of May 2016, very high and concentrated rainfall intensities led to severe flash floods in several southern German municipalities. The small town of Braunsbach stood as a prime example of the devastating potential of such events. Eight to ten days after the flash flood event, damage assessment and data collection were conducted in Braunsbach by investigating all affected buildings and their surroundings. To record and store the data on site, the open-source software bundle KoBoCollect was used as an efficient and easy way to gather information. Since the damage driving factors of flash floods are expected to differ from those of riverine flooding, a post-hoc data analysis was performed, aiming to identify the influence of flood processes and building attributes on damage grades, which reflect the extent of structural damage. Data analyses include the application of random forest, a random general linear model and multinomial logistic regression as well as the construction of a local impact map to reveal influences on the damage grades. Further, a Spearman's Rho correlation matrix was calculated. The results reveal that the damage driving factors of flash floods differ from those of riverine floods to a certain extent. The exposition of a building in flow direction shows an especially strong correlation with the damage grade and has a high predictive power within the constructed damage models. Additionally, the results suggest that building materials as well as various building aspects, such as the existence of a shop window and the surroundings, might have an effect on the resulting damage. To verify and confirm the outcomes as well as to support future mitigation strategies, risk management and planning, more comprehensive and systematic data collection is necessary.
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W. Henry McNab; David L. Loftis; Callie J. Schweitzer; Raymond Sheffield
2004-01-01
We used tree indicator species occurring on 438 plots in the Plateau counties of Tennessee to test the uniqueness of four conterminous ecoregions. Multinomial logistic regression indicated that the presence of 14 tree species allowed classification of sample plots according to ecoregion with an average overall accuracy of 75 percent (range 45 to 94 percent). Additional...
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ERIC Educational Resources Information Center
Rudolph, Christiane E. S.; Lundin, Andreas; Åhs, Jill W.; Dalman, Christina; Kosidou, Kyriaki
2018-01-01
We examined the association between autistic traits and sexual orientation in a general adult population (N = 47,356). Autistic traits were measured with the ten items Autistic Quotient questionnaire using a cut-off score of = 6. Sexual orientation was assessed by self-report. Multinomial logistic regression was used to estimate odds ratios (ORs)…
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ERIC Educational Resources Information Center
Thorn, Annabel S. C.; Gathercole, Susan E.; Frankish, Clive R.
2005-01-01
The impact of four long-term knowledge variables on serial recall accuracy was investigated. Serial recall was tested for high and low frequency words and high and low phonotactic frequency nonwords in 2 groups: monolingual English speakers and French-English bilinguals. For both groups the recall advantage for words over nonwords reflected more…
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ERIC Educational Resources Information Center
Meins, Elizabeth; Fernyhough, Charles; de Rosnay, Marc; Arnott, Bronia; Leekam, Susan R.; Turner, Michelle
2012-01-01
In a socially diverse sample of 206 infant-mother pairs, we investigated predictors of infants' attachment security at 15 months, with a particular emphasis on mothers' tendency to comment appropriately or in a non-attuned manner on their 8-month-olds' internal states (so-called mind-mindedness). Multinomial logistic regression analyses showed…
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ERIC Educational Resources Information Center
Wood, J. Luke; Palmer, Robert T.
2016-01-01
Background/Context: Transfer is a core function of community colleges; this is a critical point given that these institutions serve as the primary pathway into postsecondary education for Black men. However, too few Black men identify transfer as a primary goal and/or eventually transfer to a 4-year college or university.…
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ERIC Educational Resources Information Center
Xu, Xueli; von Davier, Matthias
2008-01-01
The general diagnostic model (GDM) utilizes located latent classes for modeling a multidimensional proficiency variable. In this paper, the GDM is extended by employing a log-linear model for multiple populations that assumes constraints on parameters across multiple groups. This constrained model is compared to log-linear models that assume…
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Morales Ruán, María Del Carmen; Valenzuela Bravo, Danae Gabriela; Jiménez Aguilar, Alejandra; Cuevas Nasu, Lucía; Méndez Gómez Humarán, Ignacio; Shamah Levy, Teresa
2018-02-16
food diversity is an approximation of diet quality. In Mexico, the Food Support Program (PAL, by its acronym in Spanish) grants support to families facing food poverty, in form of cash (PAL EFECTIVO) or through monetary transfers on a card intended exclusively for the purchase of food (PAL SIN-HAMBRE), seeking to improve their food diversity. to compare the dietary diversity in women beneficiaries of both schemes and their association with the level of food insecurity (FI) at household level. a cross-sectional study was carried out in a national random sample of 243 women beneficiaries from PAL EFECTIVO and 277 from PAL SIN-HAMBRE in 14 states. A multinomial logistic regression model was constructed to measure the association between the FI perception index and its relationship with the PAL and the dietary diversity index. the PAL SIN-HAMBRE scheme is associated with a lower probability of mild and severe FI with respect to the PAL EFECTIVO. The interaction between the type of scheme and the dietary diversity index showed that the PAL EFECTIVO had a lower probability of severe FI when the dietary diversity index was greater with respect to the PAL SIN-HAMBRE. the FI in the household and the low dietary diversity seem to be strongly associated in women of childbearing age and this relationship is higher in those beneficiaries of the PAL SIN-HAMBRE scheme.
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Borchani, Hanen; Bielza, Concha; Martı Nez-Martı N, Pablo; Larrañaga, Pedro
2012-12-01
Multi-dimensional Bayesian network classifiers (MBCs) are probabilistic graphical models recently proposed to deal with multi-dimensional classification problems, where each instance in the data set has to be assigned to more than one class variable. In this paper, we propose a Markov blanket-based approach for learning MBCs from data. Basically, it consists of determining the Markov blanket around each class variable using the HITON algorithm, then specifying the directionality over the MBC subgraphs. Our approach is applied to the prediction problem of the European Quality of Life-5 Dimensions (EQ-5D) from the 39-item Parkinson's Disease Questionnaire (PDQ-39) in order to estimate the health-related quality of life of Parkinson's patients. Fivefold cross-validation experiments were carried out on randomly generated synthetic data sets, Yeast data set, as well as on a real-world Parkinson's disease data set containing 488 patients. The experimental study, including comparison with additional Bayesian network-based approaches, back propagation for multi-label learning, multi-label k-nearest neighbor, multinomial logistic regression, ordinary least squares, and censored least absolute deviations, shows encouraging results in terms of predictive accuracy as well as the identification of dependence relationships among class and feature variables. Copyright © 2012 Elsevier Inc. All rights reserved.
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Kolodinsky, Jane; Reynolds, Travis William; Cannella, Mark; Timmons, David; Bromberg, Daniel
2009-01-01
To identify different segments of U.S. consumers based on food choices, exercise patterns, and desire for restaurant calorie labeling. Using a stratified (by region) random sample of the U.S. population, trained interviewers collected data for this cross-sectional study through telephone surveys. Center for Rural Studies U.S. national health survey. The final sample included 580 responses (22% response rate); data were weighted to be representative of age and gender characteristics of the U.S. population. Self-reported behaviors related to food choices, exercise patterns, desire for calorie information in restaurants, and sample demographics. Clusters were identified using Schwartz Bayesian criteria. Impacts of demographic characteristics on cluster membership were analyzed using bivariate tests of association and multinomial logit regression. Cluster analysis revealed three clusters based on respondents' food choices, activity levels, and desire for restaurant labeling. Two clusters, comprising three quarters of the sample, desired calorie labeling in restaurants. The remaining cluster opposed restaurant labeling. Demographic variables significantly predicting cluster membership included region of residence (p < .10), income (p < .05), gender (p < .01), and age (p < .10). Though limited by a low response and potential self-reporting bias in the phone survey, this study suggests that several groups are likely to benefit from restaurant calorie labeling. Specific demographic clusters could be targeted through labeling initiatives.
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Young physicians and the Finnish welfare state.
Saarinen, Arttu
2009-01-01
This article aims to focus on how young physicians in general and different subpopulations, in particular, see the role of the welfare state. The author seeks to compare young physicians' opinions with those of older physicians, a similar age group in the general population and all physicians. A random sample was picked from the Finnish Medical Association register (n = 1,092). Data were analysed using descriptive statistics and multinomial logistic regression analysis. Results show that young physicians--when compared with an overall population of the same age, with physicians overall, or with older physicians--are more critical of the degree of social security currently offered. Young physicians also want to give more responsibility to the private sector than do older physicians. On the other hand, young physicians are not very critical of healthcare system functionality. All in all, young physicians' opinions about the welfare state are not particularly radical. Results indicate that physicians' opinions about the welfare state will not change dramatically in the near future. Views on social security, healthcare system functionality and the role of the private sector correlate best with political orientation. There are some studies about physicians' attitudes towards the welfare state, but the opinions of young physicians have not been studied in countries with large social security systems. The paper addresses this gap because it is important to study young physicians' opinions because future services will be structured on them.
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Schnitzspahn, Katharina M; Horn, Sebastian S; Bayen, Ute J; Kliegel, Matthias
2012-06-01
While first studies suggested that emotional task material may enhance prospective memory performance in young and older adults, the extent and mechanisms of this effect are under debate. The authors explored possible differential effects of cue valence on the prospective and retrospective component of prospective memory in young and older adults. Forty-five young and 41 older adults performed a prospective memory task in which emotional valence of the prospective memory cue was manipulated (positive, negative, neutral). The multinomial model of event-based prospective memory was used to analyze effects of valence and age on the two prospective memory components separately. Results revealed an interaction indicating that age differences were smaller in both emotional valence conditions. For older adults positive cues improved the prospective component, while negative cues improved the retrospective component. No main effect of valence was found for younger adults on an overt accuracy measure, but model-based analyses showed that the retrospective component was enhanced in the positive compared with the negative cue condition. The study extends the literature in demonstrating that processes underlying emotional effects on prospective memory may differ depending on valence and age. PsycINFO Database Record (c) 2012 APA, all rights reserved
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Estimation of population trajectories from count data
Link, W.A.; Sauer, J.R.
1997-01-01
Monitoring of changes in animal population size is rarely possible through complete censuses; frequently, the only feasible means of monitoring changes in population size is to use counts of animals obtained by skilled observers as indices to abundance. Analysis of changes in population size can be severely biased if factors related to the acquisition of data are not adequately controlled for. In particular we identify two types of observer effects: these correspond to baseline differences in observer competence, and to changes through time in the ability of individual observers. We present a family of models for count data in which the first of these observer effects is treated as a nuisance parameter. Conditioning on totals of negative binomial counts yields a Dirichlet compound multinomial vector for each observer. Quasi-likelihood is used to estimate parameters related to population trajectory and other parameters of interest; model selection is carried out on the basis of Akaike's information criterion. An example is presented using data on Wood thrush from the North American Breeding Bird Survey.
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Predictors of Place of Death for Seniors in Ontario: A Population-Based Cohort Analysis
ERIC Educational Resources Information Center
Motiwala, Sanober S.; Croxford, Ruth; Guerriere, Denise N.; Coyte, Peter C.
2006-01-01
Place of death was determined for all 58,689 seniors (age greater than or equal to 66 years) in Ontario who died during fiscal year 2001/2002. The relationship of place of death to medical and socio-demographic characteristics was examined using a multinomial logit model. Half (49.2 %) of these individuals died in hospital, 30.5 per cent died in a…
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E. H. Helmer; Thomas J. Brandeis; Ariel E. Lugo; Todd Kennaway
2008-01-01
Little is known about the tropical forests that undergo clearing as urban/built-up and other developed lands spread. This study uses remote sensing-based maps of Puerto Rico, multinomial logit models and forest inventory data to explain patterns of forest age and the age of forests cleared for land development and assess their implications for forest carbon storage and...
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Modeling the Distribution of Fingerprint Characteristics. Revision 1.
1980-09-19
the details of the print. The ridge-line details are termed Galton characteristics since Sir Francis Galton was among the first to study them...U.S.A. CONTENTS Abstract 1. Introduction 2. Background Information on Fingerprints 2.1. Types 2.2. Ridge counts 2.3. The Galton details 3. Data...The Multinomial Markov Model 7. The Poisson Markov Model 8. The Infinitely Divisible Model Acknowledgements References Appendices A The Galton
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Modeling of orthotropic plate fracture under impact load using various strength criteria
NASA Astrophysics Data System (ADS)
Radchenko, Andrey; Krivosheina, Marina; Kobenko, Sergei; Radchenko, Pavel; Grebenyuk, Grigory
2017-01-01
The paper presents the comparative analysis of various tensor multinomial criteria of strength for modeling of orthotropic organic plastic plate fracture under impact load. Ashkenazi, Hoffman and Wu strength criteria were used. They allowed fracture modeling of orthotropic materials with various compressive and tensile strength properties. The modeling of organic plastic fracture was performed numerically within the impact velocity range of 700-1500 m/s.
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Masquerade Detection Using a Taxonomy-Based Multinomial Modeling Approach in UNIX Systems
2008-08-25
primarily the modeling of statistical features , such as the frequency of events, the duration of events, the co- occurrence of multiple events...are identified, we can extract features representing such behavior while auditing the user’s behavior. Figure1: Taxonomy of Linux and Unix...achieved when the features are extracted just from simple commands. Method Hit Rate False Positive Rate ocSVM using simple cmds (freq.-based
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NASA Astrophysics Data System (ADS)
Thurner, Stefan; Corominas-Murtra, Bernat; Hanel, Rudolf
2017-09-01
There are at least three distinct ways to conceptualize entropy: entropy as an extensive thermodynamic quantity of physical systems (Clausius, Boltzmann, Gibbs), entropy as a measure for information production of ergodic sources (Shannon), and entropy as a means for statistical inference on multinomial processes (Jaynes maximum entropy principle). Even though these notions represent fundamentally different concepts, the functional form of the entropy for thermodynamic systems in equilibrium, for ergodic sources in information theory, and for independent sampling processes in statistical systems, is degenerate, H (p ) =-∑ipilogpi . For many complex systems, which are typically history-dependent, nonergodic, and nonmultinomial, this is no longer the case. Here we show that for such processes, the three entropy concepts lead to different functional forms of entropy, which we will refer to as SEXT for extensive entropy, SIT for the source information rate in information theory, and SMEP for the entropy functional that appears in the so-called maximum entropy principle, which characterizes the most likely observable distribution functions of a system. We explicitly compute these three entropy functionals for three concrete examples: for Pólya urn processes, which are simple self-reinforcing processes, for sample-space-reducing (SSR) processes, which are simple history dependent processes that are associated with power-law statistics, and finally for multinomial mixture processes.
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Khorramdel, Lale; von Davier, Matthias
2014-01-01
This study shows how to address the problem of trait-unrelated response styles (RS) in rating scales using multidimensional item response theory. The aim is to test and correct data for RS in order to provide fair assessments of personality. Expanding on an approach presented by Böckenholt (2012), observed rating data are decomposed into multiple response processes based on a multinomial processing tree. The data come from a questionnaire consisting of 50 items of the International Personality Item Pool measuring the Big Five dimensions administered to 2,026 U.S. students with a 5-point rating scale. It is shown that this approach can be used to test if RS exist in the data and that RS can be differentiated from trait-related responses. Although the extreme RS appear to be unidimensional after exclusion of only 1 item, a unidimensional measure for the midpoint RS is obtained only after exclusion of 10 items. Both RS measurements show high cross-scale correlations and item response theory-based (marginal) reliabilities. Cultural differences could be found in giving extreme responses. Moreover, it is shown how to score rating data to correct for RS after being proved to exist in the data.
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Identifiability in N-mixture models: a large-scale screening test with bird data.
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.
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Patient choice modelling: how do patients choose their hospitals?
Smith, Honora; Currie, Christine; Chaiwuttisak, Pornpimol; Kyprianou, Andreas
2018-06-01
As an aid to predicting future hospital admissions, we compare use of the Multinomial Logit and the Utility Maximising Nested Logit models to describe how patients choose their hospitals. The models are fitted to real data from Derbyshire, United Kingdom, which lists the postcodes of more than 200,000 admissions to six different local hospitals. Both elective and emergency admissions are analysed for this mixed urban/rural area. For characteristics that may affect a patient's choice of hospital, we consider the distance of the patient from the hospital, the number of beds at the hospital and the number of car parking spaces available at the hospital, as well as several statistics publicly available on National Health Service (NHS) websites: an average waiting time, the patient survey score for ward cleanliness, the patient safety score and the inpatient survey score for overall care. The Multinomial Logit model is successfully fitted to the data. Results obtained with the Utility Maximising Nested Logit model show that nesting according to city or town may be invalid for these data; in other words, the choice of hospital does not appear to be preceded by choice of city. In all of the analysis carried out, distance appears to be one of the main influences on a patient's choice of hospital rather than statistics available on the Internet.
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Classification of vegetation types in military region
NASA Astrophysics Data System (ADS)
Gonçalves, Miguel; Silva, Jose Silvestre; Bioucas-Dias, Jose
2015-10-01
In decision-making process regarding planning and execution of military operations, the terrain is a determining factor. Aerial photographs are a source of vital information for the success of an operation in hostile region, namely when the cartographic information behind enemy lines is scarce or non-existent. The objective of present work is the development of a tool capable of processing aerial photos. The methodology implemented starts with feature extraction, followed by the application of an automatic selector of features. The next step, using the k-fold cross validation technique, estimates the input parameters for the following classifiers: Sparse Multinomial Logist Regression (SMLR), K Nearest Neighbor (KNN), Linear Classifier using Principal Component Expansion on the Joint Data (PCLDC) and Multi-Class Support Vector Machine (MSVM). These classifiers were used in two different studies with distinct objectives: discrimination of vegetation's density and identification of vegetation's main components. It was found that the best classifier on the first approach is the Sparse Logistic Multinomial Regression (SMLR). On the second approach, the implemented methodology applied to high resolution images showed that the better performance was achieved by KNN classifier and PCLDC. Comparing the two approaches there is a multiscale issue, in which for different resolutions, the best solution to the problem requires different classifiers and the extraction of different features.
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Patiño-Galindo, Juan Ángel; Torres-Puente, Manoli; Bracho, María Alma; Alastrué, Ignacio; Juan, Amparo; Navarro, David; Galindo, María José; Ocete, Dolores; Ortega, Enrique; Gimeno, Concepción; Belda, Josefina; Domínguez, Victoria; Moreno, Rosario; González-Candelas, Fernando
2017-09-14
HIV infections are still a very serious concern for public heath worldwide. We have applied molecular evolution methods to study the HIV-1 epidemics in the Comunidad Valenciana (CV, Spain) from a public health surveillance perspective. For this, we analysed 1804 HIV-1 sequences comprising protease and reverse transcriptase (PR/RT) coding regions, sampled between 2004 and 2014. These sequences were subtyped and subjected to phylogenetic analyses in order to detect transmission clusters. In addition, univariate and multinomial comparisons were performed to detect epidemiological differences between HIV-1 subtypes, and risk groups. The HIV epidemic in the CV is dominated by subtype B infections among local men who have sex with men (MSM). 270 transmission clusters were identified (>57% of the dataset), 12 of which included ≥10 patients; 11 of subtype B (9 affecting MSMs) and one (n = 21) of CRF14, affecting predominately intravenous drug users (IDUs). Dated phylogenies revealed these large clusters to have originated from the mid-80s to the early 00 s. Subtype B is more likely to form transmission clusters than non-B variants and MSMs to cluster than other risk groups. Multinomial analyses revealed an association between non-B variants, which are not established in the local population yet, and different foreign groups.
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Source and destination memory in face-to-face interaction: A multinomial modeling approach.
Fischer, Nele M; Schult, Janette C; Steffens, Melanie C
2015-06-01
Arguing that people are often in doubt concerning to whom they have presented what information, Gopie and MacLeod (2009) introduced a new memory component, destination memory: remembering the destination of output information (i.e., "Who did you tell this to?"). They investigated source (i.e., "Who told you that?") versus destination memory in computer-based imagined interactions. The present study investigated destination memory in real interaction situations. In 2 experiments with mixed-gender (N = 53) versus same-gender (N = 89) groups, source and destination memory were manipulated by creating a setup similar to speed dating. In dyads, participants completed phrase fragments with personal information, taking turns. At recognition, participants decided whether fragments were new or old and, if old, whether they were listened to or spoken and which depicted person was the source or the destination of the information. A multinomial model was used for analyses. Source memory significantly exceeded destination memory, whereas information itself was better remembered in the destination than in the source condition. These findings corroborate the trade-off hypothesis: Context is better remembered in input than in output events, but information itself is better remembered in output than in input events. We discuss the implications of these findings for real-world conversation situations. (c) 2015 APA, all rights reserved).
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Implicit moral evaluations: A multinomial modeling approach.
Cameron, C Daryl; Payne, B Keith; Sinnott-Armstrong, Walter; Scheffer, Julian A; Inzlicht, Michael
2017-01-01
Implicit moral evaluations-i.e., immediate, unintentional assessments of the wrongness of actions or persons-play a central role in supporting moral behavior in everyday life. Yet little research has employed methods that rigorously measure individual differences in implicit moral evaluations. In five experiments, we develop a new sequential priming measure-the Moral Categorization Task-and a multinomial model that decomposes judgment on this task into multiple component processes. These include implicit moral evaluations of moral transgression primes (Unintentional Judgment), accurate moral judgments about target actions (Intentional Judgment), and a directional tendency to judge actions as morally wrong (Response Bias). Speeded response deadlines reduced Intentional Judgment but not Unintentional Judgment (Experiment 1). Unintentional Judgment was stronger toward moral transgression primes than non-moral negative primes (Experiments 2-4). Intentional Judgment was associated with increased error-related negativity, a neurophysiological indicator of behavioral control (Experiment 4). Finally, people who voted for an anti-gay marriage amendment had stronger Unintentional Judgment toward gay marriage primes (Experiment 5). Across Experiments 1-4, implicit moral evaluations converged with moral personality: Unintentional Judgment about wrong primes, but not negative primes, was negatively associated with psychopathic tendencies and positively associated with moral identity and guilt proneness. Theoretical and practical applications of formal modeling for moral psychology are discussed. Copyright © 2016 Elsevier B.V. All rights reserved.
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Esfahani, Mohammad Shahrokh; Dougherty, Edward R
2015-01-01
Phenotype classification via genomic data is hampered by small sample sizes that negatively impact classifier design. Utilization of prior biological knowledge in conjunction with training data can improve both classifier design and error estimation via the construction of the optimal Bayesian classifier. In the genomic setting, gene/protein signaling pathways provide a key source of biological knowledge. Although these pathways are neither complete, nor regulatory, with no timing associated with them, they are capable of constraining the set of possible models representing the underlying interaction between molecules. The aim of this paper is to provide a framework and the mathematical tools to transform signaling pathways to prior probabilities governing uncertainty classes of feature-label distributions used in classifier design. Structural motifs extracted from the signaling pathways are mapped to a set of constraints on a prior probability on a Multinomial distribution. Being the conjugate prior for the Multinomial distribution, we propose optimization paradigms to estimate the parameters of a Dirichlet distribution in the Bayesian setting. The performance of the proposed methods is tested on two widely studied pathways: mammalian cell cycle and a p53 pathway model.
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Reis-Santos, Barbara; Gomes, Teresa; Horta, Bernardo Lessa; Maciel, Ethel Leonor Noia
2013-01-01
OBJECTIVE: To analyze the association between clinical/epidemiological characteristics and outcomes of tuberculosis treatment in patients with concomitant tuberculosis and chronic kidney disease (CKD) in Brazil. METHODS: We used the Brazilian Ministry of Health National Case Registry Database to identify patients with tuberculosis and CKD, treated between 2007 and 2011. The tuberculosis treatment outcomes were compared with epidemiological and clinical characteristics of the subjects using a hierarchical multinomial logistic regression model, in which cure was the reference outcome. RESULTS: The prevalence of CKD among patients with tuberculosis was 0.4% (95% CI: 0.37-0.42%). The sample comprised 1,077 subjects. The outcomes were cure, in 58%; treatment abandonment, in 7%; death from tuberculosis, in 13%; and death from other causes, in 22%. The characteristics that differentiated the ORs for treatment abandonment or death were age; alcoholism; AIDS; previous noncompliance with treatment; transfer to another facility; suspected tuberculosis on chest X-ray; positive results in the first smear microscopy; and indications for/use of directly observed treatment, short-course strategy. CONCLUSIONS: Our data indicate the importance of sociodemographic characteristics for the diagnosis of tuberculosis in patients with CKD and underscore the need for tuberculosis control strategies targeting patients with chronic noncommunicable diseases, such as CKD. PMID:24310632
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Ismail, Abbas; Josephat, Peter
2014-01-01
Tuberculosis (TB) is one of the most important public health problems in Tanzania and was declared as a national public health emergency in 2006. Community and individual knowledge and perceptions are critical factors in the control of the disease. The objective of this study was to analyze the knowledge and perception on the transmission of TB in Tanzania. Multinomial Logistic Regression analysis was considered in order to quantify the impact of knowledge and perception on TB. The data used was adopted as secondary data from larger national survey 2007-08 Tanzania HIV/AIDS and Malaria Indicator Survey. The findings across groups revealed that knowledge on TB transmission increased with an increase in age and level of education. People in rural areas had less knowledge regarding tuberculosis transmission compared to urban areas [OR = 0.7]. People with the access to radio [OR = 1.7] were more knowledgeable on tuberculosis transmission compared to those who did not have access to radio. People who did not have telephone [OR = 0.6] were less knowledgeable on tuberculosis route of transmission compared to those who had telephone. The findings showed that socio-demographic factors such as age, education, place of residence and owning telephone or radio varied systematically with knowledge on tuberculosis transmission.
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Dai, Huanping; Micheyl, Christophe
2012-11-01
Psychophysical "reverse-correlation" methods allow researchers to gain insight into the perceptual representations and decision weighting strategies of individual subjects in perceptual tasks. Although these methods have gained momentum, until recently their development was limited to experiments involving only two response categories. Recently, two approaches for estimating decision weights in m-alternative experiments have been put forward. One approach extends the two-category correlation method to m > 2 alternatives; the second uses multinomial logistic regression (MLR). In this article, the relative merits of the two methods are discussed, and the issues of convergence and statistical efficiency of the methods are evaluated quantitatively using Monte Carlo simulations. The results indicate that, for a range of values of the number of trials, the estimated weighting patterns are closer to their asymptotic values for the correlation method than for the MLR method. Moreover, for the MLR method, weight estimates for different stimulus components can exhibit strong correlations, making the analysis and interpretation of measured weighting patterns less straightforward than for the correlation method. These and other advantages of the correlation method, which include computational simplicity and a close relationship to other well-established psychophysical reverse-correlation methods, make it an attractive tool to uncover decision strategies in m-alternative experiments.
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Rooks, Ronica N.; Simonsick, Eleanor M.; Schulz, Richard; Rubin, Susan; Harris, Tamara
2017-01-01
Objective: The aim of this study is to examine social, economic, and health factors related to paid work in well-functioning older adults and if and how these factors vary by race. Method: We used sex-stratified logistic and multinomial logistic regression to examine cross-sectional data in the Health, Aging, and Body Composition cohort study. The sample included 3,075 community-dwelling Black (42%) and White adults aged 70 to 79 at baseline. Results: Multinomial logistic regression analyses show Black men were more likely to work full-time, and Black women were more likely to work part-time. Men with ≥US$50,000 family income were more likely to work full-time. Men with better physical functioning were more likely to work full- and part-time. Women with ≥US$50,000 family income and fewer chronic diseases were more likely to work full-time. Women who were overweight and had fewer chronic diseases were more likely to work part-time. Discussion: Results suggest that well-functioning, older Black adults were more likely to work than their White counterparts, and working relates to better health and higher income, providing support for a productive or successful aging perspective. PMID:28894767
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Knowledge does not protect against illusory truth.
Fazio, Lisa K; Brashier, Nadia M; Payne, B Keith; Marsh, Elizabeth J
2015-10-01
In daily life, we frequently encounter false claims in the form of consumer advertisements, political propaganda, and rumors. Repetition may be one way that insidious misconceptions, such as the belief that vitamin C prevents the common cold, enter our knowledge base. Research on the illusory truth effect demonstrates that repeated statements are easier to process, and subsequently perceived to be more truthful, than new statements. The prevailing assumption in the literature has been that knowledge constrains this effect (i.e., repeating the statement "The Atlantic Ocean is the largest ocean on Earth" will not make you believe it). We tested this assumption using both normed estimates of knowledge and individuals' demonstrated knowledge on a postexperimental knowledge check (Experiment 1). Contrary to prior suppositions, illusory truth effects occurred even when participants knew better. Multinomial modeling demonstrated that participants sometimes rely on fluency even if knowledge is also available to them (Experiment 2). Thus, participants demonstrated knowledge neglect, or the failure to rely on stored knowledge, in the face of fluent processing experiences. (c) 2015 APA, all rights reserved).
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Mendes dos Santos, Maíra; Quintana, Maria Ines; Moreira, Fernanda Gonçalves; Taborda, José Geraldo Vernet; Mari, Jair de Jesus; Andreoli, Sérgio Baxter
2014-01-01
To analyze the association between drug (DAD) and alcohol (AAD) abuse and dependency and criminal and clinical background by gender of prisoners in São Paulo, Brazil. Cross-sectional study, random sample stratified by administrative district, from which prisons and prisoners were selected via random, multistage sampling. Psychiatric diagnoses were made with the CIDI 2.1. Lifetime prevalence and 95% CI were calculated and adjusted via analysis of complex samples. Multinomial logistic regression analysis was carried out with four categories of dependent variables: presence AAD; presence DAD; presence of another mental disorder; no mental disorders. For female alcohol and drug abuse and dependency (ADAD) were combined into a single category. The sample was composed by 1809 interviewed prisoners (1192 men and 617 women). Prevalence of DAD and AAD was 25.2% and 15.6%, respectively, among female prisoners, and 26.5% and 18.5% among males. Male prisoners with DAD were more likely to have a criminal record as an adolescent (OR 2.17), to be a repeat offender (OR 2.85), and to have committed a property crime (OR 2.18). Prisoners with AAD were repeat offenders (OR 2.18). Among female prisoners, ADAD was associated with repeat offenses (OR 3.39), a criminal record as an adolescent (OR 9.24), a clinical or infectious condition (OR 5.09), another health problem (OR 3.04), and violent crime (OR 2.5). The study confirmed an association between drug-use disorders and the criminal and clinical background in the study population. Prisoners with such disorders were more likely to be repeat offenders and to have a criminal record as adolescents. Among female prisoners disorders were also associated with violent crime and health problems, while among males they were associated with property crime. These patterns in clinical and criminal backgrounds illustrate the need for social rehabilitation programs and specific medical treatment for prison populations.
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dos Santos, Maíra Mendes; Quintana, Maria Ines; Moreira, Fernanda Gonçalves; Taborda, José Geraldo Vernet; Mari, Jair de Jesus; Andreoli, Sérgio Baxter
2014-01-01
Objective To analyze the association between drug (DAD) and alcohol (AAD) abuse and dependency and criminal and clinical background by gender of prisoners in São Paulo, Brazil. Method Cross-sectional study, random sample stratified by administrative district, from which prisons and prisoners were selected via random, multistage sampling. Psychiatric diagnoses were made with the CIDI 2.1. Lifetime prevalence and 95% CI were calculated and adjusted via analysis of complex samples. Multinomial logistic regression analysis was carried out with four categories of dependent variables: presence AAD; presence DAD; presence of another mental disorder; no mental disorders. For female alcohol and drug abuse and dependency (ADAD) were combined into a single category. Results The sample was composed by 1809 interviewed prisoners (1192 men and 617 women). Prevalence of DAD and AAD was 25.2% and 15.6%, respectively, among female prisoners, and 26.5% and 18.5% among males. Male prisoners with DAD were more likely to have a criminal record as an adolescent (OR 2.17), to be a repeat offender (OR 2.85), and to have committed a property crime (OR 2.18). Prisoners with AAD were repeat offenders (OR 2.18). Among female prisoners, ADAD was associated with repeat offenses (OR 3.39), a criminal record as an adolescent (OR 9.24), a clinical or infectious condition (OR 5.09), another health problem (OR 3.04), and violent crime (OR 2.5). Conclusion The study confirmed an association between drug-use disorders and the criminal and clinical background in the study population. Prisoners with such disorders were more likely to be repeat offenders and to have a criminal record as adolescents. Among female prisoners disorders were also associated with violent crime and health problems, while among males they were associated with property crime. These patterns in clinical and criminal backgrounds illustrate the need for social rehabilitation programs and specific medical treatment for prison populations. PMID:25409091
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Help-seeking in people with exceptional experiences: results from a general population sample.
Landolt, Karin; Wittwer, Amrei; Wyss, Thomas; Unterassner, Lui; Fach, Wolfgang; Krummenacher, Peter; Brugger, Peter; Haker, Helene; Kawohl, Wolfram; Schubiger, Pius August; Folkers, Gerd; Rössler, Wulf
2014-01-01
Exceptional experiences (EE) are experiences that deviate from ordinary experiences, for example precognition, supernatural appearances, or déjà vues. In spite of the high frequency of EE in the general population, little is known about their effect on mental health and about the way people cope with EE. This study aimed to assess the quality and quantity of EE in persons from the Swiss general population, to identify the predictors of their help-seeking, and to determine how many of them approach the mental health system. An on-line survey was used to evaluate a quota sample of 1580 persons representing the Swiss general population with respect to gender, age, and level of education. Multinomial logistic regression was applied to integrate help-seeking, self-reported mental disorder, and other variables in a statistical model designed to identify predictors of help-seeking in persons with EE. Almost all participants (91%) experienced at least one EE. Generally, help-seeking was more frequent when the EE were of negative valence. Help-seeking because of EE was less frequent in persons without a self-reported mental disorder (8.6%) than in persons with a disorder (35.1%) (OR = 5.7). Even when frequency and attributes of EE were controlled for, people without a disorder sought four times less often help because of EE than expected. Persons with a self-reported diagnosis of mental disorder preferred seeing a mental health professional. Multinomial regression revealed a preference for healers in women with less education, who described themselves as believing and also having had more impressive EE. Persons with EE who do not indicate a mental disorder less often sought help because of EE than persons who indicated a mental disorder. We attribute this imbalance to a high inhibition threshold to seek professional help. Moreover, especially less educated women did not approach the mental health care system as often as other persons with EE, but preferred seeing a healer.
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Sosa-Rubí, Sandra G; Galárraga, Omar; Harris, Jeffrey E
2009-01-01
We evaluated the impact of Seguro Popular (SP), a program introduced in 2001 in Mexico primarily to finance health care for the poor. We focused on the effect of household enrollment in SP on pregnant women's access to obstetrical services, an important outcome measure of both maternal and infant health. We relied upon data from the cross-sectional 2006 National Health and Nutrition Survey (ENSANUT) in Mexico. We analyzed the responses of 3890 women who delivered babies during 2001-2006 and whose households lacked employer-based health care coverage. We formulated a multinomial probit model that distinguished between three mutually exclusive sites for delivering a baby: a health unit specifically accredited by SP; a non-SP-accredited clinic run by the Department of Health (Secretaría de Salud, or SSA); and private obstetrical care. Our model accounted for the endogeneity of the household's binary decision to enroll in the SP program. Women in households that participated in the SP program had a much stronger preference for having a baby in a SP-sponsored unit rather than paying out of pocket for a private delivery. At the same time, participation in SP was associated with a stronger preference for delivering in the private sector rather than at a state-run SSA clinic. On balance, the Seguro Popular program reduced pregnant women's attendance at an SSA clinic much more than it reduced the probability of delivering a baby in the private sector. The quantitative impact of the SP program varied with the woman's education and health, as well as the assets and location (rural vs. urban) of the household. The SP program had a robust, significantly positive impact on access to obstetrical services. Our finding that women enrolled in SP switched from non-SP state-run facilities, rather than from out-of-pocket private services, is important for public policy and requires further exploration.
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An Assessment of Correlation between Dermatoglyphic Patterns and Sagittal Skeletal Discrepancies
Philip, Biju; Madathody, Deepika; Mathew, Manu; Paul, Jose; Dlima, Johnson Prakash
2017-01-01
Introduction Investigators over years have been fascinated by dermatoglyphic patterns which has led to the development of dermatoglyphics as a science with numerous applications in various fields other than being the best and most widely used method for personal identification. Aim To assess the correlation between dermatoglyphic patterns and sagittal skeletal discrepancies. Materials and Methods A total of 180 patients, aged 18-40 years, were selected from those who attended the outpatient clinic of the Deparment of Orthodontics and Dentofacial Orthopedics, Mar Baselios Dental College, Kothamangalam, Kerala, India. The fingerprints of both hands were taken by ink and stamp method after proper hand washing. The patterns of arches, loops and whorls in fingerprints were assessed. The total ridge count was also evaluated. Data was also sent to the fingerprint experts for expert evaluation. The sagittal jaw relation was determined from the patient’s lateral cephalogram. The collected data was then statistically analyzed using Chi-square tests, ANOVA and Post-hoc tests and a Multinomial regression prediction was also done. Results A significant association was observed between the dermatoglyphic pattern exhibited by eight fingers and the sagittal skeletal discrepancies (p<0.05). An increased distribution of whorl pattern was observed in the skeletal Class II with maxillary excess group and skeletal Class II with mandibular deficiency group while an increased distribution of loop pattern was seen in the skeletal Class III with mandibular excess group and skeletal Class III with maxillary deficiency group. Higher mean of total ridge count was also seen in the groups of skeletal Class II with maxillary excess and skeletal Class II with mandibular deficiency. Multinomial regression predicting skeletal pattern with respect to the fingerprint pattern showed that the left thumb impression fits the best model for predicting the skeletal pattern. Conclusion There was a significant association between dermatoglyphic patterns and sagittal skeletal discrepancies. Dermatoglyphics could serve as a cost effective screening tool of these craniofacial problems. PMID:28511506
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Page, Charlotte M.; Patel, Archana; Hibberd, Patricia L.
2015-01-01
Background Anemia affects upwards of 50% of pregnant women in developing countries and is associated with adverse outcomes for mother and child. We hypothesized that exposure to smoke from biomass fuel – which is widely used for household energy needs in resource-limited settings – could exacerbate anemia in pregnancy, possibly as a result of systemic inflammation. Objective To evaluate whether exposure to smoke from biomass fuel (wood, straw, crop residues, or dung) as opposed to clean fuel (electricity, liquefied petroleum gas, natural gas, or biogas) is an independent risk factor for anemia in pregnancy, classified by severity. Methods A secondary analysis was performed using data collected from a rural pregnancy cohort (N = 12,782) in Nagpur, India in 2011-2013 as part of the NIH-funded Maternal and Newborn Health Registry Study. Multinomial logistic regression was used to estimate the effect of biomass fuel vs. clean fuel use on anemia in pregnancy, controlling for maternal age, body mass index, education level, exposure to household tobacco smoke, parity, trimester when hemoglobin was measured, and receipt of prenatal iron and folate supplements. Results The prevalence of any anemia (hemoglobin < 11 g/dl) was 93% in biomass fuel users and 88% in clean fuel users. Moderate-to-severe anemia (hemoglobin < 10 g/dl) occurred in 53% and 40% of the women, respectively. Multinomial logistic regression showed higher relative risks of mild anemia in pregnancy (hemoglobin 10-11 g/dl; RRR = 1.38, 95% CI = 1.19-1.61) and of moderate-to-severe anemia in pregnancy (RRR = 1.79, 95% CI = 1.53-2.09) in biomass fuel vs. clean fuel users, after adjusting for covariates. Conclusion In our study population, exposure to biomass smoke was associated with higher risks of mild and moderate-to-severe anemia in pregnancy, independent of covariates. Trial Registration ClinicalTrials.gov NCT 01073475 PMID:26024473
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2014-01-01
Background Research demonstrates that tobacco packaging elements (including health warning labels, descriptive characteristics, and corporate branding) are associated with knowledge of health risks and product appeal with cigarettes. Yet, little research has assessed this with smokeless tobacco (SLT) packaging. This study evaluates the association between three SLT packaging elements with knowledge of health risks and perceptions of novelty and appeal. Additionally, we assess how effects of these messages may differ across age groups, including youth (14-17 years), young adults (18-25 years), and older adults (26-65 years). Methods 1000 participants were administered a web-based survey in 2010 and shown three sets of SLT packs in random order, varied by descriptor (flavor descriptor vs. none), warning label format (graphic vs. text), and corporate branding (branded vs. plain packaging). Participants rated the packs compared with “no difference” on appeal, novelty, and risk perceptions associated with product use. Chi-square tests were used to test for significant differences in pack selections. Multinomial regression was employed to evaluate the association between effects of packaging elements and participant age. Results More respondents selected the pack with the graphic warning label as the pack to make them consider the health risks associated with SLT use, attract their attention, and be least attractive to a smoker. The product with the text warning label was the product someone their age would want to be seen using and would appeal to peers. The SLT pack with the flavor descriptor was not associated with health risks associated with product use. The pack with corporate branding was selected as more appealing, to attract attention, and one they would want to be seen using; the plain pack was less attractive to smokers. Youth and young adults were more likely to indicate that pack elements affected their perceptions of appeal and risk associated with SLT products. Conclusion These results suggest that SLT pack characteristics have a measurable effect on perceptions of health risk and product appeal. Future research should assess these findings in the context of harm reduction. Specifically, research is needed to determine whether pack elements on SLT products can effectively convey risk and harm. PMID:24433301
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Adkison, Sarah E; Bansal-Travers, Maansi; Smith, Danielle M; O'Connor, Richard J; Hyland, Andrew J
2014-01-17
Research demonstrates that tobacco packaging elements (including health warning labels, descriptive characteristics, and corporate branding) are associated with knowledge of health risks and product appeal with cigarettes. Yet, little research has assessed this with smokeless tobacco (SLT) packaging. This study evaluates the association between three SLT packaging elements with knowledge of health risks and perceptions of novelty and appeal. Additionally, we assess how effects of these messages may differ across age groups, including youth (14-17 years), young adults (18-25 years), and older adults (26-65 years). 1000 participants were administered a web-based survey in 2010 and shown three sets of SLT packs in random order, varied by descriptor (flavor descriptor vs. none), warning label format (graphic vs. text), and corporate branding (branded vs. plain packaging). Participants rated the packs compared with "no difference" on appeal, novelty, and risk perceptions associated with product use. Chi-square tests were used to test for significant differences in pack selections. Multinomial regression was employed to evaluate the association between effects of packaging elements and participant age. More respondents selected the pack with the graphic warning label as the pack to make them consider the health risks associated with SLT use, attract their attention, and be least attractive to a smoker. The product with the text warning label was the product someone their age would want to be seen using and would appeal to peers. The SLT pack with the flavor descriptor was not associated with health risks associated with product use. The pack with corporate branding was selected as more appealing, to attract attention, and one they would want to be seen using; the plain pack was less attractive to smokers. Youth and young adults were more likely to indicate that pack elements affected their perceptions of appeal and risk associated with SLT products. These results suggest that SLT pack characteristics have a measurable effect on perceptions of health risk and product appeal. Future research should assess these findings in the context of harm reduction. Specifically, research is needed to determine whether pack elements on SLT products can effectively convey risk and harm.
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Generalizing the Iterative Proportional Fitting Procedure.
1980-04-01
Csiszar gives conditions under which P (R) exists (it is always unique) and develops a geometry of I-divergence by using an analogue of Pythagoras ...8217 Theorem . As our goal is to study maximum likelihood estimation in contingency tables, we turn briefly to the problem of estimating a multinomial...envoke a result of Csiszir (due originally to Kullback (1959)), giving the form of the density of the I-projection. Csiszar’s Theorem 3.1, which we
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Castelló, Adela; Boldo, Elena; Pérez-Gómez, Beatriz; Lope, Virginia; Altzibar, Jone M; Martín, Vicente; Castaño-Vinyals, Gemma; Guevara, Marcela; Dierssen-Sotos, Trinidad; Tardón, Adonina; Moreno, Víctor; Puig-Vives, Montserrat; Llorens-Ivorra, Cristóbal; Alguacil, Juan; Gómez-Acebo, Inés; Castilla, Jesús; Gràcia-Lavedán, Esther; Dávila-Batista, Verónica; Kogevinas, Manolis; Aragonés, Nuria; Amiano, Pilar; Pollán, Marina
2017-09-01
To externally validate the previously identified effect on breast cancer risk of the Western, Prudent and Mediterranean dietary patterns. MCC-Spain is a multicase-control study that collected epidemiological information on 1181 incident cases of female breast cancer and 1682 healthy controls from 10 Spanish provinces. Three dietary patterns derived in another Spanish case-control study were analysed in the MCC-Spain study. These patterns were termed Western (high intakes of fatty and sugary products and red and processed meat), Prudent (high intakes of low-fat dairy products, vegetables, fruits, whole grains and juices) and Mediterranean (high intake of fish, vegetables, legumes, boiled potatoes, fruits, olives, and vegetable oil, and a low intake of juices). Their association with breast cancer was assessed using logistic regression models with random province-specific intercepts considering an interaction with menopausal status. Risk according to tumour subtypes - based on oestrogen (ER), progesterone (PR) and human epidermal growth factor 2 (HER2) receptors (ER+/PR+ & HER2-; HER2+; ER-/PR- & HER2-) - was evaluated with multinomial regression models. Breast cancer and histological subtype. Our results confirm most of the associations found in the previous case-control study. A high adherence to the Western dietary pattern seems to increase breast cancer risk in both premenopausal women (OR 4 th vs.1 st quartile (95% CI):1.68 (1.02;2.79); OR 1SD-increase (95% CI):1.19 (1.02;1.40)) and postmenopausal women (OR 4 th vs.1 st quartile (95% CI):1.48(1.07;2.05); OR 1SD-increase (95% CI): 1.14 (1.01;1.29)). While high adherence to the Prudent pattern did not show any effect on breast cancer, the Mediterranean dietary pattern seemed to be protective, but only among postmenopausal women (OR 4 th vs.1 st quartile (95% CI): 0.72 (95% CI 0.53;0.98); p-int=0.075). There were no significant differences by tumour subtype. Dietary recommendations based on a departure from the Western dietary pattern in favour of the Mediterranean diet could reduce breast cancer risk in the general population. Copyright © 2017 Elsevier B.V. All rights reserved.
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Young women's consistency of contraceptive use – Does depression or stress matter?
Moreau, Caroline; Trussell, James; Barber, Jennifer
2013-01-01
Background We prospectively examined the influence of young women's depression and stress symptoms on their weekly consistency of contraceptive method use. Study Design Women ages 18-20 years (n=689) participating in a longitudinal cohort study completed weekly journals assessing reproductive, relationship and health characteristics. We used data through 12 months follow-up (n=8,877 journals) to examine relationships between baseline depression (CES-D) and stress (PSS-10) symptoms and consistency of contraceptive methods use with sexual activity each week. We analyzed data with random effects multinomial logistic regression. Results Consistent contraceptive use (72% of weeks) was 10-15 percentage points lower among women with moderate/severe baseline depression and stress symptoms than those without symptoms (p-values<0.001). Controlling for covariates, women with depression and stress symptoms had 47% and 69% reduced odds of contraceptive consistency each week than those without symptoms, respectively (OR 0.53, CI 0.31-0.91 and OR 0.31, CI 0.18-0.52). Stress predicted inconsistent use of oral contraceptives (OR 0.27, CI 0.12-0.58), condoms (OR 0.40, CI 0.23-0.69) and withdrawal (OR 0.12, CI 0.03-0.50). Conclusion Women with depression and stress symptoms appear to be at increased risk for user-related contraceptive failures, especially for the most commonly used methods. Implications Our study has shown that young women with elevated depression and stress symptoms appear to be at risk for inconsistent contraceptive use patterns, especially for the most common methods that require greater user effort and diligence. Based upon these findings, clinicians should consider women's psychological and emotional status when helping patients with contraceptive decision-making and management. User-dependent contraceptive method efficacy is important to address in education and counseling sessions, and women with stress or depression may be ideal candidates for long-acting reversible methods, which offer highly effective options with less user-related burden. Ongoing research will provide a greater understanding of how young women's dynamic mental health symptoms impact family planning behaviors and outcomes over time. PMID:23850075
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Zickmund, Susan L; Burkitt, Kelly H; Gao, Shasha; Stone, Roslyn A; Jones, Audrey L; Hausmann, Leslie R M; Switzer, Galen E; Borrero, Sonya; Rodriguez, Keri L; Fine, Michael J
2018-03-01
Patient satisfaction is an important dimension of health care quality. The Veterans Health Administration (VA) is committed to providing high-quality care to an increasingly diverse patient population. To assess Veteran satisfaction with VA health care by race/ethnicity and gender. We conducted semi-structured telephone interviews with gender-specific stratified samples of black, white, and Hispanic Veterans from 25 predominantly minority-serving VA Medical Centers from June 2013 to January 2015. Satisfaction with health care was assessed in 16 domains using five-point Likert scales. We compared the proportions of Veterans who were very satisfied, somewhat satisfied, and less than satisfied (i.e., neither satisfied nor dissatisfied, somewhat dissatisfied, or very dissatisfied) in each domain, and used random-effects multinomial regression to estimate racial/ethnic differences by gender and gender differences by race/ethnicity. Interviews were completed for 1222 of the 1929 Veterans known to be eligible for the interview (63.3%), including 421 white, 389 black, and 396 Hispanic Veterans, 616 of whom were female. Veterans were less likely to be somewhat satisfied or less than satisfied versus very satisfied with care in each of the 16 domains. The highest satisfaction ratings were reported for costs, outpatient facilities, and pharmacy (74-76% very satisfied); the lowest ratings were reported for access, pain management, and mental health care (21-24% less than satisfied). None of the joint tests of racial/ethnic or gender differences in satisfaction (simultaneously comparing all three satisfaction levels) was statistically significant (p > 0.05). Pairwise comparisons of specific levels of satisfaction revealed racial/ethnic differences by gender in three domains and gender differences by race/ethnicity in five domains, with no consistent directionality across demographic subgroups. Our multisite interviews of a diverse sample of Veterans at primarily minority-serving sites showed generally high levels of health care satisfaction across 16 domains, with few quantitative differences by race/ethnicity or gender.
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A bivariate model for analyzing recurrent multi-type automobile failures
NASA Astrophysics Data System (ADS)
Sunethra, A. A.; Sooriyarachchi, M. R.
2017-09-01
The failure mechanism in an automobile can be defined as a system of multi-type recurrent failures where failures can occur due to various multi-type failure modes and these failures are repetitive such that more than one failure can occur from each failure mode. In analysing such automobile failures, both the time and type of the failure serve as response variables. However, these two response variables are highly correlated with each other since the timing of failures has an association with the mode of the failure. When there are more than one correlated response variables, the fitting of a multivariate model is more preferable than separate univariate models. Therefore, a bivariate model of time and type of failure becomes appealing for such automobile failure data. When there are multiple failure observations pertaining to a single automobile, such data cannot be treated as independent data because failure instances of a single automobile are correlated with each other while failures among different automobiles can be treated as independent. Therefore, this study proposes a bivariate model consisting time and type of failure as responses adjusted for correlated data. The proposed model was formulated following the approaches of shared parameter models and random effects models for joining the responses and for representing the correlated data respectively. The proposed model is applied to a sample of automobile failures with three types of failure modes and up to five failure recurrences. The parametric distributions that were suitable for the two responses of time to failure and type of failure were Weibull distribution and multinomial distribution respectively. The proposed bivariate model was programmed in SAS Procedure Proc NLMIXED by user programming appropriate likelihood functions. The performance of the bivariate model was compared with separate univariate models fitted for the two responses and it was identified that better performance is secured by the bivariate model. The proposed model can be used to determine the time and type of failure that would occur in the automobiles considered here.
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Nightmares: Risk Factors Among the Finnish General Adult Population
Sandman, Nils; Valli, Katja; Kronholm, Erkki; Revonsuo, Antti; Laatikainen, Tiina; Paunio, Tiina
2015-01-01
Study Objectives: To identify risk factors for experiencing nightmares among the Finnish general adult population. The study aimed to both test whether previously reported correlates of frequent nightmares could be reproduced in a large population sample and to explore previously unreported associations. Design: Two independent cross-sectional population surveys of the National FINRISK Study. Setting: Age- and sex-stratified random samples of the Finnish population in 2007 and 2012. Participants: A total of 13,922 participants (6,515 men and 7,407 women) aged 25–74 y. Interventions: N/A. Measurements and results: Nightmare frequency as well as several items related to socioeconomic status, sleep, mental well-being, life satisfaction, alcohol use, medication, and physical well-being were recorded with a questionnaire. In multinomial logistic regression analysis, a depression-related negative attitude toward the self (odds ratio [OR] 1.32 per 1-point increase), insomnia (OR 6.90), and exhaustion and fatigue (OR 6.86) were the strongest risk factors for experiencing frequent nightmares (P < 0.001 for all). Sex, age, a self-reported impaired ability to work, low life satisfaction, the use of antidepressants or hypnotics, and frequent heavy use of alcohol were also strongly associated with frequent nightmares (P < 0.001 for all). Conclusions: Symptoms of depression and insomnia were the strongest predictors of frequent nightmares in this dataset. Additionally, a wide variety of factors related to psychological and physical well-being were associated with nightmare frequency with modest effect sizes. Hence, nightmare frequency appears to have a strong connection with sleep and mood problems, but is also associated with a variety of measures of psychological and physical well-being. Citation: Sandman N, Valli K, Kronholm E, Revonsuo A, Laatikainen T, Paunio T. Nightmares: risk factors among the finnish general adult population. SLEEP 2015;38(4):507–514. PMID:25325474
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Knox, Stephanie A; Viney, Rosalie C; Street, Deborah J; Haas, Marion R; Fiebig, Denzil G; Weisberg, Edith; Bateson, Deborah
2012-12-01
In the past decade, the range of contraceptives available has increased dramatically. There are limited data on the factors that determine women's choices on contraceptive alternatives or what factors providers consider most important when recommending contraceptive products to women. Our objectives were to compare women's (consumers') preferences and GPs' (providers') views in relation to existing and new contraceptive methods, and particularly to examine what factors increase the acceptability of different contraceptive products. A best-worst attribute stated-choice experiment was completed online. Participants (Australian women of reproductive age and Australian GPs) completed questions on 16 contraceptive profiles. 200 women of reproductive age were recruited through a commercial panel. GPs from all states of Australia were randomly sampled and approached by phone; 162 GPs agreed to participate. Participants chose the best and worst attribute levels of hypothetical but realistic prescribed contraceptive products. Best and worst choices were modelled using multinomial logit and product features were ranked from best to worst according to the size of model coefficients. The most attractive feature of the contraceptive products for both GPs and women consumers were an administration frequency of longer than 1 year and light or no bleeding. Women indicated that the hormonal vaginal ring was the least attractive mode of administration. Women and GPs agree that longer-acting methods with less bleeding are important features in preferred methods of contraception; however, women are also attracted to products involving less invasive modes of administration. While the vaginal ring may fill the niche in Australia for a relatively non-invasive, moderately long-acting and effective contraceptive, the results of this study indicate that GPs will need to promote the benefits of the vaginal ring to overcome negative perceptions about this method among women who may benefit from using it.
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Meat intake, methods and degrees of cooking and breast cancer risk in the MCC-Spain study.
Boldo, Elena; Castelló, Adela; Aragonés, Nuria; Amiano, Pilar; Pérez-Gómez, Beatriz; Castaño-Vinyals, Gemma; Martín, Vicente; Guevara, Marcela; Urtiaga, Carmen; Dierssen-Sotos, Trinidad; Fernández-Tardón, Guillermo; Moreno, Victor; Solans, Marta; Peiró, Rosanna; Capelo, Rocio; Gómez-Acebo, Inés; Castilla, Jesús; Molina, Antonio José; Castells, Xavier; Altzibar, Jone M; Lope, Virginia; Kogevinas, Manolis; Romieu, Isabelle; Pollán, Marina
2018-04-01
To analyse the relationship of the risk of breast cancer (BC) to meat intake, preference regarding degree of cooking ('doneness') and cooking methods, using data from a population-based case-control study (MCC-Spain). 1006 Histologically confirmed incident BC cases and 1370 controls were recruited in 10 Spanish provinces. Participants were 23-85 years old. They answered an epidemiological survey and a food frequency questionnaire. BC risk was assessed overall, by menopausal status and by pathological subtypes, using logistic and multinomial regression mixed models adjusted for known confounding factors and including province as a random effects term. Breast cancer and pathological subtype. High total intake of meat (OR Q4-Q1 (95% IC) = 1.39 (1.03-1.88)) was associated with increased BC risk among post-menopausal women. Similar results were found for processed/cured meat (OR Q4-Q1 (95% IC) = 1.47 (1.10-1.97)), and this association was particularly strong for triple-negative tumours (ER-, PR- and HER2-) (OR Q4-Q1 (95% IC) = 2.52 (1.15-5.49)). Intakes of well-done (OR well-donevsrare (95% CI) = 1.62 (1.15-2.30)) and stewed (OR (95% CI) = 1.49 (1.20-1.84)) red meat were associated with increased BC risk, with a high risk observed for HR+ tumours (ER+/PR+ and HER2-). Pan-fried/bread-coated fried white meat, but not doneness preference, was associated with an increased BC risk for all women (OR (95% CI) = 1.38 (1.14-1.65)), with a stronger association for pre-menopausal women (OR (95% CI) = 1.78 (1.29-2.46)). The risk of developing BC could be reduced by moderating the consumption of well-done or stewed red meat, pan-fried/bread-coated fried white meat and, especially, processed/cured meat. Copyright © 2018 Elsevier B.V. All rights reserved.
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The role of intelligence in posttraumatic stress disorder: does it vary by trauma severity?
Breslau, Naomi; Chen, Qiaoling; Luo, Zhehui
2013-01-01
Only a small minority of trauma victims develops post-traumatic stress disorder (PTSD), suggesting that victims vary in their predispositions to the PTSD response to stressors. It is assumed that the role of predispositions in PTSD varies by trauma severity: when stressors are less severe, predispositions play a bigger role. In this study, we test whether the role of intelligence in PTSD varies by trauma severity. Specifically, does low intelligence plays a bigger part among victims of lower magnitude stressors than among victims of extreme stressors? Data come from a longitudinal study of randomly selected sample in Southeast Michigan (n = 713). IQ was measured at age 6. PTSD was measured at age 17, using the NIMH-DIS for DSM-IV. Stressors were classified as extreme if they involved assaultive violence (e.g. rape, sexual assault, threatened with a weapon); other stressors in the list (e.g. disaster, accidents) were classified as lower magnitude. Assaultive violence victims had experienced assaultive violence plus other event types or only assaultive violence. Victims of other stressors were participants who had never experienced assaultive violence. We compared the influence of age 6 IQ on PTSD among persons exposed to assaultive violence vs. other stressors, using multinomial logistic regression. Relative risk ratio (RRR) for PTSD associated with a one point drop in age 6 IQ among victims of assaultive violence was 1.04 (95% CI 1.01, 1.06); among victims of other stressors, it was 1.03 (95% CI 0.99, 1.06). A comparison of the two RRRs indicates no significant difference between the two estimates (p = 0.652). IQ does not play a bigger role in PTSD among victims of other stressors than it does among victims of assaultive violence. Lower IQ exerts an adverse PTSD effect on trauma victims, with no evidence of variability by the severity of trauma they have experienced.
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Burns, Cate; Bentley, Rebecca; Thornton, Lukar; Kavanagh, Anne
2015-01-01
To examine the associations between financial, physical and transport conditions that may restrict food access (which we define as food security indicators) and the purchase of fast foods and nutritious staples such as bread and milk. Multilevel logistic and multinomial regression analysis of cross-sectional survey data to assess associations between the three indicators of food insecurity and household food shopping adjusted for sociodemographic and socio-economic variables. Random selection of households (n 3995) from fifty Census Collector Districts in Melbourne, Australia, in 2003. The main food shoppers in each household (n 2564). After adjustment for confounders, analysis showed that a greater likelihood of purchasing chain-brand fast food on a weekly basis compared with never was associated with running out of money to buy food (OR = 1·59; 95 % CI 1·08, 2·34) and reporting difficulties lifting groceries (OR = 1·77; 95 % CI 1·23, 2·54). Respondents without regular access to a car to do food shopping were less likely to purchase bread types considered more nutritious than white bread (OR = 0·75; 95 % CI 0·59, 0·95) and milk types considered more nutritious than full-cream milk (OR = 0·62; 95 % CI 0·47, 0·81). The food insecurity indicators were not associated with the purchasing of fruits, vegetables or non-chain fast food. Householders experiencing financial and physical barriers were more likely to frequently purchase chain fast foods while limited access to a car resulted in a lower likelihood that the nutritious options were purchased for two core food items (bread and milk). Policies and interventions that improve financial access to food and lessen the effect of physical limitations to carrying groceries may reduce the purchasing of fast foods. Further research is required on food sourcing and dietary quality among those with food access restrictions.
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Rummo, Pasquale E; Guilkey, David K; Shikany, James M; Reis, Jared P; Gordon-Larsen, Penny
2017-03-01
Little is known about how diet-related and activity-related amenities relate to residential location behaviour. Understanding these relationships is essential for addressing residential self-selection bias. Using 25 years (6 examinations) of data from the Coronary Artery Risk Development in Young Adults (CARDIA) study (n=11 013 observations) and linked neighbourhood-level data from the 4 CARDIA baseline cities (Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; Oakland, California, USA), we characterised participants' neighbourhoods as having low, average or high road connectivity and amenities using non-hierarchical cluster analysis. We then used repeated measures multinomial logistic regression with random effects to examine the associations between individual-level sociodemographics and neighbourhood-level characteristics with residential neighbourhood types over the 25-year period, and whether these associations differed by individual-level income. Being female was positively associated with living in neighbourhoods with low (vs high) road connectivity and activity-related and diet-related amenities among high-income individuals only. At all income levels, a higher percentage of neighbourhood white population and neighbourhood population <18 years were associated with living in neighbourhoods with low (vs high) connectivity and amenities. Individual-level race; age; and educational attainment, neighbourhood socioeconomic status and housing prices did not influence residential location behaviour related to neighbourhood connectivity and amenities at any income level. Neighbourhood-level factors appeared to play a comparatively greater role in shaping residential location behaviour than individual-level sociodemographics. Our study is an important step in understanding how residential locational behaviour relates to amenities and physical activity opportunities, and may help mitigate residential self-selection bias in built environment studies. 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/.
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Pain in methadone patients: Time to address undertreatment and suicide risk (ANRS-Methaville trial)
Nordmann, Sandra; Vilotitch, Antoine; Lions, Caroline; Michel, Laurent; Mora, Marion; Spire, Bruno; Maradan, Gwenaelle; Bendiane, Marc-Karim; Morel, Alain; Roux, Perrine; Carrieri, Patrizia
2017-01-01
Background Pain in opioid-dependent patients is common but data measuring the course of pain (and its correlates) using validated scales in patients initiating methadone treatment are sparse. We aimed to assess pain and its interference in daily life, associated correlates, and undertreatment before and during methadone treatment. Methods This is a secondary analysis using longitudinal data of a randomized trial comparing two methadone initiation models. We assessed the effect of methadone initiation and other correlates on pain intensity and interference (using the Brief Pain Inventory) at months 0, 6 and 12 using a mixed multinomial logistic regression model. Results The study group comprised 168 patients who had data for either pain intensity or interference for at least one visit. Moderate to severe pain was reported in 12.9% of patients at M0, 5.4% at M6 and 7.3% at M12. Substantial interference with daily functioning was reported in 36.0% at M0, 14.5% at M6 and 17.1% at M12. Of the 98 visits where patients reported moderate to severe pain or substantial interference, 55.1% reported no treatment for pain relief, non-opioid analgesics were reported by 34.7%, opioid analgesics by 3.1% and both opioid and non-opioid analgesics by 7.1%. Methadone was associated with decreased pain intensity at 6 months (OR = 0.29, p = 0.04) and 12 months (OR = 0.30, p = 0.05) of follow-up and tended to be associated with substantial pain interference. Suicide risk was associated with both pain intensity and pain interference. Conclusions Methadone in opioid-dependent patients can reduce pain. However, undertreatment of pain in methadone patients remains a major clinical concern. Patients with pain are at higher risk of suicide. Adequate screening and management of pain in this population is a priority and needs to be integrated into routine comprehensive care. PMID:28520735
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Social influence, agent heterogeneity and the emergence of the urban informal sector
NASA Astrophysics Data System (ADS)
García-Díaz, César; Moreno-Monroy, Ana I.
2012-02-01
We develop an agent-based computational model in which the urban informal sector acts as a buffer where rural migrants can earn some income while queuing for higher paying modern-sector jobs. In the model, the informal sector emerges as a result of rural-urban migration decisions of heterogeneous agents subject to social influence in the form of neighboring effects of varying strengths. Besides using a multinomial logit choice model that allows for agent idiosyncrasy, explicit agent heterogeneity is introduced in the form of socio-demographic characteristics preferred by modern-sector employers. We find that different combinations of the strength of social influence and the socio-economic composition of the workforce lead to very different urbanization and urban informal sector shares. In particular, moderate levels of social influence and a large proportion of rural inhabitants with preferred socio-demographic characteristics are conducive to a higher urbanization rate and a larger informal sector.
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Impacts of geographical locations and sociocultural traits on the Vietnamese entrepreneurship.
Vuong, Quan Hoang
2016-01-01
This paper presents new results obtained from investigating the data from a 2015 Vietnamese entrepreneurs' survey, containing 3071 observations. Evidence from the estimations using multinomial logits was found to support relationships between several sociocultural factors and entrepreneurship-related performance or traits. Specifically, those relationships include: (a) Active participation in entrepreneurs' social networks and reported value of creativity; (b) CSR-willingness and reported entrepreneurs' perseverance; (c) Transforming of sociocultural values and entrepreneurs' decisiveness; and, (d) Lessons learned from others' failures and perceived chance of success. Using geographical locations as the control variate, evaluations of the baseline-category logits models indicate their varying effects on the outcomes when combined with the sociocultural factors that are found to be statistically significant. Empirical probabilities that give further detail about behavioral patterns are provided; and toward the end, the paper offers some conclusions with some striking insights and useful explanations on the Vietnamese entrepreneurship processes.
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Heterogeneous Tensor Decomposition for Clustering via Manifold Optimization.
Sun, Yanfeng; Gao, Junbin; Hong, Xia; Mishra, Bamdev; Yin, Baocai
2016-03-01
Tensor clustering is an important tool that exploits intrinsically rich structures in real-world multiarray or Tensor datasets. Often in dealing with those datasets, standard practice is to use subspace clustering that is based on vectorizing multiarray data. However, vectorization of tensorial data does not exploit complete structure information. In this paper, we propose a subspace clustering algorithm without adopting any vectorization process. Our approach is based on a novel heterogeneous Tucker decomposition model taking into account cluster membership information. We propose a new clustering algorithm that alternates between different modes of the proposed heterogeneous tensor model. All but the last mode have closed-form updates. Updating the last mode reduces to optimizing over the multinomial manifold for which we investigate second order Riemannian geometry and propose a trust-region algorithm. Numerical experiments show that our proposed algorithm compete effectively with state-of-the-art clustering algorithms that are based on tensor factorization.
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Romantic attraction and adolescent smoking trajectories.
Pollard, Michael S; Tucker, Joan S; Green, Harold D; Kennedy, David P; Go, Myong-Hyun
2011-12-01
Research on sexual orientation and substance use has established that lesbian, gay, and bisexual (LGB) individuals are more likely to smoke than heterosexuals. This analysis furthers the examination of smoking behaviors across sexual orientation groups by describing how same- and opposite-sex romantic attraction, and changes in romantic attraction, are associated with distinct six-year developmental trajectories of smoking. The National Longitudinal Study of Adolescent Health dataset is used to test our hypotheses. Multinomial logistic regressions predicting smoking trajectory membership as a function of romantic attraction were separately estimated for men and women. Romantic attraction effects were found only for women. The change from self-reported heterosexual attraction to lesbian or bisexual attraction was more predictive of higher smoking trajectories than was a consistent lesbian or bisexual attraction, with potentially important differences between the smoking patterns of these two groups. Copyright © 2011 Elsevier Ltd. All rights reserved.
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Customization in Prescribing for Bipolar Disorder
Hodgkin, Dominic; Volpe-Vartanian, Joanna; Merrick, Elizabeth L.; Horgan, Constance M.; Nierenberg, Andrew A.; Frank, Richard G.; Lee, Sue
2011-01-01
For many disorders, patient heterogeneity requires physicians to customize their treatment to each patient’s needs. We test for the existence of customization in physicians’ prescribing for bipolar disorder, using data from a naturalistic clinical effectiveness trial of bipolar disorder treatment (STEP-BD), which did not constrain physician prescribing. Multinomial logit is used to model the physician’s choice among five combinations of drug classes. We find that our observed measure of the patient’s clinical status played only a limited role in the choice among drug class combinations, even for conditions such as mania that are expected to affect class choice. However, treatment of a patient with given characteristics differed widely depending on which physician was seen. The explanatory power of the model was low. There was variation within each physician’s prescribing, but the results do not suggest a high degree of customization in physicians’ prescribing, based on our measure of clinical status. PMID:21506194
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Customization in prescribing for bipolar disorder.
Hodgkin, Dominic; Volpe-Vartanian, Joanna; Merrick, Elizabeth L; Horgan, Constance M; Nierenberg, Andrew A; Frank, Richard G; Lee, Sue
2012-06-01
For many disorders, patient heterogeneity requires physicians to customize their treatment to each patient's needs. We test for the existence of customization in physicians' prescribing for bipolar disorder, using data from a naturalistic clinical effectiveness trial of bipolar disorder treatment (STEP-BD), which did not constrain physician prescribing. Multinomial logit is used to model the physician's choice among five combinations of drug classes. We find that our observed measure of the patient's clinical status played only a limited role in the choice among drug class combinations, even for conditions such as mania that are expected to affect class choice. However, treatment of a patient with given characteristics differed widely depending on which physician was seen. The explanatory power of the model was low. There was variation within each physician's prescribing, but the results do not suggest a high degree of customization in physicians' prescribing, based on our measure of clinical status. Copyright © 2011 John Wiley & Sons, Ltd.
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Spatial distribution of the risk of dengue fever in southeast Brazil, 2006-2007
2011-01-01
Background Many factors have been associated with circulation of the dengue fever virus and vector, although the dynamics of transmission are not yet fully understood. The aim of this work is to estimate the spatial distribution of the risk of dengue fever in an area of continuous dengue occurrence. Methods This is a spatial population-based case-control study that analyzed 538 cases and 727 controls in one district of the municipality of Campinas, São Paulo, Brazil, from 2006-2007, considering socio-demographic, ecological, case severity, and household infestation variables. Information was collected by in-home interviews and inspection of living conditions in and around the homes studied. Cases were classified as mild or severe according to clinical data, and they were compared with controls through a multinomial logistic model. A generalized additive model was used in order to include space in a non-parametric fashion with cubic smoothing splines. Results Variables associated with increased incidence of all dengue cases in the multiple binomial regression model were: higher larval density (odds ratio (OR) = 2.3 (95%CI: 2.0-2.7)), reports of mosquito bites during the day (OR = 1.8 (95%CI: 1.4-2.4)), the practice of water storage at home (OR = 2.5 (95%CI: 1.4, 4.3)), low frequency of garbage collection (OR = 2.6 (95%CI: 1.6-4.5)) and lack of basic sanitation (OR = 2.9 (95%CI: 1.8-4.9)). Staying at home during the day was protective against the disease (OR = 0.5 (95%CI: 0.3-0.6)). When cases were analyzed by categories (mild and severe) in the multinomial model, age and number of breeding sites more than 10 were significant only for the occurrence of severe cases (OR = 0.97, (95%CI: 0.96-0.99) and OR = 2.1 (95%CI: 1.2-3.5), respectively. Spatial distribution of risks of mild and severe dengue fever differed from each other in the 2006/2007 epidemic, in the study area. Conclusions Age and presence of more than 10 breeding sites were significant only for severe cases. Other predictors of mild and severe cases were similar in the multiple models. The analyses of multinomial models and spatial distribution maps of dengue fever probabilities suggest an area-specific epidemic with varying clinical and demographic characteristics. PMID:21599980
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Predicting Prostate Cancer Progression At Time of Diagnosis
2016-09-01
greater or less than 50% pattern 4—is again arbitrary and may not capture biology adequately [see an unrelated paper we published during the study period...predictor of major upgrading (p=0.02 and p=0.18, respectively). On multinomial analysis, which we feel best reflects the spectrum of biology we are...predictive of outcomes, and that unique insights into tumor biology may be gleaned by analysis of both types of biomarkers. Task 6 As noted
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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.
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Knowledge about tuberculosis transmission among ever-married women in Bangladesh.
Khandoker, A; Khan, M M H; Krämer, A; Mori, M
2011-03-01
To identify the level of knowledge about TB transmission among ever-married women aged 15-49 years (n = 10 996) in Bangladesh, one of the highest tuberculosis (TB) burden countries. We analysed data from the Bangladesh Demographic and Health Survey conducted in 2007. Covariate factors included age, district, urban/rural residence, marital status, education, husband's education and access to the media (television, radio, newspaper/magazine). Bivariate and multinomial logistic regression analyses were performed to find the correlates of correct knowledge of TB transmission. Knowledge about TB transmission was correctly reported by approximately 7.0% of women, and was significantly associated with education, district and access to media using multinomial logistic regression. The likelihood of correct knowledge was 3.5 times (OR 3.5, 95%CI 2.5-4.9) higher among women with ≥11 years of education than among women with no/primary education. A significantly higher OR for correct knowledge of TB transmission (OR 1.5, 95%CI 1.2-1.9) was found among women who watched television almost every day compared to women who watched less than once a week. Correct knowledge about TB transmission was very low among married women in Bangladesh. Factors such as education and access to media, especially television, could play an important role in improving knowledge about TB transmission among women in Bangladesh.
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Lewis, Kristin Nicole; Heckman, Bernadette Davantes; Himawan, Lina
2011-08-01
Growth mixture modeling (GMM) identified latent groups based on treatment outcome trajectories of headache disability measures in patients in headache subspecialty treatment clinics. Using a longitudinal design, 219 patients in headache subspecialty clinics in 4 large cities throughout Ohio provided data on their headache disability at pretreatment and 3 follow-up assessments. GMM identified 3 treatment outcome trajectory groups: (1) patients who initiated treatment with elevated disability levels and who reported statistically significant reductions in headache disability (high-disability improvers; 11%); (2) patients who initiated treatment with elevated disability but who reported no reductions in disability (high-disability nonimprovers; 34%); and (3) patients who initiated treatment with moderate disability and who reported statistically significant reductions in headache disability (moderate-disability improvers; 55%). Based on the final multinomial logistic regression model, a dichotomized treatment appointment attendance variable was a statistically significant predictor for differentiating high-disability improvers from high-disability nonimprovers. Three-fourths of patients who initiated treatment with elevated disability levels did not report reductions in disability after 5 months of treatment with new preventive pharmacotherapies. Preventive headache agents may be most efficacious for patients with moderate levels of disability and for patients with high disability levels who attend all treatment appointments. Copyright © 2011 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.
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Prevalence of bullying by gender and education in a city with high violence and migration in Mexico.
Ramos-Jiménez, Arnulfo; Hernández-Torres, Rosa P; Murguía-Romero, Miguel; Villalobos-Molina, Rafael
2017-05-25
To understand the prevalence of bullying, by gender and educational level, in Ciudad Juárez, Mexico, a city with high rates of violence and migration. This was a cross-sectional, observational study conducted in 2012 - 2014 using a questionnaire known as the Bullying-Mexican. A probabilistic multistage cluster-sampling method obtained a study sample of 2 347 students (10 - 27 years of age) from the 400 000 enrolled in grade 5 - university level at the 611 public schools in Ciudad Juárez. Bullying prevalence and frequency (never, rarely, sometimes, often, every day) were analyzed with descriptive statistics. The statistical differences between males and females was assessed using a chi-square test; associations between frequency and academic level were determined by correspondence analysis and the Spearman Rho correlation. A multinomial logistic regression was performed to analyze whether gender and academic level acted independently in the frequency of bullying. Bullying prevalence was reported by 38% of females and 47% of males: 'only victim' represented 8.7%; 'only aggressor,' 13.2%; and 'victim and aggressor,' 21%. At higher levels of education, bullying prevalence declined; however, at the university, prevalence increased in the last semesters. Mockery and social exclusion were the two most dominant types of bullying, followed by beating, threats, and punishment. The prevalence of bullying in Ciudad Juárez public schools is among the highest compared to other random studies and surveys. Bullying diminishes with age and educational level.
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Hossain, Moinul; Muromachi, Yasunori
2012-03-01
The concept of measuring the crash risk for a very short time window in near future is gaining more practicality due to the recent advancements in the fields of information systems and traffic sensor technology. Although some real-time crash prediction models have already been proposed, they are still primitive in nature and require substantial improvements to be implemented in real-life. This manuscript investigates the major shortcomings of the existing models and offers solutions to overcome them with an improved framework and modeling method. It employs random multinomial logit model to identify the most important predictors as well as the most suitable detector locations to acquire data to build such a model. Afterwards, it applies Bayesian belief net (BBN) to build the real-time crash prediction model. The model has been constructed using high resolution detector data collected from Shibuya 3 and Shinjuku 4 expressways under the jurisdiction of Tokyo Metropolitan Expressway Company Limited, Japan. It has been specifically built for the basic freeway segments and it predicts the chance of formation of a hazardous traffic condition within the next 4-9 min for a particular 250 meter long road section. The performance evaluation results reflect that at an average threshold value the model is able to successful classify 66% of the future crashes with a false alarm rate less than 20%. Copyright © 2011 Elsevier Ltd. All rights reserved.
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Development of scales relating to professional development of community college administrators.
Wolfe, Edward W; Van Der Linden, Kim E
2010-01-01
This article reports the results of an application of the Multidimensional Random Coefficients Multinomial Logit Model (MRCMLM) to the measurement of professional development activities in which community college administrators participate. The analyses focus on confirmation of the factorial structure of the instrument, evaluation of the quality of the activities calibrations, examination of the internal structure of the instrument, and comparison of groups of administrators. The dimensionality analysis results suggest a five-dimensional model that is consistent with previous literature concerning career paths of community college administrators - education and specialized training, internal professional development and mentoring, external professional development, employer support, and seniority. The indicators of the quality of the activity calibrations suggest that measures of the five dimensions are adequately reliable, that the activities in each dimension are internally consistent, and that the observed responses to each activity are consistent with the expected values of the MRCMLM. The hierarchy of administrator measure means and of activity calibrations is consistent with substantive theory relating to professional development for community college administrators. For example, readily available activities that occur at the institution were most likely to be engaged in by administrators, while participation in selective specialized training institutes were the least likely activities. Finally, group differences with respect to age and title were consistent with substantive expectations - the greater the administrator's age and the higher the rank of the administrator's title, the greater the probability of having engaged in various types of professional development.
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Nonfatal Injuries and Psychosocial Correlates among Middle School Students in Cambodia and Vietnam.
Peltzer, Karl; Pengpid, Supa
2017-03-08
The aim of the study was to estimate the prevalence and psychosocial correlates of nonfatal injury among middle school students in Cambodia and Vietnam. Cross-sectional data from 7137 school children (mean age 15.5 years, SD = 1.4) who were randomly sampled for participation in nationally representative Global School-based Health Surveys (GSHS) in Cambodia and Vietnam were analyzed. The proportion of school children reporting one or more serious injuries in the past year was 22.6% among boys and 17.5% among girls in Cambodia and 34.3% among boys and 25.1% among girls in Vietnam. The most prevalent cause of the most serious injury in Cambodia was traffic injuries (4.7% among boys and 4.3% among girls) and in Vietnam it was falls (10.0% among boys and 7.0% among girls). In multinomial logistic regression analyses, experiencing hunger (as an indicator for low socioeconomic status) and drug use were associated with having sustained one injury and two or more injuries in the past 12 months in Cambodia. In addition, poor mental health was associated with two or more injuries. In Vietnam, being male, experiencing hunger, current alcohol use, poor mental health and ever having had sex were associated with having sustained one injury and two or more injuries in the past 12 months. Several psychosocial variables were identified which could help in designing injury prevention strategies among middle school children in Cambodia and Vietnam.
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Statistical analysis of dendritic spine distributions in rat hippocampal cultures
2013-01-01
Background Dendritic spines serve as key computational structures in brain plasticity. Much remains to be learned about their spatial and temporal distribution among neurons. Our aim in this study was to perform exploratory analyses based on the population distributions of dendritic spines with regard to their morphological characteristics and period of growth in dissociated hippocampal neurons. We fit a log-linear model to the contingency table of spine features such as spine type and distance from the soma to first determine which features were important in modeling the spines, as well as the relationships between such features. A multinomial logistic regression was then used to predict the spine types using the features suggested by the log-linear model, along with neighboring spine information. Finally, an important variant of Ripley’s K-function applicable to linear networks was used to study the spatial distribution of spines along dendrites. Results Our study indicated that in the culture system, (i) dendritic spine densities were "completely spatially random", (ii) spine type and distance from the soma were independent quantities, and most importantly, (iii) spines had a tendency to cluster with other spines of the same type. Conclusions Although these results may vary with other systems, our primary contribution is the set of statistical tools for morphological modeling of spines which can be used to assess neuronal cultures following gene manipulation such as RNAi, and to study induced pluripotent stem cells differentiated to neurons. PMID:24088199
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Tooth wear and the role of salivary measures in general practice patients
Rothen, Marilynn; Scott, JoAnna; Cunha-Cruz, Joana
2014-01-01
Objectives The goal of this study was to investigate the association between tooth wear and salivary measures in a random sample of patients from practices of dentist members of a practice-based research network. Materials and methods Patients completed a questionnaire on oral self-care, health, dietary habits, medications, and socio-demographic variables. Six salivary characteristics (consistency, resting salivary flow, resting salivary pH, stimulated salivary flow, stimulated salivary pH, and buffering capacity) were measured, and a dental examination included categorizing patients according to the dentist’s judgment of the degree of tooth wear (i.e., none/minimal, some, or severe/extreme). Bivariate and multinomial logistic regression models were used to relate salivary characteristics and other factors to the outcome of tooth wear. Results Data are reported from 1,323 patients (age range 16–97 years) from 61 practices. Patient age, gender, number of teeth, and perception of dry mouth were associated with tooth wear, but salivary and dietary factors were either weakly or not related. Conclusions The findings of this cross-sectional assessment suggest that using these salivary tests and dietary assessments in real-life clinical settings is unlikely to be useful in assessing tooth wear risk. Suggestions are offered about risk assessment for tooth wear. Clinical relevance Assessing a dental patient’s risk of tooth wear using salivary measures and dietary assessments as described is not recommended for general dental practice until stronger evidence exists indicating its utility. PMID:24647789
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2013-01-01
Background The participation of children and adolescents in sports has become increasingly frequent, including soccer. This growing involvement gives rise to concerns regarding the risk of sports injuries. Therefore, the aim of the present study was to describe the musculoskeletal injuries in young soccer players. Methods 301 male soccer players with a mean age 14.67 ± 2.08 years were randomly recruited. The Referred Condition Inquiry was used to collect information on the mechanism of injury and anatomic site affected as well as personal data on the participants. The variables were analyzed based on the degree of association using Goodman’s test for contrasts between multinomial populations, with the p < 0.05. Results Among the 301 athletes, 24.25% reported at least one injury. With regard to height, taller individuals reported more injuries than shorter individuals (62.5% and 37.5%, respectively; p < 0.05). Injuries were more frequent among players with a training duration greater than five years (69.65%) in comparison to those who trained for a shorter duration (30.35%) (p < 0.05). The lower limbs, especially the ankle/foot and knee, were the most affected anatomic sites. Impact was the most common mechanism of injury. Conclusion The young practitioners of soccer analyzed had low rates of injury. The main causal mechanism was the impact. A taller height and longer exposure to training were the main risk factors for injury among young soccer players. PMID:23602027
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Sripada, Rebecca K; Hannemann, Claire M; Schnurr, Paula P; Marx, Brian P; Pollack, Stacey J; McCarthy, John F
2018-04-17
To determine patterns of mental health service use before and after VA disability compensation awards for posttraumatic stress disorder (PTSD). A 10 percent random sample of VHA-enrolled Veterans with new or increased PTSD service connection between 2012 and 2014 (n = 22,249). We used latent trajectory analysis to identify utilization patterns and multinomial logistic regression to assess associations between Veteran characteristics and trajectory membership. We assessed receipt of VHA mental health encounters in each of the 52 weeks prior to and following PTSD disability rating or rating increase. The best fitting model had five groups: No Use (36.6 percent), Low Use (37.7 percent), Increasing Use (9.4 percent), Decreasing Use (11.2 percent), and High Use (5.1 percent). Adjusting for demographic characteristics and compared with the No Use group, Veterans in the other groups were more likely to reside closer to a VHA facility, receive a higher PTSD disability rating, and screen positive for military sexual trauma. Service use remained stable (80 percent) or increased (9 percent) for the vast majority of Veterans. Service utilization declined for only 11 percent. Data did not indicate substantial service discontinuation following rating. Low VHA service utilization suggests opportunities to enhance outreach for Veterans with PTSD-related disability benefits. © Published 2018. This article is a U.S. Government work and is in the public domain in the USA.
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Visual difficulty and employment status in the world.
Harrabi, Hanen; Aubin, Marie-Josee; Zunzunegui, Maria Victoria; Haddad, Slim; Freeman, Ellen E
2014-01-01
Using a world-wide, population-based dataset, we sought to examine the relationship between visual difficulty and employment status. The World Health Survey was conducted in 70 countries throughout the world in 2003 using a random, multi-stage, stratified, cluster sampling design. Far vision was assessed by asking about the level of difficulty in seeing and recognizing a person you know across the road (i.e. from a distance of about 20 meters). Responses included none, mild, moderate, severe, or extreme/unable. Participants were asked about their current job, and if they were not working, the reason why (unable to find job, ill health, homemaker, studies, unpaid work, other). The occupation in the last 12 months was obtained. Multinomial regression was used accounting for the complex survey design. Of those who wanted to work, 79% of those with severe visual difficulty and 64% of those with extreme visual difficulty were actually working. People who had moderate, severe, or extreme visual difficulty had a higher odds of not working due to an inability to find a job and of not working due to ill health after adjusting for demographic and health factors (P<0.05). As the major causes of visual impairment in the world are uncorrected refractive error and cataract, countries are losing a great deal of labor productivity by failing to provide for the vision health needs of their citizens and failing to help them integrate into the workforce.
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Shamah-Levy, Teresa; Cuevas-Nasu, Lucía; Gómez-Acosta, Luz María; Morales-Ruan, Ma Del Carmen; Méndez-Gómez Humarán, Ignacio; Robles-Villaseñor, Mara Nadiezhda; Hernández-Ávila, Mauricio
2017-01-01
To assess the effect of Education in Nutrition and Food Assistance components of the SaludArte program in participant schools during 2013-2015. A three cohort comparative study was used, with two type of follow-up panel structures: a complete panel and a continuous time, with a total of consisting on 1620 scholar children from 144 schools. Information on food intake, feeding behaviors, food preservation and hygiene, physical activity (PI) and anthropometry was registered. To stablish effect estimates, a difference in difference method combined with propensity score matching was carried out; as an alternative procedure, logistic-multinomial and logistic regression models were also used. Program attributable estimated effects were as follows: an increase in personal hygiene (p=0.045), increase in nutrition knowledges (p=0.003), PI (p=0.002 2013-2014; p=0.032 2015) and increase in fiber Intake (p=0.064). Sugar intake, contrary to the expected showed a significant increase (p=0.012 continuous time and; p=0.037 complete time). SaludArte shows positive effects over some components as expected. However in order to institutionalize the SaludArte program, it is necessary to consider these learned lessons, give it permanence and impulse it in the schools.
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Effects of payment changes on trends in post-acute care.
Buntin, Melinda Beeuwkes; Colla, Carrie Hoverman; Escarce, José J
2009-08-01
To test how the implementation of new Medicare post-acute payment systems affected the use of inpatient rehabilitation facilities (IRFs), skilled nursing facilities (SNFs), and home health agencies. Medicare acute hospital, IRF, and SNF claims; provider of services file; enrollment file; and Area Resource File data. We used multinomial logit models to measure realized access to post-acute care and to predict how access to alternative sites of care changed in response to prospective payment systems. A file was constructed linking data for elderly Medicare patients discharged from acute care facilities between 1996 and 2003 with a diagnosis of hip fracture, stroke, or lower extremity joint replacement. Although the effects of the payment systems on the use of post-acute care varied, most reduced the use of the site of care they directly affected and boosted the use of alternative sites of care. Payment system changes do not appear to have differentially affected the severely ill. Payment system incentives play a significant role in determining where Medicare beneficiaries receive their post-acute care. Changing these incentives results in shifting of patients between post-acute sites.
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Wright, Jim; Dzodzomenyo, Mawuli; Wardrop, Nicola A.; Johnston, Richard; Hill, Allan; Aryeetey, Genevieve; Adanu, Richard
2016-01-01
There remain few nationally representative studies of drinking water quality at the point of consumption in developing countries. This study aimed to examine factors associated with E. coli contamination in Ghana. It drew on a nationally representative household survey, the 2012−2013 Living Standards Survey 6, which incorporated a novel water quality module. E. coli contamination in 3096 point-of-consumption samples was examined using multinomial regression. Surface water use was the strongest risk factor for high E. coli contamination (relative risk ratio (RRR) = 32.3, p < 0.001), whilst packaged (sachet or bottled) water use had the greatest protective effect (RRR = 0.06, p < 0.001), compared to water piped to premises. E. coli contamination followed plausible patterns with digit preference (tendency to report values ending in zero) in bacteria counts. The analysis suggests packaged drinking water use provides some protection against point-of-consumption E. coli contamination and may therefore benefit public health. It also suggests viable water quality data can be collected alongside household surveys, but field protocols require further revision. PMID:27005650
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Wright, Jim; Dzodzomenyo, Mawuli; Wardrop, Nicola A; Johnston, Richard; Hill, Allan; Aryeetey, Genevieve; Adanu, Richard
2016-03-09
There remain few nationally representative studies of drinking water quality at the point of consumption in developing countries. This study aimed to examine factors associated with E. coli contamination in Ghana. It drew on a nationally representative household survey, the 2012-2013 Living Standards Survey 6, which incorporated a novel water quality module. E. coli contamination in 3096 point-of-consumption samples was examined using multinomial regression. Surface water use was the strongest risk factor for high E. coli contamination (relative risk ratio (RRR) = 32.3, p < 0.001), whilst packaged (sachet or bottled) water use had the greatest protective effect (RRR = 0.06, p < 0.001), compared to water piped to premises. E. coli contamination followed plausible patterns with digit preference (tendency to report values ending in zero) in bacteria counts. The analysis suggests packaged drinking water use provides some protection against point-of-consumption E. coli contamination and may therefore benefit public health. It also suggests viable water quality data can be collected alongside household surveys, but field protocols require further revision.
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Keith, Verna M; Nguyen, Ann W; Taylor, Robert Joseph; Mouzon, Dawne M; Chatters, Linda M
2017-05-01
Data from the 2001-2003National Survey of American Life are used to investigate the effects of phenotype on everyday experiences with discrimination among African Americans (N=3343). Latent class analysis is used to identify four classes of discriminatory treatment: 1) low levels of discrimination, 2) disrespect and condescension, 3) character-based discrimination, and 4) high levels of discrimination. We then employ latent class multinomial logistic regression to evaluate the association between skin tone and body weight and these four classes of discrimination. Designating the low level discrimination class as the reference group, findings revealed that respondents with darker skin were more likely to be classified into the disrespect/condescension and the high level microaggression types. BMI was unrelated to the discrimination type, although there was a significant interaction effect between gender and BMI. BMI was strongly and positively associated with membership in the disrespect and condescension type among men but not among women. These findings indicate that skin tone and body weight are two phenotypic characteristics that influence the type and frequency of discrimination experienced by African Americans.
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Asymptotic Normality Through Factorial Cumulants and Partition Identities
Bobecka, Konstancja; Hitczenko, Paweł; López-Blázquez, Fernando; Rempała, Grzegorz; Wesołowski, Jacek
2013-01-01
In the paper we develop an approach to asymptotic normality through factorial cumulants. Factorial cumulants arise in the same manner from factorial moments as do (ordinary) cumulants from (ordinary) moments. Another tool we exploit is a new identity for ‘moments’ of partitions of numbers. The general limiting result is then used to (re-)derive asymptotic normality for several models including classical discrete distributions, occupancy problems in some generalized allocation schemes and two models related to negative multinomial distribution. PMID:24591773
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NASA Astrophysics Data System (ADS)
Yoo, Jin Woo
In my 1st essay, the study explores Pennsylvania residents. willingness to pay for development of renewable energy technologies such as solar power, wind power, biomass electricity, and other renewable energy using a choice experiment method. Principle component analysis identified 3 independent attitude components that affect the variation of preference, a desire for renewable energy and environmental quality and concern over cost. The results show that urban residents have a higher desire for environmental quality and concern less about cost than rural residents and consequently have a higher willingness to pay to increase renewable energy production. The results of sub-sample analysis show that a representative respondent in rural (urban) Pennsylvania is willing to pay 3.8(5.9) and 4.1(5.7)/month for increasing the share of Pennsylvania electricity generated from wind power and other renewable energy by 1 percent point, respectively. Mean WTP for solar and biomass electricity was not significantly different from zero. In my second essay, heterogeneity of individual WTP for various renewable energy technologies is investigated using several different variants of the multinomial logit model: a simple MNL with interaction terms, a latent class choice model, a random parameter mixed logit choice model, and a random parameter-latent class choice model. The results of all models consistently show that respondents. preference for individual renewable technology is heterogeneous, but the degree of heterogeneity differs for different renewable technologies. In general, the random parameter logit model with interactions and a hybrid random parameter logit-latent class model fit better than other models and better capture respondents. heterogeneity of preference for renewable energy. The impact of the land under agricultural conservation easement (ACE) contract on the values of nearby residential properties is investigated using housing sales data in two Pennsylvania Counties. The spatial-lag (SLM), the spatial error (SEM) and the spatial error component (SEC) models were compared. A geographically weighted regression (GWR) model is estimated to study the spatial heterogeneity of the marginal implicit prices of ACE impact within each county. New hybrid spatial hedonic models, the GWR-SEC and a modified GWR-SEM, are estimated such that both spatial autocorrelation and heterogeneity are accounted. The results show that the coefficient of land under easement contract varies spatially within one county, but not within the other county studied. Also, ACE's are found to have both positive and negative impacts on the values of nearby residential properties. Among global spatial models, the SEM fit better than the SLM and the SEC. Statistical goodness of fit measures showed that the GWR-SEC model fit better than the GWR or the GWR-SEC model. Finally, the GWR-SEC showed spatial autocorrelation is stronger in one county than in the other county.
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Wilhelm, Michelle; Ritz, Beate
2013-01-01
Objectives. The purpose of our study was to examine the effects of indoor residential air quality on preterm birth and term low birth weight (LBW). Methods. We evaluated 1761 nonsmoking women from a case-control survey of mothers who delivered a baby in 2003 in Los Angeles County, California. In multinomial logistic regression models adjusted for maternal age, education, race/ethnicity, parity and birthplace, we evaluated the effects of living with smokers or using personal or household products that may contain volatile organic compounds and examined the influence of household ventilation. Results. Compared with unexposed mothers, women exposed to secondhand smoke (SHS) at home had increased odds of term LBW (adjusted odds ratio [OR] = 1.36; 95% confidence interval [CI] = 0.85, 2.18) and preterm birth (adjusted OR = 1.27; 95% CI = 0.95, 1.70), although 95% CIs included the null. No increase in risk was observed for SHS-exposed mothers reporting moderate or high window ventilation. Associations were also observed for product usage, but only for women reporting low or no window ventilation. Conclusions. Residential window ventilation may mitigate the effects of indoor air pollution among pregnant women in Los Angeles County, California. PMID:23409879
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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.
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Brink, Michel S; Visscher, Chris; Arends, Suzanne; Zwerver, Johannes; Post, Wendy J; Lemmink, Koen Apm
2010-09-01
Elite youth soccer players have a relatively high risk for injuries and illnesses due to increased physical and psychosocial stress. The aim of this study is to investigate how measures to monitor stress and recovery, and its analysis, provide useful information for the prevention of injuries and illnesses in elite youth soccer players. 53 elite soccer players between 15 and 18 years of age participated in this study. To determine physical stress, soccer players registered training and match duration and session rating of perceived exertion for two competitive seasons by means of daily training logs. The Dutch version of the Recovery Stress Questionnaire for athletes (RESTQ-Sport) was administered monthly to assess the psychosocial stress-recovery state of players. The medical staff collected injury and illness data using the standardised Fédération Internationale de Football Association registration system. ORs and 95% CIs were calculated for injuries and illnesses using multinomial regression analyses. The independent measures were stress and recovery. During the study period, 320 injuries and 82 illnesses occurred. Multinomial regression demonstrated that physical stress was related to both injury and illness (range OR 1.01 to 2.59). Psychosocial stress and recovery were related the occurrence of illness (range OR 0.56 to 2.27). Injuries are related to physical stress. Physical stress and psychosocial stress and recovery are important in relation to illness. Individual monitoring of stress and recovery may provide useful information to prevent soccer players from injuries and illnesses.
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Medina-Solis, Carlo Eduardo; Maupomé, Gerardo; del Socorro, Herrera Miriam; Pérez-Núñez, Ricardo; Avila-Burgos, Leticia; Lamadrid-Figueroa, Hector
2008-01-01
To determine the factors associated with the dental health services utilization among children ages 6 to 12 in León, Nicaragua. A cross-sectional study was carried out in 1,400 schoolchildren. Using a questionnaire, we determined information related to utilization and independent variables in the previous year. Oral health needs were established by means of a dental examination. To identify the independent variables associated with dental health services utilization, two types of multivariate regression models were used, according to the measurement scale of the outcome variable: a) frequency of utilization as (0) none, (1) one, and (2) two or more, analyzed with the ordered logistic regression and b) the type of service utilized as (0) none, (1) preventive services, (2) curative services, and (3) both services, analyzed with the multinomial logistic regression. The proportion of children who received at least one dental service in the 12 months prior to the study was 27.7 percent. The variables associated with utilization in the two models were older age, female sex, more frequent toothbrushing, positive attitude of the mother toward the child's oral health, higher socioeconomic level, and higher oral health needs. Various predisposing, enabling, and oral health needs variables were associated with higher dental health services utilization. As in prior reports elsewhere, these results from Nicaragua confirmed that utilization inequalities exist between socioeconomic groups. The multinomial logistic regression model evidenced the association of different variables depending on the type of service used.
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Circulating Prolactin Associates With Diabetes and Impaired Glucose Regulation
Wang, Tiange; Lu, Jieli; Xu, Yu; Li, Mian; Sun, Jichao; Zhang, Jie; Xu, Baihui; Xu, Min; Chen, Yuhong; Bi, Yufang; Wang, Weiqing; Ning, Guang
2013-01-01
OBJECTIVE Prolactin is a major stimulus for the β-cell adaptation during gestation and guards postpartum women against gestational diabetes. Most studies of the role of prolactin on glucose metabolism have been conducted in humans and animals during pregnancy. However, little is known concerning the association between circulating prolactin and glucose metabolism outside pregnancy in epidemiological studies. We aimed to determine whether the variation of circulating prolactin concentration associates with diabetes and impaired glucose regulation (IGR) in a cross-sectional study. RESEARCH DESIGN AND METHODS We recruited 2,377 participants (1,034 men and 1,343 postmenopausal women) without hyperprolactinemia, aged 40 years and older, in Shanghai, China. Diabetes and IGR were determined by an oral glucose tolerance test. Multinomial logit analyses were performed to evaluate the relationship of prolactin with diabetes and IGR. RESULTS Prolactin levels decreased from normal glucose regulation to IGR to diabetes. Multinomial logit analyses, adjusted for potential confounding factors, showed that high circulating prolactin was associated with lower prevalence of diabetes and IGR. The adjusted odds ratios (95% CI) for IGR and diabetes for the highest compared with the lowest quartile of prolactin were 0.54 (95% CI 0.33–0.89) and 0.38 (0.24–0.59) in men and 0.54 (0.36–0.81) and 0.47 (0.32–0.70) in women. CONCLUSIONS High circulating prolactin associates with lower prevalence of diabetes and IGR in the current study. Further studies are warranted to confirm this association. PMID:23340889
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Shared clinical decision making
AlHaqwi, Ali I.; AlDrees, Turki M.; AlRumayyan, Ahmad; AlFarhan, Ali I.; Alotaibi, Sultan S.; AlKhashan, Hesham I.; Badri, Motasim
2015-01-01
Objectives: To determine preferences of patients regarding their involvement in the clinical decision making process and the related factors in Saudi Arabia. Methods: This cross-sectional study was conducted in a major family practice center in King Abdulaziz Medical City, Riyadh, Saudi Arabia, between March and May 2012. Multivariate multinomial regression models were fitted to identify factors associated with patients preferences. Results: The study included 236 participants. The most preferred decision-making style was shared decision-making (57%), followed by paternalistic (28%), and informed consumerism (14%). The preference for shared clinical decision making was significantly higher among male patients and those with higher level of education, whereas paternalism was significantly higher among older patients and those with chronic health conditions, and consumerism was significantly higher in younger age groups. In multivariate multinomial regression analysis, compared with the shared group, the consumerism group were more likely to be female [adjusted odds ratio (AOR) =2.87, 95% confidence interval [CI] 1.31-6.27, p=0.008] and non-dyslipidemic (AOR=2.90, 95% CI: 1.03-8.09, p=0.04), and the paternalism group were more likely to be older (AOR=1.03, 95% CI: 1.01-1.05, p=0.04), and female (AOR=2.47, 95% CI: 1.32-4.06, p=0.008). Conclusion: Preferences of patients for involvement in the clinical decision-making varied considerably. In our setting, underlying factors that influence these preferences identified in this study should be considered and tailored individually to achieve optimal treatment outcomes. PMID:26620990
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Grav, Siv; Romild, Ulla; Hellzèn, Ove; Stordal, Eystein
2013-08-01
The aim of the current study was to examine the association of personality, neighbourhood, and civic participation with the level of perceived social support if needed. The sample consists of a total of 35,797 men (16,035) and women (19,762) drawn from the Nord-Trøndelag Health Study 3 (HUNT3), aged 20-89, with a fully completed short version of the Eysenck Personality Questionnaire (EPQ) including a complete response to questions regarding perceived social support. A multinomial logistic regression model was used to investigate the association between the three-category outcomes (high, medium, and low) of perceived social support. The Chi-square test detected a significant (p < 0.001) association between personality, sense of community, civic participation, self-rated health, living arrangement, age groups, gender, and perceived social support, except between perceived social support and loss of social network, in which no significance was found. The crude and adjusted multinomial logistic regression models show a relation between medium and low scores on perceived social support, personality, and sources of social support. Interactions were observed between gender and self-rated health. There is an association between the level of perceived social support and personality, sense of community in the neighbourhood, and civic participation. Even if the interaction between men and self-reported health decreases the odds for low and medium social support, health professionals should be aware of men with poor health and their lack of social support.
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NASA Astrophysics Data System (ADS)
Zhang, Min; Gong, Zhaoning; Zhao, Wenji; Pu, Ruiliang; Liu, Ke
2016-01-01
Mapping vegetation abundance by using remote sensing data is an efficient means for detecting changes of an eco-environment. With Landsat-8 operational land imager (OLI) imagery acquired on July 31, 2013, both linear spectral mixture analysis (LSMA) and multinomial logit model (MNLM) methods were applied to estimate and assess the vegetation abundance in the Wild Duck Lake Wetland in Beijing, China. To improve mapping vegetation abundance and increase the number of endmembers in spectral mixture analysis, normalized difference vegetation index was extracted from OLI imagery along with the seven reflective bands of OLI data for estimating the vegetation abundance. Five endmembers were selected, which include terrestrial plants, aquatic plants, bare soil, high albedo, and low albedo. The vegetation abundance mapping results from Landsat OLI data were finally evaluated by utilizing a WorldView-2 multispectral imagery. Similar spatial patterns of vegetation abundance produced by both fully constrained LSMA algorithm and MNLM methods were observed: higher vegetation abundance levels were distributed in agricultural and riparian areas while lower levels in urban/built-up areas. The experimental results also indicate that the MNLM model outperformed the LSMA algorithm with smaller root mean square error (0.0152 versus 0.0252) and higher coefficient of determination (0.7856 versus 0.7214) as the MNLM model could handle the nonlinear reflection phenomenon better than the LSMA with mixed pixels.
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Determinants of modern contraceptive use among sexually active men in Kenya.
Ochako, Rhoune; Temmerman, Marleen; Mbondo, Mwende; Askew, Ian
2017-04-27
Research in Kenya has focussed on family planning from women's perspectives, with the aim of helping reduce the burden of unintended pregnancies. As such, the determinants of modern contraceptive use among sexually active women are well documented. However, the perspectives of men should be considered not only as women's partners, but also as individuals with distinct reproductive histories and desires of their own. This study seeks to understand the determinants of modern contraceptive use among sexually active men, by exploring factors that are correlated with modern contraceptive use. The data source is the nationally representative 2014 Kenya Demographic and Health Survey (DHS) of men aged 15-54 years. The analysis is restricted to 9,514 men who reported being sexually active in the past 12 months prior to the survey, as they were likely to report either doing something or not to avoid or delay pregnancy. We use bivariate and multinomial logistic regression to assess factors that influence modern contraceptive use among sexually active men. Findings from the bivariate and multinomial logistic regression indicate that region of residence, marital status, religion, wealth, interaction with a health care provider, fertility preference, number of sexual partners and access to media were all significantly associated with modern contraceptive use among sexually active men. Provider-client interaction as well as dissemination of information through mass media has the potential to increase knowledge and uptake of modern contraceptives. Similar efforts targeting segments of the population where contraceptive uptake is low are recommended.
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Food and Drug Administration tobacco regulation and product judgments.
Kaufman, Annette R; Finney Rutten, Lila J; Parascandola, Mark; Blake, Kelly D; Augustson, Erik M
2015-04-01
The Family Smoking Prevention and Tobacco Control Act granted the Food and Drug Administration (FDA) the authority to regulate tobacco products in the U.S. However, little is known about how regulation may be related to judgments about tobacco product-related risks. To understand how FDA tobacco regulation beliefs are associated with judgments about tobacco product-related risks. The Health Information National Trends Survey is a national survey of the U.S. adult population. Data used in this analysis were collected from October 2012 through January 2013 (N=3,630) by mailed questionnaire and analyzed in 2013. Weighted bivariate chi-square analyses were used to assess associations among FDA regulation belief, tobacco harm judgments, sociodemographics, and smoking status. A weighted multinomial logistic regression was conducted where FDA regulation belief was regressed on tobacco product judgments, controlling for sociodemographic variables and smoking status. About 41% believed that the FDA regulates tobacco products in the U.S., 23.6% reported the FDA does not, and 35.3% did not know. Chi-square analyses showed that smoking status was significantly related to harm judgments about electronic cigarettes (p<0.0001). The multinomial logistic regression revealed that uncertainty about FDA regulation was associated with tobacco product harm judgment uncertainty. Tobacco product harm perceptions are associated with beliefs about tobacco product regulation by the FDA. These findings suggest the need for increased public awareness and understanding of the role of tobacco product regulation in protecting public health. Copyright © 2015. Published by Elsevier Inc.
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Association between employee benefits and frailty in community-dwelling older adults.
Avila-Funes, José Alberto; Paniagua-Santos, Diana Leticia; Escobar-Rivera, Vicente; Navarrete-Reyes, Ana Patricia; Aguilar-Navarro, Sara; Amieva, Hélène
2016-05-01
The phenotype of frailty has been associated with an increased vulnerability for the development of adverse health-related outcomes. The origin of frailty is multifactorial and financial issues could be implicated, as they have been associated with health status, well-being and mortality. However, the association between economic benefits and frailty has been poorly explored. Therefore, the objective was to determine the association between employee benefits and frailty. A cross-sectional study of 927 community-dwelling older adults aged 70 years and older participating in the Mexican Study of Nutritional and Psychosocial Markers of Frailty was carried out. Employee benefits were established according to eight characteristics: bonus, profit sharing, pension, health insurance, food stamps, housing credit, life insurance, and Christmas bonus. Frailty was defined according to a slightly modified version of the phenotype proposed by Fried et al. Multinomial logistic regression models were run to determine the association between employee benefits and frailty adjusting by sociodemographic and health covariates. The prevalence of frailty was 14.1%, and 4.4% of participants rated their health status as "poor." Multinomial logistic regression analyses showed that employee benefits were statistically and independently associated with the frail subgroup (OR 0.85; 95% CI 0.74-0.98; P = 0.027) even after adjusting for potential confounders. Fewer employee benefits are associated with frailty. Supporting spreading employee benefits for older people could have a positive impact on the development of frailty and its consequences. Geriatr Gerontol Int 2016; 16: 606-611. © 2015 Japan Geriatrics Society.
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2014-01-01
Background This paper constitutes an important ethnobiological survey in the context of utilizing biological resources by residents of Kala Chitta hills of Pothwar region, Pakistan. The fundamental aim of this research endeavour was to catalogue and analyse the indigenous knowledge of native community about plants and animals. The study is distinctive in the sense to explore both ethnobotanical and ethnozoological aspects of indigenous culture, and exhibits novelty, being based on empirical approach of Multinomial Logit Specifications (MLS) for examining ethnobotanical and ethnozoological uses of specific plants and animals. Methods To document the ethnobiological knowledge, the survey was conducted during 2011–12 by employing a semi-structured questionnaire and thus 54 informants were interviewed. Plant and animal specimens were collected, photographed and properly identified. Distribution of plants and animals were explored by descriptive and graphical examination. MLS were further incorporated to identify the probability of occurrence of diversified utilization of plants and animals in multipurpose domains. Results Traditional uses of 91 plant and 65 animal species were reported. Data analysis revealed more medicinal use of plants and animals than all other use categories. MLS findings are also in line with these proportional configurations. They reveal that medicinal and food consumption of underground and perennial plants was more as compared to aerial and annual categories of plants. Likewise, medicinal utilization of wild animals and domestic animals were more commonly observed as food items. However, invertebrates are more in the domain of medicinal and food utilization. Also carnivores are fairly common in the use of medicine while herbivores are in the category of food consumption. Conclusion This study empirically scans a good chunk of ethnobiological knowledge and depicts its strong connection with indigenous traditions. It is important to make local residents beware of conservation status of species and authentication of this knowledge needs to be done in near future. Moreover, Statistically significant findings impart novelty in the existing literature in the field of ethnobiology. Future conservation, phytochemical and pharmacological studies are recommended on these identified plants and animals in order to use them in a more sustainable and effective way. PMID:24467739
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Frei, Anja; Siebeling, Lara; Wolters, Callista; Held, Leonhard; Muggensturm, Patrick; Strassmann, Alexandra; Zoller, Marco; Ter Riet, Gerben; Puhan, Milo A
2016-10-01
COPD exacerbation incidence rates are often ascertained retrospectively through patient recall and self-reports. We compared exacerbation ascertainment through patient self-reports and single-physician chart review to central adjudication by a committee and explored determinants and consequences of misclassification. Self-reported exacerbations (event-based definition) in 409 primary care patients with COPD participating in the International Collaborative Effort on Chronic Obstructive Lung Disease: Exacerbation Risk Index Cohorts (ICE COLD ERIC) cohort were ascertained every 6 months over 3 years. Exacerbations were adjudicated by single experienced physicians and an adjudication committee who had information from patient charts. We assessed the accuracy (sensitivities and specificities) of self-reports and single-physician chart review against a central adjudication committee (AC) (reference standard). We used multinomial logistic regression and bootstrap stability analyses to explore determinants of misclassifications. The AC identified 648 exacerbations, corresponding to an incidence rate of 0.60 ± 0.83 exacerbations/patient-year and a cumulative incidence proportion of 58.9%. Patients self-reported 841 exacerbations (incidence rate, 0.75 ± 1.01; incidence proportion, 59.7%). The sensitivity and specificity of self-reports were 84% and 76%, respectively, those of single-physician chart review were between 89% and 96% and 87% and 99%, respectively. The multinomial regression model and bootstrap selection showed that having experienced more exacerbations was the only factor consistently associated with underreporting and overreporting of exacerbations (underreporters: relative risk ratio [RRR], 2.16; 95% CI, 1.76-2.65 and overreporters: RRR, 1.67; 95% CI, 1.39-2.00). Patient 6-month recall of exacerbation events are inaccurate. This may lead to inaccurate estimates of incidence measures and underestimation of treatment effects. The use of multiple data sources combined with event adjudication could substantially reduce sample size requirements and possibly cost of studies. www.ClinicalTrials.gov, NCT00706602. Copyright © 2016 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.
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Help-Seeking in People with Exceptional Experiences: Results from a General Population Sample
Landolt, Karin; Wittwer, Amrei; Wyss, Thomas; Unterassner, Lui; Fach, Wolfgang; Krummenacher, Peter; Brugger, Peter; Haker, Helene; Kawohl, Wolfram; Schubiger, Pius August; Folkers, Gerd; Rössler, Wulf
2014-01-01
Background: Exceptional experiences (EE) are experiences that deviate from ordinary experiences, for example precognition, supernatural appearances, or déjà vues. In spite of the high frequency of EE in the general population, little is known about their effect on mental health and about the way people cope with EE. This study aimed to assess the quality and quantity of EE in persons from the Swiss general population, to identify the predictors of their help-seeking, and to determine how many of them approach the mental health system. Methods: An on-line survey was used to evaluate a quota sample of 1580 persons representing the Swiss general population with respect to gender, age, and level of education. Multinomial logistic regression was applied to integrate help-seeking, self-reported mental disorder, and other variables in a statistical model designed to identify predictors of help-seeking in persons with EE. Results: Almost all participants (91%) experienced at least one EE. Generally, help-seeking was more frequent when the EE were of negative valence. Help-seeking because of EE was less frequent in persons without a self-reported mental disorder (8.6%) than in persons with a disorder (35.1%) (OR = 5.7). Even when frequency and attributes of EE were controlled for, people without a disorder sought four times less often help because of EE than expected. Persons with a self-reported diagnosis of mental disorder preferred seeing a mental health professional. Multinomial regression revealed a preference for healers in women with less education, who described themselves as believing and also having had more impressive EE. Conclusion: Persons with EE who do not indicate a mental disorder less often sought help because of EE than persons who indicated a mental disorder. We attribute this imbalance to a high inhibition threshold to seek professional help. Moreover, especially less educated women did not approach the mental health care system as often as other persons with EE, but preferred seeing a healer. PMID:24904915
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Association of childhood abuse with homeless women's social networks.
Green, Harold D; Tucker, Joan S; Wenzel, Suzanne L; Golinelli, Daniela; Kennedy, David P; Ryan, Gery W; Zhou, Annie J
2012-01-01
Childhood abuse has been linked to negative sequelae for women later in life including drug and alcohol use and violence as victim or perpetrator and may also affect the development of women's social networks. Childhood abuse is prevalent among at-risk populations of women (such as the homeless) and thus may have a stronger impact on their social networks. We conducted a study to: (a) develop a typology of sheltered homeless women's social networks; (b) determine whether childhood abuse was associated with the social networks of sheltered homeless women; and (c) determine whether those associations remained after accounting for past-year substance abuse and recent intimate partner abuse. A probability sample of 428 homeless women from temporary shelter settings in Los Angeles County completed a personal network survey that provided respondent information as well as information about their network members' demographics and level of interaction with each other. Cluster analyses identified groups of women who shared specific social network characteristics. Multinomial logistic regressions revealed variables associated with group membership. We identified three groups of women with differing social network characteristics: low-risk networks, densely connected risky networks (dense, risky), and sparsely connected risky networks (sparse, risky). Multinomial logistic regressions indicated that membership in the sparse, risky network group, when compared to the low-risk group, was associated with history of childhood physical abuse (but not sexual or emotional abuse). Recent drug abuse was associated with membership in both risky network groups; however, the association of childhood physical abuse with sparse, risky network group membership remained. Although these findings support theories proposing that the experience of childhood abuse can shape women's social networks, they suggest that it may be childhood physical abuse that has the most impact among homeless women. The effects of childhood physical abuse should be more actively investigated in clinical settings, especially those frequented by homeless women, particularly with respect to the formation of social networks in social contexts that may expose these women to greater risks. Copyright © 2012. Published by Elsevier Ltd.
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NASA Astrophysics Data System (ADS)
Duffy, P.; Keller, M.; Longo, M.; Morton, D. C.; dos-Santos, M. N.; Pinagé, E. R.
2017-12-01
There is an urgent need to quantify the effects of land use and land cover change on carbon stocks in tropical forests to support REDD+ policies and improve characterization of global carbon budgets. This need is underscored by the fact that the variability in forest biomass estimates from global forest carbon maps is artificially low relative to estimates generated from forest inventory and high-resolution airborne lidar data. Both deforestation and degradation processes (e.g. logging, fire, and fragmentation) affect carbon fluxes at varying spatial and temporal scales. While the spatial extent and impact of deforestation has been relatively well characterized, the quantification of degradation processes is still poorly constrained. In the Brazilian Amazon, the largest source of uncertainty in CO2 emissions estimates is data on changes in tropical forest carbon stocks through time, followed closely by incomplete information on the carbon losses from forest degradation. In this work, we present a method for classifying the degradation status of tropical forests using higher order moments (skewness and kurtosis) of lidar return distributions aggregated at grids with resolution ranging from 50 m to 250 m. Across multiple spatial resolutions, we quantify the strength of the functional relationship between the lidar returns and the classification based on historical time series of Landsat imagery. Our results show that the higher order moments of the lidar return distributions provide sufficient information to build multinomial models that accurately classify the landscape into intact, logged, and burned forests. Model fit improved with coarser spatial resolution with Kappa statistics of 0.70 at 50 m, and 0.77 at 250 m. In addition, multi-class AUC was estimated as 0.87 at 50 m, and 0.95 at 250 m. This classification provides important information regarding the applicability of the use of lidar data for regional monitoring of recent logging, as well as the trajectory of the carbon budget. Differentiating between the biomass changes associated with deforestation and degradation processes is critical for accurate accounting of disturbance impacts on carbon cycling within the Brazilian Amazon and global tropical forests.
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Exploratory Analysis of Survey Data for Understanding Adoption of Novel Aerospace Systems
NASA Astrophysics Data System (ADS)
Reddy, Lauren M.
In order to meet the increasing demand for manned and unmanned flight, the air transportation system must constantly evolve. As new technologies or operational procedures are conceived, we must determine their effect on humans in the system. In this research, we introduce a strategy to assess how individuals or organizations would respond to a novel aerospace system. We employ the most appropriate and sophisticated exploratory analysis techniques on the survey data to generate insight and identify significant variables. We employ three different methods for eliciting views from individuals or organizations who are affected by a system: an opinion survey, a stated preference survey, and structured interviews. We conduct an opinion survey of both the general public and stakeholders in the unmanned aircraft industry to assess their knowledge, attitude, and practices regarding unmanned aircraft. We complete a statistical analysis of the multiple-choice questions using multinomial logit and multivariate probit models and conduct qualitative analysis on free-text questions. We next present a stated preference survey of the general public on the use of an unmanned aircraft package delivery service. We complete a statistical analysis of the questions using multinomial logit, ordered probit, linear regression, and negative binomial models. Finally, we discuss structured interviews conducted on stakeholders from ANSPs and airlines operating in the North Atlantic. We describe how these groups may choose to adopt a new technology (space-based ADS-B) or operational procedure (in-trail procedures). We discuss similarities and differences between the stakeholders groups, the benefits and costs of in-trail procedures and space-based ADS-B as reported by the stakeholders, and interdependencies between the groups interviewed. To demonstrate the value of the data we generated, we explore how the findings from the surveys can be used to better characterize uncertainty in the cost-benefit analysis of aerospace systems. We demonstrate how the findings from the opinion and stated preference surveys can be infused into the cost-benefit analysis of an unmanned aircraft delivery system. We also demonstrate how to apply the findings from the interviews to characterize uncertainty in the estimation of the benefits of space-based ADS-B.
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Sosa-Rubi, Sandra G.; Galárraga, Omar
2009-01-01
Objective We evaluated the impact of Seguro Popular (SP), a program introduced in 2001 in Mexico primarily to finance health care for the poor. We focused on the effect of household enrollment in SP on pregnant women’s access to obstetrical services, an important outcome measure of both maternal and infant health. Data We relied upon data from the cross-sectional 2006 National Health and Nutrition Survey (ENSANUT) in Mexico. We analyzed the responses of 3,890 women who delivered babies during 2001–2006 and whose households lacked employer-based health care coverage. Methods We formulated a multinomial probit model that distinguished between three mutually exclusive sites for delivering a baby: a health unit specifically accredited by SP; a non-SP-accredited clinic run by the Department of Health (Secretaría de Salud, or SSA); and private obstetrical care. Our model accounted for the endogeneity of the household’s binary decision to enroll in the SP program. Results Women in households that participated in the SP program had a much stronger preference for having a baby in a SP-sponsored unit rather than paying out of pocket for a private delivery. At the same time, participation in SP was associated with a stronger preference for delivering in the private sector rather than at a state-run SSA clinic. On balance, the Seguro Popular program reduced pregnant women’s attendance at an SSA clinic much more than it reduced the probability of delivering a baby in the private sector. The quantitative impact of the SP program varied with the woman’s education and health, as well as the assets and location (rural versus urban) of the household. Conclusions The SP program had a robust, significantly positive impact on access to obstetrical services. Our finding that women enrolled in SP switched from non-SP state-run facilities, rather than from out-of-pocket private services, is important for public policy and requires further exploration. PMID:18824268
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Thompson, Michelle E; Nowakowski, A Justin; Donnelly, Maureen A
2016-04-01
Habitat loss and degradation are primary threats to amphibians and reptiles, but the relative effects of common land uses on assemblages and the mechanisms that underlie faunal responses are poorly studied. We reviewed the effects of four prevalent types of habitat alteration (urbanization, agriculture, livestock grazing, and silviculture) on amphibian and reptile species richness and abundance by summarizing reported responses in the literature and by estimating effect sizes across studies for species richness in each land-use type. We then used a multinomial model to classify species as natural habitat specialists, generalists, and disturbed habitat specialists and examined variation in effect sizes for each land-use type according to habitat specialization categories. There were mixed conclusions from individual studies, some reporting negative, neutral, or positive effects of land use on species richness and total abundance. A large proportion of studies reported species-specific effects of individual species abundance. However, in our analysis of effect sizes, we found a general trend of negative effects of land use on species richness. We also demonstrate that habitat associations of common species and species turnover can explain variation in the effect of land use on herpetofauna. Our review highlights the pervasive negative effects of common land uses on amphibians and reptiles, the importance of identifying groups vulnerable to land-use change (e.g., forest-associated species) in conservation studies, and the potential influence of disturbance-associated species on whole assemblage analyses. © 2015 Society for Conservation Biology.
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Liu, Xin; Hong, Xiumei; Tsai, Hui-Ju; Mestan, Karen K.; Shi, Min; Kefi, Amira; Hao, Ke; Chen, Qi; Wang, Guoying; Caruso, Deanna; Geng, Hua; Gao, Yufeng; He, Jianlin; Kumar, Rajesh; Wang, Hongjian; Yu, Yunxian; Bartell, Tami; Tan, Xiao-Di; Schleimer, Robert P.; Weeks, Daniel E.; Pongracic, Jacqueline A.; Wang, Xiaobin
2018-01-01
Abstract Previous genetic studies of food allergy (FA) have mainly focused on inherited genotypic effects. The role of parental genotypic effects remains largely unexplored. Leveraging existing genome-wide association study (GWAS) data generated from the Chicago Food Allergy Study, we examined maternal genotypic and parent-of-origin (PO) effects using multinomial likelihood ratio tests in 588 complete and incomplete Caucasian FA trios. We identified 1 single nucleotide polymorphism with significant (P < 5×10−8) maternal effect on any FA (rs4235235), which is located in a noncoding RNA (LOC101927947) with unknown function. We also identified 3 suggestive (P < 5×10−7) loci with maternal genetic effects: 1 for any FA (rs976078, in a gene desert region on 13q31.1) and 2 for egg allergy (rs1343795 and rs4572450, in the ZNF652 gene, where genetic variants have been associated with atopic dermatitis). Three suggestive loci with PO effect were observed: 1 for peanut allergy (rs4896888 in the ADGB gene) and 2 for any FA in boys only (rs1036504 and rs2917750 in the IQCE gene). Findings from this family-based GWAS of FA provided some preliminary evidence on maternal genotypic or PO effects on FA. Additional family-based studies are needed to confirm our findings and gain new insight into maternal and paternal genetic contribution to FA. PMID:29489655
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Parker, Pete; Thapa, Brijesh; Jacob, Aerin
2015-12-01
To alleviate poverty and enhance conservation in resource dependent communities, managers must identify existing livelihood strategies and the associated factors that impede household access to livelihood assets. Researchers increasingly advocate reallocating management power from exclusionary central institutions to a decentralized system of management based on local and inclusive participation. However, it is yet to be shown if decentralizing conservation leads to diversified livelihoods within a protected area. The purpose of this study was to identify and assess factors affecting household livelihood diversification within Nepal's Kanchenjunga Conservation Area Project, the first protected area in Asia to decentralize conservation. We randomly surveyed 25% of Kanchenjunga households to assess household socioeconomic and demographic characteristics and access to livelihood assets. We used a cluster analysis with the ten most common income generating activities (both on- and off-farm) to group the strategies households use to diversify livelihoods, and a multinomial logistic regression to identify predictors of livelihood diversification. We found four distinct groups of household livelihood strategies with a range of diversification that directly corresponded to household income. The predictors of livelihood diversification were more related to pre-existing socioeconomic and demographic factors (e.g., more landholdings and livestock, fewer dependents, receiving remittances) than activities sponsored by decentralizing conservation (e.g., microcredit, training, education, interaction with project staff). Taken together, our findings indicate that without direct policies to target marginalized groups, decentralized conservation in Kanchenjunga will continue to exclude marginalized groups, limiting a household's ability to diversify their livelihood and perpetuating their dependence on natural resources. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Park, Jinsung; Suh, Beomseok; Lee, Myung Shin; Woo, Seung Hyo; Shin, Dong Wook
2016-12-01
Despite high prevalence of upper urinary tract calculi (UUTC), there are few studies regarding patterns of care in Asian populations. We investigated treatment patterns and time trends in patients with newly diagnosed UUTC in Korea using the National Health Insurance database that includes de-identified claims from a random 2% sample of the entire population (> 1 million people). A total of 14,282 patients who received active treatments, including shock wave lithotripsy (SWL), ureteroscopic surgery (URS), percutaneous nephrolithotomy (PNL), and uretero/pyelolithotomy (UPL), for newly diagnosed UUTC between 2003 and 2013 were included. The number of primary and all treated cases of UUTC significantly (43% and 103.3%, respectively) increased over the 10-year period. While patients undergoing SWL, URS, PNL, and UPL as primary treatment increased by 43.7%, 31.9%, 87.5%, and 0%, respectively, the relative proportion undergoing each treatment remained constant over the 10 years (SWL > 90%, URS 4.5% to 7.8%, PNL 0.4% to 1.0%, and UPL < 0.4%, respectively). Multinomial logistic regression analysis showed that age > 40 years (compared to age < 30 years) was significantly associated with URS, PNL, and UPL, rather than SWL, while patients living in urban or suburban/rural areas (compared to metropolitan) were significantly less likely to undergo URS and PNL. In summary, the majority of Korean patients underwent SWL as primary treatment for UUTC, and the predominant use of SWL remained steady over a 10-year period in Korea. Our results will be valuable in examining treatment patterns and time trends in Korean UUTC patients.
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Li, Y.; Graubard, B. I.; Huang, P.; Gastwirth, J. L.
2015-01-01
Determining the extent of a disparity, if any, between groups of people, for example, race or gender, is of interest in many fields, including public health for medical treatment and prevention of disease. An observed difference in the mean outcome between an advantaged group (AG) and disadvantaged group (DG) can be due to differences in the distribution of relevant covariates. The Peters–Belson (PB) method fits a regression model with covariates to the AG to predict, for each DG member, their outcome measure as if they had been from the AG. The difference between the mean predicted and the mean observed outcomes of DG members is the (unexplained) disparity of interest. We focus on applying the PB method to estimate the disparity based on binary/multinomial/proportional odds logistic regression models using data collected from complex surveys with more than one DG. Estimators of the unexplained disparity, an analytic variance–covariance estimator that is based on the Taylor linearization variance–covariance estimation method, as well as a Wald test for testing a joint null hypothesis of zero for unexplained disparities between two or more minority groups and a majority group, are provided. Simulation studies with data selected from simple random sampling and cluster sampling, as well as the analyses of disparity in body mass index in the National Health and Nutrition Examination Survey 1999–2004, are conducted. Empirical results indicate that the Taylor linearization variance–covariance estimation is accurate and that the proposed Wald test maintains the nominal level. PMID:25382235
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Hyland, Philip; Murphy, Jamie; Shevlin, Mark; Vallières, Frédérique; McElroy, Eoin; Elklit, Ask; Christoffersen, Mogens; Cloitre, Marylène
2017-06-01
The World Health Organization's 11th revision to the International Classification of Diseases manual (ICD-11) will differentiate between two stress-related disorders: PTSD and Complex PTSD (CPTSD). ICD-11 proposals suggest that trauma exposure which is prolonged and/or repeated, or consists of multiple forms, that also occurs under circumstances where escape from the trauma is difficult or impossible (e.g., childhood abuse) will confer greater risk for CPTSD as compared to PTSD. The primary objective of the current study was to provide an empirical assessment of this proposal. A stratified, random probability sample of a Danish birth cohort (aged 24) was interviewed by the Danish National Centre for Social Research (N = 2980) in 2008-2009. Data from this interview were used to generate an ICD-11 symptom-based classification of PTSD and CPTSD. The majority of the sample (87.1%) experienced at least one of eight traumatic events spanning childhood and early adulthood. There was some indication that being female increased the risk for both PTSD and CPTSD classification. Multinomial logistic regression results found that childhood sexual abuse (OR = 4.98) and unemployment status (OR = 4.20) significantly increased risk of CPTSD classification as compared to PTSD. A dose-response relationship was observed between exposure to multiple forms of childhood interpersonal trauma and risk of CPTSD classification, as compared to PTSD. Results provide empirical support for the ICD-11 proposals that childhood interpersonal traumatic exposure increases risk of CPTSD symptom development.
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Anderson, RaeAnn E; Bonar, Erin E; Walton, Maureen A; Goldstick, Jason E; Rauch, Sheila A M; Epstein-Ngo, Quyen M; Chermack, Stephen T
2017-07-01
This study examined patterns of violence victimization and aggression in both intimate partner and nonpartner relationships among U.S. military veterans using latent profile analysis to identify subtypes of violence involvement. Participants were 839 substance use treatment-seeking veterans (93% male) from a large Veterans Affairs Medical Center who completed screening measures for a randomized controlled trial. Past-year violence involvement, including both intimate partner violence (IPV) and nonpartner violence (NPV), was common in the sample, although NPV occurred at somewhat higher rates. When we included either IPV or NPV aggression or victimization, more than 40% reported involvement with physical violence, 30% with violence involving injury, and 86% with psychological aggression. Latent profile analysis including both aggression and victimization in partner and nonpartner relationships indicated a four-profile solution: no/low violence (NLV; n = 377), predominantly IPV (n = 219), predominantly NPV (n = 134), and high general violence (HGV; n = 109). Multinomial logistic regression analyses revealed that, compared with the NLV group, the remaining three groups differed in age, cocaine use, posttraumatic stress disorder (PTSD) symptoms, and legal involvement. Legal issues appeared to differentiate the profiles most, with the predominantly NPV and HGV profiles reporting more instances of driving under the influence and the HGV profile reporting legal problems related to aggression. IPV and NPV are fairly common among veterans seeking substance use treatment. The clinical characteristics of violence profiles indicate that cocaine use, PTSD symptoms, and legal involvement are treatment needs that vary with violence profile and may be useful for clinical decision making.
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Risk of falls in older people during fast-walking--the TASCOG study.
Callisaya, M L; Blizzard, L; McGinley, J L; Srikanth, V K
2012-07-01
To investigate the relationship between fast-walking and falls in older people. Individuals aged 60-86 years were randomly selected from the electoral roll (n=176). Gait speed, step length, cadence and a walk ratio were recorded during preferred- and fast-walking using an instrumented walkway. Falls were recorded prospectively over 12 months. Log multinomial regression was used to estimate the relative risk of single and multiple falls associated with gait variables during fast-walking and change between preferred- and fast-walking. Covariates included age, sex, mood, physical activity, sensorimotor and cognitive measures. The risk of multiple falls was increased for those with a smaller walk ratio (shorter steps, faster cadence) during fast-walking (RR 0.92, CI 0.87, 0.97) and greater reduction in the walk ratio (smaller increase in step length, larger increase in cadence) when changing to fast-walking (RR 0.73, CI 0.63, 0.85). These gait patterns were associated with poorer physiological and cognitive function (p<0.05). A higher risk of multiple falls was also seen for those in the fastest quarter of gait speed (p=0.01) at fast-walking. A trend for better reaction time, balance, memory and physical activity for higher categories of gait speed was stronger for fallers than non-fallers (p<0.05). Tests of fast-walking may be useful in identifying older individuals at risk of multiple falls. There may be two distinct groups at risk--the frail person with short shuffling steps, and the healthy person exposed to greater risk. Copyright © 2012 Elsevier B.V. All rights reserved.
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Exavery, Amon; Kanté, Almamy Malick; Njozi, Mustafa; Tani, Kassimu; Doctor, Henry V; Hingora, Ahmed; Phillips, James F
2014-08-08
While unintended pregnancies pose a serious threat to the health and well-being of families globally, characteristics of Tanzanian women who conceive unintentionally are rarely documented. This analysis identifies factors associated with unintended pregnancies-both mistimed and unwanted-in three rural districts of Tanzania. A cross-sectional survey of 2,183 random households was conducted in three Tanzanian districts of Rufiji, Kilombero, and Ulanga in 2011 to assess women's health behavior and service utilization patterns. These households produced 3,127 women age 15+ years from which 2,199 gravid women aged 15-49 were selected for the current analysis. Unintended pregnancies were identified as either mistimed (wanted later) or unwanted (not wanted at all). Correlates of mistimed, and unwanted pregnancies were identified through Chi-squared tests to assess associations and multinomial logistic regression for multivariate analysis. Mean age of the participants was 32.1 years. While 54.1% of the participants reported that their most recent pregnancy was intended, 32.5% indicated their most recent pregnancy as mistimed and 13.4% as unwanted. Multivariate analysis revealed that young age (<20 years), and single marital status were significant predictors of both mistimed and unwanted pregnancies. Lack of inter-partner communication about family planning increased the risk of mistimed pregnancy significantly, and multi-gravidity was shown to significantly increase the risk of unwanted pregnancy. About one half of women in Rufiji, Kilombero, and Ulanga districts of Tanzania conceive unintentionally. Women, especially the most vulnerable should be empowered to avoid pregnancy at their own will and discretion.
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Leppänen, Marja; Aittasalo, Minna; Raitanen, Jani; Kinnunen, Tarja I; Kujala, Urho M; Luoto, Riitta
2014-11-01
The aim of this study was to examine the predictors of change in intensity-specific leisure-time physical activity (LTPA) during pregnancy, and the perceived support and barriers of LTPA in Finnish pregnant women at increased risk of gestational diabetes. The study population consisted of 399 pregnant women who participated in a randomized controlled trial aiming to prevent gestational diabetes. Evaluation of LTPA was based on a self-report at baseline, 26-28, and 36-37 weeks' gestation. Data on predictors of change, perceived support and barriers were collected with questionnaires and from the maternity cards. Multinomial logistic regression was used to assess associations between the variables. The average weekly minutes of light-intensity LTPA were 179 at baseline, 161 at 26-28 weeks' gestation, and 179 at 36-37 weeks' gestation. The corresponding minutes of moderate-to-vigorous-intensity LTPA were 187, 133 and 99. At 26-28 weeks' gestation, the strongest predictors for light-intensity LTPA were meeting the PA recommendations prior to pregnancy, having polytechnic education and working part-time, while having a physically active spouse prior to pregnancy was the strongest predictor for moderate-to-vigorous-intensity LTPA. The people and/or factors that encouraged women to LTPA the most were the spouse, a child, other family members and weather, whereas tiredness, nausea, perceived health, work and lack of time restricted their LTPA the most. The strongest predictors for maintaining LTPA during pregnancy were pre-pregnancy LTPA, education, working part-time and a spouse's LTPA. Most common barriers were perceived health, work and lack of time.
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Using choice-based conjoint to determine the relative importance of dental benefit plan attributes.
Cunningham, M A; Gaeth, G J; Juang, C; Chakraborty, G
1999-05-01
The purpose of this study was to use conjoint analysis to determine the importance of specific dental benefit plan features for University of Iowa (UI) staff and to build a model to predict enrollment. From a random sample of 2000 UI staff, 40 percent responded (N = 773). The survey instrument was developed using seven attributes (five dental benefit plan features and two facility characteristics) each offered at three levels (e.g., premium = $20, $15, $10/month). Pilot testing was used to find a realistic range of plan options. Twenty-seven hypothetical dental benefit plans were developed using fractional factorial combinations of the three levels for each of the seven attributes. For all of the hypothetical plans, dental care was to be provided in the UI predoctoral dental clinic. Plan profiles were arranged four per page by combining the existing plan with three hypothetical plans, for a total of nine pages. Respondents' task was to select one plan from each set of four. A regression-like statistical model (Multinomial Logit) was used to estimate importance of each attribute and each attribute level. Relative importance (and coefficients) for each of the seven attributes are as follows: maximum annual benefit (.98), orthodontic coverage (.72), routine restorative (.70), major restorative (.67), time to complete treatment (.61), clinic hours of operation (.47), premium (.18). For each attribute, relative importance of each of three levels will also be presented. These coefficients for each level are used to predict enrollment for plans with specific combinations of the dental benefit plan features.
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Richer, Isabelle; Lee, Jennifer E C; Born, Jennifer
2016-04-07
Heavy drinking increases the risk of injury, adverse physical and mental health outcomes, and loss of productivity. Nonetheless, patterns of alcohol use and related symptomatology among military personnel remain poorly understood. A latent class analysis (LCA) was used to explore the presence of subgroups of alcohol users among Canadian Armed Forces (CAF) Regular Forces members. Correlates of empirically derived subgroups were further explored. Analyses were performed on a subsample of alcohol users who participated in a 2008/09 cross-sectional survey of a stratified random sample of currently serving CAF Regular Force members (N = 1980). Multinomial logistic regression models were conducted to verify physical and mental health differences across subgroups of alcohol users. All analyses were adjusted for complex survey design. A 4-class solution was considered the best fit for the data. Subgroups were labeled as follows: Class 1 - Infrequent drinkers (27.2%); Class 2 - Moderate drinkers (41.5%); Class 3 - Regular binge drinkers with minimal problems (14.8%); and Class 4 - Problem drinkers (16.6%). Significant differences by age, sex, marital status, element, rank, recent serious injuries, chronic conditions, psychological distress, posttraumatic stress disorder, and depression symptoms were found across the subgroups. Problem drinkers demonstrated the most degraded physical and mental health. Findings highlight the heterogeneity of alcohol users and heavy drinkers among CAF members and the need for tailored interventions addressing high-risk alcohol use. Results have the potential to inform prevention strategies and screening efforts. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
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From margarine to butter: predictors of changing bread spread in an 11-year population follow-up.
Prättälä, Ritva; Levälahti, Esko; Lallukka, Tea; Männistö, Satu; Paalanen, Laura; Raulio, Susanna; Roos, Eva; Suominen, Sakari; Mäki-Opas, Tomi
2016-06-01
Finland is known for a sharp decrease in the intake of saturated fat and cardiovascular mortality. Since 2000, however, the consumption of butter-containing spreads - an important source of saturated fats - has increased. We examined social and health-related predictors of the increase among Finnish men and women. An 11-year population follow-up. A representative random sample of adult Finns, invited to a health survey in 2000. Altogether 5414 persons aged 30-64 years at baseline in 2000 were re-invited in 2011. Of men 1529 (59 %) and of women 1853 (66 %) answered the questions on bread spreads at both time points. Respondents reported the use of bread spreads by choosing one of the following alternatives: no fat, soft margarine, butter-vegetable oil mixture and butter, which were later categorized into margarine/no spread and butter/butter-vegetable oil mixture (= butter). The predictors included gender, age, marital status, education, employment status, place of residence, health behaviours, BMI and health. Multinomial regression models were fitted. Of the 2582 baseline margarine/no spread users, 24.6% shifted to butter. Only a few of the baseline sociodemographic or health-related determinants predicted the change. Finnish women were more likely to change to butter than men. Living with a spouse predicted the change among men. The change from margarine to butter between 2000 and 2011 seemed not to be a matter of compliance with official nutrition recommendations. Further longitudinal studies on social, behavioural and motivational predictors of dietary changes are needed.
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Tessier, Sophie; Traissac, Pierre; Bricas, Nicolas; Maire, Bernard; Eymard-Duvernay, Sabrina; El Ati, Jalila; Delpeuch, Francis
2010-09-01
In the context of the nutrition transition and associated changes in the food retail sector, to examine the socio-economic characteristics and motivations of shoppers using different retail formats (large supermarkets (LSM), medium-sized supermarkets (MSM) or traditional outlets) in Tunisia. Cross-sectional survey (2006). Socio-economic status, type of food retailer and motivations data were collected during house visits. Associations between socio-economic factors and type of retailer were assessed by multinomial regression; correspondence analysis was used to analyse declared motivations. Peri-urban area around Tunis, Tunisia, North Africa. Clustered random sample of 724 households. One-third of the households used LSM, two-thirds used either type of supermarket, but less than 5 % used supermarkets only. Those who shopped for food at supermarkets were of higher socio-economic status; those who used LSM were much wealthier, more often had a steady income or owned a credit card, while MSM users were more urban and had a higher level of education. Most households still frequently used traditional outlets, mostly their neighbourhood grocer. Reasons given for shopping at the different retailers were most markedly leisure for LSM, while for the neighbourhood grocer the reasons were fidelity, proximity and availability of credit (the latter even more for lower-income customers). The results pertain to the transition in food shopping practices in a south Mediterranean country; they should be considered in the context of growing inequalities in health linked to the nutritional transition, as they differentiate use and motivations for the choice of supermarkets v. traditional food retailers according to socio-economic status.
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Random effects coefficient of determination for mixed and meta-analysis models
Demidenko, Eugene; Sargent, James; Onega, Tracy
2011-01-01
The key feature of a mixed model is the presence of random effects. We have developed a coefficient, called the random effects coefficient of determination, Rr2, that estimates the proportion of the conditional variance of the dependent variable explained by random effects. This coefficient takes values from 0 to 1 and indicates how strong the random effects are. The difference from the earlier suggested fixed effects coefficient of determination is emphasized. If Rr2 is close to 0, there is weak support for random effects in the model because the reduction of the variance of the dependent variable due to random effects is small; consequently, random effects may be ignored and the model simplifies to standard linear regression. The value of Rr2 apart from 0 indicates the evidence of the variance reduction in support of the mixed model. If random effects coefficient of determination is close to 1 the variance of random effects is very large and random effects turn into free fixed effects—the model can be estimated using the dummy variable approach. We derive explicit formulas for Rr2 in three special cases: the random intercept model, the growth curve model, and meta-analysis model. Theoretical results are illustrated with three mixed model examples: (1) travel time to the nearest cancer center for women with breast cancer in the U.S., (2) cumulative time watching alcohol related scenes in movies among young U.S. teens, as a risk factor for early drinking onset, and (3) the classic example of the meta-analysis model for combination of 13 studies on tuberculosis vaccine. PMID:23750070
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Frailty syndrome and socioeconomic and health characteristics among older adults
de Freitas Corrêa, Thais Aline; Dias, Flavia Aparecida; dos Santos Ferreira, Pollyana Cristina; Sousa Pegorari, Maycon
2017-01-01
Abstract Objective: To investigate the association of frailty syndrome with socioeconomic and health variables among older adults. Methods: This is a cross-sectional, observational and analytical household research conducted with a sample of 1,609 urban elderly. We used: semi-structured questionnaire, scales (Katz, Lawton and shortened version of Geriatric Depression Scale) and Fragility Phenotype proposed by Fried. Descriptive analysis was performed along with a bivariate and multinomial logistic regression model (p <0.05). Results: The prevalence of pre-frailty condition was 52.0% and the fragility corresponded to 13.6%. Pre-frailty and frailty associated factors were, respectively: age range between 70-79 years and ≥80 years; one to four morbidities and five or more morbidities categories; functional disability for basic and instrumental activities of daily life and depression indicative; whilst lack of a companion or income and female gender were only associated to pre-frailty. Conclusion: The conditions of pre-frailty and frailty levels were elevated with negative effects on the health of the elderly. PMID:29213155
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Smoking intensity among male factory workers in Kunming, China.
Cheng, Kai-Wen; Tsoh, Janice Y; Cui, Wenlong; Li, Xiaoliang; Kohrman, Matthew
2015-03-01
This study investigated the intensity of cigarette consumption and its correlates in China among urban male factory workers, a cohort especially vulnerable to tobacco exposure, one that appears to have benefitted little from recent public health efforts to reduce smoking rates. Data were collected from men working in factories of Kunming city, Yunnan, China, who are current daily smokers (N = 490). A multinomial logistic regression was conducted to examine the factors in association with smoking intensity in light, moderate, and heavy levels. Light smoking correlated with social smoking, smoking the first cigarette later in the day, self-reported health condition, and quit intention. Heavy smoking was associated with purchase of lower priced cigarettes, difficulty refraining from smoking, and prehypertensive blood pressure. Even in regions where smoking is highly prevalent, even among cohorts who smoke heavily, variation exists in how cigarettes are consumed. Analyses of this consumption, with special consideration given to smoking intensity and its correlates, can help guide tobacco-control strategists in developing more effective interventions. © 2013 APJPH.
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Spence, Naomi J.; Henderson, Kathryn A.; Elder, Glen H.
2013-01-01
This paper investigates the link between adolescent family structure and the likelihood of military enlistment in young adulthood, as compared to alternative post-high school activities. We use data from the National Longitudinal Study of Adolescent Health and multinomial logistic regression analyses to compare the odds of military enlistment with college attendance or labor force involvement. We find that alternative family structures predict enlistment relative to college attendance. Living in a single-parent household during adolescence increased odds of military enlistment, but the effect is accounted for by socioeconomic status and early feelings of social isolation. Living with a stepparent or with neither biological parent more than doubles the odds of enlistment, independent of socioeconomic status, characteristics of parent-child relationships, or feelings of social isolation. Although college attendance is widely promoted as a valued post-high school activity, military service may offer a route to independence and a greater sense of belonging. PMID:24000268
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Discrimination, drugs, and alcohol among Latina/os in Brooklyn, New York: Differences by gender
Gee, Gilbert C.; Iguchi, Martin Y.; Ford, Chandra L.; Friedman, Samuel R.
2013-01-01
BACKGROUND Based on a stress-coping framework, the present study investigates the relationship between discrimination and substance use, and the moderating effects of gender. METHODS This cross-sectional study analyzes data from Latina/o young adults aged 18 to 25 (n=401) from Brooklyn, New York. Multinomial logistic regression was used to test the association between discrimination and substance use. RESULTS Discrimination was significantly associated with increased odds of substance use adjusting for covariates (e.g. age, education). Gender was a moderator. Discrimination was associated with increased risk of alcohol/marijuana and hard drug use among young Latina women. However, discrimination was associated with decreased risk of alcohol/marijuana use and increased risk of hard drug use among young Latino men. CONCLUSION These findings suggest that discrimination is generally associated with risk for substance use, but further that the outcomes vary by gender. Future research should explore gender-specific dimensions of discrimination and their associations with other outcomes. PMID:23481289
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Transitions between states of labor-force participation among older Israelis.
Achdut, Leah; Tur-Sinai, Aviad; Troitsky, Rita
2015-03-01
The study examines the labor-force behavior of Israelis at older ages, focusing on the determinants of the transitions between states of labor-force participation between 2005 and 2010. The study uses panel data from the first two waves of the SHARE-Israel longitudinal survey. A multinomial logit model is used to examine the impact of sociodemographic characteristics, health state, and economic resources on labor-force transitions of people aged 50-67. The results emphasize the role of age and poor health in "pushing" older people out of the labor force or "keeping" them there. Spouse's participation is found to encourage individuals to leave the labor force or to refrain from joining it. However, living with a participating spouse is negatively associated with staying out of the labor force, consistent with the dominance of the complementarity of leisure effect found in the literature. Wealth as an economic resource available to individuals for retirement is also found to encourage individuals to leave the labor force or to refrain from joining it.
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Irrigation water sources and irrigation application methods used by U.S. plant nursery producers
NASA Astrophysics Data System (ADS)
Paudel, Krishna P.; Pandit, Mahesh; Hinson, Roger
2016-02-01
We examine irrigation water sources and irrigation methods used by U.S. nursery plant producers using nested multinomial fractional regression models. We use data collected from the National Nursery Survey (2009) to identify effects of different firm and sales characteristics on the fraction of water sources and irrigation methods used. We find that regions, sales of plants types, farm income, and farm age have significant roles in what water source is used. Given the fraction of alternative water sources used, results indicated that use of computer, annual sales, region, and the number of IPM practices adopted play an important role in the choice of irrigation method. Based on the findings from this study, government can provide subsidies to nursery producers in water deficit regions to adopt drip irrigation method or use recycled water or combination of both. Additionally, encouraging farmers to adopt IPM may enhance the use of drip irrigation and recycled water in nursery plant production.
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Carr, Dawn C; King, Katherine; Matz-Costa, Christina
2015-04-01
Gaps in existing literature hinder our knowledge of how life stage-related identities (e.g., worker, parent, student, etc.) influence individuals' decisions about whether and how to get involved in community service. Interventions to increase volunteerism throughout the life course require a more nuanced understanding of this relationship. We use multinomial logistic models to analyze how life phase factors relate to involvement in different types of voluntary organizations across the adult life course in the Chicago Community Adult Health Study. Half of the adults did not volunteer. Those who did volunteer were categorized as charitable, youth-oriented, religious, civic, or multidomain volunteers. Age, employment, family structure, demographics, and self-rated health differentially predicted volunteering in specific domains. Findings from this study suggest that recruitment and retention efforts employed by different nonprofit organizations may be more effective if they take into consideration the life phase factors that enhance or detract from likelihood of engagement. © The Author(s) 2015.
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McBride, Orla; Adamson, Gary; Bunting, Brendan; McCann, Siobhan
2009-01-01
Research has highlighted the significant alcohol symptoms and mental health problems experienced by diagnostic orphans - individuals who experience 1-2 criteria of DSM-IV alcohol dependence but do not meet the criteria for a DSM-IV alcohol use disorder. This study used a sub-sample (n=34827) from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), and formed mutually exclusive groups to compare the self-report retrospective course of diagnostic orphans to individuals with DSM-IV abuse and dependence. Multinomial logistic regressions were conducted to examine the associations between the groups and a range of demographic and clinical variables. Collectively, the findings demonstrate that diagnostic orphans shared similar characteristics to the abuse and dependence groups, but appeared to experience specific comorbid mental health problems. Orphan status has the potential to be a persistent condition and may result in significant dysfunction. In conclusion, diagnostic orphans represent a distinct group that may benefit from cost-effective treatment or intervention, designed to prevent the escalation of alcohol symptoms.
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Reforming Access: Trends in Medicaid Enrollment for New Medicare Beneficiaries, 2008-2011.
Keohane, Laura M; Rahman, Momotazur; Mor, Vincent
2016-04-01
To evaluate whether aligning the Part D low-income subsidy and Medicaid program enrollment pathways in 2010 increased Medicaid participation among new Medicare beneficiaries. Medicare enrollment records for years 2007-2011. We used a multinomial logistic model with state fixed effects to examine the annual change in limited and full Medicaid enrollment among new Medicare beneficiaries for 2 years before and after the reforms (2008-2011). We identified new Medicare beneficiaries in the years 2008-2011 and their participation in Medicaid based on Medicare enrollment records. The percentage of beneficiaries enrolling in limited Medicaid at the start of Medicare coverage increased in 2010 by 0.3 percentage points for individuals aging into Medicare and by 1.3 percentage points for those qualifying due to disability (p < .001). There was no significant difference in the size of enrollment increases between states with and without concurrent limited Medicaid eligibility expansions. Our findings suggest that streamlining financial assistance programs may improve Medicare beneficiaries' access to benefits. © Health Research and Educational Trust.
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Hübner, Ronald; Volberg, Gregor
2005-06-01
This article presents and tests the authors' integration hypothesis of global/local processing, which proposes that at early stages of processing, the identities of global and local units of a hierarchical stimulus are represented separately from information about their respective levels and that, therefore, identity and level information have to be integrated at later stages. It further states that the cerebral hemispheres differ in their capacities for these binding processes. Three experiments are reported in which the integration hypothesis was tested. Participants had to identify a letter at a prespecified level with the viewing duration restricted by a mask. False reporting of the letter at the nontarget level was predicted to occur more often when the integration of identity and level could fail. This was the case. Moreover, visual-field effects occurred, as expected. Finally, a multinomial model was constructed and fitted to the data. ((c) 2005 APA, all rights reserved).
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Matzen, Laura E.; Taylor, Eric G.; Benjamin, Aaron S.
2010-01-01
It has been suggested that both familiarity and recollection contribute to the recognition decision process. In this paper, we leverage the form of false alarm rate functions—in which false-alarm rates describe an inverted U-shaped function as the time between study and test increases—to assess how these processes support retention of semantic and surface form information from previously studied words. We directly compare the maxima of these functions for lures that are semantically related and lures that are related by surface form to previously studied material. This analysis reveals a more rapid loss of access to surface form than to semantic information. To separate the contributions of item familiarity and reminding-induced recollection rejection to this effect, we use a simple multinomial process model; this analysis reveals that this loss of access reflects both a more rapid loss of familiarity and lower rates of recollection for surface form information. PMID:21240745
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Impact of Perceived Risk and Friend Influence on Alcohol and Marijuana Use Among Students.
Merianos, Ashley L; Rosen, Brittany L; Montgomery, LaTrice; Barry, Adam E; Smith, Matthew Lee
2017-12-01
We performed a secondary analysis of Adolescent Health Risk Behavior Survey data ( N = 937), examining associations between lifetime alcohol and marijuana use with intrapersonal (i.e., risk perceptions) and interpersonal (e.g., peer approval and behavior) factors. Multinomial and binary logistic regression analyses contend students reporting lifetime alcohol use-compared to students who had never used alcohol or marijuana-perceived lower alcohol risk ( p < .001), higher friend drinking approval ( p < .001), and greater friend drinking ( p = .003). Using both alcohol and marijuana in one's life was associated with being in public schools ( p = .010), higher grade levels ( p = .001), lower perceived alcohol ( p = .011) and marijuana use risk ( p = .003), higher friend approval of alcohol ( p < .001) and marijuana use ( p < .001), and believed more friends used alcohol ( p < .001). Compared to lifetime alcohol only, perceived friend academic performance decreased the risk of lifetime alcohol and marijuana use ( p = .043). Findings are beneficial to school nurses with students experiencing effects associated with substance use.
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Otiniano Verissimo, Angie Denisse; Grella, Christine E; Amaro, Hortensia; Gee, Gilbert C
2014-08-01
We examined the relationship between discrimination and substance use disorders among a diverse sample of Latinos. We also investigated whether the relationship between discrimination and substance use disorders varied by gender, nativity, and ethnicity. Our analyses focused on 6294 Latinos who participated in the National Epidemiologic Survey on Alcohol and Related Conditions from 2004 to 2005. We used multinomial logistic regression to examine the association between discrimination and substance use disorders. Discrimination was significantly associated with increased odds of alcohol and drug use disorders among Latinos. However, the relationship between discrimination and substance use disorders varied by gender, nativity, and ethnicity. Discrimination was associated with increased odds of alcohol and drug use disorders for certain groups, such as women, US-born Latinos, and Mexicans, but this relationship did not follow the same pattern for other subgroups. It is important to determine which subgroups among Latinos may be particularly vulnerable to the negative effects of discrimination to address their needs.
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Discrimination, drugs, and alcohol among Latina/os in Brooklyn, New York: differences by gender.
Otiniano Verissimo, Angie Denisse; Gee, Gilbert C; Iguchi, Martin Y; Ford, Chandra L; Friedman, Samuel R
2013-07-01
Based on a stress-coping framework, the present study investigates the relationship between discrimination and substance use, and the moderating effects of gender. This cross-sectional study analyzes data from Latina/o young adults aged 18-25 (N = 401) from Brooklyn, New York. Multinomial logistic regression was used to test the association between discrimination and substance use. Discrimination was significantly associated with increased odds of substance use adjusting for covariates (e.g. age, education). Gender was a moderator. Discrimination was associated with increased risk of alcohol/cannabis and hard drug use among young Latina women. However, discrimination was associated with decreased risk of alcohol/cannabis use and increased risk of hard drug use among young Latino men. These findings suggest that discrimination is generally associated with risk for substance use, but further that the outcomes vary by gender. Future research should explore gender-specific dimensions of discrimination and their associations with other outcomes. Copyright © 2013 Elsevier B.V. All rights reserved.
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Bennett, Misty M; Beehr, Terry A; Lepisto, Lawrence R
2016-09-01
Older employees are increasingly accepting bridge employment, which occurs when older workers take employment for pay after they retire from their main career. This study examined predictors of workers' decisions to engage in bridge employment versus full retirement and career employment. A national sample of 482 older people in the United States was surveyed regarding various work-related and nonwork related predictors of retirement decisions, and their retirement status was measured 5 years later. In bivariate analyses, both work-related variables (career goal achievement and experienced pressure to retire) and nonwork-related variables (psychological distress and traditional gender role orientation) predicted taking bridge employment, but in multinomial logistic regression, only nonwork variables had unique effects. Few predictors differentiated the bridge employed and fully retired groups. Nonwork variables were salient in making the decision to retire, and bridge employment may be conceptually more similar to full retirement than to career employment. © The Author(s) 2016.
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Neighbourhood food environments and obesity in southeast Louisiana.
Hutchinson, Paul L; Nicholas Bodor, J; Swalm, Chris M; Rice, Janet C; Rose, Donald
2012-07-01
Supermarkets might influence food choices, and more distal outcomes like obesity, by increasing the availability of healthy foods. However, recent evidence about their effects is ambiguous, perhaps because supermarkets also increase the availability of unhealthy options. We develop an alternative measure of food environment quality that characterizes urban neighborhoods by the relative amounts of healthy (e.g. fruits and vegetables) to unhealthy foods (e.g. energy-dense snacks). Using data from 307 food stores and 1243 telephone interviews with residents in urban southeastern Louisiana, we estimate a multilevel multinomial logistic model for overweight status. We find that higher quality food environments - but not food store types - decrease the risk of obesity (RR 0.474, 95% CI 0.269-0.835) and overweight (RR 0.532, 95% CI 0.312-0.907). The findings suggest a need to move beyond a sole consideration of food store types to a more nuanced view of the food environment when planning for change. Copyright © 2012 Elsevier Ltd. All rights reserved.
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1976-07-01
PURDUE UNIVERSITY DEPARTMENT OF STATISTICS DIVISION OF MATHEMATICAL SCIENCES ON SUBSET SELECTION PROCEDURES FOR POISSON PROCESSES AND SOME...Mathematical Sciences Mimeograph Series #457, July 1976 This research was supported by the Office of Naval Research under Contract NOOO14-75-C-0455 at Purdue...11 CON PC-111 riFIC-F ,A.F ANO ADDPFS Office of INaval ResearchJu#07 Washington, DC07 36AE 14~~~ rjCr; NF A ’ , A FAA D F 6 - I S it 9 i 1, - ,1 I
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Identifying the determinants of childhood immunization in the Philippines.
Bondy, Jennifer N; Thind, Amardeep; Koval, John J; Speechley, Kathy N
2009-01-01
A key method of reducing morbidity and mortality is childhood immunization, yet in 2003 only 69% of Filipino children received all suggested vaccinations. Data from the 2003 Philippines Demographic Health Survey were used to identify risk factors for non- and partial-immunization. Results of the multinomial logistic regression analyses indicate that mothers who have less education, and who have not attended the minimally-recommended four antenatal visits are less likely to have fully immunized children. To increase immunization coverage in the Philippines, knowledge transfer to mothers must improve.
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Heo, Moonseong; Meissner, Paul; Litwin, Alain H; Arnsten, Julia H; McKee, M Diane; Karasz, Alison; McKinley, Paula; Rehm, Colin D; Chambers, Earle C; Yeh, Ming-Chin; Wylie-Rosett, Judith
2017-01-01
Comparative effectiveness research trials in real-world settings may require participants to choose between preferred intervention options. A randomized clinical trial with parallel experimental and control arms is straightforward and regarded as a gold standard design, but by design it forces and anticipates the participants to comply with a randomly assigned intervention regardless of their preference. Therefore, the randomized clinical trial may impose impractical limitations when planning comparative effectiveness research trials. To accommodate participants' preference if they are expressed, and to maintain randomization, we propose an alternative design that allows participants' preference after randomization, which we call a "preference option randomized design (PORD)". In contrast to other preference designs, which ask whether or not participants consent to the assigned intervention after randomization, the crucial feature of preference option randomized design is its unique informed consent process before randomization. Specifically, the preference option randomized design consent process informs participants that they can opt out and switch to the other intervention only if after randomization they actively express the desire to do so. Participants who do not independently express explicit alternate preference or assent to the randomly assigned intervention are considered to not have an alternate preference. In sum, preference option randomized design intends to maximize retention, minimize possibility of forced assignment for any participants, and to maintain randomization by allowing participants with no or equal preference to represent random assignments. This design scheme enables to define five effects that are interconnected with each other through common design parameters-comparative, preference, selection, intent-to-treat, and overall/as-treated-to collectively guide decision making between interventions. Statistical power functions for testing all these effects are derived, and simulations verified the validity of the power functions under normal and binomial distributions.