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…

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.…

Modeling Polytomous Item Responses Using Simultaneously Estimated Multinomial Logistic Regression Models

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…

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…

Comparison of multinomial logistic regression and logistic regression: which is more efficient in allocating land use?

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.

Brief Report: Association of Myositis Autoantibodies, Clinical Features, and Environmental Exposures at Illness Onset With Disease Course in Juvenile Myositis.

PubMed

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.

Composite Linear Models | Division of Cancer Prevention

Cancer.gov

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

The Source of Adult Age Differences in Event-Based Prospective Memory: A Multinomial Modeling Approach

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…

Who Is Overeducated and Why? Probit and Dynamic Mixed Multinomial Logit Analyses of Vertical Mismatch in East and West Germany

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…

A Bayesian Multinomial Probit MODEL FOR THE ANALYSIS OF PANEL CHOICE DATA.

PubMed

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.

Parameter Estimation for the Dirichlet-Multinomial Distribution Using Supplementary Beta-Binomial Data.

DTIC Science & Technology

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-. ~. - - -- .~ 𔃾 4’.) ~a 4’ ., 𔃾. ’-4. .4.: .4~ I .4. ~J3iAf a,’ -a’ 4

Predicting longitudinal trajectories of health probabilities with random-effects multinomial logit regression.

PubMed

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.

Arsenic exposure and oral cavity lesions in Bangladesh.

PubMed

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.

Multinomial N-mixture models improve the applicability of electrofishing for developing population estimates of stream-dwelling Smallmouth Bass

USGS Publications Warehouse

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.

Quality and provider choice: a multinomial logit-least-squares model with selectivity.

PubMed Central

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

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.

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.

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.

Lateralization of temporal lobe epilepsy by multimodal multinomial hippocampal response-driven models.

PubMed

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.

Modeling the dynamics of urban growth using multinomial logistic regression: a case study of Jiayu County, Hubei Province, China

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.

Bivariate categorical data analysis using normal linear conditional multinomial probability model.

PubMed

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.

A practical method to test the validity of the standard Gumbel distribution in logit-based multinomial choice models of travel behavior

DOE PAGES

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

A practical method to test the validity of the standard Gumbel distribution in logit-based multinomial choice models of travel behavior

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

A measurement theory of illusory conjunctions.

PubMed

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.

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%.

Network-constrained group lasso for high-dimensional multinomial classification with application to cancer subtype prediction.

PubMed

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.

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.

A simplified conjoint recognition paradigm for the measurement of gist and verbatim memory.

PubMed

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.

Multinomial logistic regression modelling of obesity and overweight among primary school students in a rural area of Negeri Sembilan

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

Multinomial logistic regression modelling of obesity and overweight among primary school students in a rural area of Negeri Sembilan

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.

Extreme Sparse Multinomial Logistic Regression: A Fast and Robust Framework for Hyperspectral Image Classification

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.

Uncovering a latent multinomial: Analysis of mark-recapture data with misidentification

USGS Publications Warehouse

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.

Uncovering a Latent Multinomial: Analysis of Mark-Recapture Data with Misidentification

USGS Publications Warehouse

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.

Evaluating risk factors for endemic human Salmonella Enteritidis infections with different phage types in Ontario, Canada using multinomial logistic regression and a case-case study approach

PubMed Central

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

Comparing the efficiency of digital and conventional soil mapping to predict soil types in a semi-arid region in Iran

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.

Multinomial Bayesian learning for modeling classical and nonclassical receptive field properties.

PubMed

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.

Disentangling stereotype activation and stereotype application in the stereotype misperception task.

PubMed

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.

Prospective memory after moderate-to-severe traumatic brain injury: a multinomial modeling approach.

PubMed

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.

Landscape effects on diets of two canids in Northwestern Texas: A multinomial modeling approach

USGS Publications Warehouse

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.

Ordinal probability effect measures for group comparisons in multinomial cumulative link models.

PubMed

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.

Multinomial model and zero-inflated gamma model to study time spent on leisure time physical activity: an example of ELSA-Brasil.

PubMed

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.

Regression Models For Multivariate Count Data

PubMed Central

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

Regression Models For Multivariate Count Data.

PubMed

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.

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.

Emotionally enhanced memory for negatively arousing words: storage or retrieval advantage?

PubMed

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.

Speeding Up Non-Parametric Bootstrap Computations for Statistics Based on Sample Moments in Small/Moderate Sample Size Applications

PubMed Central

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

An efficient algorithm for accurate computation of the Dirichlet-multinomial log-likelihood function.

PubMed

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.

Factors Associated with Substance Use in Adolescents with Eating Disorders

PubMed Central

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

An investigation on fatality of drivers in vehicle-fixed object accidents on expressways in China: Using multinomial logistic regression model.

PubMed

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.

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.

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.

The multinomial simulation algorithm for discrete stochastic simulation of reaction-diffusion systems.

PubMed

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.

Verbal Ability and Persistent Offending: A Race-Specific Test of Moffitt's Theory

PubMed Central

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

Identification of nonclassical properties of light with multiplexing layouts

PubMed Central

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

Grouped gene selection and multi-classification of acute leukemia via new regularized multinomial regression.

PubMed

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.

MPTinR: analysis of multinomial processing tree models in R.

PubMed

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/ .

The empathy impulse: A multinomial model of intentional and unintentional empathy for pain.

PubMed

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).

Using species spectra to evaluate plant community conservation value along a gradient of anthropogenic disturbance.

PubMed

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.

OPTIMAL DESIGN FOR MULTINOMIAL CHOICE EXPERIMENTS. (R827987)

EPA Science Inventory

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...

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…

Estimation of Multinomial Probabilities.

DTIC Science & Technology

1978-11-01

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

Caregiver Burdens and Preventive Dental Care for Children with Autism Spectrum Disorder, Developmental Disability and/or Mental Health Conditions: National Survey of CSHCN, 2009-2010.

PubMed

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.

Caregiver Burdens and Preventive Dental Care for Children with Autism Spectrum disorder, developmental disability and/or mental health conditions: National Survey of CSHCN, 2009–10

PubMed Central

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

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…

Use of negative multinomial linear models to investigate environmental effects on community structure.

EPA Science Inventory

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,...

Statistical Development and Application of Cultural Consensus Theory

DTIC Science & Technology

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

Predicting The Type Of Pregnancy Using Flexible Discriminate Analysis And Artificial Neural Networks: A Comparison Study

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

Making sense of sparse rating data in collaborative filtering via topographic organization of user preference patterns.

PubMed

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.

A multilevel model for comorbid outcomes: obesity and diabetes in the US.

PubMed

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.

Compensation of hospital-based physicians.

PubMed Central

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

Modeling Information Content Via Dirichlet-Multinomial Regression Analysis.

PubMed

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.

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…

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…

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…

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…

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…

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…

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…

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…

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…

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…

Saving for Success: Financial Education and Savings Goal Achievement in Individual Development Accounts

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…

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…

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...

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…

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…

Bullying and PTSD Symptoms

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…

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…

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…

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…

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.…

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…

Which Kindergarten Children Are at Greatest Risk for Attention-Deficit/Hyperactivity and Conduct Disorder Symptomatology as Adolescents?

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…

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…

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…

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…

Latent spatial models and sampling design for landscape genetics

Treesearch

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...

LIA at TREC 2012 Web Track: Unsupervised Search Concepts Identification from General Sources of Information

DTIC Science & Technology

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

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…

Relationship Status, Psychological Orientation, and Sexual Risk Taking in a Heterosexual African American College Sample

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,…

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,…

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…

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…

An Analysis of Losses to the Southern Commercial Timberland Base

Treesearch

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...

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…

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…

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…

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…

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…

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…

Beyond ROC Curvature: Strength Effects and Response Time Data Support Continuous-Evidence Models of Recognition Memory

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…

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…

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…

Predicting Teacher Value-Added Results in Non-Tested Subjects Based on Confounding Variables: A Multinomial Logistic Regression

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…

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…

Using Discrete Loss Functions and Weighted Kappa for Classification: An Illustration Based on Bayesian Network Analysis

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…

Comparison of standard maximum likelihood classification and polytomous logistic regression used in remote sensing

Treesearch

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...

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…

Predicting College Success: Achievement, Demographic, and Psychosocial Predictors of First-Semester College Grade Point Average

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…

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.

A panel multinomial logit analysis of elderly living arrangements: evidence from Aging In Manitoba longitudinal data, Canada.

PubMed

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.

Profiles of internalizing and externalizing symptoms associated with bullying victimization.

PubMed

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.

Prevalence of and risk factors for depressive symptoms among people living with HIV/AIDS receiving antiretroviral treatment in Wuhan, China: a short report.

PubMed

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.

A Multilevel Model for Comorbid Outcomes: Obesity and Diabetes in the US

PubMed Central

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

Body mass index and employment status: A new look.

PubMed

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.

The perception of the relationship between environment and health according to data from Italian Behavioural Risk Factor Surveillance System (PASSI).

PubMed

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. ".

Socio-economic determinants of severe and moderate stunting among under-five children of rural Bangladesh.

PubMed

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.

Towards dropout training for convolutional neural networks.

PubMed

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.

Modeling pedestrian shopping behavior using principles of bounded rationality: model comparison and validation

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.

A general equation to obtain multiple cut-off scores on a test from multinomial logistic regression.

PubMed

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.

A general class of multinomial mixture models for anuran calling survey data

USGS Publications Warehouse

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).

Modeling health survey data with excessive zero and K responses.

PubMed

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.

The Effect of Stochastic Perturbation of Fuel Distribution on the Criticality of a One Speed Reactor and the Development of Multi-Material Multinomial Line Statistics

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, , is evaluated when the total fissile loading per ensemble element, or realization, is conserved. The perturbation is proven to increase the reactor criticality on average when it is uniformly distributed. The various causes of the change in reactivity, and their relative effects are identified and ranked. From this, a path towards identifying the causes. and relative effects of reactivity fluctuations for the energy dependent problem is pointed to. The perturbation method of using multinomial distributions for representing the perturbed reactor is developed. This method has some advantages that can be of use in other stochastic problems. Finally, some of the features of this perturbation problem are related to other techniques that have been used for addressing similar problems.

Dietary Fiber Intake Is Inversely Associated with Periodontal Disease among US Adults.

PubMed

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.

"The empathy impulse: A multinomial model of intentional and unintentional empathy for pain": Correction.

PubMed

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).

How Effective Are Severe Disciplinary Policies? School Policies and Offending from Adolescence into Young Adulthood

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…

Primary and Secondary Socialization Impacts on Support for Same-Sex Marriage after Legalization in the Netherlands

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…

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.…

The Association between Electronic Bullying and School Absenteeism among High School Students in the United States

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…

Perpetration of Intimate Partner Aggression by Men and Women in the Philippines: Prevalence and Associated Factors

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…

Using Multidimensional Rasch Analysis to Validate the Chinese Version of the Motivated Strategies for Learning Questionnaire (MSLQ-CV)

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…

Persistent Nonmedical Use of Prescription Stimulants among College Students: Possible Association with ADHD Symptoms

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…

Random Walks on a Simple Cubic Lattice, the Multinomial Theorem, and Configurational Properties of Polymers

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…

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…

How Framing Statistical Statements Affects Subjective Veracity: Validation and Application of a Multinomial Model for Judgments of Truth

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.…

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…

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…

Implementing Sympson-Hetter Item-Exposure Control in a Shadow-Test Approach to Constrained Adaptive Testing

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…

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…

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…

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…

Testing an Online English Course: Lessons Learned from an Analysis of Postcourse Proficiency Change Scores

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…

Using multinomial logistic regression analysis to understand anglers willingness to substitute other fishing locations

Treesearch

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...

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…

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…

The Relationship of Selected Supply- and Demand-Side Factors to Forms of Perceived Discrimination among Adults with Multiple Sclerosis

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…

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…

High School Predictors of College Persistence: The Significance of Engagement and Teacher Interaction

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…

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

USDA-ARS?s Scientific Manuscript database

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

A Multinomial Logit Approach to Estimating Regional Inventories by Product Class

Treesearch

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...

Generalized Partial Least Squares Approach for Nominal Multinomial Logit Regression Models with a Functional Covariate

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…

False Memory for Orthographically versus Semantically Similar Words in Adolescents with Dyslexia: A Fuzzy-Trace Theory Perspective

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…

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…

Comparative Evaluation of Two Methods to Estimate Natural Gas Production in Texas

EIA Publications

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.

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…

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.

A Process View on Implementing an Antibullying Curriculum: How Teachers Differ and What Explains the Variation

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…

Emotional Reactions to Stress among Adolescent Boys and Girls: An Examination of the Mediating Mechanisms Proposed by General Strain Theory

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)…

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…

The Effects of Secondary Special Education Preparation in Reading: Research to Inform State Policy in a New Era

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…

Multinomial-Regression Modeling of the Environmental Attitudes of Higher Education Students Based on the Revised New Ecological Paradigm Scale

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…

The Effect of Participating in Indiana's Twenty-First Century Scholars Program on College Enrollments

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…

Limited-Information Goodness-of-Fit Testing of Diagnostic Classification Item Response Theory Models. CRESST Report 840

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…

How School Choice Is Framed by Parental Preferences and Family Characteristics: A Study of Western Area, Sierra Leone

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,…

The Design and Analysis of Salmonid Tagging Studies in the Columbia Basin; Volume XII; A Multinomial Model for Estimating Ocean Survival from Salmonid Coded Wire-Tag Data.

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.

Latent profile analysis of regression-based norms demonstrates relationship of compounding MS symptom burden and negative work events.

PubMed

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.

Sex-related perceptions associated with sexual activity status among Japanese adolescents who heavily use text messaging.

PubMed

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.

Factors associated with happiness in the elderly persons living in the community.

PubMed

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.

A constrained multinomial Probit route choice model in the metro network: Formulation, estimation and application

PubMed Central

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

An econometric analysis of changes in arable land utilization using multinomial logit model in Pinggu district, Beijing, China.

PubMed

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.

Redintegration and the benefits of long-term knowledge in verbal short-term memory: an evaluation of Schweickert's (1993) multinomial processing tree model.

PubMed

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.

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.

Perception of tourists regarding the smoke-free policy at Suvarnabhumi International Airport, Bangkok, Thailand.

PubMed

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.

Evaluating the Relationship between Productivity and Quality in Emergency Departments

PubMed Central

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

A Pilot Test of Indicator Species to Assess Uniqueness of Oak-Dominated Ecoregions in Central Tennessee

Treesearch

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...

Brief Report: Sexual Orientation in Individuals with Autistic Traits--Population Based Study of 47,000 Adults in Stockholm County

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)…

Redintegration and the Benefits of Long-Term Knowledge in Verbal Short-Term Memory: An Evaluation of Schweickert's (1993) Multinomial Processing Tree Model

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…

Mind-Mindedness as a Multidimensional Construct: Appropriate and Nonattuned Mind-Related Comments Independently Predict Infant-Mother Attachment in a Socially Diverse Sample

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…

Determinants of Intent to Transfer among Black Male Community College Students: A Multinomial, Multi-Level Investigation of Student Engagement

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.…

Comparing Multiple-Group Multinomial Log-Linear Models for Multidimensional Skill Distributions in the General Diagnostic Model. Research Report. ETS RR-08-35

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…

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…

Factors influencing spatial pattern in tropical forest clearance and stand age: Implications for carbon storage and species diversity.

Treesearch

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...

Modeling the Distribution of Fingerprint Characteristics. Revision 1.

DTIC Science & Technology

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

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.

Masquerade Detection Using a Taxonomy-Based Multinomial Modeling Approach in UNIX Systems

DTIC Science & Technology

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

Three faces of entropy for complex systems: Information, thermodynamics, and the maximum entropy principle

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.

Measuring Response Styles Across the Big Five: A Multiscale Extension of an Approach Using Multinomial Processing Trees.

PubMed

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.

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

PubMed

Kéry, Marc

2018-02-01

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

Patient choice modelling: how do patients choose their hospitals?

PubMed

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.

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.

The molecular epidemiology of HIV-1 in the Comunidad Valenciana (Spain): analysis of transmission clusters.

PubMed

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.

Source and destination memory in face-to-face interaction: A multinomial modeling approach.

PubMed

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).

Implicit moral evaluations: A multinomial modeling approach.

PubMed

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.

An Optimization-Based Framework for the Transformation of Incomplete Biological Knowledge into a Probabilistic Structure and Its Application to the Utilization of Gene/Protein Signaling Pathways in Discrete Phenotype Classification.

PubMed

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.

The outcome of tuberculosis treatment in subjects with chronic kidney disease in Brazil: a multinomial analysis*

PubMed Central

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

Registered dietitian's personal beliefs and characteristics predict their teaching or intention to teach fresh vegetable food safety.

PubMed

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.

Knowledge and perception on tuberculosis transmission in Tanzania: Multinomial logistic regression analysis of secondary data.

PubMed

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.

Measuring decision weights in recognition experiments with multiple response alternatives: comparing the correlation and multinomial-logistic-regression methods.

PubMed

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.

Perception of Tourists Regarding the Smoke-Free Policy at Suvarnabhumi International Airport, Bangkok, Thailand

PubMed Central

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

Who Works Among Older Black and White, Well-Functioning Adults in the Health, Aging, and Body Composition Study?

PubMed Central

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

Economic analysis of the potential impact of climate change on recreational trout fishing in the Southern Appalachian Mountains: An appication of a nested multinomial logti model

Treesearch

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...

Generalizing the Iterative Proportional Fitting Procedure.

DTIC Science & Technology

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

Spatial distribution of the risk of dengue fever in southeast Brazil, 2006-2007

PubMed Central

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

Predicting Prostate Cancer Progression At Time of Diagnosis

DTIC Science & Technology

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

Cognitive overload? An exploration of the potential impact of cognitive functioning in discrete choice experiments with older people in health care.

PubMed

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.

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

PubMed

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

2017-03-31

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

Bayesian multinomial probit modeling of daily windows of ...

EPA Pesticide Factsheets

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

Exploratory multinomial logit model-based driver injury severity analyses for teenage and adult drivers in intersection-related crashes.

PubMed

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.

Minimal intervention dentistry for early childhood caries and child dental anxiety: a randomized controlled trial.

PubMed

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.

Predictive occurrence models for coastal wetland plant communities: Delineating hydrologic response surfaces with multinomial logistic regression

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.

Knowledge about tuberculosis transmission among ever-married women in Bangladesh.

PubMed

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.

Multinomial logistic regression analysis for differentiating 3 treatment outcome trajectory groups for headache-associated disability.

PubMed

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.

Physical victimization, gender identity and suicide risk among transgender men and women.

PubMed

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.

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.

Asymptotic Normality Through Factorial Cumulants and Partition Identities

PubMed Central

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

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

PubMed

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

2016-11-01

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

Monitoring stress and recovery: new insights for the prevention of injuries and illnesses in elite youth soccer players.

PubMed

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.

Multinomial modeling and an evaluation of common data-mining algorithms for identifying signals of disproportionate reporting in pharmacovigilance databases.

PubMed

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.

Public funding of pharmaceuticals in The Netherlands: investigating the effect of evidence, process and context on CVZ decision-making.

PubMed

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.

Dental health services utilization and associated factors in children 6 to 12 years old in a low-income country.

PubMed

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.

Circulating Prolactin Associates With Diabetes and Impaired Glucose Regulation

PubMed Central

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

Analysis of crash proportion by vehicle type at traffic analysis zone level: A mixed fractional split multinomial logit modeling approach with spatial effects.

PubMed

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.

The status of diabetes control in Kurdistan province, west of Iran.

PubMed

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.

Predictive occurrence models for coastal wetland plant communities: delineating hydrologic response surfaces with multinomial logistic regression

USGS Publications Warehouse

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.

Shared clinical decision making

PubMed Central

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

Association of personality, neighbourhood, and civic participation with the level of perceived social support: the HUNT study, a cross-sectional survey.

PubMed

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.

Estimating wetland vegetation abundance from Landsat-8 operational land imager imagery: a comparison between linear spectral mixture analysis and multinomial logit modeling methods

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.

Atopic dermatitis is not associated with actinic keratosis: cross-sectional results from the Rotterdam study.

PubMed

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.

Determinants of modern contraceptive use among sexually active men in Kenya.

PubMed

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.

Food and Drug Administration tobacco regulation and product judgments.

PubMed

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.

Association between employee benefits and frailty in community-dwelling older adults.

PubMed

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.

What influences participation in genetic carrier testing? Results from a discrete choice experiment.

PubMed

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.

On Subset Selection Procedures for Poisson Processes and Some Applications to the Binomial and Multinomial Problems

DTIC Science & Technology

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

Faà di Bruno's formula and the distributions of random partitions in population genetics and physics.

PubMed

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.

Identifying the determinants of childhood immunization in the Philippines.

PubMed

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.

Contraceptive Sterilization: Introducing A Couple Perspective to Examine Sociodemographic Differences in Use.

PubMed

Eeckhaut, Mieke C W

2017-09-01

Most studies of contraceptive use have relied solely on the woman's perspective, but because men's attitudes and preferences are also important, analytic approaches based on couples should also be explored. Data from the 2006-2010 and 2011-2013 rounds of the National Survey of Family Growth yielded a sample of 4,591 men and women who were married or cohabiting with an opposite-sex partner and who had completed their intended childbearing. Respondents' reports of both their own and their partners' characteristics and behaviors were employed in two sets of analyses examining educational and racial and ethnic differences in contraceptive use: an individualistic approach (using multinomial logistic regression) and a couple approach (using multinomial logistic diagonal reference models). In the full model using the individualistic approach, respondents with less than a high school education were less likely than those with at least a college degree to rely on male sterilization (odds ratios, 0.1-0.2) or a reversible method (0.4-0.5), as opposed to female sterilization. Parallel analyses limited to couples in which partners had the same educational levels (i.e., educationally homogamous couples) showed an even greater difference between those with the least and those with the most schooling (0.03 for male sterilization and 0.2 for a reversible method). When race and ethnicity, which had a much higher level of homogamy, were examined, the approaches yielded more similar results. Research on contraceptive use can benefit from a couple approach, particularly when focusing on partners' characteristics for which homogamy is relatively low. Copyright © 2017 by the Guttmacher Institute.

Numeric score-based conditional and overall change-in-status indices for ordered categorical data.

PubMed

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.

Oral Microbiota and Risk for Esophageal Squamous Cell Carcinoma in a High-Risk Area of China.

PubMed

Chen, Xingdong; Winckler, Björn; Lu, Ming; Cheng, Hongwei; Yuan, Ziyu; Yang, Yajun; Jin, Li; Ye, Weimin

2015-01-01

Poor oral health has been linked with an increased risk of esophageal squamous cell carcinoma (ESCC). We investigated whether alteration of oral microbiota is associated with ESCC risk. Fasting saliva samples were collected from 87 incident and histopathologicallly diagnosed ESCC cases, 63 subjects with dysplasia and 85 healthy controls. All subjects were also interviewed with a questionnaire. V3-V4 region of 16S rRNA was amplified and sequenced by 454-pyrosequencing platform. Carriage of each genus was compared by means of multivariate-adjusted odds ratios derived from logistic regression model. Relative abundance was compared using Metastats method. Beta diversity was estimated using Unifrac and weighted Unifrac distances. Principal coordinate analysis (PCoA) was applied to ordinate dissimilarity matrices. Multinomial logistic regression was used to compare the coordinates between different groups. ESCC subjects had an overall decreased microbial diversity compared to control and dysplasia subjects (P<0.001). Decreased carriage of genera Lautropia, Bulleidia, Catonella, Corynebacterium, Moryella, Peptococcus and Cardiobacterium were found in ESCC subjects compared to non-ESCC subjects. Multinomial logistic regression analyses on PCoA coordinates also revealed that ESCC subjects had significantly different levels for several coordinates compared to non-ESCC subjects. In conclusion, we observed a correlation between altered salivary bacterial microbiota and ESCC risk. The results of our study on the saliva microbiome are of particular interest as it reflects the shift in microbial communities. Further studies are warranted to verify this finding, and if being verified, to explore the underlying mechanisms.

The Potential for Elimination of Racial-Ethnic Disparities in HIV Treatment Initiation in the Medicaid Population among 14 Southern States

PubMed Central

Zhang, Shun; McGoy, Shanell L.; Dawes, Daniel; Fransua, Mesfin; Rust, George; Satcher, David

2014-01-01

Objectives The purpose of this study was to explore the racial and ethnic disparities in initiation of antiretroviral treatment (ARV treatment or ART) among HIV-infected Medicaid enrollees 18–64 years of age in 14 southern states which have high prevalence of HIV/AIDS and high racial disparities in HIV treatment access and mortality. Methods We used Medicaid claims data from 2005 to 2007 for a retrospective cohort study. We compared frequency variances of HIV treatment uptake among persons of different racial- ethnic groups using univariate and multivariate methods. The unadjusted odds ratio was estimated through multinomial logistic regression. The multinomial logistic regression model was repeated with adjustment for multiple covariates. Results Of the 23,801 Medicaid enrollees who met criteria for initiation of ARV treatment, only one third (34.6%) received ART consistent with national guideline treatment protocols, and 21.5% received some ARV medication, but with sub-optimal treatment profiles. There was no significant difference in the proportion of people who received ARV treatment between black (35.8%) and non-Hispanic whites (35.7%), but Hispanic/Latino persons (26%) were significantly less likely to receive ARV treatment. Conclusions Overall ARV treatment levels for all segments of the population are less than optimal. Among the Medicaid population there are no racial HIV treatment disparities between Black and White persons living with HIV, which suggests the potential relevance of Medicaid to currently uninsured populations, and the potential to achieve similar levels of equality within Medicaid for Hispanic/Latino enrollees and other segments of the Medicaid population. PMID:24769625

A generalized nonlinear model-based mixed multinomial logit approach for crash data analysis.

PubMed

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.

Low Sex Hormone-Binding Globulin Levels Associate with Prediabetes in Chinese Men Independent of Total Testosterone

PubMed Central

Han, Bing; Li, Qin; Chen, Yi; Zhu, Chunfang; Chen, Yingchao; Xia, Fangzhen; Cang, Zhen; Lu, Meng; Chen, Chi; Lin, Dongping; Lu, Yingli

2016-01-01

Objective The association ns between prediabetes and androgens have been rarely reported, especially in Chinese men. We aimed to investigate whether androgens were associated with the prevalence of prediabetes diagnosed with new American Diabetes Association criteria in Chinese men and then to assess which androgen value was the most relevant factor. Methods A total of 2654 men (52.6±13.4 years old) were selected. Serum total testosterone (TT), sex hormone-binding globulin (SHBG) and free testosterone (FT) were measured. Covariance analysis of different androgen values were performed in age subgroups. Multinomial logistic regression was used for the association of TT, SHBG and FT with prediabetes and diabetes, as well as prediabetes in age subgroups. Results According to ADA new criteria, normoglycemia, prediabetes, and diabetes were diagnosed in 1405, 907 and 342 men, respectively. In covariance analysis, SHBG of prediabetes were found lower than that of normoglycemia but higher than that of diabetes (P <0.05). In multinomial logistic regression, serum TT and SHBG were inversely associated with prediabetes and diabetes. While, after full adjustment for age, residence area, economic status, waist circumference, metabolic factors, other two androgen values and HOMA-IR, only the associations of SHBG with prevalence of prediabetes and diabetes persisted statistically significant, especially in the elderly with prediabetes (all P for trend <0.05). Conclusions Serum androgen was inversely associated with prediabetes and diabetes in Chinese men. Low serum SHBG was the most relevant factor for prediabetes and diabetes. Whether it is an independent predictor for incident prediabetes in Chinese men needs further explorations. PMID:27583401

Leveling up the analysis of the reminiscence bump in autobiographical memory: A new approach based on multilevel multinomial models.

PubMed

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.

Women's health in a rural community in Kerala, India: do caste and socioeconomic position matter?

PubMed Central

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

Quality of life of patients from rural and urban areas in Poland with head and neck cancer treated with radiotherapy. A study of the influence of selected socio-demographic factors.

PubMed

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.

Reproductive risk factors assessment for anaemia among pregnant women in India using a multinomial logistic regression model.

PubMed

Perumal, Vanamail

2014-07-01

To assess reproductive risk factors for anaemia among pregnant women in urban and rural areas of India. The International Institute of Population Sciences, India, carried out third National Family Health Survey in 2005-2006 to estimate a key indicator from a sample of ever-married women in the reproductive age group 15-49 years. Data on various dimensions were collected using a structured questionnaire, and anaemia was measured using a portable HemoCue instrument. Anaemia prevalence among pregnant women was compared between rural and urban areas using chi-square test and odds ratio. Multinomial logistic regression analysis was used to determine risk factors. Anaemia prevalence was assessed among 3355 pregnant women from rural areas and 1962 pregnant women from urban areas. Moderate-to-severe anaemia in rural areas (32.4%) is significantly more common than in urban areas (27.3%) with an excess risk of 30%. Gestational age specific prevalence of anaemia significantly increases in rural areas after 6 months. Pregnancy duration is a significant risk factor in both urban and rural areas. In rural areas, increasing age at marriage and mass media exposure are significant protective factors of anaemia. However, more births in the last five years, alcohol consumption and smoking habits are significant risk factors. In rural areas, various reproductive factors and lifestyle characteristics constitute significant risk factors for moderate-to-severe anaemia. Therefore, intensive health education on reproductive practices and the impact of lifestyle characteristics are warranted to reduce anaemia prevalence. © 2014 John Wiley & Sons Ltd.

Urinary 8-iso-prostaglandin F2α as a marker of metabolic risks in the general Japanese population: The ROAD study.

PubMed

Mure, Kanae; Yoshimura, Noriko; Hashimoto, Marowa; Muraki, Shigeyuki; Oka, Hiroyuki; Tanaka, Sakae; Kawaguchi, Hiroshi; Nakamura, Kozo; Akune, Toru; Takeshita, Tatsuya

2015-07-01

To determine whether 8-iso-prostaglandin F2α (8-iso-PGF2α) is a reliable biomarker of the accumulation of metabolic risks [e.g., overweight, hypertension, impaired glucose tolerance (IGT), and dyslipidemia]. This was a cross-sectional study of the baseline characteristics of a Japanese general population cohort study: Research on Osteoarthritis/Osteoporosis Against Disability (ROAD). Of 1,690 participants, 1,527 fulfilled all questionnaires and examinations. Free and conjugated urinary 8-iso-PGF2α levels and metabolic syndrome (MetS) components including blood pressure, HbA1c, total cholesterol, high-density lipoprotein cholesterol (HDL-C), and non-HDL-C were analyzed. The data were analyzed by ANCOVA, multiple regression analysis, and multinomial logistic analysis. 8-iso-PGF2α was significantly associated with HbA1c and significantly inversely associated with total cholesterol and non-HDL-C. Notably, IGT with an HbA1c cut-off of 5.5% was significantly associated with 8-iso-PGF2α level in participants aged ≤50 years. Multinomial logistic regression analysis revealed 8-iso-PGF2α level was significantly associated with a greater number of MetS risks present; this association was stronger in younger participants. In participants aged ≥71 years, 8-iso-PGF2α was significantly associated with a greater number of MetS risks with higher IGT cut-offs. Urinary 8-iso-PGF2α can be a reliable marker of IGT and the accumulation of MetS risks, especially in younger people. © 2015 The Obesity Society.

Hospital financial position and the adoption of electronic health records.

PubMed

Ginn, Gregory O; Shen, Jay J; Moseley, Charles B

2011-01-01

The objective of this study was to examine the relationship between financial position and adoption of electronic health records (EHRs) in 2442 acute care hospitals. The study was cross-sectional and utilized a general linear mixed model with the multinomial distribution specification for data analysis. We verified the results by also running a multinomial logistic regression model. To measure our variables, we used data from (1) the 2007 American Hospital Association (AHA) electronic health record implementation survey, (2) the 2006 Centers for Medicare and Medicaid Cost Reports, and (3) the 2006 AHA Annual Survey containing organizational and operational data. Our dependent variable was an ordinal variable with three levels used to indicate the extent of EHR adoption by hospitals. Our independent variables were five financial ratios: (1) net days revenue in accounts receivable, (2) total margin, (3) the equity multiplier, (4) total asset turnover, and (5) the ratio of total payroll to total expenses. For control variables, we used (1) bed size, (2) ownership type, (3) teaching affiliation, (4) system membership, (5) network participation, (6) fulltime equivalent nurses per adjusted average daily census, (7) average daily census per staffed bed, (8) Medicare patients percentage, (9) Medicaid patients percentage, (10) capitation-based reimbursement, and (11) nonconcentrated market. Only liquidity was significant and positively associated with EHR adoption. Asset turnover ratio was significant but, unexpectedly, was negatively associated with EHR adoption. However, many control variables, most notably bed size, showed significant positive associations with EHR adoption. Thus, it seems that hospitals adopt EHRs as a strategic move to better align themselves with their environment.

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

PubMed

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

2018-03-08

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

Vitamin D status by sociodemographic factors and body mass index in Mexican women at reproductive age.

PubMed

Contreras-Manzano, Alejandra; Villalpando, Salvador; Robledo-Pérez, Ricardo

2017-01-01

To describe the prevalence of Vitamin D deficiency (VDD) and insufficiency (VDI), and the main dietary sources of vitamin D (VD) in a probabilistic sample of Mexican women at reproductive age participating in Ensanut 2012, stratified by sociodemographic factors and body mass index (BMI) categories. Serum concentrations of 25-hydroxyvitamin-D(25-OH-D) were determined using an ELISA technique in 4162 women participants of Ensanut 2012 and classified as VDD, VDI or optimal VD status. Sociodemographic, anthropometric and dietary data were also collected. The association between VDD/VDI and sociodemographic and anthropometry factors was assessed adjusting for potential confounders through an estimation of a multinomial logistic regression model. The prevalence of VDD was 36.8%, and that of VDI was 49.8%. The mean dietary intake of VD was 2.56 μg/d. The relative risk ratio (RRR) of VDD or VDI was calculated by a multinomial logistic regression model in 4162 women. The RRR of VDD or VDI were significantly higher in women with overweight (RRR: 1.85 and 1.44, p<0.05), obesity (RRR: 2.94 and 1.93, p<0.001), urban dwelling (RRR:1.68 and 1.31, p<0.06), belonging to the 3rd tertile of income (RRR: 5.32 and 2.22, p<0.001), or of indigenous ethnicity (RRR: 2.86 and 1.70, p<0.05), respectively. The high prevalence of VDD/VDI in Mexican women calls for stronger actions from the health authorities, strengthtening the actual policy of food supplementation and recommending a reasonable amount of sun exposure.

Concern about falling in older women with a history of falls: associations with health, functional ability, physical activity and quality of life.

PubMed

Patil, Radhika; Uusi-Rasi, Kirsti; Kannus, Pekka; Karinkanta, Saija; Sievänen, Harri

2014-01-01

Fear of falling has been linked to activity restriction, functional decline, decreased quality of life and increased risk of falling. Factors that distinguish persons with a high concern about falling from those with low concern have not been systematically studied. This study aimed to expose potential health-related, functional and psychosocial factors that correlate with fear of falling among independently living older women who had fallen in the past year. Baseline data of 409 women aged 70-80 years recruited to a randomised falls prevention trial (DEX) (NCT00986466) were used. Participants were classified according to their level of concern about falling using the Falls Efficacy Scale International (FES-I). Multinomial logistic regression analyses were performed to explore associations between health-related variables, functional performance tests, amount of physical activity, quality of life and FES-I scores. 68% of the participants reported a moderate to high concern (FES-I ≥ 20) about falls. Multinomial logistic regression showed that highly concerned women were significantly more likely to have poorer health and quality of life and lower functional ability. Reported difficulties in instrumental activities of daily living, balance, outdoor mobility and poorer quality of life contributed independently to a greater concern about falling. Concern about falling was highly prevalent in our sample of community-living older women. In particular, poor perceived general health and mobility constraints contributed independently to the difference between high and low concern of falling. Knowledge of these associations may help in developing interventions to reduce fear of falling and activity avoidance in old age.

Think twice before you book? Modelling the choice of public vs private dentist in a choice experiment.

PubMed

Kiiskinen, Urpo; Suominen-Taipale, Anna Liisa; Cairns, John

2010-06-01

This study concerns the choice of primary dental service provider by consumers. If the health service delivery system allows individuals to choose between public-care providers or if complementary private services are available, it is typically assumed that utilisation is a three-stage decision process. The patient first makes a decision to seek care, and then chooses the service provider. The final stage, involving decisions over the amount and form of treatment, is not considered here. The paper reports a discrete choice experiment (DCE) designed to evaluate attributes affecting individuals' choice of dental-care provider. The feasibility of the DCE approach in modelling consumers' choice in the context of non-acute need for dental care is assessed. The aim is to test whether a separate two-stage logit, a multinomial logit, or a nested logit best fits the choice process of consumers. A nested logit model of indirect utility functions is estimated and inclusive value (IV) constraints are tested for modelling implications. The results show that non-trading behaviour has an impact on the choice of appropriate modelling technique, but is to some extent dependent on the choice of scenarios offered. It is concluded that for traders multinomial logit is appropriate, whereas for non-traders and on average the nested logit is the method supported by the analyses. The consistent finding in all subgroup analyses is that the traditional two-stage decision process is found to be implausible in the context of consumer's choice of dental-care provider.

Prevalence and Determinants of Secondhand Smoke Exposure Among Women in Bangladesh, 2011

PubMed Central

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

The dynamics of injection drug users' personal networks and HIV risk behaviors.

PubMed

Costenbader, Elizabeth C; Astone, Nan M; Latkin, Carl A

2006-07-01

While studies of the social networks of injection drug users (IDUs) have provided insight into how the structures of interpersonal relationships among IDUs affect HIV risk behaviors, the majority of these studies have been cross-sectional. The present study examined the dynamics of IDUs' social networks and HIV risk behaviors over time. Using data from a longitudinal HIV-intervention study conducted in Baltimore, MD, this study assessed changes in the composition of the personal networks of 409 IDUs. We used a multi-nomial logistic regression analysis to assess the association between changes in network composition and simultaneous changes in levels of injection HIV risk behaviors. Using the regression parameters generated by the multi-nomial model, we estimated the predicted probability of being in each of four HIV risk behavior change groups. Compared to the base case, individuals who reported an entirely new set of drug-using network contacts at follow-up were more than three times as likely to be in the increasing risk group. In contrast, reporting all new non-drug-using contacts at follow-up increased the likelihood of being in the stable low-risk group by almost 50% and decreased the probability of being in the consistently high-risk group by more than 70%. The findings from this study show that, over and above IDUs' baseline characteristics, changes in their personal networks are associated with changes in individuals' risky injection behaviors. They also suggest that interventions aimed at reducing HIV risk among IDUs might benefit from increasing IDUs' social contacts with individuals who are not drug users.

Individual and contextual characteristics of indoor and outdoor falls in older residents of São Paulo, Brazil.

PubMed

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.

Cross-Jurisdictional Resource Sharing in Changing Public Health Landscape: Contributory Factors and Theoretical Explanations.

PubMed

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.

Contraceptive awareness among men in Bangladesh.

PubMed

Islam, Mohammad Amirul; Padmadas, Sabu S; Smith, Peter W F

2006-04-01

A considerable gap exists between contraceptive awareness and use. Traditional approaches to measuring awareness are inadequate to properly understand the linkages between awareness and use. The objective of this study was to examine the degree of men's modern contraceptive awareness in Bangladesh and the associated determinants and further testing of a hypothesis that current contraceptive use confers a high degree of method awareness. This study used the couple data set from the Bangladesh Demographic and Health Survey (1999-2000). A two-level, multinomial logistic regression was used with the degree of contraceptive awareness as the dependent variable. The degree of awareness was measured by the reported number of modern contraceptive methods known among men aged 15-59 years. Men's responses on method awareness were classified according to those reported spontaneously and probed. Nearly 100% of the study participants reported having heard of at least one method and about half reported awareness of at least eight different methods of contraception. Multinomial logistic regression analyses showed that older and educated men were more likely to have reported a high degree of awareness. The findings confirmed our hypothesis that current contraceptive use is likely to confer a high degree of modern method awareness among men (p<0.001), after controlling for other important characteristics. Men who had a low degree of contraceptive awareness seem not properly informed of the wide range of contraceptive options. It is imperative that family planning intervention strategies in Bangladesh should focus on the degree and functional knowledge of contraceptive methods to improve the uptake of especially male-based modern methods.

Inequality in the hepatitis B awareness level in rural residents from 7 provinces in China.

PubMed

Zheng, Juan; Li, Quan; Wang, Jian; Zhang, Guojie; Wangen, Knut R

2017-05-04

The hepatitis B (HB) awareness level is an important factor affecting the rates of HB virus vaccination. To better understand income-related inequalities in the HB awareness level, it is imperative to identify the sources of inequalities and assess the contribution rates of these influential factors. This study analyzed the unequal distribution of the HB awareness level and the contributions of various influential factors. We performed a cross-sectional household survey with questionnaire-based, face-to-face interviews in 7 Chinese provinces. Responses from 7271 respondents were used in this analysis. Multinomial logistic regression was used for the analysis of contributing factors, and the concentration index was used as a measure of HB awareness inequalities. The HB awareness level varied across participants with different characteristics. Multinomial logistic regression of the explanatory factors of the HB awareness level showed that several estimated coefficients and relative risk ratios were statistically significant for middle- and high-level awareness, except for sex, occupation, and household income. The concentration index of the HB knowledge score was 0.140, indicating inequality gradients disadvantageous to the poor. The contribution rate of socioeconomic factors was the largest (60.8%), followed by demographic characteristics (29.0%) and geographic factors (4.3%). Demographic, socioeconomic, and geographic factors are associated with the HB awareness inequality. Therefore, to reduce inequality, HB-related health education targeting individuals with low socioeconomic status should be performed. Less-developed provinces, especially with high proportions of poor residents, warrant particular attention. Our findings may be beneficial to improve the HB virus vaccination rate for individuals with low socioeconomic status.

Occupational outcomes of adult childhood cancer survivors: A report from the Childhood Cancer Survivor Study

PubMed Central

Kirchhoff, Anne C.; Krull, Kevin R.; Ness, Kirsten K.; Park, Elyse R.; Oeffinger, Kevin C.; Hudson, Melissa M.; Stovall, Marilyn; Robison, Leslie L.; Wickizer, Thomas; Leisenring, Wendy

2010-01-01

Background We examined whether survivors from the Childhood Cancer Survivor Study were less likely to be in higher skill occupations than a sibling comparison and whether certain survivors were at higher risk. Methods We created three mutually-exclusive occupational categories for participants aged ≥25 years: Managerial/Professional and Non-Physical and Physical Service/Blue Collar. We examined currently employed survivors (N=4845) and siblings (N=1727) in multivariable generalized linear models to evaluate the likelihood of being in the three occupational categories. Among all participants, we used multinomial logistic regression to examine the likelihood of these outcomes in comparison to being unemployed (survivors N=6671; siblings N=2129). Multivariable linear models were used to assess survivor occupational differences by cancer and treatment variables. Personal income was compared by occupation. Results Employed survivors were less often in higher skilled Managerial/Professional occupations (Relative Risk=0.93, 95% Confidence Interval 0.89–0.98) than siblings. Survivors who were Black, were diagnosed at a younger age, or had high-dose cranial radiation were less likely to hold Professional occupations than other survivors. In multinomial models, female survivors’ likelihood of being in full-time Professional occupations (27%) was lower than male survivors (42%) and female (41%) and male (50%) siblings. Survivors’ personal income was lower than siblings within each of the three occupational categories in models adjusted for sociodemographic variables. Conclusions Adult childhood cancer survivors are employed in lower skill jobs than siblings. Survivors with certain treatment histories are at higher risk and may require vocational assistance throughout adulthood. PMID:21246530

Korean, Japanese, and Chinese populations featured similar genes encoding drug-metabolizing enzymes and transporters: a DMET Plus microarray assessment.

PubMed

Yi, SoJeong; An, Hyungmi; Lee, Howard; Lee, Sangin; Ieiri, Ichiro; Lee, Youngjo; Cho, Joo-Youn; Hirota, Takeshi; Fukae, Masato; Yoshida, Kenji; Nagatsuka, Shinichiro; Kimura, Miyuki; Irie, Shin; Sugiyama, Yuichi; Shin, Dong Wan; Lim, Kyoung Soo; Chung, Jae-Yong; Yu, Kyung-Sang; Jang, In-Jin

2014-10-01

Interethnic differences in genetic polymorphism in genes encoding drug-metabolizing enzymes and transporters are one of the major factors that cause ethnic differences in drug response. This study aimed to investigate genetic polymorphisms in genes involved in drug metabolism, transport, and excretion among Korean, Japanese, and Chinese populations, the three major East Asian ethnic groups. The frequencies of 1936 variants representing 225 genes encoding drug-metabolizing enzymes and transporters were determined from 786 healthy participants (448 Korean, 208 Japanese, and 130 Chinese) using the Affymetrix Drug-Metabolizing Enzymes and Transporters Plus microarray. To compare allele or genotype frequencies in the high-dimensional data among the three East Asian ethnic groups, multiple testing, principal component analysis (PCA), and regularized multinomial logit model through least absolute shrinkage and selection operator were used. On microarray analysis, 1071 of 1936 variants (>50% of markers) were found to be monomorphic. In a large number of genetic variants, the fixation index and Pearson's correlation coefficient of minor allele frequencies were less than 0.034 and greater than 0.95, respectively, among the three ethnic groups. PCA identified 47 genetic variants with multiple testing, but was unable to discriminate ethnic groups by the first three components. Multinomial least absolute shrinkage and selection operator analysis identified 269 genetic variants that showed different frequencies among the three ethnic groups. However, none of those variants distinguished between the three ethnic groups during subsequent PCA. Korean, Japanese, and Chinese populations are not pharmacogenetically distant from one another, at least with regard to drug disposition, metabolism, and elimination.

Probabilistic treatment of the uncertainty from the finite size of weighted Monte Carlo data

NASA Astrophysics Data System (ADS)

Glüsenkamp, Thorsten

2018-06-01

Parameter estimation in HEP experiments often involves Monte Carlo simulation to model the experimental response function. A typical application are forward-folding likelihood analyses with re-weighting, or time-consuming minimization schemes with a new simulation set for each parameter value. Problematically, the finite size of such Monte Carlo samples carries intrinsic uncertainty that can lead to a substantial bias in parameter estimation if it is neglected and the sample size is small. We introduce a probabilistic treatment of this problem by replacing the usual likelihood functions with novel generalized probability distributions that incorporate the finite statistics via suitable marginalization. These new PDFs are analytic, and can be used to replace the Poisson, multinomial, and sample-based unbinned likelihoods, which covers many use cases in high-energy physics. In the limit of infinite statistics, they reduce to the respective standard probability distributions. In the general case of arbitrary Monte Carlo weights, the expressions involve the fourth Lauricella function FD, for which we find a new finite-sum representation in a certain parameter setting. The result also represents an exact form for Carlson's Dirichlet average Rn with n > 0, and thereby an efficient way to calculate the probability generating function of the Dirichlet-multinomial distribution, the extended divided difference of a monomial, or arbitrary moments of univariate B-splines. We demonstrate the bias reduction of our approach with a typical toy Monte Carlo problem, estimating the normalization of a peak in a falling energy spectrum, and compare the results with previously published methods from the literature.

Victimization and health risk factors among weapon-carrying youth.

PubMed

Stayton, Catherine; McVeigh, Katharine H; Olson, E Carolyn; Perkins, Krystal; Kerker, Bonnie D

2011-11-01

To compare health risks of 2 subgroups of weapon carriers: victimized and nonvictimized youth. 2003-2007 NYC Youth Risk Behavior Surveys were analyzed using bivariate analyses and multinomial logistic regression. Among NYC teens, 7.5% reported weapon carrying without victimization; 6.9% reported it with victimization. Both subgroups were more likely than non-weapon carriers to binge drink, use marijuana, smoke, fight, and have multiple sex partners; weapon carriers with victimization also experienced persistent sadness and attempted suicide. Subgroups of weapon carriers have distinct profiles. Optimal response should pair disciplinary action with screening for behavioral and mental health concerns and victimization.

Willingness to pay for midwife-endorsed product: An Australian best-worst study.

PubMed

Lahtinen, Ville; Rundle-Thiele, Sharyn; Adamsen, Jannie Mia

2016-01-01

This article examined the impact of midwife endorsement on stated choice preferences in one of the highest volume baby care product categories, diapers. An online survey was conducted testing 12 alternatives of which six were midwife endorsed. A total of 215 responses were analyzed using best-worst and multinomial logit modeling. Results indicate that package size, price, and brand are more sensitive predictors of stated choice preferences than midwife endorsement. Respondents were willing to pay 2.3% more for a diaper that was endorsed by midwives. These findings suggest that midwife endorsement should be pursued by health marketers.

Simulating landscape change in the Olympic Peninsula using spatial ecological and socioeconomic data

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

Flamm, R.O.; Gottfried, R.; Lee, R.G.

1994-06-01

Ecological and socioeconomic data were integrated to study landscape change for the Dungeness River basin in the Olympic Peninsula, Washington State. A multinomial logit procedure was used to evaluate twenty-two maps representing various data themes to derive transition probabilities of land cover change. Probabilities of forest disturbance were greater on private land than public. Between 1975 and 1988, forest cover increased, grassy/brushy covers decreased, and the number of forest patches increased about 30%. Simulations were run to estimate future land cover. These results were represented as frequency distributions for proportion cover and patch characteristics.

Generalized Processing Tree Models: Jointly Modeling Discrete and Continuous Variables.

PubMed

Heck, Daniel W; Erdfelder, Edgar; Kieslich, Pascal J

2018-05-24

Multinomial processing tree models assume that discrete cognitive states determine observed response frequencies. Generalized processing tree (GPT) models extend this conceptual framework to continuous variables such as response times, process-tracing measures, or neurophysiological variables. GPT models assume finite-mixture distributions, with weights determined by a processing tree structure, and continuous components modeled by parameterized distributions such as Gaussians with separate or shared parameters across states. We discuss identifiability, parameter estimation, model testing, a modeling syntax, and the improved precision of GPT estimates. Finally, a GPT version of the feature comparison model of semantic categorization is applied to computer-mouse trajectories.

The choice of facilitators in medical tourism.

PubMed

Gan, Lydia L; Frederick, James R

2018-01-01

The study identified which of the four facilitators (themselves, agents, insurers, or doctors) consumers are most likely to use when they travel for various medical procedures. A survey conducted between 2011 and 2014 yielded 964 responses. The multinomial logistic regression results showed that being 51-64 years old was positively related to going on their own or using agents to arrange for knee replacements. Having a high school education or less was positively linked to using both agents and insurers to facilitate knee replacements, whereas having a bachelor's degree was negatively associated with going on their own for stem cell therapy.

Analyzing Data for Systems Biology: Working at the Intersection of Thermodynamics and Data Analytics

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

Cannon, William R.; Baxter, Douglas J.

2012-08-15

Many challenges in systems biology have to do with analyzing data within the framework of molecular phenomena and cellular pathways. How does this relate to thermodynamics that we know govern the behavior of molecules? Making progress in relating data analysis to thermodynamics is essential in systems biology if we are to build predictive models that enable the field of synthetic biology. This report discusses work at the crossroads of thermodynamics and data analysis, and demonstrates that statistical mechanical free energy is a multinomial log likelihood. Applications to systems biology are presented.

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

Dengue-specific serotype related to clinical severity during the 2012/2013 epidemic in centre of Brazil.

PubMed

Rocha, Benigno A M; Guilarde, Adriana O; Argolo, Angela F L T; Tassara, Marianna Peres; da Silveira, Lucimeire A; Junqueira, Isabela C; Turchi, Marília D; Féres, Valéria C R; Martelli, Celina M T

2017-08-02

Please see Additional file 1 for translations of the abstract into the five official working languages of the United Nations. Currently, in Brazil, there is a co-circulation of the four dengue (DENV-1 to DENV-4) serotypes. This study aimed to assess whether different serotypes and antibody response patterns were associated with the severity of the disease during a dengue outbreak, which occurred in 2012/2013 in centre of Brazil. We conducted a prospective study with 452 patients with laboratory confirmed dengue in central Brazil, from January 2012 to July 2013. The clinical outcome was the severity of cases: dengue, dengue with warning signs, and severe dengue. The patients were evaluated at three different moments. Blood sampling for laboratory testing and confirmatory tests for dengue infection were performed. We performed a multinomial analysis considering the three categories of the dependent variable, as outlined above. The odds ratios (ORs) were calculated. A multinomial logistic regression model was applied for variables with a P-value <0.20. Statistical analysis was performed with STATA 12.0 software. Four hundred fifty-two patients (452/632, 71.5%) were diagnosed with dengue. The dengue virus (DENV) serotypes were identified in 243 cases. DENV-4 was detected in 135 patients (55.6%), DENV-1 in 91 (37.4%), DENV-3 in 13 (5.3%), and DENV-2 in 4 (1.6%). Patients with the DENV-1 serotype were more prone to present with several clinical and laboratory features as compared with DENV-4 patients, including spontaneous bleeding (P = 0.03), intense abdominal pain (P = 0.004), neurological symptoms (P = 0.09), and thrombocytopenia (P = 0.01). Secondary infection was more predominant among DENV-4 cases (80.0%) compared with DENV-1 cases (62.3%) (P = 0.03). The univariate analysis showed that females (OR = 2.12; 95% CI: 1.44-3.13; P < 0.01) had a higher risk of having dengue with warning signs. The multinomial analysis showed that severe dengue cases with secondary infection had an adjusted OR of 2.80 (95% CI: 0.78-10.00; P = 0.113) as compared with dengue fever with primary infection when adjusted for age and sex. The current data show that 5.8% of patients recruited for treatment in healthcare centres and hospitals during the study period had severe dengue. DENV-4 was the predominant serotype, followed by DENV-1, in a large outbreak of dengue in central Brazil. Our findings contribute to the understanding of clinical differences and immune status related to the serotypes DENV-1 and DENV-4 in central of Brazil.

ACUTE LOWER RESPIRATORY INFECTION IN GUARANI INDIGENOUS CHILDREN, BRAZIL.

PubMed

Souza, Patricia Gomes de; Cardoso, Andrey Moreira; Sant'Anna, Clemax Couto; March, Maria de Fátima Bazhuni Pombo

2018-03-29

To describe the clinical profile and treatment of Brazilian Guarani indigenous children aged less than five years hospitalized for acute lower respiratory infection (ALRI), living in villages in the states from Rio de Janeiro to Rio Grande do Sul. Of the 234 children, 23 were excluded (incomplete data). The analysis was conducted in 211 children. Data were extracted from charts by a form. Based on record of wheezing and x-ray findings, ALRI was classified as bacterial, viral and viral-bacterial. A bivariate analysis was conducted using multinomial regression. Median age was 11 months. From the total sample, the ALRI cases were classified as viral (40.8%), bacterial (35.1%) and viral-bacterial (24.1%). It was verified that 53.1% of hospitalizations did not have clinical-radiological-laboratorial evidence to justify them. In the multinomial regression analysis, the comparison of bacterial and viral-bacterial showed the likelihood of having a cough was 3.1 times higher in the former (95%CI 1.11-8.70), whereas having chest retractions was 61.0% lower (OR 0.39, 95%CI 0.16-0.92). Comparing viral with viral-bacterial, the likelihood of being male was 2.2 times higher in the viral (95%CI 1.05-4.69), and of having tachypnea 58.0% lower (OR 0.42, 95%CI 0.19-0.92). Higher proportion of viral processes was identified, as well as viral-bacterial co-infections. Coughing was a symptom indicative of bacterial infection, whereas chest retractions and tachypnea showed viral-bacterial ALRI. Part of the resolution of non-severe ALRI still occurs at hospital level; therefore, we concluded that health services need to implement their programs in order to improve indigenous primary care.

What is a Breast Surgeon Worth? A Salary Survey of the American Society of Breast Surgeons.

PubMed

Manahan, Eric; Wang, Li; Chen, Steven; Dickson-Witmer, Diana; Zhu, Junjia; Holmes, Dennis; Kass, Rena

2015-10-01

Breast surgeons negotiating employment agreements have little national data available. To reduce this knowledge gap, the Education Committee of the American Society of Breast Surgeons conducted a survey of its membership. In 2014, survey questionnaires were sent to society members. Data collected included gender, type of practice, percentage devoted to breast surgery, volume of breast cases, work relative value units, location, benefits, and salary. Descriptive statistics were provided, and a multinomial logistic regression was performed to analyze the impact of various potential factors on salary. Of the 2784 members, a total of 843 observations were included. Overall, 54% of respondents dedicated 100 % of their practice to breast surgery, 64.3% were female, and 40% were fellowship-trained in breast surgery or surgical oncology. The mean income in 2013 was $330.7k. Results from a multinomial model showed gender (p < 0.0001), ownership (p = 0.03), years of practice (p < 0.0001), practice setting (p < 0.0001), practice volume (p < 0.0001), and geographic location (p = 0.05) were statistically significant. After adjusting for other variables, the expected income was higher for males ($378k vs. $310k). The lowest expected income by practice setting was in solo private practice ($249.2k), followed by single-specialty private practice ($285.8k), and academic ($308.5k), with the highest being multispecialty group private practice ($346.6k) and hospital-employed practice ($368.0k). Practice 100% dedicated to breast surgery had a lower than expected income ($326k vs. $343k). Salary-specific data for breast surgeons are limited, and differences in salary were seen across geographic regions, type of practice, and gender. This type of breast-surgeon-specific data may be helpful in ensuring equitable compensation.

Treatment of Ductal Carcinoma In Situ Among Patients Cared for in Large Integrated Health Plans

PubMed Central

Haque, Reina; Achacoso, Ninah S.; Fletcher, Suzanne W.; Nekhlyudov, Larissa; Collins, Laura C.; Schnitt, Stuart J.; Quesenberry, Charles P.; Habel, Laurel A.

2013-01-01

Objective To examine whether use of adjuvant therapy varies by race/ethnicity among patients with ductal carcinoma in situ (DCIS) at 3 integrated health plan delivery sites based in California and Massachusetts. Study Design Cross-sectional study nested within a cohort of women diagnosed as having DCIS between 1990 and 2001. Methods We reviewed medical records of 3000 non-Hispanic white (69%), black (10%), Hispanic (9%), and Asian or Pacific Islander (12%) women diagnosed as having DCIS between 1990 and 2001 and treated with breast-conserving therapy. χ2 Test and multinomial logistic regression analysis were used to examine the association between race/ethnicity and use of adjuvant treatments after controlling for patient and clinical variables, including certain pathologic factors. Results We found no significant differences in DCIS adjuvant treatment among racial/ethnic groups in bivariate or multinomial analyses after adjusting for demographic characteristics, comorbidity, and clinical factors. Minority women were as likely to undergo adjuvant radiation therapy as non-Hispanic white women. However, women 70 years or older (odds ratio, 0.40; 95% confidence interval, 0.31–0.51) and women who lived in areas with low geocoded median family income (odds ratio, 0.65; 95% confidence interval, 0.48–0.89) were less likely to receive adjuvant radiation therapy. Tumor size and comedo histologic growth pattern were associated with increased likelihood of receiving radiation therapy. Conclusion Use of adjuvant therapy by minority women in these managed care plans is similar to that by non-Hispanic white women, although use was less among older women and among women who lived in poorer neighborhoods. PMID:20469955

A new strategy to analyze possible association structures between dynamic nocturnal hormone activities and sleep alterations in humans.

PubMed

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.

Constitution of traditional chinese medicine and related factors in women of childbearing age.

PubMed

Jiang, Qiao-Yu; Li, Jue; Zheng, Liang; Wang, Guang-Hua; Wang, Jing

2018-04-01

This study investigates the constitution of traditional Chinese medicine (TCM) among women who want to be pregnant in one year and explores factors related to TCM constitution. This study was conducted on women who participated in free preconception check-ups provided by the Zhabei District Maternity and Child Care Center in Shanghai, China. The information regarding the female demographic characteristics, physical condition, history of pregnancy and childbearing, diet and behavior, and social psychological factors was collected, and TCM constitution assessment was performed. The Chi-square test, t-test, logistic regression analysis, and multinomial logistic regression analysis were used to explore the related factors of TCM constitution. The participants in this study were aged 28.3 ± 3.0 years. Approximately fifty-five women in this study had Unbalanced Constitution. Logistic regression analysis showed that Shanghai residence, dysmenorrhea, gum bleeding, aversion to vegetables, preference for raw meat, job stress, and economic stress were significantly and negatively associated with Balanced Constitution. Multinomial logistic analysis showed that Shanghai residence was significantly associated with Yang-deficiency, Yin-deficiency, and Stagnant Qi Constitutions; gum bleeding was significantly associated with Yin-deficiency, Stagnant Blood, Stagnant Qi, and Inherited Special Constitutions; aversion to vegetables was significantly associated with Damp-heat Constitution; job stress was significantly associated with Yang-deficiency, Phlegm-dampness, Damp-heat, Stagnant Blood, and Stagnant Qi Constitutions; and economic stress was significantly associated with Yang-deficiency, and Stagnant Qi Constitutions. The application of TCM constitution to preconception care would be beneficial for early identification of potential TCM constitution risks and be beneficial for early intervention (e.g., health education, and dietary education), especially during the women who do not have a medical condition and those who have related factors found in this study. Copyright © 2018. Published by Elsevier Taiwan LLC.

Expert Elicitation of Multinomial Probabilities for Decision-Analytic Modeling: An Application to Rates of Disease Progression in Undiagnosed and Untreated Melanoma.

PubMed

Wilson, Edward C F; Usher-Smith, Juliet A; Emery, Jon; Corrie, Pippa G; Walter, Fiona M

2018-06-01

Expert elicitation is required to inform decision making when relevant "better quality" data either do not exist or cannot be collected. An example of this is to inform decisions as to whether to screen for melanoma. A key input is the counterfactual, in this case the natural history of melanoma in patients who are undiagnosed and hence untreated. To elicit expert opinion on the probability of disease progression in patients with melanoma that is undetected and hence untreated. A bespoke webinar-based expert elicitation protocol was administered to 14 participants in the United Kingdom, Australia, and New Zealand, comprising 12 multinomial questions on the probability of progression from one disease stage to another in the absence of treatment. A modified Connor-Mosimann distribution was fitted to individual responses to each question. Individual responses were pooled using a Monte-Carlo simulation approach. Participants were asked to provide feedback on the process. A pooled modified Connor-Mosimann distribution was successfully derived from participants' responses. Feedback from participants was generally positive, with 86% willing to take part in such an exercise again. Nevertheless, only 57% of participants felt that this was a valid approach to determine the risk of disease progression. Qualitative feedback reflected some understanding of the need to rely on expert elicitation in the absence of "hard" data. We successfully elicited and pooled the beliefs of experts in melanoma regarding the probability of disease progression in a format suitable for inclusion in a decision-analytic model. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Occupational outcomes of adult childhood cancer survivors: A report from the childhood cancer survivor study.

PubMed

Kirchhoff, Anne C; Krull, Kevin R; Ness, Kirsten K; Park, Elyse R; Oeffinger, Kevin C; Hudson, Melissa M; Stovall, Marilyn; Robison, Leslie L; Wickizer, Thomas; Leisenring, Wendy

2011-07-01

The authors examined whether survivors from the Childhood Cancer Survivor Study were less likely to be in higher-skill occupations than a sibling comparison and whether certain survivors were at higher risk for lower-skill jobs. The authors created 3 mutually exclusive occupational categories for participants aged ≥ 25 years: Managerial/Professional, Nonphysical Service/Blue Collar, and Physical Service/Blue Collar. The authors examined currently employed survivors (4845) and their siblings (1727) in multivariable generalized linear models to evaluate the likelihood of being in 1 of the 3 occupational categories. Multinomial logistic regression was used among all participants to examine the likelihood of these outcomes compared to being unemployed (survivors, 6671; siblings, 2129). Multivariable linear models were used to assess survivor occupational differences by cancer-  and treatment-related variables. Personal income was compared by occupation. Employed survivors were less often in higher-skilled Managerial/Professional occupations (relative risk, 0.93; 95% confidence interval 0.89-0.98) than their siblings. Survivors who were black, were diagnosed at a younger age, or had high-dose cranial radiation were less likely to hold Managerial/Professional occupations than other survivors. In multinomial models, female survivors' likelihood of being in full-time Managerial/Professional occupations (27%) was lower than male survivors (42%) and female (41%) and male (50%) siblings. Survivors' personal income was lower than siblings within each of the 3 occupational categories in models adjusted for sociodemographic variables. Adult childhood cancer survivors are employed in lower-skill jobs than siblings. Survivors with certain treatment histories are at higher risk for lower-skill jobs and may require vocational assistance throughout adulthood. Copyright © 2011 American Cancer Society.

Can We Determine Sasang Constitutional Body Type Merely by Facial Inspection?

PubMed

Rhee, Seung Chul; Bae, Hyo-Sang; Lee, Yung-Seop; Hwang, Rahil

2017-05-01

This study aimed to assess the inter-observer concordance rate of anthroscopic examination on facial features among experts in Sasang constitutional medicine (SCM) in order to evaluate the presence of statistical differences in facial structural characteristics among different body types of Sasang constitution (SC), and to develop an objective method for facial analysis for diagnosing SC types to prevent SCM experts from misdiagnosis by their perceptional errors about faces. This was a double-blinded cross-sectional study conducted on 174 people's faces. Ten SCM experts participated in this study. Frontal and lateral photographs of subjects were standardized and displayed to 10 SCM experts for diagnosing the SC type by anthroscopic examination alone (experiment 1). The subjects' faces were analyzed by photogrammetric method to investigate the presence of any typical structural characteristics of the faces to differentiate SC type (experiment 2). Comparing subjects' SC type with anthroscopic diagnosis by 10 SCM experts, the inter-observer concordance rates were measured (experiment 1). Using photogrammetric facial analysis, a multinomial logistic model was made for analyzing the correlation of SC type and subjects' facial structural configuration (experiment 2). The inter-observer concordance rate of anthroscopic examination was 2.9% in experiment 1. Using a multinomial logistic fitting model, the predicted probability for determining SC type was 52.8-57.6% in experiment 2 (p < 0.05). Prototype composite faces were also created from photographs of subjects who received the same SC type from the SCM experts. As SC type cannot be precisely diagnosed using anthroscopic examination alone, SCM needs a definitive objective and scientific diagnosing method to be a scientifically verified alternative medicine and be globalized in future.

Childhood abuse and late-life depression: Mediating effects of psychosocial factors for early- and late-onset depression.

PubMed

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.

Quality of life of patients from rural and urban areas in Poland with head and neck cancer treated with radiotherapy. A study of the influence of selected socio-demographic factors

PubMed Central

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

Utility of an Abbreviated Dizziness Questionnaire to Differentiate between Causes of Vertigo and Guide Appropriate Referral: A Multicenter Prospective Blinded Study

PubMed Central

Roland, Lauren T.; Kallogjeri, Dorina; Sinks, Belinda C.; Rauch, Steven D.; Shepard, Neil T.; White, Judith A.; Goebel, Joel A.

2015-01-01

Objective Test performance of a focused dizziness questionnaire’s ability to discriminate between peripheral and non-peripheral causes of vertigo. Study Design Prospective multi-center Setting Four academic centers with experienced balance specialists Patients New dizzy patients Interventions A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. Main outcomes Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and non-peripheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. Results 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and non-peripheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central and other causes were considered good as measured by c-indices of 0.75, 0.7 and 0.78, respectively. Conclusions This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from non-peripheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed. PMID:26485598

Social and Demographic Factors Associated with Morbidities in Young Children in Egypt: A Bayesian Geo-Additive Semi-Parametric Multinomial Model.

PubMed

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.

Frequencies of apolipoprotein E alleles in depressed patients undergoing hemodialysis--a case-control study.

PubMed

Su, Yan-yan; Zhang, Yun-fang; Yang, Shen; Wang, Jie-lin; Hua, Bao-jun; Luo, Jie; Wang, Qi; Zeng, De-wang; Lin, Yan-qun; Li, Hong-yan

2015-06-01

To explore the relation between the frequencies of apolipoprotein E (ApoE) alleles and the occurrence of depression in patients undergoing hemodialysis in a Chinese population. We examined the ApoE alleles in a sample of 288 subjects: 72 patients with depression under hemodialysis, 74 patients without depression under hemodialysis, 75 patients with depression under nondialytic treatment and 67 patients without depression under nondialytic treatment. The depression state was assessed using the Center for Epidemiological Studies Depression (CES-D) scale. Associations between the occurrence of depression and the frequencies of ApoE alleles were examined using multinomial logistic regression models with adjustment of relevant covariates. Information about sociodemographics, clinical data, vascular risk factors and cognitive function was also collected and evaluated. The frequencies of ApoE-ɛ2 were significantly different between depressed and non-depressed patients irrespective of dialysis (p < 0.05), but no significant difference was found in the frequencies of ApoE-ɛ4 (p > 0.05). Serum ApoE levels were significantly different between depressed and non-depressed patients in the whole sample (p < 0.05). Multinomial logistic regression models showed significant association between the frequency of ApoE-ɛ2 and the occurrence of depression in the Chinese population after control of relevant covariates, including age, sex, educational level, history of smoking and drinking, vascular risk factors and cognitive function. No association between the frequency of ApoE-ɛ4 and the occurrence of depression was found in patients undergoing hemodialysis. Further research is needed to find out if ApoE-ɛ2 acts as a protective factor in Chinese dialysis population since it might decrease the prevalence of depression and delay the onset age.

Inequality in the hepatitis B awareness level in rural residents from 7 provinces in China

PubMed Central

Zheng, Juan; Li, Quan; Wang, Jian; Zhang, Guojie; Wangen, Knut R.

2017-01-01

ABSTRACT The hepatitis B (HB) awareness level is an important factor affecting the rates of HB virus vaccination. To better understand income-related inequalities in the HB awareness level, it is imperative to identify the sources of inequalities and assess the contribution rates of these influential factors. This study analyzed the unequal distribution of the HB awareness level and the contributions of various influential factors. We performed a cross-sectional household survey with questionnaire-based, face-to-face interviews in 7 Chinese provinces. Responses from 7271 respondents were used in this analysis. Multinomial logistic regression was used for the analysis of contributing factors, and the concentration index was used as a measure of HB awareness inequalities. The HB awareness level varied across participants with different characteristics. Multinomial logistic regression of the explanatory factors of the HB awareness level showed that several estimated coefficients and relative risk ratios were statistically significant for middle- and high-level awareness, except for sex, occupation, and household income. The concentration index of the HB knowledge score was 0.140, indicating inequality gradients disadvantageous to the poor. The contribution rate of socioeconomic factors was the largest (60.8%), followed by demographic characteristics (29.0%) and geographic factors (4.3%). Demographic, socioeconomic, and geographic factors are associated with the HB awareness inequality. Therefore, to reduce inequality, HB-related health education targeting individuals with low socioeconomic status should be performed. Less-developed provinces, especially with high proportions of poor residents, warrant particular attention. Our findings may be beneficial to improve the HB virus vaccination rate for individuals with low socioeconomic status. PMID:28277091

Drinking Patterns and Victimization among Male and Female Students in Mexico

PubMed Central

Strunin, Lee; Díaz-Martínez, L. Rosa; Díaz-Martínez, Alejandro; Heeren, Timothy; Winter, Michael; Kuranz, Seth; Hernández–Ávila, Carlos A.; Fernández-Varela, Héctor; Solís-Torres, Cuauhtémoc

2015-01-01

Aims: The purpose of this study is to estimate the prevalence of alcohol use and alcohol-related consequences, identify drinking profiles using latent profile analysis (LPA), and investigate associations between profiles and violent victimization among young people in Mexico. Methods: LPA identified profiles of drinking behavior in a survey of entering first year university students. Multinomial and logistic regression examined associations between drinking patterns, socio-demographic variables and violent victimization. Results: The LPA identified five profiles of behaviors and consequences among the 22,224 current, former and never drinkers: Non/Infrequent-No Consequences, Occasional-Few Consequences, Regular-Some Consequences, Heavy-Many Consequences and Excessive-Many Consequences drinkers. The Occasional-Few Consequences profile comprised the largest, and the Excessive-Many Consequences profile the smallest, group of drinkers. Multinomial regression showed males and older students more likely to be Heavy or Excessive-Many Consequences drinkers. Living alone was associated with higher odds, and higher maternal education with lower odds, of being a Non/Infrequent-No Consequences drinker. Heavier drinking profiles were more likely to experience violent victimization adverse consequences. Logistic regression showed male and female Heavy and Excessive-Many Consequences drinkers had the highest odds, and Non/Infrequent drinkers the lowest odds, of experiencing any victimization. Conclusion: Findings suggest changes in male and female drinking behavior and a continuation of the established pattern of infrequent but high consumption among Mexican youths. Both male and female Heavy and Excessive-Many Consequences drinkers were at elevated risk for experiencing victimization. Identifying cultural gender norms about drinking including drinker expectations and drinking context that contribute to these patterns can inform prevention efforts. PMID:25534933

Opinions About Electronic Cigarette Use in Smoke-Free Areas Among U.S. Adults, 2012

PubMed Central

Dube, Shanta R.; Sterling, Kymberle; Whitney, Carrie; Eriksen, Michael P.

2015-01-01

Introduction: In the United States, electronic cigarettes (e-cigarettes) are currently unregulated, extensively marketed, and experiencing a rapid increase in use. The purpose of this study was to examine the opinions of U.S. adults about e-cigarette use in smoke-free public areas. Methods: Data were obtained from the online HealthStyle survey administered to a probability sample of a nationally representative online panel. The study included 4,043U.S. adults, aged 18 years or older who responded to this question, “Do you think e-cigarette should be allowed to be used in public areas where tobacco smoking is prohibited?” Multinomial logistic regression analyses were used to examine opinions on e-cigarette use in smoke-free areas by sex, age, race/ethnicity, household income, education, census region, and cigarette smoking status and e-cigarette awareness and ever use. Results: Overall, about 40% of adults were uncertain whether e-cigarettes should be allowed in smoke-free areas, 37% opposed, while 23% favored their use in smoke-free public places. Multinomial logistic regression analyses showed that adults who were aware, ever used e-cigarettes, and current cigarette smokers were more likely to express an “in favor” opinion than adults who expressed an uncertain opinion (don’t know). Conclusion: Over 75% of U.S. adults reported uncertainty or disapproval of the use of e-cigarettes in smoke-free areas. Current cigarette smokers, adults aware or have ever used e-cigarettes were more supportive to exempting e-cigarettes from smoking restrictions. With impending regulation and the changing e-cigarette landscape, continued monitoring and research on public opinions about e-cigarette use in smoke-free places are needed. PMID:25358659

Constipation and Incident CKD

PubMed Central

Sumida, Keiichi; Molnar, Miklos Z.; Potukuchi, Praveen K.; Thomas, Fridtjof; Lu, Jun Ling; Matsushita, Kunihiro; Yamagata, Kunihiro; Kalantar-Zadeh, Kamyar

2017-01-01

Constipation is one of the most prevalent conditions in primary care settings and increases the risk of cardiovascular disease, potentially through processes mediated by altered gut microbiota. However, little is known about the association of constipation with CKD. In a nationwide cohort of 3,504,732 United States veterans with an eGFR ≥60 ml/min per 1.73 m2, we examined the association of constipation status and severity (absent, mild, or moderate/severe), defined using diagnostic codes and laxative use, with incident CKD, incident ESRD, and change in eGFR in Cox models (for time-to-event analyses) and multinomial logistic regression models (for change in eGFR). Among patients, the mean (SD) age was 60.0 (14.1) years old; 93.2% of patients were men, and 24.7% were diabetic. After multivariable adjustments, compared with patients without constipation, patients with constipation had higher incidence rates of CKD (hazard ratio, 1.13; 95% confidence interval [95% CI], 1.11 to 1.14) and ESRD (hazard ratio, 1.09; 95% CI, 1.01 to 1.18) and faster eGFR decline (multinomial odds ratios for eGFR slope <−10, −10 to <−5, and −5 to <−1 versus −1 to <0 ml/min per 1.73 m2 per year, 1.17; 95% CI, 1.14 to 1.20; 1.07; 95% CI, 1.04 to 1.09; and 1.01; 95% CI, 1.00 to 1.03, respectively). More severe constipation associated with an incrementally higher risk for each renal outcome. In conclusion, constipation status and severity associate with higher risk of incident CKD and ESRD and with progressive eGFR decline, independent of known risk factors. Further studies should elucidate the underlying mechanisms. PMID:28122944

Trajectories of Childbearing among HIV Infected Indian Women: A Sequence Analysis Approach

PubMed Central

Darak, Shrinivas; Mills, Melinda; Kulkarni, Vinay; Kulkarni, Sanjeevani; Hutter, Inge; Janssen, Fanny

2015-01-01

Background HIV infection closely relates to and deeply affects the reproductive career of those infected. However, little is known about the reproductive career trajectories, specifically the interaction of the timing of HIV diagnosis with the timing and sequencing of reproductive events among HIV infected women. This is the first study to describe and typify this interaction. Methods Retrospective calendar data of ever married HIV infected women aged 15-45 attending a HIV clinic in Pune, Maharashtra, Western India (N=622) on reproductive events such as marriage, cohabitation with the partner, use of contraception, pregnancy, childbirth and HIV diagnosis were analyzed using sequence analysis and multinomial logistic regression. Results Optimal matching revealed three distinct trajectories: 1) HIV diagnosis concurrent with childbearing (40.7%), 2) HIV diagnosis after childbearing (32.1%), and 3) HIV diagnosis after husband’s death (27.2%). Multinomial logistic regression (trajectory 1 = baseline) showed that women who got married before the age of 21 years and who had no or primary level education had a significantly higher risk of knowing their HIV status either after childbearing or close to their husband’s death. The risk of HIV diagnosis after husband’s death was also higher among rural women and those who were diagnosed before 2005. Conclusions Three distinct patterns of interaction of timing of HIV diagnosis with timing and sequencing of events in the reproductive career were observed that have clear implications for (i) understanding of the individual life planning process in the context of HIV, (ii) formulation of assumptions for estimating HIV infected women in need of PMTCT services, and (iii) provision of care services. PMID:25906185

No compelling positive association between ovarian hormones and wearing red clothing when using multinomial analyses.

PubMed

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.

Weather impacts on single-vehicle truck crash injury severity.

PubMed

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.

The Relationship Between Developmental Assets and Food Security In Adolescents From A Low-Income Community

PubMed Central

Shtasel-Gottlieb, Zoë; Palakshappa, Deepak; Yang, Fanyu; Goodman, Elizabeth

2014-01-01

Purpose To explore the association between developmental assets (characteristics, experiences, and relationships that shape healthy development) and food insecurity among adolescents from a low-income, urban community. Methods This mixed methods study occurred in two phases. In Phase 1, using a census approach, 2350 6-12th graders from the public school district completed an anonymous survey that included the Development Assets Profile (DAP), youth self-report form of the Core Food Security Module, and demographic questions. Logistic and multinomial regression analyses determined independent associations between developmental assets and food security adjusting for demographics. In Phase 2, 20 adult key informant interviews and four semi-structured student focus groups were performed to explain findings from Phase 1. Results On average, DAP scores were consistent with national norms. Food insecurity was prevalent; 14.9% reported low food security and 8.6% very low food security (VLFS). Logistic regression revealed that higher DAP was associated with lower odds of food insecurity (OR=.96, 95% CI=.95-.97); family assets drove this association(OR=.93, 95% CI=.91-.95). In multinomial regression modeling, these associations persisted and, paradoxically, higher community assets were also associated with VLFS (ORVLFS=1.08, 95% CI=1.04-1.13). Qualitative analyses suggested that greater need among VLFS youth led to increased connections to community resources despite barriers to access such as stigma, home instability, and cultural differences. Conclusion Food insecurity is a pervasive problem among adolescents from low-income communities and is associated with lower developmental assets, particularly family assets. That community assets were higher among VLFS youth underscores the importance of community-level resources in struggling areas. PMID:25620305

The relationship between developmental assets and food security in adolescents from a low-income community.

PubMed

Shtasel-Gottlieb, Zoë; Palakshappa, Deepak; Yang, Fanyu; Goodman, Elizabeth

2015-02-01

To explore the association between developmental assets (characteristics, experiences, and relationships that shape healthy development) and food insecurity among adolescents from a low-income urban community. This mixed-methods study occurred in two phases. In phase 1, using a census approach, 2,350 6th to 12th graders from the public school district completed an anonymous survey that included the developmental assets profile (DAP), the youth self-report form of the Core Food Security Module, and demographic questions. Logistic and multinomial regression analyses determined independent associations between developmental assets and food security adjusting for demographics. In phase 2, 20 adult key informant interviews and four semistructured student focus groups were performed to explain findings from phase 1. On average, DAP scores were consistent with national norms. Food insecurity was prevalent; 14.9% reported low food security and 8.6% very low food security (VLFS). Logistic regression revealed that higher DAP was associated with lower odds of food insecurity (odds ratio [OR], .96; 95% confidence interval [CI], .95-.97); family assets drove this association (OR, .93; 95% CI, .91-.95). In multinomial regression modeling, these associations persisted, and paradoxically, higher community assets were also associated with VLFS (ORVLFS, 1.08; 95% CI, 1.04-1.13). Qualitative analyses suggested that greater need among VLFS youth led to increased connections to community resources despite barriers to access such as stigma, home instability, and cultural differences. Food insecurity is a pervasive problem among adolescents from low-income communities and is associated with lower developmental assets, particularly family assets. The fact that community assets were higher among VLFS youth underscores the importance of community-level resources in struggling areas. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Risk factors associated with recurrent homelessness after a first homeless episode.

PubMed

McQuistion, Hunter L; Gorroochurn, Prakash; Hsu, Eustace; Caton, Carol L M

2014-07-01

Alcohol and drug use are commonly associated with the experience of homelessness. In order to better understand this, we explored the prevalence of drug and alcohol use as it related to successful re-housing within a sample of first-time single homeless adults at municipal shelters. From within this sample, we compared the features of recurrent homelessness with those of chronic homelessness and of being stably housed. We interviewed 344 subjects upon shelter entry and followed each one every six months for 18 months using standardized social and mental health measures. We analyzed baseline assessments relative to housing experiences during follow-up using Chi square and multinomial logistic regression. Eighty-one percent (N = 278) obtained housing over 18 months, of which 23.7 % (N = 66) experienced homelessness again. Recurrent homelessness was more common among those with a high school education and if initially re-housed with family. Bivariate analysis resulted in the observation of the highest rate of alcohol and other drug use among this recurrent group and multinomial logistic regression supported this only with the coupling of arrest history and diagnosed antisocial personality disorder. With relatively high rates of recurrent homelessness, there were differences between subjects who experienced recurrent homelessness compared to those who were stably housed and with chronic homelessness. That alcohol and other substance use disorders were associated with recurrent homelessness only if they were linked to other risk factors highlights the complexity of causes for homelessness and a resultant need to organize them into constellations of causal risk factors. Consistent with this, there should be initiatives that span bureaucratic boundaries so as to flexibly meet multiple complex service needs, thus improving outcomes concerning episodes of recurrent homelessness.

Associations Between Perceived Race-based Discrimination and Contraceptive Use Among Women Veterans in the ECUUN Study.

PubMed

MacDonald, Serena; Hausmann, Leslie R M; Sileanu, Florentina E; Zhao, Xinhua; Mor, Maria K; Borrero, Sonya

2017-09-01

To describe perceived race-based discrimination in Veterans Affairs (VA) health care settings and assess its associations with contraceptive use among a sample of women Veterans. This study used data from a national telephone survey of women Veterans aged 18-44 receiving health care in VA who were at risk of unintended pregnancy. Participants were asked about their perceptions of race-based discrimination while seeking VA health care and about their contraceptive use at last heterosexual intercourse. Logistic and multinomial regression analyses were used to examine associations between perceived race-based discrimination with use of prescription contraception. In our sample of 1341 women Veterans, 7.9% report perceived race-based discrimination when receiving VA care, with blacks and Hispanics reporting higher levels of perceived discrimination than white women (11.3% and 11.2% vs. 4.4%; P<0.001). In logistic and multinomial regression analyses adjusting for race/ethnicity, age, income, marital status, parity, and insurance, women who perceived race-based discrimination were less likely to use any prescription birth control than women who did not (odds ratio, 0.65; 95% confidence interval, 0.42-1.00), with the largest difference seen in rates of intrauterine device or implant use (odds ratio, 0.40; 95% confidence interval, 0.20-0.79). In this national sample of women Veterans, over 10% of racial/ethnic minority women perceived race-based discrimination when receiving care in VA settings, and perceived racial/ethnic discrimination was associated with lower likelihood of prescription contraception use, especially intrauterine devices and implants. VA efforts to enhance respectful interactions may not only improve patient health care experiences, but also represent an opportunity to improve reproductive health outcomes for women Veterans.

Using a multinomial tree model for detecting mixtures in perceptual detection

PubMed Central

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

LGALS4, CEACAM6, TSPAN8, and COL1A2: Blood Markers for Colorectal Cancer-Validation in a Cohort of Subjects With Positive Fecal Immunochemical Test Result.

PubMed

Rodia, Maria Teresa; Solmi, Rossella; Pasini, Francesco; Nardi, Elena; Mattei, Gabriella; Ugolini, Giampaolo; Ricciardiello, Luigi; Strippoli, Pierluigi; Miglio, Rossella; Lauriola, Mattia

2018-06-01

A noninvasive blood test for the early detection of colorectal cancer (CRC) is highly required. We evaluated a panel of 4 mRNAs as putative markers of CRC. We tested LGALS4, CEACAM6, TSPAN8, and COL1A2, referred to as the CELTiC panel, using quantitative reverse transcription polymerase chain reaction, on subjects with positive fecal immunochemical test (FIT) results and undergoing colonoscopy. Using a nonparametric test and multinomial logistic model, FIT-positive subjects were compared with CRC patients and healthy individuals. All the genes of the CELTiC panel displayed statistically significant differences between the healthy subjects (n = 67), both low-risk (n = 36) and high-risk/CRC (n = 92) subjects, and those in the negative-colonoscopy, FIT-positive group (n = 36). The multinomial logistic model revealed LGALS4 was the most powerful marker discriminating the 4 groups. When assessing the diagnostic values by analysis of the areas under the receiver operating characteristic curves (AUCs), the CELTiC panel reached an AUC of 0.91 (sensitivity, 79%; specificity, 94%) comparing normal subjects to low-risk subjects, and 0.88 (sensitivity, 75%; specificity, 87%) comparing normal and high-risk/CRC subjects. The comparison between the normal subjects and the negative-colonoscopy, FIT-positive group revealed an AUC of 0.93 (sensitivity, 82%; specificity, 97%). The CELTiC panel could represent a useful tool for discriminating subjects with positive FIT findings and for the early detection of precancerous adenomatous lesions and CRC. Copyright © 2017 Elsevier Inc. All rights reserved.

The Effect of Task Duration on Event-Based Prospective Memory: A Multinomial Modeling Approach

PubMed Central

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

A Walk (or Cycle) to the Park: Active Transit to Neighborhood Amenities, the CARDIA Study

PubMed Central

Boone-Heinonen, Janne; Jacobs, David R.; Sidney, Stephen; Sternfeld, Barbara; Lewis, Cora E.; Gordon-Larsen, Penny

2009-01-01

Background Building on known associations between active commuting and reduced cardiovascular disease (CVD) risk, this study examines active transit to neighborhood amenities and differences between walking versus cycling for transportation. Method Year 20 data from the Coronary Artery Risk Development in Young Adults (CARDIA) study (3549 black and white adults aged 38–50 years in 2005–06) were analyzed in 2008–2009. Sociodemographic correlates of transportation mode (car-only, walk-only, any cycling, other) to neighborhood amenities were examined in multivariable multinomial logistic models. Gender-stratified, multivariable linear or multinomial regression models compared CVD risk factors across transit modes. Results Active transit was most common to parks and public transit stops; walking was more common than cycling. Among those who used each amenity, active transit (walk-only and any cycling versus car-only transit) was more common in men and those with no live-in partner and less than full-time employment [significant OR's (95% CI) ranging from 1.56 (1.08, 2.27) to 4.52 (1.70, 12.14)], and less common in those with children. Active transit to any neighborhood amenity was associated with more favorable BMI, waist circumference, and fitness [largest coefficient (95% CI) −1.68 (−2.81, −0.55) for BMI, −3.41 (−5.71, −1.11) for waist circumference (cm), and 36.65 (17.99, 55.31) for treadmill test duration (sec)]. Only cycling was associated with lower lifetime CVD risk classification. Conclusion Active transit to neighborhood amenities was related to sociodemographics and CVD risk factors. Variation in health-related benefits by active transit mode, if validated in prospective studies, may have implications for transportation planning and research. PMID:19765499

Divergent Preferences for HIV Prevention: A Discrete Choice Experiment for Multipurpose HIV Prevention Products in South Africa.

PubMed

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.

The heterogeneous health latent classes of elderly people and their socio-demographic characteristics in Taiwan.

PubMed

Liu, Li-Fan; Tian, Wei-Hua; Yao, Hui-Ping

2014-01-01

The health care needs of elderly people were influenced by their heterogeneity. This study aimed to identify the health latent classes of elderly people by using latent class analysis to deal with heterogeneity and examine their socio-demographic characteristics. Data came from the 2005 National Health Interview Survey (NHIS) in Taiwan. In total, 2449 elderly individuals with available health indicators were examined in latent class analysis (LCA), and 2217 elderly community-dwellings with complete socio-demographic data were analyzed by multinomial logistic regression. Four health latent classes were identified which included 1066 (43.5%) people in the High Comorbidity (HC), 152 (6.2%) in the Functional Impairment (FI), 252 (10.3%) in the Frail (FR), and 979 (40.0%) in the Relatively Healthy (RH) group. Multinomial logistic regressions revealed socio-demographic characteristics among health classes. The variables associated with an increased likelihood of being in the FR group were age, female, and living with families. They were also correlated to ethnicity and educations. Apart from age and gender, the Functional Impairment group was less likely to be ethnicity of Hakka, more likely to live with others than were the RH group. The HC group tended to be younger, with higher educations, and more likely to live in urban area than the Functional Impairment group. The correlations between health classes and socio-demographic factors were discussed. The health status of elderly people includes a variety of health indicators. A person-centered approach is critical to identify the health heterogeneity of elderly people and manage their care needs by targeting differential aging. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A cross-sectional study of the association of age, race and ethnicity, and body mass index with sex steroid hormone marker profiles among men in the National Health and Nutrition Examination Survey (NHANES III)

PubMed Central

Ritchey, Jamie; Karmaus, Wilfried; Sabo-Attwood, Tara; Steck, Susan E; Zhang, Hongmei

2012-01-01

Objectives Since sex hormone markers are metabolically linked, examining sex steroid hormones singly may account for inconsistent findings by age, race/ethnicity and body mass index (BMI) across studies. First, these markers were statistically combined into profiles to account for the metabolic relationship between markers. Then, the relationships between sex steroid hormone profiles and age, race/ethnicity and BMI were explored in multinomial logistic regression models. Design Cross-sectional survey. Setting The US Third National Health and Nutrition Examination Survey (NHANES III). Participants 1538 Men, >17 years. Primary outcome measure Sex hormone profiles. Results Cluster analysis was used to identify four statistically determined profiles with Blom-transformed T, E, sex hormone binding globulin (SHBG), and 3-α diol G. We used these four profiles with multinomial logistic regression models to examine differences by race/ethnicity, age and BMI. Mexican American men >50 years were associated with the profile that had lowest T, E and 3-α diol G levels compared to other profiles (p<0.05). Non-Hispanic Black, overweight (25–29.9 kg/m2) and obese (>30 kg/m2) men were most likely to be associated with the cluster with the lowest SHBG (p<0.05). Conclusion The associations of sex steroid hormone profiles by race/ethnicity are novel, while the findings by age and BMI groups are largely consistent with observations from single hormone studies. Future studies should validate these hormone profile groups and investigate these profiles in relation to chronic diseases and certain cancers. PMID:23043125

Utility of an Abbreviated Dizziness Questionnaire to Differentiate Between Causes of Vertigo and Guide Appropriate Referral: A Multicenter Prospective Blinded Study.

PubMed

Roland, Lauren T; Kallogjeri, Dorina; Sinks, Belinda C; Rauch, Steven D; Shepard, Neil T; White, Judith A; Goebel, Joel A

2015-12-01

Test performance of a focused dizziness questionnaire's ability to discriminate between peripheral and nonperipheral causes of vertigo. Prospective multicenter. Four academic centers with experienced balance specialists. New dizzy patients. A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and nonperipheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. In total, 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and nonperipheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central, and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central, and other causes was considered good as measured by c-indices of 0.75, 0.7, and 0.78, respectively. This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from nonperipheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed.

Quality and price--impact on patient satisfaction.

PubMed

Pantouvakis, Angelos; Bouranta, Nancy

2014-01-01

The purpose of this paper is to synthesize existing quality-measurement models and applies them to healthcare by combining a Nordic service-quality with an American service performance model. Results are based on a questionnaire survey of 1,298 respondents. Service quality dimensions were derived and related to satisfaction by employing a multinomial logistic model, which allows prediction and service improvement. Qualitative and empirical evidence indicates that customer satisfaction and service quality are multi-dimensional constructs, whose quality components, together with convenience and cost, influence the customer's overall satisfaction. The proposed model identifies important quality and satisfaction issues. It also enables transitions between different responses in different studies to be compared.

Factors Associated with Adoption and Adoption Intentions of Nonparental Caregivers

PubMed Central

Bramlett, Matthew D.; Radel, Laura F.

2016-01-01

Data from the 2011–2012 National Survey of Children’s Health and the 2013 National Survey of Children in Nonparental Care were used to fit a multinomial logistic model comparing three groups to those who never considered adoption: those who ever considered, but are not currently planning adoption; those planning adoption; and those who adopted. Adoption may be more likely when the caregiver is a nonkin foster parent, a foster care agency was involved, and/or financial assistance is available. Those with plans to adopt but who have not adopted may face adoption barriers such as extreme poverty, lower education and being unmarried. PMID:26949328

ABrox-A user-friendly Python module for approximate Bayesian computation with a focus on model comparison.

PubMed

Mertens, Ulf Kai; Voss, Andreas; Radev, Stefan

2018-01-01

We give an overview of the basic principles of approximate Bayesian computation (ABC), a class of stochastic methods that enable flexible and likelihood-free model comparison and parameter estimation. Our new open-source software called ABrox is used to illustrate ABC for model comparison on two prominent statistical tests, the two-sample t-test and the Levene-Test. We further highlight the flexibility of ABC compared to classical Bayesian hypothesis testing by computing an approximate Bayes factor for two multinomial processing tree models. Last but not least, throughout the paper, we introduce ABrox using the accompanied graphical user interface.

Effects of public premiums on children's health insurance coverage: evidence from 1999 to 2003.

PubMed

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.

Social factors, weight perception, and weight control practices among adolescents in Mexico.

PubMed

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.

Choice of contracts in the British National Health Service: an empirical study.

PubMed

Chalkley, Martin; McVicar, Duncan

2008-09-01

Following major reforms of the British National Health Service (NHS) in 1990, the roles of purchasing and providing health services were separated, with the relationship between purchasers and providers governed by contracts. Using a mixed multinomial logit analysis, we show how this policy shift led to a selection of contracts that is consistent with the predictions of a simple model, based on contract theory, in which the characteristics of the health services being purchased and of the contracting parties influence the choice of contract form. The paper thus provides evidence in support of the practical relevance of theory in understanding health care market reform.

Burden and predictors of Staphylococcus aureus and S. pseudintermedius infections among dogs presented at an academic veterinary hospital in South Africa (2007–2012)

PubMed Central

Oguttu, James Wabwire; Sithole, Fortune

2017-01-01

Background Staphylococci are commensals of the mucosal surface and skin of humans and animals, but have been implicated in infections such as otitis externa, pyoderma, urinary tract infections and post-surgical complications. Laboratory records provide useful information to help investigate these infections. Therefore, the objective of this study was to investigate the burdens of these infections and use multinomial regression to examine the associations between various Staphylococcus infections and demographic and temporal factors among dogs admitted to an academic veterinary hospital in South Africa. Methods Records of 1,497 clinical canine samples submitted to the bacteriology laboratory at a veterinary academic hospital between 2007 and 2012 were included in this study. Proportions of staphylococcal positive samples were calculated, and a multinomial logistic regression model was used to identify predictors of staphylococcal infections. Results Twenty-seven percent of the samples tested positive for Staphylococcus spp. The species of Staphylococcus identified were S. pseudintermedius (19.0%), S. aureus (3.8%), S. epidermidis (0.7%) and S. felis (0.1%). The remaining 2.87% consisted of unspeciated Staphylococcus. Distribution of the species by age of dog showed that S. pseudintermedius was the most common (25.6%) in dogs aged 2–4 years while S. aureus was most frequent (6.3%) in dogs aged 5–6 years. S. pseudintermedius (34.1%) and S. aureus (35.1%) were the most frequently isolated species from skin samples. The results of the multivariable multinomial logistic regression model identified specimen, year and age of the dog as significant predictors of the risk of infection with Staphylococcus. There was a significant temporal increase (RRR = 1.17; 95% CI [1.06–1.29]) in the likelihood of a dog testing positive for S. pseudintermedius compared to testing negative. Dogs ≤ 8 years of age were significantly more likely to test positive for S. aureus than those >8 years of age. Similarly, dogs between 2–8 years of age were significantly more likely to test positive for S. pseudintermedius than those >8 years of age. In addition, dogs 2–4 years of age (RRR = 1.83; 1.09–3.06) were significantly more likely to test positive for S. pseudintermedius compared to those <2 years of age. The risk of infection with S. pseudintermedius or S. aureus was significantly higher in ear canal and skin specimens compared to other specimens. Conclusions The findings suggest that S. pseudintermedius and S. aureus were the most commonly isolated species from dogs presented at the study hospital. Age of the dog and the location of infection were significant predictors of infection with both Staphylococcus species investigated. Significant increasing temporal trend was observed for S. pseudintermedius but not S. aureus. This information is useful for guiding clinical decisions as well as future research. PMID:28417060

Age-specific population frequencies of amyloidosis and neurodegeneration among cognitively normal people age 50-89 years: a cross-sectional study

PubMed Central

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

Alcohol use among university students: Considering a positive deviance approach.

PubMed

Tucker, Maryanne; Harris, Gregory E

2016-09-01

Harmful alcohol consumption among university students continues to be a significant issue. This study examined whether variables identified in the positive deviance literature would predict responsible alcohol consumption among university students. Surveyed students were categorized into three groups: abstainers, responsible drinkers and binge drinkers. Multinomial logistic regression modelling was significant (χ(2) = 274.49, degrees of freedom = 24, p < .001), with several variables predicting group membership. While the model classification accuracy rate (i.e. 71.2%) exceeded the proportional by chance accuracy rate (i.e. 38.4%), providing further support for the model, the model itself best predicted binge drinker membership over the other two groups. © The Author(s) 2015.

Volume integrals associated with the inhomogeneous Helmholtz equation. Part 1: Ellipsoidal region

NASA Technical Reports Server (NTRS)

Fu, L. S.; Mura, T.

1983-01-01

Problems of wave phenomena in fields of acoustics, electromagnetics and elasticity are often reduced to an integration of the inhomogeneous Helmholtz equation. Results are presented for volume integrals associated with the Helmholtz operator, nabla(2) to alpha(2), for the case of an ellipsoidal region. By using appropriate Taylor series expansions and multinomial theorem, these volume integrals are obtained in series form for regions r 4' and r r', where r and r' are distances from the origin to the point of observation and source, respectively. Derivatives of these integrals are easily evaluated. When the wave number approaches zero, the results reduce directly to the potentials of variable densities.

Area variations in multiple morbidity using a life table methodology.

PubMed

Congdon, Peter

Analysis of healthy life expectancy is typically based on a binary distinction between health and ill-health. By contrast, this paper considers spatial modelling of disease free life expectancy taking account of the number of chronic conditions. Thus the analysis is based on population sub-groups with no disease, those with one disease only, and those with two or more diseases (multiple morbidity). Data on health status is accordingly modelled using a multinomial likelihood. The analysis uses data for 258 small areas in north London, and shows wide differences in the disease burden related to multiple morbidity. Strong associations between area socioeconomic deprivation and multiple morbidity are demonstrated, as well as strong spatial clustering.

A Typology of Violence against Self and Others and Its Associations with Drinking and Other Drug Use among High School Students in a U.S. General Population Survey

PubMed Central

Harford, Thomas C.; Yi, Hsiao-ye; Freeman, Robert C.

2015-01-01

This study examined associations between binge drinking and other substance use and perpetration of violence against self and others. Data were pooled from the 2003, 2005, and was constructed to reflect four categories of behaviors: other-directed violence only, self-directed violence only, combined other- and self-directed violence, and no violence. Results from multinomial logistic regressions show that the frequency of binge drinking and other substance use were significant risk factors for each of the violence categories relative to no-violence. However, the strengths of these associations varied across the violence categories. PMID:26478688

Effects of ignoring baseline on modeling transitions from intact cognition to dementia.

PubMed

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.

Dietary and exercise change following acute cardiac syndrome onset: A latent class growth modelling analysis.

PubMed

Bennett, Paul; Gruszczynska, Ewa; Marke, Victoria

2016-10-01

The present study aim determine sub-group trajectories of change on measures of diet and exercise following acute coronary syndrome. 150 participants were assessed in hospital, 1 month and 6 months subsequently on measures including physical activity, diet, illness beliefs, coping and mood. Change trajectories were measured using latent class growth modelling. Multinomial logistic regression was used to predict class membership. These analyses revealed changes in exercise were confined to a sub-group of participants already reporting relatively high exercise levels; those eating less healthily evidenced modest dietary improvements. Coping, gender, depression and perceived control predicted group membership to a modest degree. © The Author(s) 2015.

Poverty and Material Hardship in Grandparent-Headed Households.

PubMed

Baker, Lindsey A; Mutchler, Jan E

2010-08-01

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 grandparent-headed households experience elevated risk of health insecurity (as measured by receipt of public insurance and uninsurance)-a disproportionate risk given rates of poverty within those households. Children living with single parents did not share this substantial risk. Risk of food and housing insecurity did not differ significantly from 2-parent households once characteristics of the household and caregivers were taken into account.

Bayesian multimodel inference for dose-response studies

USGS Publications Warehouse

Link, W.A.; Albers, P.H.

2007-01-01

Statistical inference in dose?response studies is model-based: The analyst posits a mathematical model of the relation between exposure and response, estimates parameters of the model, and reports conclusions conditional on the model. Such analyses rarely include any accounting for the uncertainties associated with model selection. The Bayesian inferential system provides a convenient framework for model selection and multimodel inference. In this paper we briefly describe the Bayesian paradigm and Bayesian multimodel inference. We then present a family of models for multinomial dose?response data and apply Bayesian multimodel inferential methods to the analysis of data on the reproductive success of American kestrels (Falco sparveriuss) exposed to various sublethal dietary concentrations of methylmercury.

Value of arsenic-free drinking water to rural households in Bangladesh.

PubMed

Ahmad, Junaid; Goldar, Bishwanath; Misra, Smita

2005-01-01

Using contingent valuation survey data for about 2700 households in rural Bangladesh, and applying a multinomial logit model, the paper estimates the value of arsenic-free drinking water to the rural people. The estimates indicate that the rural people in arsenic-affected areas of Bangladesh place a low value on arsenic-free drinking water. It is about 10-14 percent of the amount they are willing to pay for piped water and only about 0.2-0.3 percent of the average household income. The implication of the result is that robust but costly arsenic reduction technologies such as activated alumina technology may find little social acceptance, unless heavily subsidized.

A note on power and sample size calculations for the Kruskal-Wallis test for ordered categorical data.

PubMed

Fan, Chunpeng; Zhang, Donghui

2012-01-01

Although the Kruskal-Wallis test has been widely used to analyze ordered categorical data, power and sample size methods for this test have been investigated to a much lesser extent when the underlying multinomial distributions are unknown. This article generalizes the power and sample size procedures proposed by Fan et al. ( 2011 ) for continuous data to ordered categorical data, when estimates from a pilot study are used in the place of knowledge of the true underlying distribution. Simulations show that the proposed power and sample size formulas perform well. A myelin oligodendrocyte glycoprotein (MOG) induced experimental autoimmunce encephalomyelitis (EAE) mouse study is used to demonstrate the application of the methods.

Latent spatial models and sampling design for landscape genetics

USGS Publications Warehouse

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.

Added sugars and periodontal disease in young adults: an analysis of NHANES III data.

PubMed

Lula, Estevam C O; Ribeiro, Cecilia C C; Hugo, Fernando N; Alves, Cláudia M C; Silva, Antônio A M

2014-10-01

Added sugar consumption seems to trigger a hyperinflammatory state and may result in visceral adiposity, dyslipidemia, and insulin resistance. These conditions are risk factors for periodontal disease. However, the role of sugar intake in the cause of periodontal disease has not been adequately studied. We evaluated the association between the frequency of added sugar consumption and periodontal disease in young adults by using NHANES III data. Data from 2437 young adults (aged 18-25 y) who participated in NHANES III (1988-1994) were analyzed. We estimated the frequency of added sugar consumption by using food-frequency questionnaire responses. We considered periodontal disease to be present in teeth with bleeding on probing and a probing depth ≥3 mm at one or more sites. We evaluated this outcome as a discrete variable in Poisson regression models and as a categorical variable in multinomial logistic regression models adjusted for sex, age, race-ethnicity, education, poverty-income ratio, tobacco exposure, previous diagnosis of diabetes, and body mass index. A high consumption of added sugars was associated with a greater prevalence of periodontal disease in middle [prevalence ratio (PR): 1.39; 95% CI: 1.02, 1.89] and upper (PR: 1.42; 95% CI: 1.08, 1.85) tertiles of consumption in the adjusted Poisson regression model. The upper tertile of added sugar intake was associated with periodontal disease in ≥2 teeth (PR: 1.73; 95% CI: 1.19, 2.52) but not with periodontal disease in only one tooth (PR: 0.85; 95% CI: 0.54, 1.34) in the adjusted multinomial logistic regression model. A high frequency of consumption of added sugars is associated with periodontal disease, independent of traditional risk factors, suggesting that this consumption pattern may contribute to the systemic inflammation observed in periodontal disease and associated noncommunicable diseases. © 2014 American Society for Nutrition.

Clinical, biomarker, and genetic predictors of specific types of atrial fibrillation in a community-based cohort: data of the PREVEND study.

PubMed

Hobbelt, Anne H; Siland, Joylene E; Geelhoed, Bastiaan; Van Der Harst, Pim; Hillege, Hans L; Van Gelder, Isabelle C; Rienstra, Michiel

2017-02-01

Atrial fibrillation (AF) may present variously in time, and AF may progress from self-terminating to non-self-terminating AF, and is associated with impaired prognosis. However, predictors of AF types are largely unexplored. We investigate the clinical, biomarker, and genetic predictors of development of specific types of AF in a community-based cohort. We included 8042 individuals (319 with incident AF) of the PREVEND study. Types of AF were compared, and multivariate multinomial regression analysis determined associations with specific types of AF. Mean age was 48.5 ± 12.4 years and 50% were men. The types of incident AF were ascertained based on electrocardiograms; 103(32%) were classified as AF without 2-year recurrence, 158(50%) as self-terminating AF, and 58(18%) as non-self-terminating AF. With multivariate multinomial logistic regression analysis, advancing age (P< 0.001 for all three types) was associated with all AF types, male sex was associated with AF without 2-year recurrence and self-terminating AF (P= 0.031 and P= 0.008, respectively). Increasing body mass index and MR-proANP were associated with both self-terminating (P= 0.009 and P< 0.001) and non-self-terminating AF (P= 0.003 and P< 0.001). The only predictor associated with solely self-terminating AF is prescribed anti-hypertensive treatment (P= 0.019). The following predictors were associated with non-self-terminating AF; lower heart rate (P= 0.018), lipid-lowering treatment prescribed (P= 0.009), and eGFR <60 mL/min/1.73 m2 (P= 0.006). Three known AF-genetic variants (rs6666258, rs6817105, and rs10821415) were associated with self-terminating AF. We found clinical, biomarker and genetic predictors of specific types of incident AF in a community-based cohort. The genetic background seems to play a more important role than modifiable risk factors in self-terminating AF.

Associations between the home environment and children's sweet beverage consumption at 2-year follow-up: the 'Be active, eat right' study.

PubMed

van Grieken, A; Renders, C M; van de Gaar, V M; Hirasing, R A; Raat, H

2015-04-01

This study evaluates the association between home environmental characteristics and sweet beverage consumption (i.e. beverages that contain sugar) of 7-year-old children. The population for analysis consisted of n = 2047 parents and their children from the population-based 'Be active, eat right' study. Data on sociodemographic characteristics, parental beliefs, parenting practices and child's sweet beverage consumption were obtained by parental report with questionnaires. We performed linear and multinomial regression analyses evaluating associations between characteristics at age 5 years and (i) consumption at 7 years and (ii) consumption patterns between age 5 and 7 years with reference category 'low consumption'. Based on the report from their parents, 5-year-old children drank on average 3.0 (SD:1.4) sweet beverage per day. Children consumed less sweet beverages at age 7 years (beta -0.16, 95% confidence interval [CI] -0.24 to -0.09) when there were less sweet beverages available at home. The multinomial regression model showed that children with parents who discouraged sweet beverage consumption were more likely to decrease their sweet beverage consumption over the study period (odds ratio: 1.24, 95% CI 1.07 to 1.43). Moreover, when there were less sweet beverages available at home, children were less likely to increase their consumption or have a high consumption over the study period (odds ratio: 0.70, 95% CI 0.59 to 0.83 and 0.61, 95% CI 0.54 to 0.70, respectively). The results showed that characteristics of the home environment are associated with the consumption of sweet beverages among children. Specifically, the availability of sweet beverages at home is associated with the child's sweet beverage consumption. © 2014 The Authors. Pediatric Obesity © 2014 World Obesity.

Effects of road network on diversiform forest cover changes in the highest coverage region in China: An analysis of sampling strategies.

PubMed

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.

Enzymatic Activity of Glutathione S-Transferase and Dental Fluorosis Among Children Receiving Two Different Levels of Naturally Fluoridated Water.

PubMed

Bonola-Gallardo, Irvin; Irigoyen-Camacho, María Esther; Vera-Robles, Liliana; Campero, Antonio; Gómez-Quiroz, Luis

2017-03-01

This study was conducted to measure the activity of the enzyme glutathione S-transferase (GST) in saliva and to compare the activity of this enzyme in children with and without dental fluorosis in communities with different concentrations of naturally fluoridated water. A total of 141 schoolchildren participated in this cross-sectional study. Children were selected from two communities: one with a low (0.4 ppm) and the other with a high (1.8 ppm) water fluoride concentration. Dental fluorosis was evaluated by applying the Thylstrup and Fejerskov Index (TFI) criteria. Stimulated saliva was obtained, and fluoride concentration and GST activity were measured. The GST activity was compared among children with different levels of dental fluorosis using multinomial logistic regression models and odds ratios (OR). The mean age of the children was 10.6 (±1.03) years. Approximately half of the children showed dental fluorosis (52.5 %). The average GST activity was 0.5678 (±0.1959) nmol/min/μg. A higher concentration of fluoride in the saliva was detected in children with a higher GST activity (p = 0.039). A multinomial logistic regression model used to evaluate the GST activity and the dental fluorosis score identified a strong association between TFI = 2-3 (OR = 15.44, p = 0.007) and TFI ≥ 4 (OR = 55.40, p = 0.026) and the GST activity level, compared with children showing TFI = 0-1, adjusted for age and sex. Schoolchildren with higher levels of dental fluorosis and a higher fluoride concentration in the saliva showed greater GST activity. The increased GST activity most likely was the result of the body's need to inactivate free radicals produced by exposure to fluoride.

A nonparametric multiple imputation approach for missing categorical data.

PubMed

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.

Help-seeking in people with exceptional experiences: results from a general population sample.

PubMed

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.

Can integrated health services delivery have an impact on hypertension management? A cross-sectional study in two cities of China.

PubMed

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.

Heterogeneous impact of the "Seguro Popular" program on the utilization of obstetrical services in Mexico, 2001-2006: a multinomial probit model with a discrete endogenous variable.

PubMed

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.

Investigation on occupant injury severity in rear-end crashes involving trucks as the front vehicle in Beijing area, China.

PubMed

Yuan, Quan; Lu, Meng; Theofilatos, Athanasios; Li, Yi-Bing

2017-02-01

Rear-end crashes attribute to a large portion of total crashes in China, which lead to many casualties and property damage, especially when involving commercial vehicles. This paper aims to investigate the critical factors for occupant injury severity in the specific rear-end crash type involving trucks as the front vehicle (FV). This paper investigated crashes occurred from 2011 to 2013 in Beijing area, China and selected 100 qualified cases i.e., rear-end crashes involving trucks as the FV. The crash data were supplemented with interviews from police officers and vehicle inspection. A binary logistic regression model was used to build the relationship between occupant injury severity and corresponding affecting factors. Moreover, a multinomial logistic model was used to predict the likelihood of fatal or severe injury or no injury in a rear-end crash. The results provided insights on the characteristics of driver, vehicle and environment, and the corresponding influences on the likelihood of a rear-end crash. The binary logistic model showed that drivers' age, weight difference between vehicles, visibility condition and lane number of road significantly increased the likelihood for severe injury of rear-end crash. The multinomial logistic model and the average direct pseudo-elasticity of variables showed that night time, weekdays, drivers from other provinces and passenger vehicles as rear vehicles significantly increased the likelihood of rear drivers being fatal. All the abovementioned significant factors should be improved, such as the conditions of lighting and the layout of lanes on roads. Two of the most common driver factors are drivers' age and drivers' original residence. Young drivers and outsiders have a higher injury severity. Therefore it is imperative to enhance the safety education and management on the young drivers who steer heavy duty truck from other cities to Beijing on weekdays. Copyright © 2016 Daping Hospital and the Research Institute of Surgery of the Third Military Medical University. Production and hosting by Elsevier B.V. All rights reserved.

A site specific model and analysis of the neutral somatic mutation rate in whole-genome cancer data.

PubMed

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.

An Assessment of Correlation between Dermatoglyphic Patterns and Sagittal Skeletal Discrepancies

PubMed Central

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

Determinants of postnatal care non-utilization among women in Nigeria.

PubMed

Somefun, Oluwaseyi Dolapo; Ibisomi, Latifat

2016-01-11

Although, there are several programs in place in Nigeria to ensure maternal and child health, maternal and neonatal mortality rates remain high with maternal mortality rates being 576/100,000 and neonatal mortality rates at 37/1000 live births (NDHS, 2013). While there are many studies on the utilization of maternal health services such as antenatal care and skilled delivery at birth, studies on postnatal care are limited. Therefore, the aim of this study is to examine the factors associated with the non-utilization of postnatal care among mothers in Nigeria using the Nigeria Demographic and Health Survey (NDHS) 2013. For analysis, the postnatal care uptake for 19,418 children born in the 5 years preceding the survey was considered. The dependent variable was a composite variable derived from a list of questions on postnatal care. A multinomial logistic regression model was applied to examine the adjusted and unadjusted determinants of non-utilization of postnatal care. Results from this study showed that 63% of the mothers of the 19,418 children did not utilize postnatal care services in the period examined. About 42% of the study population between 25 and 34 years did not utilize postnatal care and 61% of the women who did not utilize postnatal care had no education. Results from multinomial logistic regression show that antenatal care use, distance, education, place of delivery, region and wealth status are significantly associated with the non-utilization of postnatal care services. This study revealed the low uptake of postnatal care service in Nigeria. To increase mothers' utilization of postnatal care services and improve maternal and child health in Nigeria, interventions should be targeted at women in remote areas who don't have access to services and developing mobile clinics. In addition, it is crucial that steps should be taken on educating women. This would have a significant influence on their perceptions about the use of postnatal care services in Nigeria.

Does Smoke from Biomass Fuel Contribute to Anemia in Pregnant Women in Nagpur, India? A Cross-Sectional Study

PubMed Central

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

Adrenal venous sampling in primary aldosteronism: multinomial regression modeling to detect aldosterone secretion lateralization when right adrenal sampling is missing.

PubMed

Durivage, Camille; Blanchette, Rémi; Soulez, Gilles; Chagnon, Miguel; Gilbert, Patrick; Giroux, Marie-France; Bourdeau, Isabelle; Oliva, Vincent L; Lacroix, André; Therasse, Eric

2017-02-01

Difficulty to recognize or canulate the right adrenal vein is the most frequent cause of adrenal venous sampling (AVS) failure. We aimed to assess multinomial regression modeling (MRM) of peripheral and left adrenal vein samplings to detect lateralization of aldosterone secretion when the right AVS is missing. Simultaneous bilateral AVS samplings were performed before (basal) and after intravenous cosyntropin injection in 188 consecutive patients between December 1989 and September 2015. Different reference standards for lateralization of aldosterone secretion were defined for basal and for postcosyntropin AVS and according to lateralization index cutoffs at least 2 and at least 4. MRMs were built to detect lateralization of aldosterone secretion according to these reference standards using only peripheral and left adrenal veins samplings (without the right AVS). Detection accuracy was assessed by the area under the receiver operating characteristic (AUROC) curves and detection sensitivities were reported for specificity at least 95%. For basal AVS with lateralization index at least 2, AUROC were respectively 0.931 [95% confidence interval (CI) 0.894-0.968] and 0.922 (95% CI 0.882-0.962) for right and left lateralization of aldosterone secretion detection and MRM could detect respectively 65.5 and 62.7% of the right and left lateralization of aldosterone secretion. For AVS after cosyntropin with lateralization index at least 4, AUROC were respectively 0.964 (95% CI: 0.940-0.987) and 0.955 (95% CI: 0.927-0.983) for right and left lateralization of aldosterone secretion, and MRM could detect respectively 77.2 and 72.9% of the right and left lateralization of aldosterone secretion. MRM can detect lateralization of aldosterone secretion without the right AVS in most patients and could eliminate the need for repeat AVS when right adrenal vein canulation is nonselective or impossible.

Malaria care seeking behavior of individuals in Ghana under the NHIS: Are we back to the use of informal care?

PubMed

Fenny, Ama Pokuaa; Asante, Felix A; Enemark, Ulrika; Hansen, Kristian S

2015-04-12

Malaria is Ghana's most endemic disease; occurring across most parts of the country with a significant impact on individuals and the health system as whole. Treatment seeking for malaria care takes various forms. The National Health Insurance Scheme (NHIS) was introduced in 2004 to promote access to health services to mitigate the negative impact of the user fee regime. Ten years on, national coverage is less than 40% of the total population and patients continue to make direct payments for health services. This paper analyses the care-seeking behaviour of households for treatment of malaria in Ghana under the NHI policy. Using a cross-sectional survey of household data collected from three districts in Ghana covering the 3 ecological zones namely the coastal, forest and savannah, a multinomial logit model is estimated. The sample consists of 365 adults and children reporting being ill with malaria in the last four weeks prior to the study. Out of the total, 58% were insured and 71% of them sought care from a formal health facility. Among the insured, 15% chose informal care compared to 48% among the uninsured. The results from the multinomial logit estimations show that health insurance and travel time to health facility are significant determinants of health care demand. The results show that the insured are 6 times more likely to choose regional/district hospitals: 5 times more likely to choose health centres/clinics and 7 times more likely to choose private hospitals/clinics over informal care when compared with the uninsured. Individual characteristics such as age, education and wealth status were significant determinants of health care provider choice for specific categories of health facilities. Overall, for malaria care the uninsured are more likely to choose informal care compared to the insured for the treatment of malaria.

History of family violence, childhood behavior problems, and adolescent high-risk behaviors as predictors of girls' repeated patterns of dating victimization in two developmental periods.

PubMed

Vézina, Johanne; Hébert, Martine; Poulin, François; Lavoie, Francine; Vitaro, Frank; Tremblay, Richard E

2015-04-01

This study aims to document the prevalence of repeated patterns of dating victimization and to examine, within the frameworks of an ecological model and lifestyle/routine activities theories, associations between such patterns and family, peer, and individual factors. Dating victimization in adolescence (age 15) and early adulthood (age 21) was evaluated in 443 female participants. Multinomial logistic regression analyses revealed that history of family violence, childhood behavior problems, and adolescent high-risk behaviors were associated with an increased risk for girls of being victimized (psychologically and/or physically/sexually) in their dating relationships, either in adolescence or early adulthood, or at both developmental periods. © The Author(s) 2015.

The effect of major income sources on rural household food (in)security: Evidence from Swaziland and implications for policy.

PubMed

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.

Domestic Violence Reported to the Police: Correlates of Victims' Reporting Behavior and Support to Legal Proceedings.

PubMed

Boivin, Rémi; Leclerc, Chloé

2016-01-01

This article analyzes reported incidents of domestic violence according to the source of the complaint and whether the victim initially supported judicial action against the offender. Almost three quarters of incidents studied were reported by the victim (72%), and a little more than half of victims initially wanted to press charges (55%). Using multinomial logistic regression models, situational and individual factors are used to distinguish 4 incident profiles. Incidents in which the victim made the initial report to the police and wished to press charges are the most distinct and involve partners who were already separated at the time of the incident or had a history of domestic violence. The other profiles also show important differences.

An agent-based model for queue formation of powered two-wheelers in heterogeneous traffic

NASA Astrophysics Data System (ADS)

Lee, Tzu-Chang; Wong, K. I.

2016-11-01

This paper presents an agent-based model (ABM) for simulating the queue formation of powered two-wheelers (PTWs) in heterogeneous traffic at a signalized intersection. The main novelty is that the proposed interaction rule describing the position choice behavior of PTWs when queuing in heterogeneous traffic can capture the stochastic nature of the decision making process. The interaction rule is formulated as a multinomial logit model, which is calibrated by using a microscopic traffic trajectory dataset obtained from video footage. The ABM is validated against the survey data for the vehicular trajectory patterns, queuing patterns, queue lengths, and discharge rates. The results demonstrate that the proposed model is capable of replicating the observed queue formation process for heterogeneous traffic.

Goodness-of-fit tests for discrete data: a review and an application to a health impairment scale.

PubMed

Horn, S D

1977-03-01

We review the advantages and disadvantages of several goodness-of-fit tests which may be used with discrete data: the multinomial test, the likelihood ratio test, the X2 test, the two-stage X2 test and the discrete Kolmogorov-Smirnov test. Although the X2 test is the best known and most widely used of these tests, its use with small sample sizes is controversial. If one has data which fall into ordered categories, then the discrete Kolmogorov-Smirnov test is an exact test which uses the information from the ordering and can be used for small sample sizes. We illustrate these points with an example of several analyses of health impairment data.

Religion, contraception, and method choice of married women in Ghana.

PubMed

Gyimah, Stephen Obeng; Adjei, Jones K; Takyi, Baffour K

2012-12-01

Using pooled data from the 1998 and 2003 Demographic and Health Surveys, this paper investigates the association between religion and contraceptive behavior of married women in Ghana. Guided by the particularized theology and characteristics hypotheses, multinomial logit and complementary log-log models are used to explore denominational differences in contraceptive adoption among currently married women and assess whether the differences could be explained through other characteristics. We found that while there were no differences between women of different Christian faiths, non-Christian women (Muslim and Traditional) were significantly more likely to have never used contraception compared with Christian women. Similar observations were made on current use of contraception, although the differences were greatly reduced in the multivariate models.

Factors Associated with Alcohol Use Before or During Sex Among Men Who Have Sex with Men in a Large Internet Sample from Asia.

PubMed

Yang, Cui; Guadamuz, Thomas E; Lim, Sin How; Koe, Stuart; Wei, Chongyi

2016-04-01

We explored factors associated with alcohol use before or during sex among a sample of 10,861 men who have sex with men (MSM) in Asia who were recruited online for the study. Multinomial logistic regression analysis indicated that having sex under the influence of alcohol was associated with having multiple male partners, seeking partners primarily through gay bar/gym/dance party/friends, selling sex and using multiple drugs during the past 6 months, and unprotected anal sex. More efforts are needed to better assess alcohol use and misuse among MSM in Asia and understand contextual influences on alcohol use and HIV-related behaviors in order to implement culturally-specific interventions.

Construction of moment-matching multinomial lattices using Vandermonde matrices and Gröbner bases

NASA Astrophysics Data System (ADS)

Lundengârd, Karl; Ogutu, Carolyne; Silvestrov, Sergei; Ni, Ying; Weke, Patrick

2017-01-01

In order to describe and analyze the quantitative behavior of stochastic processes, such as the process followed by a financial asset, various discretization methods are used. One such set of methods are lattice models where a time interval is divided into equal time steps and the rate of change for the process is restricted to a particular set of values in each time step. The well-known binomial- and trinomial models are the most commonly used in applications, although several kinds of higher order models have also been examined. Here we will examine various ways of designing higher order lattice schemes with different node placements in order to guarantee moment-matching with the process.

The View From the Bottom: Relative Deprivation and Bullying Victimization in Canadian Adolescents.

PubMed

Napoletano, Anthony; Elgar, Frank J; Saul, Grace; Dirks, Melanie; Craig, Wendy

2016-12-01

We investigated the relation between relative deprivation (RD)-disparity in affluence between adolescents and their more affluent schoolmates-and involvement in bullying among 23,383 students (aged 9-19) in 413 schools that participated in the 2010 Canadian Health Behavior in School-Aged Children survey. Students reported family affluence and frequency of bullying victimization and perpetration during the previous 2 months. Using the Yitzhaki index of RD and multinomial logistic regression analysis, we found that RD positively related to three types of bullying victimization (physical, relational, and cyberbullying) and to two types of perpetration (relational and cyberbullying) after differences in absolute affluence were held constant. These findings suggest that RD uniquely contributes to risk of bullying involvement. © The Author(s) 2015.

Effects of ignoring baseline on modeling transitions from intact cognition to dementia

PubMed Central

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

A Study of Commuters’ Decision-Making When Delaying Departure for Work-Home Trips

NASA Astrophysics Data System (ADS)

Que, Fangjie; Wang, Wei

2017-12-01

Studies on the travel behaviors and patterns of residents are important to the arrangement of urban layouts and urban traffic planning. However, research on the characteristics of the decision-making behavior regarding departure time is not fully expanded yet. In this paper, the research focuses on commuters’ decision-making behavior regarding departure delay. According to the 2013 travel survey data of Suzhou City, a nested logit (NL) model was built to represent the probabilities of individual choices. Parameter calibration was conducted, so that the significant factors influencing the departure delay were obtained. Ultimately, the results of the NL model indicated that it performed better and with higher precision, compared to the traditional multinomial logit (MNL) model.

Prediction of Nursing Workload in Hospital.

PubMed

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.

Promoting Informal and Professional Help-Seeking for Adolescent Dating Violence

PubMed Central

Hedge, Jasmine M.; Hudson-Flege, Matthew D.; McDonell, James R.

2016-01-01

The present study examined factors that differentiate adolescents with varied intentions of informal and professional help-seeking for dating violence. Help-seeking intentions among 518 ethnically diverse adolescents from a rural, southern county who participated in a longitudinal study of teen dating violence were categorized into three groups: adolescents unlikely to seek any help, adolescents likely to seek only informal help, and adolescents likely to seek informal and professional help. Multinomial logistic regression found that gender, family functioning, problem-solving competency, dating status, having an adult to talk to about a dating relationship, and acceptability of family violence significantly predicted membership in the help-seeking groups. Implications for promoting informal and professional help-seeking and recommendations for future research are discussed. PMID:28584387

Promoting Informal and Professional Help-Seeking for Adolescent Dating Violence.

PubMed

Hedge, Jasmine M; Hudson-Flege, Matthew D; McDonell, James R

2017-05-01

The present study examined factors that differentiate adolescents with varied intentions of informal and professional help-seeking for dating violence. Help-seeking intentions among 518 ethnically diverse adolescents from a rural, southern county who participated in a longitudinal study of teen dating violence were categorized into three groups: adolescents unlikely to seek any help, adolescents likely to seek only informal help, and adolescents likely to seek informal and professional help. Multinomial logistic regression found that gender, family functioning, problem-solving competency, dating status, having an adult to talk to about a dating relationship, and acceptability of family violence significantly predicted membership in the help-seeking groups. Implications for promoting informal and professional help-seeking and recommendations for future research are discussed.

Examining the association between race, ethnicity, and health status: do assets matter?

PubMed

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.

Planning for health: a community-based spatial analysis of park availability and chronic disease across the lifespan.

PubMed

Besenyi, Gina M; Kaczynski, Andrew T; Stanis, Sonja A Wilhelm; Bergstrom, Ryan D; Lightner, Joseph S; Hipp, J Aaron

2014-05-01

The purpose of this study was to explore the spatial relationship between park availability and chronic health conditions (CHCs) across age groups in Kansas City, MO. Multinomial logistic regression examined the association between having a park within one-half mile from home and the likelihood of having 0, 1, or 2 or more CHCs. Among respondents aged 40-59, those without a park within one-half mile from home were more than twice as likely to have 2 or more CHCs compared to respondents that had a park nearby. Parks may be an important protective factor for chronic diseases, especially among middle-aged adults among whom access to neighborhood recreational environments may be particularly important. Copyright © 2014 Elsevier Ltd. All rights reserved.

Making a Difference in Science Education: The Impact of Undergraduate Research Programs

PubMed Central

Eagan, M. Kevin; Hurtado, Sylvia; Chang, Mitchell J.; Garcia, Gina A.; Herrera, Felisha A.; Garibay, Juan C.

2014-01-01

To increase the numbers of underrepresented racial minority students in science, technology, engineering, and mathematics (STEM), federal and private agencies have allocated significant funding to undergraduate research programs, which have been shown to students’ intentions of enrolling in graduate or professional school. Analyzing a longitudinal sample of 4,152 aspiring STEM majors who completed the 2004 Freshman Survey and 2008 College Senior Survey, this study utilizes multinomial hierarchical generalized linear modeling (HGLM) and propensity score matching techniques to examine how participation in undergraduate research affects STEM students’ intentions to enroll in STEM and non-STEM graduate and professional programs. Findings indicate that participation in an undergraduate research program significantly improved students’ probability of indicating plans to enroll in a STEM graduate program. PMID:25190821

Sleep duration and health correlates among university students in 26 countries.

PubMed

Peltzer, Karl; Pengpid, Supa

2016-01-01

The aim of this study was to investigate sleep duration and its health correlates in university students from 26 low-, middle- and high-income countries. Using anonymous questionnaires and anthropometric measurements, data were collected from 19417 undergraduate university students (mean age 20.8, SD = 2.8) from 27 universities from 26 countries across Asia, Africa and the Americas. Results indicate that the average number of self-reported hours of sleep was 7.07 (CI = 7.04-7.09), with the prevalence of reporting ≤ 6, 7-8, and ≥ 9 h sleep duration of 39.2, 46.9, and 13.9%, respectively. Multinomial logistic regression found that sociodemographic variables, health risk behaviour and health status variables were found to be associated with short and long sleep duration.

Ecstasy Use and Suicidal Behavior Among Adolescents: Findings from a National Survey

PubMed Central

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

Women's labor force participation in later life: the effects of early work and family experiences.

PubMed

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.

Declining Fertility and the Use of Cesarean Delivery: Evidence from a Population-Based Study in Taiwan

PubMed Central

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

Factors Associated with Alcohol Use Before or During Sex Among Men Who Have Sex with Men in a Large Internet Sample from Asia

PubMed Central

Guadamuz, Thomas E.; Lim, Sin How; Koe, Stuart; Wei, Chongyi

2016-01-01

Abstract We explored factors associated with alcohol use before or during sex among a sample of 10,861 men who have sex with men (MSM) in Asia who were recruited online for the study. Multinomial logistic regression analysis indicated that having sex under the influence of alcohol was associated with having multiple male partners, seeking partners primarily through gay bar/gym/dance party/friends, selling sex and using multiple drugs during the past 6 months, and unprotected anal sex. More efforts are needed to better assess alcohol use and misuse among MSM in Asia and understand contextual influences on alcohol use and HIV-related behaviors in order to implement culturally-specific interventions. PMID:26789393

Smoking, alcohol consumption and betal-quid chewing among young adult Myanmar laborers in Thailand.

PubMed

Htin, Kyaw; Howteerakull, Nopporn; Suwannapong, Nawarat; TipayamongkholgulI, Mathuros

2014-07-01

Health-risk behaviors among young adults are a serious public health problem. This cross sectional study aimed to estimate the prevalence of single and concurrent multiple health-risk behaviors: smoking tobacco, consuming alcohol, and chewing betel quid among young adult Myanmar laborers in Mae Sot District, Tak Province, Thailand. Three hundred Myanmar laborers, aged 18-24 years, were interviewed using a structured questionnaire. About 33.6% reported no risk behaviors, 24.7% had one, and 41.7% had two or three risk behaviors. Multinomial logistic regression analysis showed six variables were significantly associated with health-risk behaviors: male gender, high/moderate custom/traditional influences, friends who smoked/consumed alcohol/chewed betel quid, and exposure to betel-quid chewing by other family members.

Aging, subjective experience, and cognitive control: dramatic false remembering by older adults.

PubMed

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.

The intersectionality of postsecondary pathways: the case of high school students with special education needs.

PubMed

Robson, Karen L; Anisef, Paul; Brown, Robert S; Parekh, Gillian

2014-08-01

Using data from the Toronto District School Board, we examine the postsecondary pathways of students with special education needs (SEN). We consider both university and college pathways, employing multilevel multinomial logistic regressions, conceptualizing our findings within a life course and intersectionality framework. Our findings reveal that having SEN reduces the likelihood of confirming university, but increases the likelihood of college confirmation. We examine a set of known determinants of postsecondary education (PSE) pathways that were derived from the literature and employ exploratory statistical interactions to examine if the intersection of various traits differentially impacts upon the PSE trajectories of students with SEN. Our findings reveal that parental education, neighborhood wealth, race, and streaming impact on the postsecondary pathways of students with SEN in Toronto.

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

PubMed Central

Radey, Melissa

2017-01-01

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

Meta-analysis data for 104 Energy-Economy Nexus papers.

PubMed

Hajko, Vladimír; Kociánová, Agáta; Buličková, Martina

2017-06-01

The data presented here are manually encoded characteristics of research papers in the area of Energy-Economy Nexus (empirical investigation of Granger causality between energy consumption and economic growth) that describe the methods, samples, and other details related to the individual estimations done in the examined empirical papers. Data cover papers indexed by Scopus, published in economic journals, written in English, after year 2000. In addition, papers were manually filtered to only those that deal with Energy-Economy Nexus investigation and have at least 10 citations at (at the time of query - November 2015). This data are to be used to conduct meta-analysis - associated dataset was used in Hajko [1]. Early version of the dataset was used for multinomial logit estimation in Master thesis by Kociánová [2].

Inferring Markov chains: Bayesian estimation, model comparison, entropy rate, and out-of-class modeling.

PubMed

Strelioff, Christopher C; Crutchfield, James P; Hübler, Alfred W

2007-07-01

Markov chains are a natural and well understood tool for describing one-dimensional patterns in time or space. We show how to infer kth order Markov chains, for arbitrary k , from finite data by applying Bayesian methods to both parameter estimation and model-order selection. Extending existing results for multinomial models of discrete data, we connect inference to statistical mechanics through information-theoretic (type theory) techniques. We establish a direct relationship between Bayesian evidence and the partition function which allows for straightforward calculation of the expectation and variance of the conditional relative entropy and the source entropy rate. Finally, we introduce a method that uses finite data-size scaling with model-order comparison to infer the structure of out-of-class processes.

Design and analysis of simple choice surveys for natural resource management

USGS Publications Warehouse

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.

A constrained rasch model of trace redintegration in serial recall.

PubMed

Roodenrys, Steven; Miller, Leonie M

2008-04-01

The notion that verbal short-term memory tasks, such as serial recall, make use of information in long-term as well as in short-term memory is instantiated in many models of these tasks. Such models incorporate a process in which degraded traces retrieved from a short-term store are reconstructed, or redintegrated (Schweickert, 1993), through the use of information in long-term memory. This article presents a conceptual and mathematical model of this process based on a class of item-response theory models. It is demonstrated that this model provides a better fit to three sets of data than does the multinomial processing tree model of redintegration (Schweickert, 1993) and that a number of conceptual accounts of serial recall can be related to the parameters of the model.

Multinomial Logistic Regression & Bootstrapping for Bayesian Estimation of Vertical Facies Prediction in Heterogeneous Sandstone Reservoirs

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.

Exploring consumers’ attitudes towards informal patient payments using the combined method of cluster and multinomial regression analysis - the case of Hungary

PubMed Central

2013-01-01

Background Previous studies on informal patient payments have mostly focused on the magnitude and determinants of these payments while the attitudes of health care actors towards these payments are less well known. This study aims to reveal the attitudes of Hungarian health care consumers towards informal payments to provide a better understanding of this phenomenon. Methods For the analysis, we use data from a survey carried out in 2010 in Hungary involving a representative sample of 1037 respondents. We use cluster analysis to identify the main attitude groups related to informal payments based on the respondents’ perception of and behavior related to informal payments. Multinomial logistic regression is applied to examine the differences between these groups in terms of socio-demographic characteristics, as well as past utilization and informal payments paid for health care services. Results We identified three main different attitudes towards informal payments: accepting informal payments, doubting about informal payments and opposing informal payments. Those who accept informal payments (mostly young or elderly people, living in the capital) consider these payments as an expression of gratitude and perceive them as inevitable due to the low funding of the health care system. Those who doubt about informal payments (mostly respondents outside the capital, with higher education and higher household income) are not certain whether these payments are inevitable, perceive them as similar to corruption rather than gratitude, and would rather use private services to avoid these payments. We find that the opposition to informal payments (mostly among men from small households and low income households) can be explained by their lower ability and willingness to pay. Conclusions A large share of Hungarian health care consumers has a rather positive attitude towards informal payments, perceiving them as “inevitable due to the low funding of the health care system”. From a policy point-of-view, the change of this consumer attitude will be essential to deal with these payments in addition to other policy strategies. PMID:23414488

Associations of financial stressors and physical intimate partner violence perpetration.

PubMed

Schwab-Reese, Laura M; Peek-Asa, Corinne; Parker, Edith

2016-12-01

Contextual factors, such as exposure to stressors, may be antecedents to IPV perpetration. These contextual factors may be amenable to modification through intervention and prevention. However, few studies have examined specific contextual factors. To begin to address this gap, we examined the associations between financial stressors and three types of physical IPV perpetration. This analysis used data from Wave IV of The National Longitudinal Study of Adolescent to Adult Health. We used logistic regression to examine the associations of financial stressors and each type of IPV (minor, severe, causing injury), and multinomial logit regression to examine the associations of financial stressors and patterns of co-occurring types of IPV perpetration (only minor; only severe; minor and severe; minor, severe, and causing injury; compared with no perpetration). Fewer men perpetrated threats/minor physical IPV (6.7 %) or severe physical IPV (3.4 %) compared with women (11.4 % and 8.8 %, respectively). However, among physical IPV perpetrators, a higher percentage of men (32.0 %) than women (21.0 %) reported their partner was injured as a result of the IPV. In logistic regression models of each type of IPV perpetration, both the number of stressors experienced and several types of financial stressors were associated with perpetrating each type of IPV. Utilities nonpayment, housing nonpayment, food insecurity, and no phone service were associated with increased odds of perpetrating each form of IPV in adjusted analysis. Eviction was associated with perpetrating severe physical IPV but not threats/minor IPV or IPV causing injury. In multinomial logit regression comparing patterns of IPV perpetration to perpetrating no physical IPV, the relationships of financial stressors were less consistent. Food insecurity was associated with perpetrating only minor physical IPV. Comparatively, overall number of financial stressors and four types of financial stressors (utilities nonpayment, housing nonpayment, food insecurity, and disconnected phone service) were associated with perpetrating all three forms of physical IPV. Combined with prior research, our results suggested interventions to improve financial well-being may be a novel way to reduce physical IPV perpetration.

Associations of financial stressors and physical intimate partner violence perpetration.

PubMed

Schwab-Reese, Laura M; Peek-Asa, Corinne; Parker, Edith

Contextual factors, such as exposure to stressors, may be antecedents to IPV perpetration. These contextual factors may be amenable to modification through intervention and prevention. However, few studies have examined specific contextual factors. To begin to address this gap, we examined the associations between financial stressors and three types of physical IPV perpetration. This analysis used data from Wave IV of The National Longitudinal Study of Adolescent to Adult Health. We used logistic regression to examine the associations of financial stressors and each type of IPV (minor, severe, causing injury), and multinomial logit regression to examine the associations of financial stressors and patterns of co-occurring types of IPV perpetration ( only minor; only severe; minor and severe; minor, severe, and causing injury; compared with no perpetration). Fewer men perpetrated threats/minor physical IPV (6.7 %) or severe physical IPV (3.4 %) compared with women (11.4 % and 8.8 %, respectively). However, among physical IPV perpetrators, a higher percentage of men (32.0 %) than women (21.0 %) reported their partner was injured as a result of the IPV. In logistic regression models of each type of IPV perpetration, both the number of stressors experienced and several types of financial stressors were associated with perpetrating each type of IPV. Utilities nonpayment, housing nonpayment, food insecurity, and no phone service were associated with increased odds of perpetrating each form of IPV in adjusted analysis. Eviction was associated with perpetrating severe physical IPV but not threats/minor IPV or IPV causing injury. In multinomial logit regression comparing patterns of IPV perpetration to perpetrating no physical IPV, the relationships of financial stressors were less consistent. Food insecurity was associated with perpetrating only minor physical IPV. Comparatively, overall number of financial stressors and four types of financial stressors (utilities nonpayment, housing nonpayment, food insecurity, and disconnected phone service) were associated with perpetrating all three forms of physical IPV. Combined with prior research, our results suggested interventions to improve financial well-being may be a novel way to reduce physical IPV perpetration.

An ethnobiological study in Kala Chitta hills of Pothwar region, Pakistan: multinomial logit specification

PubMed Central

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

The Inaccuracy of Patient Recall for COPD Exacerbation Rate Estimation and Its Implications: Results from Central Adjudication.

PubMed

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.

Chronic fatigue syndrome (CFS/ME) symptom-based phenotypes and 1-year treatment outcomes in two clinical cohorts of adult patients in the UK and The Netherlands.

PubMed

Collin, Simon M; Heron, Jon; Nikolaus, Stephanie; Knoop, Hans; Crawley, Esther

2018-01-01

We previously described symptom-based chronic fatigue syndrome (CFS/ME) phenotypes in clinical assessment data from 7041 UK and 1392 Dutch adult CFS/ME patients. Here we aim to replicate these phenotypes in a more recent UK patient cohort, and investigate whether phenotypes are associated with 1-year treatment outcome. 12 specialist CFS/ME services (11 UK, 1 NL) recorded the presence/absence of 5 symptoms (muscle pain, joint pain, headache, sore throat, and painful lymph nodes) which can occur in addition to the 3 symptoms (post-exertional malaise, cognitive dysfunction, and disturbed/unrefreshing sleep) that are present for almost all patients. Latent Class Analysis (LCA) was used to assign symptom profiles (phenotypes). Multinomial logistic regression models were fitted to quantify associations between phenotypes and overall change in health 1year after the start of treatment. Baseline data were available for N=918 UK and N=1392 Dutch patients, of whom 416 (45.3%) and 912 (65.5%) had 1-year follow-up data, respectively. 3- and 4-class phenotypes identified in the previous UK patient cohort were replicated in the new UK cohort. UK patients who presented with 'polysymptomatic' and 'pain-only' phenotypes were 57% and 67% less likely (multinomial odds ratio (MOR) 0.43 (95% CI 0.19-0.94) and 0.33 (95% CI 0.13-0.84)) to report that their health was "very much better" or "much better" than patients who presented with an 'oligosymptomatic' phenotype. For Dutch patients, polysymptomatic and pain-only phenotypes were associated with 72% and 55% lower odds of improvement (MOR 0.28 (95% CI 0.11, 0.69) and 0.45 (95% CI 0.21, 0.99)) compared with oligosymptomatic patients. Adult CFS/ME patients with multiple symptoms or pain symptoms who present for specialist treatment are much less likely to report favourable treatment outcomes than patients who present with few symptoms. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Clusters of anthropometric indicators of body fat associated with maximum oxygen uptake in adolescents

PubMed Central

2018-01-01

Introduction The aim of this study was to evaluate different clusters of anthropometric indicators (body mass index | BMI |, waist circumference | WC |, waist-to-height ratio | WHtR |, triceps skinfold |TR SF|, subscapular skinfold |SE SF|, sum of the triceps and subscapular skinfolds | ΣTR + SE |, and sum of the triceps, subscapular and suprailiac folds | ΣTR + SE + SI|) associated with the VO2max levels in adolescents. Methods The study included 1,132 adolescents (aged 14–19 years) enrolled in public schools of São José, Santa Catarina, Brazil, in the 2014 academic year. The dependent variable was the cluster of anthropometric indicators (BMI, WC, WHtR, TR SF, SE SF, SI SF, ΣTR + SE and ΣTR + SE + SI) of excess body fat. The independent variable was maximum oxygen uptake (VO2max), estimated by the modified Canadian aerobic fitness test—mCAFT. Control variables were: age, skin color, economic level, maternal education, physical activity and sexual maturation. Multinomial logistic regression was used for associations between the dependent and independent variables. Binary logistic regression was performed to identify the association between adolescents with all anthropometric indicators in excess and independent variables. Results One in ten adolescents presented all anthropometric indicators of excess body fat. Multinomial regression showed that with each increase of one VO2max unit, the odds of adolescents having three, four, five or more anthropometric indicators of excess body fat decreased by 0.92, 0.85 and 0.73 times, respectively. In the binary regression, this fact was reconfirmed, demonstrating that with each increase of one VO2max unit, the odds of adolescents having simultaneously the eight anthropometric indicators of excess body fat decreased by 0.55. Conclusion It was concluded that with each increase of one VO2max unit, adolescents decreased the odds of simultaneously presenting three or more anthropometric indicators of excess body fat, regardless of biological, economic and lifestyle factors. In addition, the present study identified that one in ten adolescents had all anthropometric indicators of excess body fat. PMID:29534098

Help-Seeking in People with Exceptional Experiences: Results from a General Population Sample

PubMed Central

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

Determinants of financial performance of home-visit nursing agencies in Japan.

PubMed

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.

Association of childhood abuse with homeless women's social networks.

PubMed

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.

The prevalence of underweight, overweight and obesity and their related socio-demographic and lifestyle factors among adult women in Myanmar, 2015-16

PubMed Central

Hong, Seo Ah; Lwin, Kyi Tun; Aung, La Seng

2018-01-01

Background The aim of the study was to estimate the prevalence of underweight and overweight or obesity and their socio-demographic and lifestyle factors in a female adult population in Myanmar. Material and methods In a national cross-sectional population-based survey in the 2015–16 Myanmar Demographic and Health Survey, 12,160 women aged 18–49 years and not currently pregnant completed questionnaires and anthropometric measurements. Nutritional status was determined using Asian body mass index cut-offs: underweight (BMI<18.5 kg/m2), overweight (23.0–27.4 kg/m2), and obesity (≥27.5 kg/m2). Multinomial logistic regression modelling was used to determine the association between socio-demographic and lifestyle factors and weight status. Results The prevalence of underweight was 14.1%, overweight 28.1% and obesity 13.1%. Among different age groups, the prevalence of underweight was the highest among 18 to 29 year-olds (20.2%), while overweight or obesity was the highest in the age group 30 to 49 years (around 50%). In multinomial logistic regression, being 30 to 49 years old, poorer and richer wealth status, living in all the other regions of Myanmar and ever contraceptive use were inversely and current tobacco use, not working and having less than two children ever born were positively associated with underweight relative to normal weight. Older age, having secondary education, urban residence, wealthier economic status, living with a partner, living in the Northern and Southern regions of Myanmar, having less than two children ever born and having ever used contraceptives were positively and current tobacco use was negatively associated with overweight or obesity relative to normal weight. Conclusions A dual burden of both underweight and overweight or obesity among female adults was found in Myanmar. Sociodemographic and health risk behaviour factors were identified for underweight and overweight or obesity that can guide public health interventions to address both of these conditions. PMID:29547655

Lidar-based multinomial classification algorithms for tropical forest degradation status: Implications for biomass estimation

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.

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.

Heterogeneous Impact of the “Seguro Popular” Program on the Utilization of Obstetrical Services in Mexico, 2001–2006: A Multinomial Probit Model with a Discrete Endogenous Variable

PubMed Central

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

The relationship between red blood cell distribution width and blood pressure abnormal dipping in patients with essential hypertension: a cross-sectional study.

PubMed

Su, Dan; Guo, Qi; Gao, Ya; Han, Jin; Yan, Bin; Peng, Liyuan; Song, Anqi; Zhou, Fuling; Wang, Gang

2016-02-23

To investigate whether red blood cell distribution width (RDW) is associated with the blood pressure (BP) reverse-dipper pattern in patients with hypertension. Cross-sectional study. Single centre. Patients with essential hypertension were included in our study (n=708). The exclusion criteria included age <18 or >90 years, incomplete clinical data, night workers, diagnosis of secondary hypertension, under antihypertensive treatment, intolerance for the 24 h ambulatory BP monitoring (ABPM) and BP reading success rate <70%. Physical examination and ABPM were performed for all patients in our study. The value of RDW was measured using an automated haematology analyser. The distribution of RDW in patients with hypertension among different circadian BP pattern groups was analyzed using analysis of variance (ANOVA). Multinomial logistic regression was applied to explore the associations of RDW and other relevant variables with ABPM results. There was significantly increased RDW in reverse dippers (13.52 ± 1.05) than dippers (13.25 ± 0.85) of hypertension (p=0.012). Moreover, multinomial logistic regression analysis showed that RDW (OR 1.325, 95% CI 1.037 to 1.692, p=0.024) and diabetes mellitus (OR 2.286, 95% CI 1.380 to 3.788, p=0.001) were significantly different when comparing the reverse-dipper BP pattern with the dipper pattern. However, there was no difference of RDW between the non-dipper pattern and the reverse-dipper pattern (OR 1.036, 95% CI 0.867 to 1.238, p=0.693). In addition to this, RDW was negatively correlated with the decline rate of nocturnal systolic BP (r=-0.113; p=0.003) and diastolic BP (r=-0.101; p=0.007). Our results suggested that RDW might associate with the abnormal dipper BP patterns of either reverse dipping or non-dipping homogeneously examined with 24 h ABPM. 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/

Determinants of financial performance of home-visit nursing agencies in Japan

PubMed Central

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

Relation of socio-economic status to impaired fasting glucose and Type 2 diabetes: findings based on a large population-based cross-sectional study in Tianjin, China.

PubMed

Zhang, H; Xu, W; Dahl, A K; Xu, Z; Wang, H-X; Qi, X

2013-05-01

Studies on the relationship between socio-economic status and Type 2 diabetes mellitus in the Chinese population are sparse. We aimed to examine the relation of socio-economic status as represented by income, education and occupation to impaired fasting glucose, Type 2 diabetes, and the control of Type 2 diabetes in a large Chinese population. This study included 7315 individuals who were aged 20-79 years and living in Tianjin, China. Impaired fasting glucose and Type 2 diabetes were ascertained according to the 1999 World Health Organization criteria. Data were analysed using multinomial and binary logistic regression, with adjustment for potential confounders. Among all participants, 532 (7.3%) persons had impaired fasting glucose, 688 (9.4%) persons had Type 2 diabetes, including 288 (3.9%) previously undiagnosed Type 2 diabetes. In fully adjusted multinomial logistic regression, compared with higher income (≥ 2000 yuan, $243.3/month), lower income (< 1000 yuan, $121.70/month) showed odds ratios (95% confidence intervals) of 3.31 (2.48-4.41) for impaired fasting glucose, 4.50 (3.07-6.61) for undiagnosed Type 2 diabetes and 4.56 (3.20-6.48) for diagnosed Type 2 diabetes. These results remained significant in the analysis stratified by education and occupation. Furthermore, persons who were retired were more likely to have impaired fasting glucose [odds ratio 1.91 (1.40-2.45)], undiagnosed Type 2 diabetes [odds ratio 2.01) 1.40-2.89] and diagnosed Type 2 diabetes [odds ratio 3.02 (2.12-4.22)]. Among the patients with Type 2 diabetes previously diagnosed, lower education (less than senior high school), non-manual work and unemployment were related to worse glycaemic control (fasting blood glucose level > 8.5 mmol/l). Lower income and retirement are associated with increased odds of impaired fasting glucose and Type 2 diabetes in Tianjin, China. Education and occupation may play a role in glycaemic control among patients with Type 2 diabetes. © 2013 The Authors. Diabetic Medicine © 2013 Diabetes UK.

Assessment of Malawian Mothers’ Malaria Knowledge, Healthcare Preferences and Timeliness of Seeking Fever Treatments for Children Under Five

PubMed Central

Oyekale, Abayomi Samuel

2015-01-01

Malaria is one of the major public health problems in Malawi, contributing to the majority of morbidity and mortality among children under five. Ignorance of malaria symptoms results in delayed treatment, which often degenerates into fatal emergencies. This study analyzed the impact of maternal malaria knowledge on healthcare preferences and timeliness of treating children with reported fever. The Malaria Indicator Survey data for 2012, which were adequately weighted, were analyzed using multinomial logit and Poisson regression models. The results showed low maternal average years of formal education (3.52) and average mothers’ age was 27.97 years. Majority of the women (84.98%) associated fever with malaria, while 44.17% associated it with chilling. Also, 54.42% and 32.43% of the children were treated for fever on the same day and the following day that fever started, respectively. About 9.70% paid for fever treatment from their regular incomes, while 51.38% sought treatment from either public or private health centers. Multinomial Logit regression results showed that relative to using of other treatments, probabilities of selecting private hospitals and public health centers increased with age of the household heads, resident in urban areas, mothers’ years of education, number of days taken off for treatment, paying medical bills from regular, occasional and borrowed incomes, and knowledge of diarrhea and shivering as symptoms of malaria. In the Poisson regression results, timeliness of seeking treatment was significantly enhanced by knowledge of fever as malaria symptom, residence in northern and central regions of Malawi and use of income from sale of assets to pay medical bills (p < 0.10).However, delays in treating children was motivated by age of the household heads, number of days taken off to care for sick child and usage of regular, borrowed and other incomes to pay medical bills. (p < 0.05). It was concluded that efficiency of public sector in treating malaria holds significant prospects for fighting malaria in Malawi. However, adequate efforts should be channeled in enhancing the knowledge of women on malaria symptoms, among others. PMID:25584420

Assessment of Malawian mothers' malaria knowledge, healthcare preferences and timeliness of seeking fever treatments for children under five.

PubMed

Oyekale, Abayomi Samuel

2015-01-09

Malaria is one of the major public health problems in Malawi, contributing to the majority of morbidity and mortality among children under five. Ignorance of malaria symptoms results in delayed treatment, which often degenerates into fatal emergencies. This study analyzed the impact of maternal malaria knowledge on healthcare preferences and timeliness of treating children with reported fever. The Malaria Indicator Survey data for 2012, which were adequately weighted, were analyzed using multinomial logit and Poisson regression models. The results showed low maternal average years of formal education (3.52) and average mothers' age was 27.97 years. Majority of the women (84.98%) associated fever with malaria, while 44.17% associated it with chilling. Also, 54.42% and 32.43% of the children were treated for fever on the same day and the following day that fever started, respectively. About 9.70% paid for fever treatment from their regular incomes, while 51.38% sought treatment from either public or private health centers. Multinomial Logit regression results showed that relative to using of other treatments, probabilities of selecting private hospitals and public health centers increased with age of the household heads, resident in urban areas, mothers' years of education, number of days taken off for treatment, paying medical bills from regular, occasional and borrowed incomes, and knowledge of diarrhea and shivering as symptoms of malaria. In the Poisson regression results, timeliness of seeking treatment was significantly enhanced by knowledge of fever as malaria symptom, residence in northern and central regions of Malawi and use of income from sale of assets to pay medical bills (p < 0.10).However, delays in treating children was motivated by age of the household heads, number of days taken off to care for sick child and usage of regular, borrowed and other incomes to pay medical bills. (p < 0.05). It was concluded that efficiency of public sector in treating malaria holds significant prospects for fighting malaria in Malawi. However, adequate efforts should be channeled in enhancing the knowledge of women on malaria symptoms, among others.

Infection and Co-infection with Helminths and Plasmodium among School Children in Côte d’Ivoire: Results from a National Cross-Sectional Survey

PubMed Central

Yapi, Richard B.; Hürlimann, Eveline; Houngbedji, Clarisse A.; Ndri, Prisca B.; Silué, Kigbafori D.; Soro, Gotianwa; Kouamé, Ferdinand N.; Vounatsou, Penelope; Fürst, Thomas; N’Goran, Eliézer K.; Utzinger, Jürg; Raso, Giovanna

2014-01-01

Background Helminth infection and malaria remain major causes of ill-health in the tropics and subtropics. There are several shared risk factors (e.g., poverty), and hence, helminth infection and malaria overlap geographically and temporally. However, the extent and consequences of helminth-Plasmodium co-infection at different spatial scales are poorly understood. Methodology This study was conducted in 92 schools across Côte d’Ivoire during the dry season, from November 2011 to February 2012. School children provided blood samples for detection of Plasmodium infection, stool samples for diagnosis of soil-transmitted helminth (STH) and Schistosoma mansoni infections, and urine samples for appraisal of Schistosoma haematobium infection. A questionnaire was administered to obtain demographic, socioeconomic, and behavioral data. Multinomial regression models were utilized to determine risk factors for STH-Plasmodium and Schistosoma-Plasmodium co-infection. Principal Findings Complete parasitological and questionnaire data were available for 5,104 children aged 5-16 years. 26.2% of the children were infected with any helminth species, whilst the prevalence of Plasmodium infection was 63.3%. STH-Plasmodium co-infection was detected in 13.5% and Schistosoma-Plasmodium in 5.6% of the children. Multinomial regression analysis revealed that boys, children aged 10 years and above, and activities involving close contact to water were significantly and positively associated with STH-Plasmodium co-infection. Boys, wells as source of drinking water, and water contact were significantly and positively associated with Schistosoma-Plasmodium co-infection. Access to latrines, deworming, higher socioeconomic status, and living in urban settings were negatively associated with STH-Plasmodium co-infection; whilst use of deworming drugs and access to modern latrines were negatively associated with Schistosoma-Plasmodium co-infection. Conclusions/Significance More than 60% of the school children surveyed were infected with Plasmodium across Côte d’Ivoire, and about one out of six had a helminth-Plasmodium co-infection. Our findings provide a rationale to combine control interventions that simultaneously aim at helminthiases and malaria. PMID:24901333

Clusters of anthropometric indicators of body fat associated with maximum oxygen uptake in adolescents.

PubMed

Gonçalves, Eliane Cristina de Andrade; Nunes, Heloyse Elaine Gimenes; Silva, Diego Augusto Santos

2018-01-01

The aim of this study was to evaluate different clusters of anthropometric indicators (body mass index | BMI |, waist circumference | WC |, waist-to-height ratio | WHtR |, triceps skinfold |TR SF|, subscapular skinfold |SE SF|, sum of the triceps and subscapular skinfolds | ΣTR + SE |, and sum of the triceps, subscapular and suprailiac folds | ΣTR + SE + SI|) associated with the VO2max levels in adolescents. The study included 1,132 adolescents (aged 14-19 years) enrolled in public schools of São José, Santa Catarina, Brazil, in the 2014 academic year. The dependent variable was the cluster of anthropometric indicators (BMI, WC, WHtR, TR SF, SE SF, SI SF, ΣTR + SE and ΣTR + SE + SI) of excess body fat. The independent variable was maximum oxygen uptake (VO2max), estimated by the modified Canadian aerobic fitness test-mCAFT. Control variables were: age, skin color, economic level, maternal education, physical activity and sexual maturation. Multinomial logistic regression was used for associations between the dependent and independent variables. Binary logistic regression was performed to identify the association between adolescents with all anthropometric indicators in excess and independent variables. One in ten adolescents presented all anthropometric indicators of excess body fat. Multinomial regression showed that with each increase of one VO2max unit, the odds of adolescents having three, four, five or more anthropometric indicators of excess body fat decreased by 0.92, 0.85 and 0.73 times, respectively. In the binary regression, this fact was reconfirmed, demonstrating that with each increase of one VO2max unit, the odds of adolescents having simultaneously the eight anthropometric indicators of excess body fat decreased by 0.55. It was concluded that with each increase of one VO2max unit, adolescents decreased the odds of simultaneously presenting three or more anthropometric indicators of excess body fat, regardless of biological, economic and lifestyle factors. In addition, the present study identified that one in ten adolescents had all anthropometric indicators of excess body fat.

Clinical characteristics of type 2 diabetes patients with discordance between HbA1c and fasting plasma glucose in the real world: An analysis of the ORBIT study.

PubMed

Shu, Hua; Lu, Juming; Zhang, Puhong; Zhu, Dongshan; Li, Xian; Ji, Jiachao; Zhao, Fang; Ji, Linong

2018-05-01

We aimed to determine the clinical characteristics of type 2 diabetes patients on basal insulin therapy with inadequate glucose control due to discordance between glycated haemoglobin (HbA 1c ) and fasting plasma glucose (FPG) in the real world. This was a retrospective analysis of data from the ORBIT study in China. Clinical characteristics of patients with discordance between HbA 1c and FPG at baseline and at the end of 6 months of follow-up were analysed using multinomial logistic regression in 4 study groups divided by HbA 1c and FPG. Overall, of 6721 patients initiated on basal insulin, 853 achieved HbA 1c  < 7% but FPG ≥ 7 mmol/L (group 2), while 997 had FPG < 7 mmol/L but HbA 1c  ≥ 7% (group 3) at the end of follow-up. Patients in group 3 had a longer duration of type 2 diabetes compared with those in group 2 (7.22 ± 5.30 vs 6.00 ± 4.80 y, P < .05). Patients on glargine (32.90%) or detemir (36.88%) treatment accounted for a higher proportion of patients with both HbA 1c and FPG controlled than those on neutral protamine Hagedorn therapy (23.45%; P < .05). Per the multinomial logistic analysis, higher frequency of self-monitoring of blood glucose (SMBG) and use of glargine or detemir therapy were significantly inversely associated with risk of discordance between HbA 1c and FPG, while dose of insulin was a risk factor for discordance at the end of follow-up (all P < .05). Patients treated with insulin analogues (glargine or detemir), instead of neutral protamine Hagedorn, and with more frequent SMBG are more likely to exhibit concordance between HbA 1c and FPG. Copyright © 2018 John Wiley & Sons, Ltd.

Dental caries clusters among adolescents.

PubMed

Warren, John J; Van Buren, John M; Levy, Steven M; Marshall, Teresa A; Cavanaugh, Joseph E; Curtis, Alexandra M; Kolker, Justine L; Weber-Gasparoni, Karin

2017-12-01

There have been very few longitudinal studies of dental caries in adolescents, and little study of the caries risk factors in this age group. The purpose of this study was to describe different caries trajectories and associated risk factors among members of the Iowa Fluoride Study (IFS) cohort. The IFS recruited a birth cohort from 1992 to 1995, and has gathered dietary, fluoride and behavioural data at least twice yearly since recruitment. Examinations for dental caries were completed when participants were ages 5, 9, 13 and 17 years. For this study, only participants with decayed and filled surface (DFS) caries data at ages 9, 13 and 17 were included (N=396). The individual DFS counts at age 13 and the DFS increment from 13 to 17 were used to identify distinct caries trajectories using Ward's hierarchical clustering algorithm. A number of multinomial logistic regression models were developed to predict trajectory membership, using longitudinal dietary, fluoride and demographic/behavioural data from 9 to 17 years. Model selection was based on the akaike information criterion (AIC). Several different trajectory schemes were considered, and a three-trajectory scheme-no DFS at age 17 (n=142), low DFS (n=145) and high DFS (n=109)-was chosen to balance sample sizes and interpretability. The model selection process resulted in use of an arithmetic average for dietary variables across the period from 9 to 17 years. The multinomial logistic regression model with the best fit included the variables maternal education level, 100% juice consumption, brushing frequency and sex. Other favoured models also included water and milk consumption and home water fluoride concentration. The high caries cluster was most consistently associated with lower maternal education level, lower 100% juice consumption, lower brushing frequency and being female. The use of a clustering algorithm and use of Akaike's Information Criterion (AIC) to determine the best representation of the data were useful means in presenting longitudinal caries data. Findings suggest that high caries incidence in adolescence is associated with lower maternal educational level, less frequent tooth brushing, lower 100% juice consumption and being female. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Neighborhood Structural Inequality, Collective Efficacy, and Sexual Risk Behavior among Urban Youth

PubMed Central

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

Analysis of brute-force break-ins of a palmprint authentication system.

PubMed

Kong, Adams W K; Zhang, David; Kamel, Mohamed

2006-10-01

Biometric authentication systems are widely applied because they offer inherent advantages over classical knowledge-based and token-based personal-identification approaches. This has led to the development of products using palmprints as biometric traits and their use in several real applications. However, as biometric systems are vulnerable to replay, database, and brute-force attacks, such potential attacks must be analyzed before biometric systems are massively deployed in security systems. This correspondence proposes a projected multinomial distribution for studying the probability of successfully using brute-force attacks to break into a palmprint system. To validate the proposed model, we have conducted a simulation. Its results demonstrate that the proposed model can accurately estimate the probability. The proposed model indicates that it is computationally infeasible to break into the palmprint system using brute-force attacks.

Suicidal ideation and attempts in adolescents: associations with depression and six domains of self-esteem.

PubMed

Wild, Lauren G; Flisher, Alan J; Lombard, Carl

2004-12-01

This study aimed to disentangle the influence of depression and self-esteem on suicidal behaviour in adolescence. Grades 8 and 11 students in Cape Town, South Africa (n = 939) completed questionnaires assessing suicidal ideation and behaviour, depression, and self-esteem with respect to family, peers, school, sports/athletics, body image and global self-worth. Data were analysed using a series of multinomial logistic regression models adjusted for gender, grade, race and the sampling strategy. Results indicated that depression and low self-esteem in the family context were independently associated with suicide ideation and attempts. Moreover, low family self-esteem significantly differentiated suicide attempters from ideators. Screening for depression and low self-esteem in the family context is discussed as a possible strategy for helping to identify adolescents at risk for suicide attempts.

Recognition and source memory as multivariate decision processes.

PubMed

Banks, W P

2000-07-01

Recognition memory, source memory, and exclusion performance are three important domains of study in memory, each with its own findings, it specific theoretical developments, and its separate research literature. It is proposed here that results from all three domains can be treated with a single analytic model. This article shows how to generate a comprehensive memory representation based on multidimensional signal detection theory and how to make predictions for each of these paradigms using decision axes drawn through the space. The detection model is simpler than the comparable multinomial model, it is more easily generalizable, and it does not make threshold assumptions. An experiment using the same memory set for all three tasks demonstrates the analysis and tests the model. The results show that some seemingly complex relations between the paradigms derive from an underlying simplicity of structure.

Classification of independent components of EEG into multiple artifact classes.

PubMed

Frølich, Laura; Andersen, Tobias S; Mørup, Morten

2015-01-01

In this study, we aim to automatically identify multiple artifact types in EEG. We used multinomial regression to classify independent components of EEG data, selecting from 65 spatial, spectral, and temporal features of independent components using forward selection. The classifier identified neural and five nonneural types of components. Between subjects within studies, high classification performances were obtained. Between studies, however, classification was more difficult. For neural versus nonneural classifications, performance was on par with previous results obtained by others. We found that automatic separation of multiple artifact classes is possible with a small feature set. Our method can reduce manual workload and allow for the selective removal of artifact classes. Identifying artifacts during EEG recording may be used to instruct subjects to refrain from activity causing them. Copyright © 2014 Society for Psychophysiological Research.

Association of comorbid mental health symptoms and physical health conditions with employee productivity.

PubMed

Parker, Kristin M; Wilson, Mark G; Vandenberg, Robert J; DeJoy, David M; Orpinas, Pamela

2009-10-01

This study tests the hypothesis that employees with comorbid physical health conditions and mental health symptoms are less productive than other employees. Self-reported health status and productivity measures were collected from 1723 employees of a national retail organization. chi2, analysis of variance, and linear contrast analyses were conducted to evaluate whether health status groups differed on productivity measures. Multivariate linear regression and multinomial logistic regression analyses were conducted to analyze how predictive health status was of productivity. Those with comorbidities were significantly less productive on all productivity measures compared with all other health status groups and those with only physical health conditions or mental health symptoms. Health status also significantly predicted levels of employee productivity. These findings provide evidence for the relationship between health statuses and productivity, which has potential programmatic implications.

Demographic and Motivation Differences Among Online Sex Offenders by Type of Offense: An Exploration of Routine Activities Theories.

PubMed

Navarro, Jordana N; Jasinski, Jana L

2015-01-01

This article presents an analysis of the relationship between online sexual offenders' demographic background and characteristics indicative of motivation and offense type. Specifically, we investigate whether these characteristics can distinguish different online sexual offender groups from one another as well as inform routine activity theorists on what potentially motivates perpetrators. Using multinomial logistic regression, this study found that online sexual offenders' demographic backgrounds and characteristics indicative of motivation do vary by offense types. Two important implications of this study are that the term "online sexual offender" encompasses different types of offenders, including some who do not align with mainstream media's characterization of "predators," and that the potential offender within routine activity theory can be the focus of empirical investigation rather than taken as a given in research.

[Depression Symptoms of Mothers and Fathers of Persons with Schizophrenia].

PubMed

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.

The impact of childhood experiences and family members outside the household on residential environment choices.

PubMed

Blaauboer, Marjolein

2011-01-01

Choices of urban, suburban or rural residential environments have often been studied from a life-course perspective. In this paper, an examination is made of the influence of childhood experiences and of residential environment choices of family members outside the household. It is argued that socialisation, location-specific capital and the wish to maintain close family ties may result in living in a similar residential environment later in life and in similar environments to siblings and parents. Results of multinomial logistic regression analyses of data from the Netherlands Kinship Panel Study show that the residential environment during childhood is indeed strongly associated with the current residential environment. Moreover, individuals show a strong similarity to their parents and siblings in their residential environment, even after accounting for residential inertia and return migration.

Town-Level Characteristics and Smoking Policy Adoption in Massachusetts: Are Local Restaurant Smoking Regulations Fostering Disparities in Health Protection?

PubMed Central

Skeer, Margie; George, Sarah; Hamilton, William L.; Cheng, Debbie M.; Siegel, Michael

2004-01-01

Objectives. We identified and quantified differences in sociodemographic characteristics of communities relative to the strength of local restaurant smoking regulations in Massachusetts. Methods. We examined the relationship between the strength of the 351 local restaurant smoking regulations in Massachusetts and a number of town-level characteristics, using a multinomial logistic regression model. Results. Characteristics important to the adoption of stronger restaurant smoking regulations included higher education and per capita income, geographic region, voter support for a state cigarette tax initiative, board of health funding to promote clean indoor air policymaking, and the presence of a bordering town with a strong regulation. Conclusions. The current pattern of smoke-free restaurant policy enactment fosters socioeconomic and geographic disparities in health protection, undermining an important national health goal. PMID:14759944

Employee well-being, early-retirement intentions, and company performance.

PubMed

von Bonsdorff, Monika E; Vanhala, Sinikka; Seitsamo, Jorma; Janhonen, Minna; Husman, Päivi

2010-12-01

To explore the relationship between employee well-being and early-retirement intentions, and the extent to which early-retirement intentions are associated with company performance. This study is based on cross-sectional survey data on the ageing employees of the Finnish metal industry and retail trade, collected in 2007 (company-level n = 129, employee-level n = 1281). It was analyzed using multinomial logistic and multiple regression analysis. Poor work ability, frequent emotional exhaustion, low organizational commitment, and job control were associated with the prevalence of early-retirement intentions among aging employees in both industries. Metal industry employees' early-retirement intentions were associated with weaker company performance measured by the perceptions of the manager. By enhancing well-being, employees may stay at work for longer rather than retiring early. Early-retirement intentions can be counterproductive for companies.

Configurations of Adolescents' Peer Experiences: Associations With Parent-Child Relationship Quality and Parental Problem Behavior.

PubMed

Kretschmer, Tina; Sentse, Miranda; Meeus, Wim; Verhulst, Frank C; Veenstra, René; Oldehinkel, Albertine J

2016-09-01

Adolescents' peer experiences embrace behavior, relationship quality, status, and victimization, but studies that account for multiple dimensions are rare. Using latent profile modeling and measures of peer behavior, relationship quality, peer status, and victimization assessed from 1,677 adolescents, four profiles were identified: High Quality, Low Quality, Low Quality Victimized, and Deviant Peers. Multinomial logistic regressions showed that negative parent-child relationships in preadolescence reduced the likelihood of High Quality peer relations in mid-adolescence but only partly differentiated between the other three profiles. Moderation by gender was partly found with girls showing greater sensitivity to parent-child relationship quality with respect to peer experiences. Results underline the multifaceted nature of peer experiences, and practical and theoretical implications are discussed. © 2015 The Authors. Journal of Research on Adolescence © 2015 Society for Research on Adolescence.

Associations between low back pain and depression and somatization in a Canadian emerging adult population

PubMed Central

Robertson, David; Kumbhare, Dinesh; Nolet, Paul; Srbely, John; Newton, Genevieve

2017-01-01

Introduction The association between depression, somatization and low back pain has been minimally investigated in a Canadian emerging adult population. Methods 1013 first year Canadian university students completed the Modified Zung Depression Index, the Modified Somatic Perception Questionnaire, and a survey about low back pain frequency and intensity. Multinomial logistic regression was used to measure associations between low back pain and depression and somatization, both independently and co-occurring. Results Over 50% of subjects reported low back pain across grades, and both depression and somatization were significantly positively associated with low back pain. Several positive associations between the cooccurrence of somatization and depression with various grades of low back pain were observed. Discussion These results suggest that low back pain, depression and somatization are relatively common at the onset of adulthood, and should be considered an important focus of public health. PMID:28928493

Expenditures on family dental care by active duty soldiers.

PubMed

Chisick, M C

1996-01-01

Expenditures on family dental care by U.S. active duty soldiers were explored in this 1992 worldwide survey. Of 9,560 respondents (62% response rate), 7,187 claimed dependents and 5,569 provided reliable data. Mean annual expenditures and multinomial regression on a distribution of expenditures were calculated. Results show average family dental care expenditures were as follows: total sample, $135; childless couples, $59; couples with children, $154; and single parents, $120. Between 72 and 83% of families spent $0 on dental care. Excluding non-spenders, overall expenditures averaged as follows: total sample, $531; childless couples, $354; couples with children, $560; and single parents, $470. Regression results show that expenditures on family dental care by soldiers are influenced by different factors depending on family composition. Policy measures to encourage optimal dental care by families of active duty soldiers should focus on increasing insurance coverage and use.

Predicting Time Spent in Treatment in a Sample of Danish Survivors of Child Sexual Abuse.

PubMed

Fletcher, Shelley; Elklit, Ask; Shevlin, Mark; Armour, Cherie

2017-07-01

The aim of this study was to identify significant predictors of length of time spent in treatment. In a convenience sample of 439 Danish survivors of child sexual abuse, predictors of time spent in treatment were examined. Assessments were conducted on a 6-month basis over a period of 18 months. A multinomial logistic regression analysis revealed that the experience of neglect in childhood and having experienced rape at any life stage were associated with less time in treatment. Higher educational attainment and being male were associated with staying in treatment for longer periods of time. These factors may be important for identifying those at risk of terminating treatment prematurely. It is hoped that a better understanding of the factors that predict time spent in treatment will help to improve treatment outcomes for individuals who are at risk of dropping out of treatment at an early stage.

The development of episodic memory: items, contexts, and relations.

PubMed

Yim, Hyungwook; Dennis, Simon J; Sloutsky, Vladimir M

2013-11-01

Episodic memory involves the formation of relational structures that bind information about the stimuli people experience to the contexts in which they experience them. The ability to form and retain such structures may be at the core of the development of episodic memory. In the first experiment reported here, 4- and 7-year-olds were presented with paired-associate learning tasks requiring memory structures of different complexity. A multinomial-processing tree model was applied to estimate the use of different structures in the two age groups. The use of two-way list-context-to-target structures and three-way structures was found to increase between the ages of 4 and 7. Experiment 2 demonstrated that the ability to form increasingly complex relational memory structures develops between the ages of 4 and 7 years and that this development extends well into adulthood. These results have important implications for theories of memory development.

Going Back Part-time: Family Leave Legislation and Women’s Return to Work

PubMed Central

2012-01-01

Using a multinomial logit model with data from the Survey of Income and Program Participation, this paper tests whether the implementation of the Family and Medical Leave Act (FMLA) is associated with an increase in return to work at part-time status among first-time mothers working full-time during their pregnancy. I find a statistically significant trend of increasingly higher odds of returning to work at part-time status relative to return at full-time status, beginning in 1993 (the year in which the FMLA is implemented). Furthermore, an additional week of either state or federal leave is significantly associated with a higher odds of return at part-time status. This article provides evidence that job protection and leave legislation may help facilitate higher levels of labor force participation among women with small children, through more flexible work arrangements. PMID:22685365

The demand for child curative care in two rural thanas of Bangladesh: effect of income and women's employment.

PubMed

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.

Variations in pastors' perceptions of the etiology of depression by race and religious affiliation.

PubMed

Payne, Jennifer Shepard

2009-10-01

Depression is a major, preventable problem in the United States, yet relatively few individuals seek care in traditional mental health settings. Instead, many choose to confide in friends, family, or clergy. Thus, it is important to discover how clergy perceive the definition of and etiology of depression. The author conducted a survey with 204 Protestant pastors in California. Multinomial logistic regression revealed a statistically significant difference in how depression is perceived based on race. Caucasian American pastors more readily agreed with the statement that depression was a biological mood disorder, while African American pastors more readily agreed that depression was a moment of weakness when dealing with trials and tribulations. Also, mainline Protestants more frequently disagreed with statements about spiritual causes of depression than Pentecostals and non-denominational pastors. The findings suggest that racial and religious affiliational influences shape how pastors view, and ultimately intervene, in the area of depression.

College Student Attitudes Towards "Smart" Guns: Results from a Nationwide Survey.

PubMed

Wallace, Lacey N; Dunn, Kaylin C

2018-02-01

Existing studies focusing on "smart" guns, weapons that can only be fired by an authorized user, have focused largely on overall views towards the topic. Little is known about how views differ within key demographics or why Americans feel positively or negatively towards smart guns. This study used data from a nationwide web survey of 520 college students to address these concerns. Multinomial regression was used to identify patterns of smart gun preference in quantitative data. Respondents' open-ended reasoning for their views was examined through common themes and descriptive statistics. About half of the sample preferred smart guns over traditional firearms, with support more likely among females and liberals. Those with more advanced academic standing were more likely to have a traditional gun preference. The sample did not rank cost as a significant concern. Child protection was a much less prominent theme than concerns over (un)authorized users.

School Socioeconomic Composition and Adolescent Sexual Initiation in Malawi.

PubMed

Kim, Jinho

2015-09-01

Numerous studies have documented the determinants of sexual behavior among adolescents in less-developed countries, yet relatively little is known about the influence of social contexts such as school and neighborhood. Using two waves of data from a school-based longitudinal survey conducted in Malawi from 2011-13, this study advances our understanding of the relationship between school-level socioeconomic contexts and adolescents' sexual activity. The results from two-level multinomial logistic regression models suggest that high socioeconomic composition of the student body in school decreases the odds of initiation of sexual activity, independent of other important features of schools and individual-level characteristics. This study also finds that the association between school socioeconomic composition and sexual activity is statistically significant among male adolescents but not female adolescents, suggesting that schools' socioeconomic contexts may be more relevant to male adolescents' initiation of sexual activity. © 2015 The Population Council, Inc.

School socioeconomic composition and adolescent sexual initiation in Malawi

PubMed Central

Kim, Jinho

2015-01-01

While numerous studies have documented the determinants of sexual behavior among adolescents in less developed countries, relatively little is known about the influence of social contexts such as school and neighborhood. Using two waves of data from a school-based longitudinal survey conducted in Malawi from 2011 to 2013, this study advances our understanding of the relationship between school-level socioeconomic contexts and adolescents’ sexual activity. The results from two-level multinomial logistic regression models suggest that high socioeconomic composition of the student body in school decreases the odds of initiating sexual activity, independently of other important features of schools as well as individual-level characteristics. This study also finds that the association between school socioeconomic composition and sexual activity is statistically significant only among males, but not females, suggesting that school’s socioeconomic contexts may be more relevant to male adolescents’ initiation of sexual activity. PMID:26347090

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.

Behavioral Changes Predicting Temporal Changes in Perceived Popular Status

PubMed Central

Bowker, Julie C.; Rubin, Kenneth H.; Buskirk-Cohen, Alison; Rose-Krasnor, Linda; Booth-LaForce, Cathryn

2009-01-01

The primary objectives of this investigation were to determine the extent to which young adolescents are stable in high perceived popular status across the middle school transition and to examine whether changes in social behaviors predict the stability, gain, and loss of perceived popular status after the transition. The sample included 672 young adolescents (323 boys) who completed peer-nomination assessments of social behavior and perceived popularity at the end of elementary school (5th grade) and the beginning of middle school (6th grade). Findings indicated that 62 percent of perceived popular adolescents remained stable in their high popular status across the middle school transition. Multinomial logistic regression analyses revealed that a combination of aggression and arrogance/conceit was associated with stable and newly-gained perceived popular status after the middle school transition. Taken together, findings highlight the significance of contextual and temporal changes in adolescents’ perceived popular status. PMID:20209113

Determinants of edible oil choice by households in Tamil Nadu, India.

PubMed

Govindaraj, Gurrappa Naidu; Suryaprakash, Satrasala

2013-01-01

This study investigated the major determinants that influence the choice of edible oils by households across geographical zones in Tamil Nadu state, India. The primary data from 1,000 sample households were collected using a structured pre-tested questionnaire. Multinomial logit model was fitted for determining the factors. The results revealed that education, income, and households with a history of health problems were the important determinants that influenced the choice of low-saturated-fat oils, whereas the larger size households and weaker section households preferred low-priced palm oil. Income and education levels in Tamil Nadu state surged ahead in recent years. In consonance to these changes the nontraditional low-saturated fat containing sunflower oil demand will increase in many folds in coming years. Hence, besides traditional oils, sunflower oil production has to be stepped up on "mission mode" through appropriate production programs to meet the present and future edible oil demand domestically.

Performance of the likelihood ratio difference (G2 Diff) test for detecting unidimensionality in applications of the multidimensional Rasch model.

PubMed

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.

The Validity of Dependence as a Health Outcome Measure in Alzheimer’s Disease

PubMed Central

Spackman, D. Eldon; Kadiyala, Srikanth; Neumann, Peter J.; Veenstra, David L.; Sullivan, Sean D.

2013-01-01

Background Relating to Alzheimer’s disease (AD), dependence has been defined as the increased need for assistance due to deterioration in cognition, physical functioning, and behavior. Our objective was to evaluate the association between dependence and measures of functional impairment. Methods Data were compiled by the National Alzheimer’s Coordinating Center. We used multinomial logistic regression to estimate the association between dependence and cognition, physical functioning, and behavior. Results The independent association with dependence was positive. Dependence was most strongly associated with physical functioning. A secondary analysis suggested a strong association of dependence with multiple impairments, as measured by the interaction terms, in more severe patients. Conclusions We find that dependence is simultaneously associated with physical functioning, cognition, and behavior, which support the construct validity of dependence. Dependence might be a more simple measure to explain the multifaceted disease progression of AD and convey the increasing need for care. PMID:23512996

The validity of dependence as a health outcome measure in Alzheimer's disease.

PubMed

Spackman, D Eldon; Kadiyala, Srikanth; Neumann, Peter J; Veenstra, David L; Sullivan, Sean D

2013-05-01

Relating to Alzheimer's disease (AD), dependence has been defined as the increased need for assistance due to deterioration in cognition, physical functioning, and behavior. Our objective was to evaluate the association between dependence and measures of functional impairment. Data were compiled by the National Alzheimer's Coordinating Center. We used multinomial logistic regression to estimate the association between dependence and cognition, physical functioning, and behavior. The independent association with dependence was positive. Dependence was most strongly associated with physical functioning. A secondary analysis suggested a strong association of dependence with multiple impairments, as measured by the interaction terms, in more severe patients. We find that dependence is simultaneously associated with physical functioning, cognition, and behavior, which support the construct validity of dependence. Dependence might be a more simple measure to explain the multifaceted disease progression of AD and convey the increasing need for care.

Assessing the Relationship Between Chronic Health Conditions and Productivity Loss Trajectories

PubMed Central

Pranksy, Glenn

2014-01-01

Objective: To examine the relationship between health conditions and the risk for membership in longitudinal trajectories of productivity loss. Methods: Trajectories of productivity loss from the ages of 25 to 44 years, previously identified in the National Longitudinal Survey of Youth (NLSY79), were combined with information on health conditions from the age 40 years health module in the NLSY79. Multinomial logistic regression was used to examine the relative risk of being in the low-risk, early-onset increasing risk, late-onset increasing risk, or high-risk trajectories compared with the no-risk trajectory for having various health conditions. Results: The trajectories with the greatest probability of productivity loss longitudinally had a greater prevalence of the individual health conditions and a greater total number of health conditions experienced. Conclusions: Health conditions are associated with specific longitudinal patterns of experiencing productivity loss. PMID:25479294

Transitioning From Medicaid Disability Coverage to Long-Term Medicare Coverage: The Case of People Living With HIV/AIDS in California.

PubMed

Comulada, Warren S; Desmond, Katherine A; Gildner, Jennifer L; Leibowitz, Arleen A

2017-02-01

Medicaid can serve as a bridge to Medicare coverage for the long-term disabled with sufficient covered work experience. We perform multinomial logistic regression on 2007-2010 Medicare and Medicaid claims data to examine transitions to Medicare for people living with HIV/AIDS (PLWHA) in California who had Medicaid coverage in 2007. We find only 16% had obtained Medicare coverage by 2010. African-Americans, women, individuals with schizophrenia diagnoses, alcohol or substance abuse disorders, and any physical comorbidity were significantly less likely than others to obtain Medicare (p < 0.001). This study contributes new information on the impact of eligibility requirements for Medicare long-term disability insurance for PLWHA. About one-third of PLWHA under age 65 are covered by Medicaid. Many PLWHA get stuck in Medicaid because their disability prevents them from obtaining the additional employment experience needed to qualify for Medicare.

[Reciprocity between adult generations: family transfers over the life course].

PubMed

Brandt, Martina; Deindl, Christian; Haberkern, Klaus; Szydlik, Marc

2008-10-01

Intergenerational relations are characterised by reciprocal transfers and solidarity over the shared life span. Children care for their elderly parents, and parents support their adult children financially, for example, during their education or when they start their own household and family. From a life course-perspective, we analysed mutual transfers between parents and their adult children: Are transfers balanced over the life course and family-stages? Do we find patterns of direct or indirect reciprocity? Which factors facilitate exchange, and which do not? Using multinomial multilevel regression analyses based on the Survey of Health, Ageing and Retirement in Europe (SHARE) we trace transfers of time and money between parents and adult children back to opportunity, need and family structures. Remaining differences between European countries are explained by cultural contextual structures, here: family expenditures. The exchange between generations is reciprocal, but not necessarily balanced in various phases of family life.

Automated Detection of Diabetic Retinopathy using Deep Learning.

PubMed

Lam, Carson; Yi, Darvin; Guo, Margaret; Lindsey, Tony

2018-01-01

Diabetic retinopathy is a leading cause of blindness among working-age adults. Early detection of this condition is critical for good prognosis. In this paper, we demonstrate the use of convolutional neural networks (CNNs) on color fundus images for the recognition task of diabetic retinopathy staging. Our network models achieved test metric performance comparable to baseline literature results, with validation sensitivity of 95%. We additionally explored multinomial classification models, and demonstrate that errors primarily occur in the misclassification of mild disease as normal due to the CNNs inability to detect subtle disease features. We discovered that preprocessing with contrast limited adaptive histogram equalization and ensuring dataset fidelity by expert verification of class labels improves recognition of subtle features. Transfer learning on pretrained GoogLeNet and AlexNet models from ImageNet improved peak test set accuracies to 74.5%, 68.8%, and 57.2% on 2-ary, 3-ary, and 4-ary classification models, respectively.

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.

Work performance decrements are associated with Australian working conditions, particularly the demand to work longer hours.

PubMed

Holden, Libby; Scuffham, Paul A; Hilton, Michael F; Vecchio, Nerina N; Whiteford, Harvey A

2010-03-01

To demonstrate the importance of including a range of working conditions in models exploring the association between health- and work-related performance. The Australian Work Outcomes Research Cost-benefit study cross-sectional screening data set was used to explore health-related absenteeism and work performance losses on a sample of approximately 78,000 working Australians, including available demographic and working condition factors. Data collected using the World Health Organization Health and Productivity Questionnaire were analyzed with negative binomial logistic regression and multinomial logistic regressions for absenteeism and work performance, respectively. Hours expected to work, annual wage, and job insecurity play a vital role in the association between health- and work-related performance for both work attendance and self-reported work performance. Australian working conditions are contributing to both absenteeism and low work performance, regardless of health status.

Self-reported neck and shoulder pain in adolescents is associated with episodic and chronic migraine.

PubMed

Landgraf, Mirjam N; von Kries, Rüdiger; Heinen, Florian; Langhagen, Thyra; Straube, Andreas; Albers, Lucia

2016-07-01

The aim of this study was to verify the association between self-reported neck/shoulder pain and migraine and to compare findings of chronic and episodic migraine in adolescents. In this cross-sectional study, 601 secondary-school students filled in questionnaires about headache appearance, type and frequency, neck and shoulder pain and lifestyle factors. The adjusted strength of the association between reported neck and shoulder pain and migraine (assessed in multinomial regression models) increased with the frequency of migraine: less than once a week (OR = 1.40; 95% CI = (0.85-2.30)), weekly (OR = 2.14; 95% CI = (1.42-3.24)), and at least 15 days/month (OR = 7.27; 95% CI = (3.42-15.44)). In adolescents the association between self-reported neck and shoulder pain and migraine is most pronounced in migraine with a high attack frequency. © International Headache Society 2015.

Impacts of geographical locations and sociocultural traits on the Vietnamese entrepreneurship.

PubMed

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.

The public understanding of nanotechnology in the food domain: the hidden role of views on science, technology, and nature.

PubMed

Vandermoere, Frederic; Blanchemanche, Sandrine; Bieberstein, Andrea; Marette, Stephan; Roosen, Jutta

2011-03-01

In spite of great expectations about the potential of nanotechnology, this study shows that people are rather ambiguous and pessimistic about nanotechnology applications in the food domain. Our findings are drawn from a survey of public perceptions about nanotechnology food and nanotechnology food packaging (N = 752). Multinomial logistic regression analyses further reveal that knowledge about food risks and nanotechnology significantly influences people's views about nanotechnology food packaging. However, knowledge variables were unrelated to support for nanofood, suggesting that an increase in people's knowledge might not be sufficient to bridge the gap between the excitement some business leaders in the food sector have and the restraint of the public. Additionally, opposition to nanofood was not related to the use of heuristics but to trust in governmental agencies. Furthermore, the results indicate that public perceptions of nanoscience in the food domain significantly relate to views on science, technology, and nature.

Condensate statistics and thermodynamics of weakly interacting Bose gas: Recursion relation approach

NASA Astrophysics Data System (ADS)

Dorfman, K. E.; Kim, M.; Svidzinsky, A. A.

2011-03-01

We study condensate statistics and thermodynamics of weakly interacting Bose gas with a fixed total number N of particles in a cubic box. We find the exact recursion relation for the canonical ensemble partition function. Using this relation, we calculate the distribution function of condensate particles for N=200. We also calculate the distribution function based on multinomial expansion of the characteristic function. Similar to the ideal gas, both approaches give exact statistical moments for all temperatures in the framework of Bogoliubov model. We compare them with the results of unconstraint canonical ensemble quasiparticle formalism and the hybrid master equation approach. The present recursion relation can be used for any external potential and boundary conditions. We investigate the temperature dependence of the first few statistical moments of condensate fluctuations as well as thermodynamic potentials and heat capacity analytically and numerically in the whole temperature range.

Heterogeneous Tensor Decomposition for Clustering via Manifold Optimization.

PubMed

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.

A Budget Proposal for China's Public Long-Term Care Policy.

PubMed

Lu, Bei; Liu, Xiaoting; Yang, Mingxu

2017-01-01

Long-term care (LTC) policy is at an experimental stage in China, characterized by various regional pilot programs. The public cost of LTC is difficult to estimate due to a lack of clarity about policy detail from the central government. This article analyzes the current disabled status for vulnerable older people without sufficient financial resources and family supports. It focuses on estimating a safety net public subsidy policy for LTC services in China, both for today and into the future, using China Health and Retirement Longitudinal Survey (CHARLS) data, 2011 wave, with the methods of multinomial logistic regression and simulation. The key contribution is to estimate the future disability trend and LTC public cost based on changes in education, population ageing, and urbanization. Disability prevalence might be decreasing partly due to higher education, urbanization, and better health care, and the overall public LTC costs might be growing by the results of projection.

Recommender system based on scarce information mining.

PubMed

Lu, Wei; Chung, Fu-Lai; Lai, Kunfeng; Zhang, Liang

2017-09-01

Guessing what user may like is now a typical interface for video recommendation. Nowadays, the highly popular user generated content sites provide various sources of information such as tags for recommendation tasks. Motivated by a real world online video recommendation problem, this work targets at the long tail phenomena of user behavior and the sparsity of item features. A personalized compound recommendation framework for online video recommendation called Dirichlet mixture probit model for information scarcity (DPIS) is hence proposed. Assuming that each clicking sample is generated from a representation of user preferences, DPIS models the sample level topic proportions as a multinomial item vector, and utilizes topical clustering on the user part for recommendation through a probit classifier. As demonstrated by the real-world application, the proposed DPIS achieves better performance in accuracy, perplexity as well as diversity in coverage than traditional methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Validation of patient and nurse short forms of the Readiness for Hospital Discharge Scale and their relationship to return to the hospital.

PubMed

Weiss, Marianne E; Costa, Linda L; Yakusheva, Olga; Bobay, Kathleen L

2014-02-01

To validate patient and nurse short forms for discharge readiness assessment and their associations with 30-day readmissions and emergency department (ED) visits. A total of 254 adult medical-surgical patients and their discharging nurses from an Eastern US tertiary hospital between May and November, 2011. Prospective longitudinal design, multinomial logistic regression analysis. Nurses and patients independently completed an eight-item Readiness for Hospital Discharge Scale on the day of discharge. Patient characteristics, readmissions, and ED visits were electronically abstracted. Nurse assessment of low discharge readiness was associated with a six- to nine-fold increase in readmission risk. Patient self-assessment was not associated with readmission; neither was associated with ED visits. Nurse discharge readiness assessment should be added to existing strategies for identifying readmission risk. © Health Research and Educational Trust.

Web usage mining at an academic health sciences library: an exploratory study.

PubMed

Bracke, Paul J

2004-10-01

This paper explores the potential of multinomial logistic regression analysis to perform Web usage mining for an academic health sciences library Website. Usage of database-driven resource gateway pages was logged for a six-month period, including information about users' network addresses, referring uniform resource locators (URLs), and types of resource accessed. It was found that referring URL did vary significantly by two factors: whether a user was on-campus and what type of resource was accessed. Although the data available for analysis are limited by the nature of the Web and concerns for privacy, this method demonstrates the potential for gaining insight into Web usage that supplements Web log analysis. It can be used to improve the design of static and dynamic Websites today and could be used in the design of more advanced Web systems in the future.

Husband/Partner Intoxication and Intimate Partner Violence Against Women in the Philippines.

PubMed

Kerridge, Bradley T; Tran, Phu

2016-09-01

This study examined husband/partner intoxication and experience with physical, sexual, and emotional intimate partner violence against women (IPVAW) using data derived from a nationally representative survey conducted in the Philippines in 2013. Multivariate logistic regression analyses were used to examine the association between intoxication and 3 different types of intimate partner violence against women. Multinomial logistic regression was used to examine intoxication and severity of violence. In this sample, 28.8% of women reported experiencing any form of intimate partner violence and 92.9% of women reported their partner being intoxicated at least sometimes. Intoxication was significantly associated with all 3 types of intimate partner violence, while the odds of experiencing one form of IPVAW versus no form of IPVAW and 2 forms of IPVAW versus 1 form of IPVAW was greater among women reporting frequency of husband/partner intoxication as often. © 2016 APJPH.

[Mental disorders and participation in the labor market: a multicenter national study in Brazil].

PubMed

Assunção, Ada Ávila; Lima, Eduardo de Paula; Guimarães, Mark Drew Crosland

2017-04-03

The objective was to explore the relationship between labor market participation and patient characteristics in a representative sample of 2,475 adults admitted to 26 Brazilian mental health institutions (15 Centers for Psychosocial Care and 11 hospitals). Socio-demographic, clinical, and behavioral characteristics were obtained with structured interviews. Multinomial regression was used. Increased likelihood of temporary absence from the work market was associated with female gender, single, divorced, or widowed conjugal status, lack of stable housing, and history of first admission or treatment before the age of 18. Increased likelihood of permanent absence from the labor market was associated with older age. Temporary or permanent leave from work was directly associated with low schooling, lifetime hospitalizations, and diagnosis of severe mental disorder and inversely associated with alcohol and drug use. The occupational vulnerabilities identified in the study raise the debate on specific policies for the mental health sector.

[Changes in psychopathological symptoms during the waiting period for outpatient psychotherapy].

PubMed

Huckert, Thomas Frank; Hank, Petra; Krampen, Günter

2012-08-01

This study empirically tests symptom changes in a sample of 106 psychotherapy outpatients during a 6-month waiting period before treatment commencement. Using indirect measurement of change, the patients improve in psychopathological symptoms. Using direct measurement of change, 48% of the outpatients show no significant change in psychopathological symptoms. However, the symptoms of 29% improve and 23% worsen. Using multinomial logistic regression, group membership (no change, positive change, negative change) can be predicted by personality traits for 60% of the patients. Social trust negatively predicts changes for the worse. Liberal gender-role orientation positively predicts improvement. A positive self-concept of ability positively predicts changes for the worse. Moreover sociodemographic variables correctly predict group membership for 57% of the patients. Age positively predicts changes for the worse. Female gender negatively predicts improvement. © Georg Thieme Verlag KG Stuttgart · New York.

The relationship between organizational culture and performance in acute hospitals.

PubMed

Jacobs, Rowena; Mannion, Russell; Davies, Huw T O; Harrison, Stephen; Konteh, Fred; Walshe, Kieran

2013-01-01

This paper examines the relationship between senior management team culture and organizational performance in English acute hospitals (NHS Trusts) over three time periods between 2001/2002 and 2007/2008. We use a validated culture rating instrument, the Competing Values Framework, to measure senior management team culture. Organizational performance is assessed using a wide range of routinely collected indicators. We examine the associations between organizational culture and performance using ordered probit and multinomial logit models. We find that organizational culture varies across hospitals and over time, and this variation is at least in part associated in consistent and predictable ways with a variety of organizational characteristics and routine measures of performance. Moreover, hospitals are moving towards more competitive culture archetypes which mirror the current policy context, though with a stronger blend of cultures. The study provides evidence for a relationship between culture and performance in hospital settings. Copyright © 2012 Elsevier Ltd. All rights reserved.

Driver Vision Based Perception-Response Time Prediction and Assistance Model on Mountain Highway Curve.

PubMed

Li, Yi; Chen, Yuren

2016-12-30

To make driving assistance system more humanized, this study focused on the prediction and assistance of drivers' perception-response time on mountain highway curves. Field tests were conducted to collect real-time driving data and driver vision information. A driver-vision lane model quantified curve elements in drivers' vision. A multinomial log-linear model was established to predict perception-response time with traffic/road environment information, driver-vision lane model, and mechanical status (last second). A corresponding assistance model showed a positive impact on drivers' perception-response times on mountain highway curves. Model results revealed that the driver-vision lane model and visual elements did have important influence on drivers' perception-response time. Compared with roadside passive road safety infrastructure, proper visual geometry design, timely visual guidance, and visual information integrality of a curve are significant factors for drivers' perception-response time.

Correlates of bullying behaviors among a sample of North American Indigenous adolescents

PubMed Central

Melander, Lisa A.; Hartshorn, Kelley J. Sittner; Whitbeck, Les B.

2013-01-01

The purpose of this study was to examine the relationship between familial, educational, and psychosocial factors and bullying among 702 North American Indigenous adolescents aged 11–14 years. The study used multinomial logistic regression models to differentiate correlates of bully perpetration and victimization versus being neither and between being a perpetrator versus being a victim. Analyses reveal that being a bully victim had different correlates than being a perpetrator. Perceived discrimination was associated with increased odds of being either a victim or a perpetrator, relative to being neither. Several factors differentiated being a bully perpetrator from being a bully victim: adolescent age, parental warmth and support, depressive symptoms, anger, and school adjustment. These findings expand upon the limited understanding of the factors associated with bullying among North American Indigenous youth. Bullying intervention and prevention programs that target Indigenous adolescents should be culturally grounded and begin early within the family. PMID:23849662

Exploring Associations Between Perceived Measures of the Environment and Walking Among Brazilian Older Adults.

PubMed

Corseuil Giehl, Maruí W; Hallal, Pedro C; Brownson, Ross C; d'Orsi, Eleonora

2017-02-01

To investigate the associations between perceived environment features and walking in older adults. A cross-sectional population-based study was performed in Florianopolis, Brazil, including 1,705 older adults (60+ years). Walking was measured by the International Physical Activity Questionnaire (IPAQ), and perceived environment was assessed through the Neighborhood Environment Walkability Scale. We conducted a multinomial logistic regression to examine the association between perceived environment and walking. The presence of sidewalks was related to both walking for transportation and for leisure. Existence of crosswalks in the neighborhood, safety during the day, presence of street lighting, recreational facilities, and having dog were significant predictors of walking for transportation. Safety during the day and social support were significantly associated with walking for leisure. The perceived environment may affect walking for specific purposes among older adults. Investments in the environment may increase physical activity levels of older adults in Brazil.

Trouble Sleeping Associated with Lower Work Performance and Greater Healthcare Costs: Longitudinal Data from Kansas State Employee Wellness Program

PubMed Central

Hui, Siu-kuen Azor; Grandner, Michael A.

2015-01-01

Objective To examine the relationships between employees’ trouble sleeping and absenteeism, work performance, and healthcare expenditures over a two year period. Methods Utilizing the Kansas State employee wellness program (EWP) dataset from 2008–2009, multinomial logistic regression analyses were conducted with trouble sleeping as the predictor and absenteeism, work performance, and healthcare costs as the outcomes. Results EWP participants (N=11,698 in 2008; 5,636 followed up in 2009) who had higher levels of sleep disturbance were more likely to be absent from work (all p < 0.0005), have lower work performance ratings (all p < 0.0005), and have higher healthcare costs (p < 0.0005). Longitudinally, more trouble sleeping was significantly related to negative changes in all outcomes. Conclusions Employees’ trouble sleeping, even at a sub-clinical level, negatively impacts on work attendance, work performance, and healthcare costs. PMID:26461857

Trouble Sleeping Associated With Lower Work Performance and Greater Health Care Costs: Longitudinal Data From Kansas State Employee Wellness Program.

PubMed

Hui, Siu-kuen Azor; Grandner, Michael A

2015-10-01

To examine the relationships between employees' trouble sleeping and absenteeism, work performance, and health care expenditures over a 2-year period. Utilizing the Kansas State employee wellness program (EWP) data set from 2008 to 2009, multinomial logistic regression analyses were conducted with trouble sleeping as the predictor and absenteeism, work performance, and health care costs as the outcomes. EWP participants (N = 11,698 in 2008; 5636 followed up in 2009) who had higher levels of sleep disturbance were more likely to be absent from work (all P < 0.0005), have lower work performance ratings (all P < 0.0005), and have higher health care costs (P < 0.0005). Longitudinally, more trouble sleeping was significantly related to negative changes in all outcomes. Employees' trouble sleeping, even at a subclinical level, negatively impacts on work attendance, work performance, and health care costs.

Romantic attraction and adolescent smoking trajectories.

PubMed

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.

Consistency in reporting condom use between husbands and wives in Bangladesh.

PubMed

Islam, Mohammad Amirul; Padmadas, Sabu S; Smith, Peter W F

2010-07-01

Consistency in reporting contraceptive use between spouses is little understood, especially in developing settings. This research challenges the accuracy of measuring contraceptive prevalence rate, which is traditionally calculated based on women's responses. Multinomial logistic regression techniques are employed on a couple dataset from the 1999-2000 Bangladesh Demographic and Health Survey (DHS) to investigate the consistency in reporting condom use between husbands and wives. The level of inconsistency in reporting condom use was about 46%, of which about 32% was explained by husbands reporting condom use while wives did not, and 14% by wives reporting condom use while husbands did not. Regression analysis showed that couple education and age difference between the spouses are significant determinants of inconsistent reporting behaviour. The findings suggest the need for alternative approaches (questions) in the DHS to ensure consistency in the collection of data related to use of family planning methods.

Perceived health status and daily activity participation of older Malaysians.

PubMed

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

2011-07-01

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

Using GA-Ridge regression to select hydro-geological parameters influencing groundwater pollution vulnerability.

PubMed

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.

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.

Positive and negative generation effects in source monitoring.

PubMed

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.

Customization in Prescribing for Bipolar Disorder

PubMed Central

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

Customization in prescribing for bipolar disorder.

PubMed

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.

TRANSITIONING FROM MEDICAID DISABILITY COVERAGE TO LONG-TERM MEDICARE COVERAGE: THE CASE OF PEOPLE LIVING WITH HIV/AIDS IN CALIFORNIA

PubMed Central

Comulada, Warren S.; Desmond, Katherine A.; Gildner, Jennifer L.; Leibowitz, Arleen A

2017-01-01

Medicaid can serve as a bridge to Medicare coverage for the long-term disabled with sufficient covered work experience. We perform multinomial logistic regression on 2007–2010 Medicare and Medicaid claims data to examine transitions to Medicare for people living with HIV/AIDS (PLWHA) in California who had Medicaid coverage in 2007. We find only 16% had obtained Medicare coverage by 2010. African-Americans, women, individuals with schizophrenia diagnoses, alcohol or substance abuse disorders, and any physical comorbidity were significantly less likely than others to obtain Medicare (p < 0.001). This study contributes new information on the impact of eligibility requirements for Medicare long-term disability insurance for PLWHA. About one-third of PLWHA under age 65 are covered by Medicaid. Many PLWHA get stuck in Medicaid because their disability prevents them from obtaining the additional employment experience needed to qualify for Medicare. PMID:28195778

Factors related to meeting physical activity guidelines in active college students: A social cognitive perspective.

PubMed

Farren, G L; Zhang, T; Martin, S B; Thomas, K T

2017-01-01

To examine the relations of sex, exercise self-efficacy, outcome expectations, and social support with meeting physical activity guidelines (PAGs). Three hundred ninety-six college students participated in this study in the summer 2013. Students completed online questionnaires that assessed physical activity behaviors and psychosocial factors (ie, self-efficacy, outcome expectancies, and social support). Students' physical activity profile was categorized as meeting no PAGs, meeting aerobic PAGs only, meeting muscle-strengthening PAGs only, or meeting both PAGs. A multinomial logistic regression revealed that students' sex and psychosocial factors significantly affected the odds of meeting any and all PAGs. Sex significantly moderated the relationship between outcome expectancy and meeting aerobic PAGs and between outcome expectancy meeting muscle-strengthening PAGs. Results indicate that interventions designed to increase psychosocial factors may increase the likelihood of students meeting any and all PAGs. Social support may be especially beneficial for increasing muscle-strengthening activity.

Influence of quartz exposure on lung cancer types in cases of lymph node-only silicosis and lung silicosis in German uranium miners.

PubMed

Mielke, Stefan; Taeger, Dirk; Weitmann, Kerstin; Brüning, Thomas; Hoffmann, Wolfgang

2018-05-04

Inhaled crystalline quartz is a carcinogen. Analyses show differences in the distribution of lung cancer types depending on the status of silicosis. Using 2,524 lung tumor cases from the WISMUT autopsy repository database, silicosis was differentiated into cases without silicosis in lung parenchyma and its lymph nodes, with lymph node-only silicosis, or with lung silicosis including lymph node silicosis. The proportions of adenocarcinoma, squamous cell carcinoma, and small-cell lung carcinoma mortality for increasing quartz exposures were estimated in a multinomial logistic regression model. The relative proportions of the lung cancer subtypes in lymph node-only silicosis were more similar to lung silicosis than without any silicosis. The results support the hypothesis that quartz-related carcinogenesis in case of lymph node-only silicosis is more similar to that in lung silicosis than in without silicosis.

Going Back Part-time: Family Leave Legislation and Women's Return to Work.

PubMed

Schott, Whitney

2012-02-01

Using a multinomial logit model with data from the Survey of Income and Program Participation, this paper tests whether the implementation of the Family and Medical Leave Act (FMLA) is associated with an increase in return to work at part-time status among first-time mothers working full-time during their pregnancy. I find a statistically significant trend of increasingly higher odds of returning to work at part-time status relative to return at full-time status, beginning in 1993 (the year in which the FMLA is implemented). Furthermore, an additional week of either state or federal leave is significantly associated with a higher odds of return at part-time status. This article provides evidence that job protection and leave legislation may help facilitate higher levels of labor force participation among women with small children, through more flexible work arrangements.

The dose-response of time served in prison on mortality: New York State, 1989-2003.

PubMed

Patterson, Evelyn J

2013-03-01

I investigated the differential impact of the dose-response of length of stay on postprison mortality among parolees. Using 1989-2003 New York State parole administrative data from the Bureau of Justice Statistics on state correctional facilities, I employed multinomial logistic regression analyses and formal demographic techniques that used the life table of the populations to deduce changes in life expectancy. Each additional year in prison produced a 15.6% increase in the odds of death for parolees, which translated to a 2-year decline in life expectancy for each year served in prison. The risk was highest upon release from prison and declined over time. The time to recovery, or the lowest risk level, was approximately two thirds of the time served in prison. Incarceration reduces life span. Future research should investigate the pathways to this higher mortality and the possibilities of recovery.

The association between alcohol use and depressive symptoms across socioeconomic status among 40- and 45-year-old Norwegian adults.

PubMed

Martinez, Priscilla; Neupane, Sudan Prasad; Perlestenbakken, Berit; Toutoungi, Christina; Bramness, Jørgen G

2015-11-19

Little population-based data among middle-aged adults exists examining the relationships between depressive symptoms, alcohol use, and socio-economic status (SES). This study aimed to describe the relationships between depressive symptoms and alcohol use at different levels of SES and to determine differences across SES levels among a population-based sample of 40 and 45 year old adults in Norway. This analysis was based on data from two Norwegian health studies conducted in 2000 and 2001, and included community-dwelling Norwegian men and women aged 40 and 45 years. Self-reported frequency and quantity of alcoholic drinks was used to calculate past-year typical quantity of drinks consumed and frequency of 5+ drinks per occasion, or heavy episodic drinking (HED). Depressive symptoms were assessed with the 10-item Hopkins Symptom Checklist, and SES was measured as education level and employment status. To observe the association between depressive symptoms and alcohol use at each level of SES we fitted multinomial logistic regression models using each alcohol outcome as a dependent variable stratified by level of education and employment. To observe differences across levels of SES, we examined the interaction between depressive symptoms and SES level in multinomial logistic regression models for each alcohol measures. Having depressive symptoms was significantly associated with an increased risk of 5+ typical drinks among people in the lowest (RRR = 1.60, p ≤ 0.05) education level, and not among people in the highest. Conversely, significant associations were observed among all levels of employment. For frequency of HED, depressive symptoms was not significantly associated with frequency of HED at any education level. Depressive symptoms was associated with 13+ past year HED episodes among people with no employment (RRR = 1.97, p ≤ 0.05), and part-time employment (RRR = 2.33, p ≤ 0.01), and no association was observed among people with full-time employment. A significant interaction was observed for depressive symptoms and employment for risk of 13+ past-year HED episodes. The results show a variety of associations between depressive symptoms and alcohol use among people with lower SES, and suggest type of alcohol use and SES measure may influence the observation of an association between depressive symptoms and alcohol use at different SES levels.

Assessing coastal plain wetland composition using advanced spaceborne thermal emission and reflection radiometer imagery

NASA Astrophysics Data System (ADS)

Pantaleoni, Eva

Establishing wetland gains and losses, delineating wetland boundaries, and determining their vegetative composition are major challenges that can be improved through remote sensing studies. We used the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) to separate wetlands from uplands in a study of 870 locations on the Virginia Coastal Plain. We used the first five bands from each of two ASTER scenes (6 March 2005 and 16 October 2005), covering the visible to the short-wave infrared region (0.52-2.185mum). We included GIS data layers for soil survey, topography, and presence or absence of water in a logistic regression model that predicted the location of over 78% of the wetlands. While this was slightly less accurate (78% vs. 86%) than current National Wetland Inventory (NWI) aerial photo interpretation procedures of locating wetlands, satellite imagery analysis holds great promise for speeding wetland mapping, lowering costs, and improving update frequency. To estimate wetland vegetation composition classes, we generated a classification and regression tree (CART) model and a multinomial logistic regression (logit) model, and compared their accuracy in separating woody wetlands, emergent wetlands and open water. The overall accuracy of the CART model was 73.3%, while for the logit model was 76.7%. The CART producer's accuracy of the emergent wetlands was higher than the accuracy from the multinomial logit (57.1% vs. 40.7%). However, we obtained the opposite result for the woody wetland category (68.7% vs. 52.6%). A McNemar test between the two models and NWI maps showed that their accuracies were not statistically different. We conducted a subpixel analysis of the ASTER images to estimate canopy cover of forested wetlands. We used top-of-atmosphere reflectance from the visible and near infrared bands, Delta Normalized Difference Vegetation Index, and a tasseled cap brightness, greenness, and wetness in linear regression model with canopy cover as the dependent variable. The model achieved an adjusted-R 2 of 0.69 (RMSE = 2.7%) for canopy cover less than 16%, and an adjusted-R 2 of 0.04 (RMSE = 19.8%) for higher canopy cover values. Taken together, these findings suggest that satellite remote sensing, in concert with other spatial data, has strong potential for mapping both wetland presence and type.

Physical and temporal characteristics of under 19, under 21 and senior male beach volleyball players.

PubMed

Medeiros, Alexandre; Marcelino, Rui; Mesquita, Isabel; Palao, José Manuel

2014-09-01

This study aimed to assess the effects of age groups and players' role (blocker vs. defender specialist) in beach volleyball in relation to physical and temporal variables, considering quality of opposition. 1101 rallies from Under 19 (U19), 933 rallies from Under 21 (U21), and 1480 rallies from senior (senior) (Men's Swatch World Championships, 2010-2011) were observed using video match analysis. Cluster analysis was used to set teams' competitive levels and establish quality of opposition as "balanced", "moderate balanced" and "unbalanced" games. The analyzed variables were: temporal (duration of set, total rest time, total work time, duration of rallies, rest time between rallies) and physical (number of jumps and number of hits done by defenders and blockers) characteristics. A one-way ANOVA, independent samples t-test and multinomial logistic regression were performed to analyze the variables studied. The analysis of temporal and physical characteristics showed differences considering age group, player's role and quality of opposition. The duration of set, total rest time, and number of jumps done by defenders significantly increased from the U19 to senior category. Multinomial logistic regression showed that in: a) balanced games, rest time between rallies was higher in seniors than in U19 or U21; number of jumps done by defenders was higher in seniors than in U19) and U21; b) moderate balanced games, number of jumps done by defenders was higher in seniors than in U21 and number of jumps done by blockers was smaller in U19 than U21 or seniors; c) unbalanced games, no significant findings were shown. This study suggests differences in players' performances according to age group and players' role in different qualities of opposition. The article provides reference values that can be useful to guide training and create scenarios that resemble a competition, taking into account physical and temporal characteristics. Key PointsPlayer roles, quality of opposition, and competitive level of the teams influence physical and temporal characteristics, and they may be taken into consideration during the training by strength and conditioning coaches and coaches.More experienced players adopt strategies to better manage their effort and rest time between rallies.The game strategy affects the physical actions done by players (e.g. tendency to serve more to one player of the team affects the number of jumps performed by this player).

Factors associated with being underweight, overweight and obese among ever-married non-pregnant urban women in Bangladesh.

PubMed

Khan, M M H; Kraemer, A

2009-08-01

Extremes of body mass index (BMI), viz. underweight, overweight and obese categories, are associated with a variety of adverse health outcomes such as diabetes mellitus, cardiovascular diseases, low birth weight, poor quality of life and higher mortality. In Bangladesh, the prevalence of underweightness is very high with an increasing trend of overweightness and obesity. This is a serious public health concern as it indicates a dual burden of disease. The present study assessed the associations of being underweight, overweight and obese with socioeconomic, demographical and migration variables among ever-married non-pregnant urban Bangladeshi women aged 13-49 years. The data was extracted from the Bangladesh Demographic and Health Survey 2004. Bivariable, factor and multinomial logistic regression analyses were performed in this study. The prevalence of being underweight, overweight and obese among ever-married non-pregnant urban women in Bangladesh was 25.2 percent, 15.7 percent and 3.9 percent, respectively. Age, education, region of residence, marital status, current use of contraception and type of occupation were significantly associated with BMI categories. Adjusted multinomial logistic regression analysis indicated that women with a high socioeconomic status were significantly negatively associated with being underweight (odds ratio [OR] 0.55, 95 percent confidence interval [CI] 0.48-0.63) but positively associated with being overweight (OR 1.70, 95 percent CI 1.48-1.96) and obese (OR 2.48, 95 percent CI 1.89-3.26), as compared to the women with normal BMI. In contrast, women who migrated from rural to urban areas showed a significantly positive association with being underweight (OR 1.15, 95 percent CI 1.04-1.27) but negative associations with being overweight (OR 0.80, 95 percent CI 0.71-0.89) and obese (OR 0.75, 95 percent CI 0.62-0.92), when compared with women who did not migrate. Suitable interventions based on further studies are needed to reduce the prevalence of being underweight and overweight among ever-married non-pregnant urban women in Bangladesh. Factors, viz. socioeconomic status, rural-urban migration and education, should be considered while developing interventional strategies to reduce the prevalence of extreme BMIs among women living in urban areas of Bangladesh.

The association between maternal antioxidant levels in midpregnancy and preeclampsia.

PubMed

Cohen, Jacqueline M; Kramer, Michael S; Platt, Robert W; Basso, Olga; Evans, Rhobert W; Kahn, Susan R

2015-11-01

We sought to determine whether midpregnancy antioxidant levels are associated with preeclampsia, overall and by timing of onset. We carried out a case-control study, nested within a cohort of 5337 pregnant women in Montreal, Quebec, Canada. Blood samples obtained at 24-26 weeks were assayed for nonenzymatic antioxidant levels among cases of preeclampsia (n = 111) and unaffected controls (n = 441). We excluded women diagnosed with gestational hypertension only. We used logistic regression with the z-score of each antioxidant level as the main predictor variable for preeclampsia risk. We further stratified early-onset (<34 weeks) and late-onset preeclampsia and carried out multinomial logistic regression. Finally, we assessed associations between antioxidant biomarkers and timing of onset (in weeks) by Cox regression, with appropriate selection weights. We summed levels of correlated biomarkers (r(2) > 0.3) and log-transformed positively skewed distributions. We adjusted for body mass index, nulliparity, preexisting diabetes, hypertension, smoking, and proxies for ethnicity and socioeconomic status. The odds ratios for α-tocopherol, α-tocopherol:cholesterol, lycopene, lutein, and carotenoids (sum of α-carotene, β-carotene, anhydrolutein, α-cryptoxanthin, and β-cryptoxanthin) suggested an inverse association between antioxidant levels and overall preeclampsia risk; however, only lutein was significantly associated with overall preeclampsia in adjusted models (odds ratio, 0.60; 95% confidence interval, 0.46-0.77) per SD. In multinomial logistic models, the relative risk ratio (RRR) estimates for the early-onset subgroup were farther from the null than those for the late-onset subgroup. The ratio of α-tocopherol to cholesterol and retinol were significantly associated with early- but not late-onset preeclampsia: RRRs (95% confidence intervals) for early-onset preeclampsia 0.67 (0.46-0.99) and 1.61 (1.12-2.33), respectively. Lutein was significantly associated with both early- and late-onset subtypes in adjusted models; RRRs 0.53 (0.35-0.80) and 0.62 (0.47-0.82), respectively. Survival analyses confirmed these trends. Most antioxidants were more strongly associated with early-onset preeclampsia, suggesting that oxidative stress may play a greater role in the pathophysiology of early-onset preeclampsia. Alternatively, reverse causality may explain this pattern. Lutein was associated with both early- and late-onset preeclampsia and may be a promising nutrient to consider in preeclampsia prevention trials, if this finding is corroborated. Copyright © 2015 Elsevier Inc. All rights reserved.

An empirical comparison of methods for analyzing correlated data from a discrete choice survey to elicit patient preference for colorectal cancer screening

PubMed Central

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

Levels and patterns of physical activity and sedentary time among superdiverse adolescents in East London: a cross-sectional study.

PubMed

Curry, Whitney B; Dagkas, Symeon; Wilson, Marcia

2017-06-01

Little is known about the physical activity (PA) and sedentary time (ST) habits of adolescents from superdiverse communities in the UK. The objectives of this study are to examine and report the patterns of PA/ST among adolescents in East London living in superdiverse communities, to identify opportunities/barriers to PA and inform policy/practice. A total of 1260 young people (aged 11-13 years) from seven secondary schools in East London completed a questionnaire on PA/ST over the past seven days as part of the Newham's Every Child a Sports Person (NECaSP) intervention. Socio-demographic and anthropometric data were obtained. Significance tests were conducted to determine differences between socio-demographic and anthropometric predictors and PA/ST. Multinomial logit regression was used to explore the effects of ethnicity, sex, and body mass index (BMI) on PA levels. Males were significantly more likely to engage in PA at least five times during school in the past week (U = 5.07, z = -11.76, p < .05). Obese participants were less likely to report engaging in PA five times in the past week (U = 4.11, z =-1.17, p < .05). Black Caribbean girls (U = 5.08, z = -1.92, p < .05) were significantly more likely to report engaging in no activity. Multinomial logit regression analyses revealed that girls with higher BMI were less likely to engage in PA at least four times after school in the last week than boys (b = .11, Wald X 2 (1) = 9.81, p < .01). Walking (36.4%), jogging/running (29.9%), and football (28%) were the most frequently reported activities. Engaging girls in PA during and after school is important and making sports clubs and activities available and attractive to this target group may help increase engagement in PA and reduce ST. Findings support the need for more sex-specific and culturally responsive pedagogy in schools with curricula that respects diversity and individuality and has meaning and value amongst superdiverse young people. Finally, we need to extend current work presented and provide substantial evidence of the ways young people from minority ethnic groups process and act on the public health policy and the ways they understand and enact PA.

Association between serum alkaline phosphatase and primary resistance to erythropoiesis stimulating agents in chronic kidney disease: a secondary analysis of the HERO trial.

PubMed

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).

Long working hours and emotional well-being in korean manufacturing industry employees.

PubMed

Lee, Kyoung-Hye; Kim, Jong-Eun; Kim, Young-Ki; Kang, Dong-Mug; Yun, Myeong-Ja; Park, Shin-Goo; Song, Jae-Seok; Lee, Sang-Gil

2013-12-05

Korea is well known for its long work hours amongst employees. Because workers of the manufacturing industry are constantly exposed to extended work hours, this study was based on how long work hours affect their emotional well-being. The analysis was done using the secondary Korean Working Condition Survey (KWCS). Long work hours were defined to be more than 48 hours, and they were subcategorized into units of 52 hours and 60 hours. Based on the WHO (five) well-being index, emotional state was subdivided into three groups - reference group, low-mood group, and possible depression group- where 28 points and 50 points were division points, and two groups were compared at a time. Association between long work hours and emotional state was analyzed using binary and multinomial logistic regression analysis. Working for extended working hours in the manufacturing industry showed a statistically significant increase (t test p < 0.001) in trend among the possible depression group when compared to the reference group and the low-mood group. When demographical characteristics, health behaviors, socioeconomic state, and work-related characteristics were fixed as controlled variables, as work hours increased the odds ratio of the possible depression group increased compared to the reference group, and especially the odds ratio was 2.73 times increased for work hours between 48-52 and 4.09 times increased for 60 hours or more and both were statistically significant. In comparing the low-mood group and possible depression group, as work hours increased the odds ratio increased to 1.73, 2.39, and 4.16 times, and all work hours from working 48-52 hours, 53-60 hours, and 60 hours or more were statistically significant. Multinomial logistic regression analysis also showed that among the reference group and possible group, the possible depression group was statistically significant as odds ratio increased to 2.94 times in working 53-60 hours, and 4.35 times in 60 hours or more. Long work hours have an adverse effect on emotional well-being. A more diversified research towards variables that affect long work hours and emotional well-being and how they interact with each other and their relationship to overall health is imperative.

Patterns and determinants of care seeking for obstetric complications in rural northwest Bangladesh: analysis from a prospective cohort study.

PubMed

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 .

Oral health-related quality of life and related factors among residents in a disaster area of the Great East Japan Earthquake and giant tsunami.

PubMed

Kishi, Mitsuo; Aizawa, Fumie; Matsui, Miki; Yokoyama, Yukari; Abe, Akiko; Minami, Kentaro; Suzuki, Ruriko; Miura, Hiroyuki; Sakata, Kiyomi; Ogawa, Akira

2015-09-15

Oral health is one of the most important issues for disaster survivors. The aim of this study was to determine post-disaster distribution of oral health-related quality of life (OHRQoL) and related factors in survivors of the Great East Japan Earthquake and Tsunami. Questionnaires to assess OHRQoL, psychological distress, disaster-related experiences, and current systemic-health and economic conditions were sent to survivors over 18 years of age living in Otsuchi, one of the most severely damaged municipalities. OHRQoL and psychological distress were assessed using the General Oral Health Assessment Index (GOHAI) and the Kessler Psychological Distress Scale (K6), Japanese version, respectively. Among 11,411 residents, 1,987 returned the questionnaire (response rate, 17.4%) and received an oral examination to determine number of present teeth, dental caries status, and tooth-mobility grade, and to assess periodontal health using the Community Periodontal Index. Relationships between GOHAI and related factors were examined by nonparametric bivariate and multinomial logistic regression analyses using GOHAI cutoff points at the 25(th) and 50(th) national standard percentiles. GOHAI scores were significantly lower in the 50-69-age group compared with other age groups in this study and compared with the national standard score. In bivariate analyses, all factors assessed in this study (i.e., sex, age, evacuation from home, interruption of dental treatment, lost or fractured dentures, self-rated systemic health, serious psychological distress (SPD), economic status, number of teeth, having decayed teeth, CPI code, and tooth mobility) were significantly associated with OHRQoL. Subsequent multinomial logistic regression analyses revealed that participants of upper-middle age, who had received dental treatment before the disaster, who had lost or fractured dentures, and who had clinical oral health problems were likely to show low levels of OHRQoL. In addition, perceived systemic health and SPD were also related with OHRQoL. OHRQoL of disaster survivors was associated with oral problems stemming from the disaster in addition to factors related to OHRQoL in ordinary times such as clinical oral status and perceived systemic health. Furthermore, SPD was also associated with OHRQoL, which suggests the disaster's great negative impact on both oral and mental health conditions.

The development of response surface pathway design to reduce animal numbers in toxicity studies

PubMed Central

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

A person-centered analysis of posttraumatic stress disorder symptoms following a natural disaster: predictors of latent class membership.

PubMed

Rosellini, Anthony J; Coffey, Scott F; Tracy, Melissa; Galea, Sandro

2014-01-01

The present study applied latent class analysis to a sample of 810 participants residing in southern Mississippi at the time of Hurricane Katrina to determine if people would report distinct, meaningful PTSD symptom classes following a natural disaster. We found a four-class solution that distinguished persons on the basis of PTSD symptom severity/pervasiveness (Severe, Moderate, Mild, and Negligible Classes). Multinomial logistic regression models demonstrated that membership in the Severe and Moderate Classes was associated with potentially traumatic hurricane-specific experiences (e.g., being physically injured, seeing dead bodies), pre-hurricane traumatic events, co-occurring depression symptom severity and suicidal ideation, certain religious beliefs, and post-hurricane stressors (e.g., social support). Collectively, the findings suggest that more severe/pervasive typologies of natural disaster PTSD may be predicted by the frequency and severity of exposure to stressful/traumatic experiences (before, during, and after the disaster), co-occurring psychopathology, and specific internal beliefs. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Person-Centered Analysis of Posttraumatic Stress Disorder Symptoms Following a Natural Disaster: Predictors of Latent Class Membership

PubMed Central

Rosellini, Anthony J.; Coffey, Scott F.; Tracy, Melissa; Galea, Sandro

2014-01-01

The present study applied latent class analysis to a sample of 810 participants residing in southern Mississippi at the time of Hurricane Katrina to determine if people would report distinct, meaningful PTSD symptom classes following a natural disaster. We found a four-class solution that distinguished persons on the basis of PTSD symptom severity/pervasiveness (Severe, Moderate, Mild, and Negligible Classes). Multinomial logistic regression models demonstrated that membership in the Severe and Moderate Classes was associated with potentially traumatic hurricane-specific experiences (e.g., being physically injured, seeing dead bodies), pre-hurricane traumatic events, co-occurring depression symptom severity and suicidal ideation, certain religious beliefs, and post-hurricane stressors (e.g., social support). Collectively, the findings suggest that more severe/pervasive typologies of natural disaster PTSD may be predicted by the frequency and severity of exposure to stressful/traumatic experiences (before, during, and after the disaster), co-occurring psychopathology, and specific internal beliefs. PMID:24334161

Trust in health information sources differs between young/middle and oldest old.

PubMed

Le, Thai; Chaudhuri, Shomir; White, Cathy; Thompson, Hilaire; Demiris, George

2014-01-01

Examine differences in trust of health information sources between the oldest old and young/middle old. Cross-sectional survey using convenience sampling. Eleven retirement communities. Older adults ≥65 years (N = 353). Self-rated trust in health information sources. Mann-Whitney U-test or Fisher exact test to compare trust between age groups; multinomial ordered logistic regression analyses to model trust in Internet information sources. The overall survey response rate was 26.6%. Differences in trust were identified between oldest old (n = 108) and young/middle old (n = 245) for pharmacist (p < .05), Internet (p < .001), television (p < .05), radio (p < .001), and newspaper (p < .05) sources. In the oldest old, we found associations between levels of trust in Internet sources and frequency of Internet use (β = 4.13, p < .001). Understanding where differences in trust arise can inform the design of resources to support the information-seeking process. When planning widespread distribution of health information to these distinct groups, program developers need to consider these differences.

Willingness to Pay for Improving the Residential Waste Disposal System in Korea: A Choice Experiment Study

NASA Astrophysics Data System (ADS)

Ku, Se-Ju; Yoo, Seung-Hoon; Kwak, Seung-Jun

2009-08-01

This study attempts to apply choice experiments with regard to the residential waste disposal system (RWDS) in Korea by considering various attributes that are related to RWDS. Using data from a survey conducted on 492 households, the empirical analysis yields estimates of the willingness to pay for a clean food-waste collection facility, the collection of small items (such as obsolete mobile phones and add-ons for personal computers), and a more convenient large waste disposal system. The estimation results of multinomial logit models are quite similar to those of nested logit models. The results reveal that residents have preferences for the cleanliness of facilities and the collection of small items. In Korea, residents are required to purchase and attach stickers for the disposal of large items; they want to be able to obtain stickers at not only village offices but also supermarkets. On the other hand, the frequency of waste collection is not a significant factor in the choice of the improved waste management program.