Bayesian inferences of latent class models with an unknown number of classes. 2014

Jia-Chiun Pan, and Guan-Hua Huang
Department of Mathematics, National Chung Cheng University, Minxiong, Taiwan.

This paper focuses on analyzing data collected in situations where investigators use multiple discrete indicators as surrogates, for example, a set of questionnaires. A very flexible latent class model is used for analysis. We propose a Bayesian framework to perform the joint estimation of the number of latent classes and model parameters. The proposed approach applies the reversible jump Markov chain Monte Carlo to analyze finite mixtures of multivariate multinomial distributions. In the paper, we also develop a procedure for the unique labeling of the classes. We have carried out a detailed sensitivity analysis for various hyperparameter specifications, which leads us to make standard default recommendations for the choice of priors. The usefulness of the proposed method is demonstrated through computer simulations and a study on subtypes of schizophrenia using the Positive and Negative Syndrome Scale (PANSS).

UI MeSH Term Description Entries
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D001499 Bayes Theorem A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result. Bayesian Analysis,Bayesian Estimation,Bayesian Forecast,Bayesian Method,Bayesian Prediction,Analysis, Bayesian,Bayesian Approach,Approach, Bayesian,Approachs, Bayesian,Bayesian Approachs,Estimation, Bayesian,Forecast, Bayesian,Method, Bayesian,Prediction, Bayesian,Theorem, Bayes
D012559 Schizophrenia A severe emotional disorder of psychotic depth characteristically marked by a retreat from reality with delusion formation, HALLUCINATIONS, emotional disharmony, and regressive behavior. Dementia Praecox,Schizophrenic Disorders,Disorder, Schizophrenic,Disorders, Schizophrenic,Schizophrenias,Schizophrenic Disorder
D013223 Statistics as Topic Works about the science and art of collecting, summarizing, and analyzing data that are subject to random variation. Area Analysis,Estimation Technics,Estimation Techniques,Indirect Estimation Technics,Indirect Estimation Techniques,Multiple Classification Analysis,Service Statistics,Statistical Study,Statistics, Service,Tables and Charts as Topic,Analyses, Area,Analyses, Multiple Classification,Area Analyses,Classification Analyses, Multiple,Classification Analysis, Multiple,Estimation Technic, Indirect,Estimation Technics, Indirect,Estimation Technique,Estimation Technique, Indirect,Estimation Techniques, Indirect,Indirect Estimation Technic,Indirect Estimation Technique,Multiple Classification Analyses,Statistical Studies,Studies, Statistical,Study, Statistical,Technic, Indirect Estimation,Technics, Estimation,Technics, Indirect Estimation,Technique, Estimation,Technique, Indirect Estimation,Techniques, Estimation,Techniques, Indirect Estimation
D015233 Models, Statistical Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc. Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model

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