{"title":"Model comparison of linear and nonlinear Bayesian structural equation models with dichotomous data","authors":"Thanoon Y. Thanoon, Robiah Adnan","doi":"10.1080/03610918.2015.1122052","DOIUrl":null,"url":null,"abstract":"ABSTRACT In this article, dichotomous variables are used to compare between linear and nonlinear Bayesian structural equation models. Gibbs sampling method is applied for estimation and model comparison. Statistical inferences that involve estimation of parameters and their standard deviations and residuals analysis for testing the selected model are discussed. Hidden continuous normal distribution (censored normal distribution) is used to solve the problem of dichotomous variables. The proposed procedure is illustrated by a simulation data obtained from R program. Analyses are done by using R2WinBUGS package in R-program.","PeriodicalId":55240,"journal":{"name":"Communications in Statistics-Simulation and Computation","volume":"80 1","pages":"4578 - 4599"},"PeriodicalIF":0.8000,"publicationDate":"2017-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications in Statistics-Simulation and Computation","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/03610918.2015.1122052","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
引用次数: 7
Abstract
ABSTRACT In this article, dichotomous variables are used to compare between linear and nonlinear Bayesian structural equation models. Gibbs sampling method is applied for estimation and model comparison. Statistical inferences that involve estimation of parameters and their standard deviations and residuals analysis for testing the selected model are discussed. Hidden continuous normal distribution (censored normal distribution) is used to solve the problem of dichotomous variables. The proposed procedure is illustrated by a simulation data obtained from R program. Analyses are done by using R2WinBUGS package in R-program.
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The Simulation and Computation series intends to publish papers that make theoretical and methodological advances relating to computational aspects of Probability and Statistics. Simulational assessment and comparison of the performance of statistical and probabilistic methods will also be considered for publication. Papers stressing graphical methods, resampling and other computationally intensive methods will be particularly relevant. In addition, special issues dedicated to a specific topic of current interest will also be published in this series periodically, providing an exhaustive and up-to-date review of that topic to the readership.
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