Model comparison of linear and nonlinear Bayesian structural equation models with dichotomous data
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...
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my.utm.809822019-07-24T00:13:44Z http://eprints.utm.my/id/eprint/80982/ Model comparison of linear and nonlinear Bayesian structural equation models with dichotomous data Thanoon, T. Y. Adnan, R. QA Mathematics 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. Taylor and Francis Inc. 2017 Article PeerReviewed Thanoon, T. Y. and Adnan, R. (2017) Model comparison of linear and nonlinear Bayesian structural equation models with dichotomous data. Communications in Statistics: Simulation and Computation, 46 (6). pp. 4578-4599. ISSN 0361-0918 http://dx.doi.org/10.1080/03610918.2015.1122052 DOI:10.1080/03610918.2015.1122052 |
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QA Mathematics Thanoon, T. Y. Adnan, R. Model comparison of linear and nonlinear Bayesian structural equation models with dichotomous data |
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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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Thanoon, T. Y. Adnan, R. |
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Thanoon, T. Y. Adnan, R. |
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Thanoon, T. Y. |
title |
Model comparison of linear and nonlinear Bayesian structural equation models with dichotomous data |
title_short |
Model comparison of linear and nonlinear Bayesian structural equation models with dichotomous data |
title_full |
Model comparison of linear and nonlinear Bayesian structural equation models with dichotomous data |
title_fullStr |
Model comparison of linear and nonlinear Bayesian structural equation models with dichotomous data |
title_full_unstemmed |
Model comparison of linear and nonlinear Bayesian structural equation models with dichotomous data |
title_sort |
model comparison of linear and nonlinear bayesian structural equation models with dichotomous data |
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Taylor and Francis Inc. |
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2017 |
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http://eprints.utm.my/id/eprint/80982/ http://dx.doi.org/10.1080/03610918.2015.1122052 |
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