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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| Main Authors: | , |
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| Format: | Article |
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Taylor and Francis Inc.
2017
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/80982/ http://dx.doi.org/10.1080/03610918.2015.1122052 |
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| Summary: | 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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