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Bayesian Analysis of Linear and Nonlinear Latent Variable Models with Fixed Covariate and Ordered Categorical Data

Author(s)
Thanoon Y. Thanoon Department of Mathematical Science, Faculty of Science Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia Department of Operation Management Technique, Technical College of Management, Northern Technical University, Mosul, Iraq
Robiah Adnan Department of Mathematical Science, Faculty of Science Universiti Teknologi Malaysia, 81310, Skudai, Johor, Malaysia.
Abstract
In this paper, ordered categorical variables are used to compare between linear with covariate and nonlinear interactions of covariates and latent variables in Bayesian structural equation models. Gibbs sampling method is applied for estimation and model comparison. Hidden continuous normal distribution (censored normal distribution) is used to handle the problem of ordered categorical data. Statistical inferences, which involve estimation of parameters and their standard deviations, and residuals analyses for testing the selected model, are discussed. The proposed procedure is illustrated by a real data. Analyses are done by using OpenBUGS program. 
Publication Details
Page(s) 125-140
DOI DOI not available
Published Journal: Pakistan Journal of Statistics and Operation Research, Volume: 12, Issue: 1, Year: 2016

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Keywords
Gibbs sampling, Structural equation models, latent variables, Bayesian analysis, ordered categorical data
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