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Bayesian Nonlinear Latent variable Models with Mixed Non-normal Variables and Covariates for Multi-sample Psychological Data

Author(s)
Thanoon Y. Thanoon Department of Business Management Techniques, Administrative Technical College Northern Technical University, Iraq
Athar Talal Hamed Department of Financial and Banking Sciences, College of Administration and Economics Iraq
Robiah Adnan Department of Mathematical Sciences, Faculty of Science University Technology Malaysia, Malaysia
Abstract
The purpose of this paper is to develop a latent variable model with nonlinear covariates and latent variables. Mixed ordered categorical and dichotomous variables and covariates with two different types of thresholds (with equal and unequal spaces) are used in Bayesian multi-sample nonlinear latent variable models and the Gibbs sampling method is applied for estimation and model comparison. Hidden continuous normal distribution (censored normal distribution) and (truncated normal distribution with known parameters) are used to handle the problem of mixed ordered categorical and dichotomous data. Hidden continuous normal distribution (truncated normal distribution with known parameters) is used to handle the problem of mixed ordered categorical and dichotomous data in covariates. Statistical analysis, which involves the estimation of parameters, standard deviations and their highest posterior density, are discussed. The proposed procedure is illustrated using psychological data with the results obtained from the OpenBUGS program.
Publication Details
Page(s) 627-645
DOI DOI not available
Published Journal: Pakistan Journal of Statistics and Operation Research, Volume: 15, Issue: 3, Year: 2019

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Keywords
Bayesian analysis, Latent variable Models, Multi-Sample Data, Mixed Variables, Covariates
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