A Bayes Inference for Ordinal Response with Latent Variable Approach

Naijun Sha and Benard Owusu Dechi
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Naijun Sha: Department of Mathematical Sciences, University of Texas at El Paso, El Paso, TX 79968, USA
Benard Owusu Dechi: Department of Mathematical Sciences, University of Texas at El Paso, El Paso, TX 79968, USA

Stats, 2019, vol. 2, issue 2, 1-11

Abstract: In this paper, we propose a Bayesian model for the analysis of categorical data with an ordered outcome. The method provides a latent variable approach with an informative prior transformed from a Dirichlet distribution for the boundary parameters. A simulation study is carried out to assess the performance of the methods under various settings of the data structure. Our method produces predictive accuracy over the conventional classification procedures. Real data are analyzed to demonstrate the efficiency of the proposed method.

Keywords: ordinal outcome; latent variable; Bayesian inference; Dirichlet prior; MCMC sampling (search for similar items in EconPapers)
JEL-codes: C1 C10 C11 C14 C15 C16 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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