A Bayes Inference for Ordinal Response with Latent Variable Approach

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.