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http://dx.doi.org/10.5351/KJAS.2005.18.1.173

A Bayesian Threshold Model for Ordered Categorical Traits  

Choi Byangsu (School of Computer Engineering, Hansung University)
Lee Seung-Chun (Department of Statistics, Hanshin University)
Publication Information
The Korean Journal of Applied Statistics / v.18, no.1, 2005 , pp. 173-182 More about this Journal
Abstract
A Bayesian threshold model is considered to analyze binary or ordered categorical traits. Gibbs sampler for making full Bayesian inferences about the category probability as well as the regression coefficients is described. The model can be regarded as an alternative to the ordered logit regression model. Numerical examples are shown to demonstrate the efficiency of the model.
Keywords
Bayesian threshold model; Gibbs sampling; Ordered logit regression model; Logistic regression model;
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