Document Type
Article
Publication Date
2012
Abstract
This paper presents a Bayesian analysis of bivariate ordered probit regression model with excess of zeros. Specifically, in the context of joint modeling of two ordered outcomes, we develop zero-inflated bivariate ordered probit model and carry out estimation using Markov Chain Monte Carlo techniques. Using household tobacco survey data with substantial proportion of zeros, we analyze the socioeconomic determinants of individual problem of smoking and chewing tobacco. In our illustration, we find strong evidence that accounting for excess zeros provides good fit to the data. The example shows that the use of a model that ignores zero-inflation masks differential effects of covariates on nonusers and users.
Recommended Citation
Gurmu, S., and Dagne, G.A. (2012). Bayesian approach to zero-inflated bivariate ordered probit regression model, with an application to tobacco use. Journal of Probability and Statistics, 2012, Article ID 617678, 1-26. doi: 10.1155/2012/617678
Comments
This article was originally published in Journal of Probability and Statistics and is reposted here with the permission of the authors. Copyright © 2012 Shiferaw Gurmu and Getachew A. Dagne. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.