Bayesian Approach to Zero-Inflated Bivariate Ordered Probit Regression Model, with an Application to Tobacco Use. (12th December 2011)

• Record Type: Journal Article
• Authors: Gurmu, Shiferaw; Dagne, Getachew A.
• Other Names: Lu Wenbin Academic Editor.
• Is Part Of: Journal of probability and statistics. Volume 2012(2012)
• Publication Date: 2011-12-12
• Subjects: Probabilities -- Periodicals; Mathematical statistics -- Periodicals; Mathematical statistics; Probabilities; Periodicals; 519
• DOI: 10.1155/2012/617678
• Languages: English
• ISSNs: 1687-952X

Abstract

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.