Document Type
Article
Publication Date
2012
Digital Object Identifier (DOI)
https://doi.org/10.1155/2012/617678
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.
Rights Information
This work is licensed under a Creative Commons Attribution 3.0 License.
Was this content written or created while at USF?
Yes
Citation / Publisher Attribution
Journal of Probability and Statistics, v. 2012, art. 617678
Scholar Commons Citation
Gurmu, Shiferaw and Dagne, Getachew A., "Bayesian Approach to Zero-Inflated Bivariate Ordered Probit Regression Model, with an Application to Tobacco Use" (2012). Epidemiology and Biostatistics Faculty Publications. 22.
https://digitalcommons.usf.edu/epb_facpub/22
