Analysis of multivariate probit models

作者：Siddhartha Chib · 发表于：Biometrika · 年份：1998 · DOI：10.1093/biomet/85.2.347 · 被引用次数：850 · 研究领域：Statistical Methods and Bayesian Inference、Economic and Environmental Valuation、Spatial and Panel Data Analysis

This paper provides a practical simulation-based Bayesian and non-Bayesian analysis of correlated binary data using the multivariate probit model. The posterior distribution is simulated by Markov chain Monte Carlo methods and maximum likelihood estimates are obtained by a Monte Carlo version of the EM algorithm. A practical approach for the computation of Bayes factors from the simulation output is also developed. The methods are applied to a dataset with a bivariate binary response, to a four-year longitudinal dataset from the Six Cities study of the health effects of air pollution and to a sevenvariate binary response dataset on the labour supply of married women from the Panel survey of Income Dynamics.