A MULTIVARIATE PROBIT LATENT VARIABLE MODEL FOR ANALYZING DICHOTOMOUS RESPONSES

Abstract

We propose a multivariate probit model that is dened by a conrmatory factor analysis model with covariates for analyzing dichotomous data in medical re- search. Our proposal is a generalization of several useful multivariate probit models, and provides a exible framework for practical applications. We implement a Monte Carlo EM algorithm for maximum likelihood estimation of the model, and develop a path sampling procedure to compute the observed-data log-likelihood for evalu- ating the Bayesian Information Criterion for model comparison. Our methodology is illustrated by analyzing two data sets in medical research.

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