PMID: 11550929Sep 12, 2001Paper

Maximum likelihood estimation of two-level latent variable models with mixed continuous and polytomous data

S Y Lee, J Q Shi


Two-level data with hierarchical structure and mixed continuous and polytomous data are very common in biomedical research. In this article, we propose a maximum likelihood approach for analyzing a latent variable model with these data. The maximum likelihood estimates are obtained by a Monte Carlo EM algorithm that involves the Gibbs sampler for approximating the E-step and the M-step and the bridge sampling for monitoring the convergence. The approach is illustrated by a two-level data set concerning the development and preliminary findings from an AIDS preventative intervention for Filipina commercial sex workers where the relationship between some latent quantities is investigated.


Jan 1, 1992·Statistical Methods in Medical Research·P M Bentler, J A Stein
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