Maximum likelihood estimation of two-level latent variable models with mixed continuous and polytomous data
Maximum likelihood estimation of two-level latent variable models with mixed continuous and polytomous data
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DOI：
10.1111/j.0006-341x.2001.00787.x
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发表时间：
2001-09-01
期刊：
影响因子：
1.9
通讯作者：
Shi, JQ
中科院分区：
文献类型：
--
作者：
Lee, SY;Shi, JQ
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.
