Multilevel Latent Class Models
نویسنده
چکیده
The latent class (LC) models that have been developed so far assume that observations are independent. Parametric and nonparametric random-coefficient LC models are proposed here, which will make it possible to modify this assumption. For example, the models can be used for the analysis of data collected with complex sampling designs, data with a multilevel structure, and multiple-group data for more than a few groups. An adapted EM algorithm is presented that makes maximumlikelihood estimation feasible. The new model is illustrated with examples from organizational, educational, and cross-national comparative research.
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