7. Multilevel Latent Class Models

Jeroen Kornelis Vermunt

467 citations0/0 files storedSociological Methodology

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Psychometric Methodologies and Testing Statistical Methods and Bayesian Inference Bayesian Methods and Mixture Models

Abstract

The latent class (LC) models that have been developed so far assume that observations are independent. Parametric and non-parametric 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 maximum-likelihood estimation feasible. The new model is illustrated with examples from organizational, educational, and cross-national comparative research.

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References

1981Marginal Maximum Likelihood Estimation of Item Parameters: Application of an EM Algorithm 1977The silent revolution 1950Measurement and prediction 1972Estimating Item Parameters and Latent Ability when Responses are Scored in Two or More Nominal Categories 1974The Analysis of Systems of Qualitative Variables When Some of the Variables Are Unobservable. Part I-A Modified Latent Structure Approach 1988Concomitant-Variable Latent-Class Models

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