Latent class models for classification

J.K. Vermunt, J. Magidson

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Abstract

An overview is provided of recent developments in the use of latent class (LC) and other types of finite mixture models for classification purposes. Several extensions of existing models are presented. Two basic types of LC models for classification are defined: supervised and unsupervised structures. Their most important special cases are presented and illustrated with an empirical example.
Original languageEnglish
Pages (from-to)531-537
JournalComputational Statistics and Data Analysis
Volume41
Issue number3-4
Publication statusPublished - 2003

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