This paper develops a probabilistic clustering model for mixeddata. The model allows analysis of variables of mixed type: thevariables may be nominal, ordinal and/or quantitative. The modelcontains the well-known models of latent class analysis as submodels.As in latent class analysis, local independence of the variables isassumed. The parameters of the model are estimated by the EMalgorithm. Test statistics and goodness-of-fit measures are proposedfor model selection. Two artificial data sets show the usefulness ofthese tests. An empirical example completes the presentation.
Quality & Quantity – Springer Journals
Published: Oct 16, 2004
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