Chunk #33 — Three methods to decide between latent dimensionality and latent categories — Model-based clustering

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Does nature have joints worth carving? A discussion of taxometrics, model-based clustering and latent variable mixture modeling.

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To summarize, model-based clustering is based on the assumptions that (1) each component distribution corresponds to a cluster in the population, and (2) model comparisons result in selecting an adequate model for the data. The selected model provides a detailed description of each cluster in terms of how the data are distributed and permits post-hoc assignment of subjects to clusters using Bayes’ formula.