Abstract:
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In the Bayesian paradigm, the Bayes factor summarizes evidence from data for comparing alternative hypotheses. For latent-class analysis, a unit-level estimate of the Bayes factor allows us to separate the estimation of within-class item-response parameters from the estimation of regression coefficients for predicting class prevalences or subsequent outcomes. Bayes factors for item-response categories neatly summarize an item's contribution to diagnostic classification.
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