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Random effects clustering in multilevel modeling: choosing a proper partition. (English) Zbl 07061249
Summary: A novel criterion for estimating a latent partition of the observed groups based on the output of a hierarchical model is presented. It is based on a loss function combining the Gini income inequality ratio and the predictability index of Goodman and Kruskal in order to achieve maximum heterogeneity of random effects across groups and maximum homogeneity of predicted probabilities inside estimated clusters. The index is compared with alternative approaches in a simulation study and applied in a case study concerning the role of hospital level variables in deciding for a cesarean section.
MSC:
62C10 Bayesian problems; characterization of Bayes procedures
62C12 Empirical decision procedures; empirical Bayes procedures
62H30 Classification and discrimination; cluster analysis (statistical aspects)
62J12 Generalized linear models (logistic models)
62J20 Diagnostics, and linear inference and regression
Software:
DPpackage; R2WinBUGS
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