Abstract
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.
Lingua originale | English |
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pagine (da-a) | 279-301 |
Numero di pagine | 23 |
Rivista | Advances in Data Analysis and Classification |
Volume | 13 |
DOI | |
Stato di pubblicazione | Pubblicato - 2019 |
Keywords
- multilevel