Cluster-Specific Variable Selection for Product Partition Models

Cluster-Specific Variable Selection for Product Partition Models

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Article ID: iaor2016324
Volume: 42
Issue: 4
Start Page Number: 1065
End Page Number: 1077
Publication Date: Dec 2015
Journal: Scandinavian Journal of Statistics
Authors: , ,
Keywords: statistics: regression, health services
Abstract:

We propose a random partition model that implements prediction with many candidate covariates and interactions. The model is based on a modified product partition model that includes a regression on covariates by favouring homogeneous clusters in terms of these covariates. Additionally, the model allows for a cluster‐specific choice of the covariates that are included in this evaluation of homogeneity. The variable selection is implemented by introducing a set of cluster‐specific latent indicators that include or exclude covariates. The proposed model is motivated by an application to predicting mortality in an intensive care unit in Lisboa, Portugal.

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