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Multivariate survival trees: a maximum likelihood approach based on frailty models
Authors:Su Xiaogang  Fan Juanjuan
Affiliation:Department of Statistics and Actuarial Science, University of Central Florida, Orlando, Florida 32816, USA. xsu@pegasus.cc.ucf.edu
Abstract:A method of constructing trees for correlated failure times is put forward. It adopts the backfitting idea of classification and regression trees (CART) (Breiman et al., 1984, in Classification and Regression Trees). The tree method is developed based on the maximized likelihoods associated with the gamma frailty model and standard likelihood-related techniques are incorporated. The proposed method is assessed through simulations conducted under a variety of model configurations and illustrated using the chronic granulomatous disease (CGD) study data.
Keywords:Akaike information criterion    Frailty models    Multivariate survival times    Regression trees
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