Title: An Akaike information criterion for multiple event mixture cure models
Authors: Dirick, Lore
Claeskens, Gerda
Baesens, Bart
Issue Date: Aug-2014
Publisher: KU Leuven - Faculty of Economics and Business
Series Title: FEB Research Report KBI_1418
Abstract: We derive the proper form of the Akaike information criterion for variable selection for mixture cure models, which are often fit via the expectation-maximization
algorithm. Separate covariate sets may be used in the mixture components. The selection criteria are applicable to survival models for right-censored data with multiple competing risks and allow for the presence of an insusceptible group. The method is illustrated on credit loan data, with pre-payment and default as events and maturity as the insusceptible case and is used in a simulation study.
Publication status: published
KU Leuven publication type: IR
Appears in Collections:Research Center for Operations Research and Business Statistics (ORSTAT), Leuven
Research Center for Management Informatics (LIRIS), Leuven

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