An Akaike information criterion for multiple event mixture cure models

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.

DOI: 10.1016/j.ejor.2014.08.038

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Cite this paper

@article{Dirick2015AnAI, title={An Akaike information criterion for multiple event mixture cure models}, author={Lore Dirick and Gerda Claeskens and Bart Baesens}, journal={European Journal of Operational Research}, year={2015}, volume={241}, pages={449-457} }