Covariate selection for semiparametric hazard function regression models

Florentina Bunea and Ian W. McKeague

Journal of Multivariate Analysis, 2005, vol. 92, issue 1, 186-204

Abstract: We study a flexible class of nonproportional hazard function regression models in which the influence of the covariates splits into the sum of a parametric part and a time-dependent nonparametric part. We develop a method of covariate selection for the parametric part by adjusting for the implicit fitting of the nonparametric part. Asymptotic consistency of the proposed covariate selection method is established, leading to asymptotically normal estimators of both parametric and nonparametric parts of the model in the presence of covariate selection. The approach is applied to a real data set and a simulation study is presented.

Keywords: Additive; risk; model; Cox; model; Penalized; partial; likelihood; Penalized; likelihood; Model; selection; Survival; analysis (search for similar items in EconPapers)
Date: 2005
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Citations: View citations in EconPapers (2)

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