New Inference Procedures for Semiparametric Varying-Coefficient Partially Linear Cox Models

Yunbei Ma and Xuan Luo

Journal of Applied Mathematics, 2014, vol. 2014, 1-16

Abstract:

In biomedical research, one major objective is to identify risk factors and study their risk impacts, as this identification can help clinicians to both properly make a decision and increase efficiency of treatments and resource allocation. A two-step penalized-based procedure is proposed to select linear regression coefficients for linear components and to identify significant nonparametric varying-coefficient functions for semiparametric varying-coefficient partially linear Cox models. It is shown that the penalized-based resulting estimators of the linear regression coefficients are asymptotically normal and have oracle properties, and the resulting estimators of the varying-coefficient functions have optimal convergence rates. A simulation study and an empirical example are presented for illustration.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnljam:360249

DOI: 10.1155/2014/360249

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