Variable selection in partially linear hazard regression for multivariate failure time data.
- Resource Type
- Article
- Authors
- Jicai, Liu; Zhang, Riquan; Zhao, Weihua; Lv, Yazhao
- Source
- Journal of Nonparametric Statistics. Jun2016, Vol. 28 Issue 2, p375-394. 20p.
- Subject
- *REGRESSION analysis
*MATHEMATICAL variables
*MULTIVARIATE analysis
*FAILURE time data analysis
*ASYMPTOTIC normality
- Language
- ISSN
- 1048-5252
The aim of this paper is to explore variable selection approaches in the partially linear proportional hazards model for multivariate failure time data. A new penalised pseudo-partial likelihood method is proposed to select important covariates. Under certain regularity conditions, we establish the rate of convergence and asymptotic normality of the resulting estimates. We further show that the proposed procedure can correctly select the true submodel, as if it was known in advance. Both simulated and real data examples are presented to illustrate the proposed methodology. [ABSTRACT FROM AUTHOR]