Partially varying coefficient single-index additive hazard models

被引:1
|
作者
Wang, Xuan [1 ]
Wang, Qihua [1 ,2 ]
Zhou, Xiao-Hua Andrew [3 ]
机构
[1] Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
[2] Shenzhen Univ, Inst Stat Sci, Shenzhen 518060, Peoples R China
[3] Univ Washington, Dept Biostat, Seattle, WA 98198 USA
基金
中国国家自然科学基金;
关键词
Varying coefficient; Partially linear single-index; Two sets of estimating functions; Iteration; Asymptotic normality; TRANSFORMATION MODELS; REGRESSION-MODELS; RISK MODEL; SEMIPARAMETRIC ANALYSIS; CENSORED-DATA; LIKELIHOOD;
D O I
10.1007/s10463-014-0484-7
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
The partially linear additive hazards model has been proposed to study the interaction between some covariates and an exposure variable. In this paper, we extend it to the partially varying coefficient single-index additive hazard model where the high dimension covariates are collapsed to a single index, due to practical needs. Two sets of estimating equations were proposed to estimate the varying coefficient functions in the linear components: the link function for the single index and the single-index parameter vector separately. It was shown that the proposed local and global estimators are asymptotically normal. Simulation studies were conducted to examine the finite-sample performance of our method to compare the relative performance of our method with existing ones. A real data analysis was used to illustrate the proposed methods.
引用
收藏
页码:817 / 841
页数:25
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