Estimation in Varying-coefficient Proportional Hazard Regression Model

被引：0
|
作者：
Qihua Wang
Lili Yao
机构：
[1] Chinese Academy of Science,Academy of Mathematics and Systems Science
[2] The University of Hong Kong,Department of Statistics and Actuarial Science
来源：
Metrika | 2006年 / 64卷
关键词：
Proportional hazard regression; Weighted partial likelihood; Strong consistency; Asymptotic normality; Primary 62G05; Secondary 62E20;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, varying coefficient proportional hazard regression models are considered. The model is an important extension of the Cox model, and arises naturally if the coefficients change over different groups characterized by certain covariates in practice. Under random censorship, weighted partial likelihood estimators are defined for the varying coefficients by maximizing weighted partial likelihoods. It is shown that the proposed estimators are consistent and asymptotically normal.
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页码：271 / 288
页数：17
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