Estimation in varying-coefficient proportional hazard regression model

被引：1
|
作者：
Wang, Qihua [1 ]
Yao, Lili
机构：
[1] Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China
[2] Univ Hong Kong, Dept Stat & Actuarial Sci, Hong Kong, Hong Kong, Peoples R China
来源：
METRIKA | 2006年 / 64卷 / 03期
关键词：
proportional hazard regression; weighted partial likelihood; strong consistency; asymptotic normality; Primary; 62G05; Secondary; 62E20;
D O I：
10.1007/s00184-006-0048-9
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：
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.
引用
收藏
页码：271 / 288
页数：18
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