Asymptotic properties of the maximum likelihood estimator for the proportional hazards model with doubly censored data

被引：12

作者：

Kim, Yongdai ^{[2
]}

Kim, Bumsoo ^{[2
]}

Jang, Woncheol ^{[1
]}

机构：

[1] Univ Georgia, Dept Epidemiol & Biostat, Athens, GA 30602 USA

[2] Seoul Natl Univ, Dept Stat, Seoul 151747, South Korea

来源：

JOURNAL OF MULTIVARIATE ANALYSIS | 2010年 / 101卷 / 06期

关键词：

Doubly censored data; Empirical likelihood; Maximum likelihood estimator; Proportional hazards model; Semiparametric efficiency; SELF-CONSISTENT; SURVIVAL FUNCTION; FRAILTY MODEL; LARGE SAMPLE; REGRESSION;

D O I：

10.1016/j.jmva.2010.01.010

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：

Doubly censored data, which include left as well as right censored observations, are frequently met in practice. Though estimation of the distribution function with doubly censored data has seen much study, relatively little is known about the inference of regression coefficients in the proportional hazards model for doubly censored data. In particular, theoretical properties of the maximum likelihood estimator of the regression coefficients in the proportional hazards model have not been proved yet. In this paper, we show the consistency and asymptotic normality of the maximum likelihood estimator and prove its semiparametric efficiency. The proposed methods are illustrated with simulation studies and analysis of an application from a medical study. (C) 2010 Elsevier Inc. All rights reserved.

引用

页码：1339 / 1351

页数：13

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