ANALYSIS OF MULTIVARIATE FAILURE TIME DATA USING MARGINAL PROPORTIONAL HAZARDS MODEL

被引：0

作者：

Chen, Ying ^{[1
]}

Chen, Kani ^{[2
]}

Ying, Zhiliang ^{[3
]}

机构：

[1] Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai 200433, Peoples R China

[2] Hong Kong Univ Sci & Technol, Dept Math, Kowloon, Hong Kong, Peoples R China

[3] Columbia Univ, Dept Stat, New York, NY 10027 USA

来源：

STATISTICA SINICA | 2010年 / 20卷 / 03期

基金：

美国国家卫生研究院; 美国国家科学基金会;

关键词：

Alternating projection; counting process martingale; marginal likelihood; martingale residual; semiparametric efficiency; ESTIMATING EQUATIONS; REGRESSION; DISTRIBUTIONS; ASSOCIATIONS; COVARIANCE;

D O I：

暂无

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 marginal proportional hazards model is an important tool in the analysis of multivariate failure time data in the presence of censoring. We propose a method of estimation via the linear combinations of martingale residuals. The estimation and inference procedures are easy to implement numerically. The estimation is generally more accurate than the existing pseudo-likelihood approach: the size of efficiency gain can be considerable in some cases, and the maximum relative efficiency in theory is infinite. Consistency and asymptotic normality are established. Empirical evidence in support of the theoretical claims is shown in simulation studies.

引用

页码：1025 / 1041

页数：17

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