COVARIANCE AND SURVIVOR FUNCTION ESTIMATION USING CENSORED MULTIVARIATE FAILURE TIME DATA

被引:70
作者
PRENTICE, RL
CAI, J
机构
[1] Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington 98104
关键词
CENSORING; CORRELATED FAILURE TIMES; COUNTING PROCESS; COVARIANCE; MARGINAL HAZARD RATES; MARTINGALE; MULTIVARIATE SURVIVOR FUNCTION ESTIMATION; NONPARAMETRIC ESTIMATION; PEANO SERIES; RELATIVE RISK REGRESSION; SURVIVAL DATA; VOLTERRA INTEGRAL EQUATION;
D O I
10.1093/biomet/79.3.495
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
The covariance between counting process martingales is used to characterize the dependence between two failure time variates. A representation of the bivariate survivor function is obtained in terms of the marginal survivor functions and this covariance function. A closely related representation expresses the bivariate survivor function in terms of marginal survivor functions and a conditional covariance function, leading to a new nonparametric survivor function estimator. Generalizations to higher dimensional failure time variates are also given. Simulation evaluations of the survivor function estimator are presented, and generalizations to regression problems are outlined.
引用
收藏
页码:495 / 512
页数:18
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