Incorporating time-dependent covariates in survival analysis using the LVAR method

被引:2
|
作者
Liu, Yali [1 ]
Craig, Bruce A. [1 ]
机构
[1] Purdue Univ, Dept Stat, W Lafayette, IN 47907 USA
关键词
proportional hazards model; partial likelihood; time-dependent covariates; observational data;
D O I
10.1002/sim.2296
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
In survival analysis, use of the Cox proportional hazards model requires knowledge of all covariates under consideration at every failure time. Since failure times rarely coincide with observation times, time-dependent covariates (covariates that vary over time) need to be inferred from the observed values. In this paper, we introduce the last value auto-regressed (LVAR) estimation method and compare it to several other established estimation approaches via a simulation study. The comparison shows that under several time-dependent covariate processes this method results in a smaller mean square error when considering the time-dependent covariate effect. Copyright (c) 2005 John Wiley & Sons, Ltd.
引用
收藏
页码:1729 / 1740
页数:12
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