ESTIMATION OF THE TIME-DEPENDENT ACCELERATED FAILURE TIME MODEL IN THE PRESENCE OF CONFOUNDING FACTORS

被引:39
作者
ROBINS, J [1 ]
机构
[1] HARVARD UNIV,SCH PUBL HLTH,DEPT BIOSTAT,BOSTON,MA 02115
关键词
AIDS; CAUSAL; OBSERVATIONAL STUDY; SEMIPARAMETRIC ANALYSIS; SURVIVAL DATA; TIME-DEPENDENT COVARIATE;
D O I
10.1093/biomet/79.2.321
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Cox & Oakes (1984, p. 66) introduced the 'strong version' of the accelerated failure time model with time-dependent exposures. We provide conditions under which this model could be used to estimate, from observational data, the causal effect of a time-varying exposure or treatment on time to an event of interest in the presence of time-dependent confounding variables. We propose a class of semiparametric tests and estimators for the model parameters. This class contains an estimator that is semiparametric efficient in the sense of Begun et al. (1983).
引用
收藏
页码:321 / 334
页数:14
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