Estimating the marginal survival function in the presence of time dependent covariates

✍ Scribed by Glen A. Satten; Somnath Datta; James Robins

• Publisher: Elsevier Science
• Year: 2001
• Tongue: English
• Weight: 104 KB
• Volume: 54
• Category: Article
• ISSN: 0167-7152
• DOI: 10.1016/s0167-7152(01)00113-4

✦ Synopsis

We propose a new estimator of the marginal (overall) survival function of failure times that is in the class of survival function estimators proposed by Robins (Proceedings of the American Statistical Association-Biopharmaceutical Section, 1993, p. 24). These estimators are appropriate when, in addition to (right-censored) failure times, we also observe covariates for each individual that a ect both the hazard of failure and the hazard of being censored. The observed data are re-weighted at each failure time t according to Aalen's linear model of the cumulative hazard for being censored at some time greater than or equal to t given each individual's covariates; then, a product-limit estimator is calculated using the weighted data. When covariates have no e ect on censoring times, our estimator reduces to the ordinary Kaplan-Meier estimator. An expression for its asymptotic variance formula is obtained using martingale techniques.