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

Glen A. Satten, Somnath Datta and James Robins

Statistics & Probability Letters, 2001, vol. 54, issue 4, 397-403

Abstract: 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 affect 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 effect on censoring times, our estimator reduces to the ordinary Kaplan-Meier estimator. An expression for its asymptotic variance formula is obtained using martingale techniques.

Keywords: Aalen's; linear; hazard; model; Informative; censoring; Non-parametric; estimation; Right; censoring; Survival; analysis (search for similar items in EconPapers)
Date: 2001
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Citations: View citations in EconPapers (11)

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