Open Access
August 2004 Estimating marginal survival function by adjusting for dependent censoring using many covariates
Donglin Zeng
Ann. Statist. 32(4): 1533-1555 (August 2004). DOI: 10.1214/009053604000000508


One goal in survival analysis of right-censored data is to estimate the marginal survival function in the presence of dependent censoring. When many auxiliary covariates are sufficient to explain the dependent censoring, estimation based on either a semiparametric model or a nonparametric model of the conditional survival function can be problematic due to the high dimensionality of the auxiliary information. In this paper, we use two working models to condense these high-dimensional covariates in dimension reduction; then an estimate of the marginal survival function can be derived nonparametrically in a low-dimensional space. We show that such an estimator has the following double robust property: when either working model is correct, the estimator is consistent and asymptotically Gaussian; when both working models are correct, the asymptotic variance attains the efficiency bound.


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Donglin Zeng. "Estimating marginal survival function by adjusting for dependent censoring using many covariates." Ann. Statist. 32 (4) 1533 - 1555, August 2004.


Published: August 2004
First available in Project Euclid: 4 August 2004

zbMATH: 1047.62092
MathSciNet: MR2089133
Digital Object Identifier: 10.1214/009053604000000508

Primary: 62G07
Secondary: 62F12

Keywords: dependent censoring , double robustness , Semiparametric efficiency

Rights: Copyright © 2004 Institute of Mathematical Statistics

Vol.32 • No. 4 • August 2004
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