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Article

The Central Limit Theorem under Censoring

Michael G. AkritasDepartment of Statistics, Penn State University
2000en
ABI

Abstract

The central limit theorem for integrals of the Kaplan-Meier estimator is obtained. The basic tools are the martingale methods developed by Gill and the identities and inequalities of Efron and Johnstone. The assumptions needed are both weaker and more transparent than those in the recent literature, and the resulting variance expression is simpler, especially for distributions with atoms.

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