The central limit theorem under censoring

Research output: Contribution to journalArticle

11 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)1109-1120
Number of pages12
JournalBernoulli
Volume6
Issue number6
DOIs
StatePublished - Jan 1 2000

All Science Journal Classification (ASJC) codes

  • Statistics and Probability

Fingerprint Dive into the research topics of 'The central limit theorem under censoring'. Together they form a unique fingerprint.

  • Cite this