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 language | English (US) |
|---|---|
| Pages (from-to) | 1109-1120 |
| Number of pages | 12 |
| Journal | Bernoulli |
| Volume | 6 |
| Issue number | 6 |
| DOIs | |
| State | Published - Jan 1 2000 |
All Science Journal Classification (ASJC) codes
- Statistics and Probability
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Cite this
Akritas, M. G. (2000). The central limit theorem under censoring. Bernoulli, 6(6), 1109-1120. https://doi.org/10.2307/3318473