On bootstrap accuracy with censored data

• 成果类型: Article
• 署名作者: Chen, K; Lo, SH
• 署名单位: Columbia University
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• 发表日期: 1996
• 页码: 569-595
• 关键词: product-limit estimator; linear rank-tests; Edgeworth Expansion; large sample; approximation; statistics

摘要

In survival analysis with censored data, we consider three closely related survival function estimators: the Kaplan-Meier, Nelson and moment estimators. We derive the Edgeworth expansions for these three estimators with Studentization. Edgeworth expansions for the corresponding bootstrap statistics are also given. It is found that the bootstrap approximation is better than the normal approximation for the Studentized Kaplan-Meier and Nelson estimators, but not so for the Studentized moment estimator. With these results, we construct bootstrap-based confidence intervals with better coverage probabilities. We also include some simulations which show strong agreement with our theoretical findings.