LARGE-SAMPLE PROPERTIES FOR A GENERAL ESTIMATOR OF THE TREATMENT EFFECT IN THE 2-SAMPLE PROBLEM WITH RIGHT CENSORING

• 成果类型: Article
• 署名作者: MENG, XL; BASSIAKOS, Y; LO, SH
• 署名单位: Northeastern University; Columbia University
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/aos/1176348371
• 发表日期: 1991
• 页码: 1786-1812
• 关键词: rank-tests

摘要

The estimation of the treatment effect in the two-sample problem with right censoring is of interest in survival analysis. In this article we consider both the location shift model and the scale change model. We establish the large-sample properties of a generalized Hodges-Lehmann type estimator. The strong consistency is established under the minimal possible conditions. The asymptotic normality is also obtained without imposing any conditions on the censoring mechanisms. As a by-product, we also establish a result for the oscillation behavior of the Kaplan-Meier process, which extends the Bahadur result for the empirical process to the censored case.