ASYMPTOTIC NORMALITY OF THE SYNTHETIC DATA REGRESSION ESTIMATOR FOR CENSORED SURVIVAL-DATA

• 成果类型: Article
• 署名作者: ZHOU, M
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/aos/1176348667
• 发表日期: 1992
• 页码: 1002-1021
• 关键词: models

摘要

This article studies the large sample behavior of the censored data least squares estimator derived from the synthetic data method proposed by Leurgans and Zheng. The asymptotic distributions are derived by representing the estimator as a martingale plus a higher-order remainder term. Recently developed counting process techniques are used. The results are then compared to the censored regression estimator of Koul, Susarla and Van Ryzin.