INFORMATION AND ASYMPTOTIC EFFICIENCY IN SOME GENERALIZED PROPORTIONAL HAZARDS MODELS FOR COUNTING-PROCESSES

• 成果类型: Article
• 署名作者: CHANG, IS; HSIUNG, CA
• 署名单位: Academia Sinica - Taiwan
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/aos/1176325629
• 发表日期: 1994
• 页码: 1275-1298
• 关键词: regression

摘要

Proportional hazards models with stochastic baseline hazards and estimators of the relative risk coefficient in these models were proposed by Prentice, Williams and Peterson and by Chang and Hsiung in medical and industrial contexts. The form of the estimating functions recommended varies according to the form of the unknown stochastic baseline hazards. This paper examines the same estimation problem in the context of large-sample theory. It is shown that the proposed estimators are regular, asymptotically normal and asmptotically efficient. Asymptotic information and representation theorems in the sense of Begun, Hall, Huang and Wellner are also provided for these models.