Towards a general asymptotic theory for Cox model with staggered entry

• 成果类型: Article
• 署名作者: Bilias, Y; Gu, MG; Ying, ZL
• 署名单位: Iowa State University; McGill University; Rutgers University System; Rutgers University New Brunswick
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• 发表日期: 1997
• 页码: 662-682
• 关键词: censored survival-data; partial likelihood; REGRESSION-MODEL; tests

摘要

A general asymptotic theory is established for the two-parameter Cox score process with staggered entry data. It extends in several directions the existing theory developed by Sellke and Siegmund, Slud and Gu and Lai. An essential tool employed here is a modern empirical process theory, as elucidated in a recent monograph by Pollard.