SOME NEW ESTIMATORS FOR COX REGRESSION

• 成果类型: Article
• 署名作者: SASIENI, P
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/aos/1176349395
• 发表日期: 1993
• 页码: 1721-1759
• 关键词: large sample; nonparametric-tests; survival analysis; general-class; case-cohort; MODEL; EFFICIENCY; INFORMATION; FAMILY

摘要

New estimators for Cox regression are considered. Their asymptotic properties, both on and off the model, are established. Corollaries include conditions under which the maximum partial likelihood estimator defines a parameter in the population and the asymptotics of the case-cohort estimator. Robust estimators that minimize the asymptotic variance subject to a bound on the maximal bias on infinitesimal neighborhoods are discussed. The estimators are illustrated with medical data.