A note on nonparametric quantile inference for competing risks and more complex multistate models

• 成果类型: Article
• 署名作者: Beyersmann, Jan; Schumacher, Martin
• 署名单位: University of Freiburg; University of Freiburg
• 刊物名称: BIOMETRIKA
• ISSN/ISSBN: 0006-3444
• DOI: 10.1093/biomet/asn044
• 发表日期: 2008
• 页码: 10061008
• 关键词: probabilities; estimators

摘要

Nonparametric quantile inference for competing risks has recently been studied by Peng & Fine (2007). Their key result establishes uniform consistency and weak convergence of the inverse of the Aalen-Johansen estimator of the cumulative incidence function, using the representation of the cumulative incidence estimator as a sum of independent and identically distributed random variables. The limit process is of a form similar to that of the standard survival result, but with the cause-specific hazard of interest replacing the all-causes hazard. We show that this fact is not a coincidence, but can be derived from a general Hadamard differentiation result. We discuss a simplified proof and extensions of the approach to more complex multistate models. As a further consequence, we find that the bootstrap works.