A GENERAL SEMIPARAMETRIC Z-ESTIMATION APPROACH FOR CASE-COHORT STUDIES

作者：Nan Bin^*; Wellner Jon A

来源：Statistica Sinica, 2013, 23(3): 1155-1180.

DOI：10.5705/ss.2012.117

• Additive hazards model
• bundled parameters
• case-cohort study
• Cox model
• Donsker class
• empirical process
• Glivenko-Cantelli class
• missing covariates
• semiparametric estimation function
• Z-estimation

Case-cohort design, an outcome-dependent sampling design for censored survival data, is increasingly used in biomedical research. The development of asymptotic theory for a case-cohort design in the current literature primarily relies on counting process stochastic integrals. Such an approach, however, is rather limited and lacks theoretical justification for outcome-dependent weighted methods due to non-predictability. Instead of stochastic integrals, we derive asymptotic properties for case-cohort studies based on a general Z-estimation theory for semiparametric models with bundled parameters using empirical process theory. Both the Cox model and the additive hazards model with time-dependent covariates are considered.

• 出版日期2013-7