Computational methods for case-cohort studies

Computational methods, which can be implemented using standard Cox regression software, are given for fitting “exact” pseudolikehood estimates and robust and asymptotic variance estimators from case-cohort data. These methods are based on the computational approach of Therneau and Li [1999. Computing the Cox model for case cohort designs. Lifetime Data Anal. 5, 99-112] but will be less subject to small sample bias. Further, it is shown how to accommodate time-dependent covariates and estimate absolute risk. Extensions to stratified case-cohort sampled data are also provided. The methods are illustrated in analyses of case-cohort samples from a study of radiation exposure from fluoroscopy and breast cancer using SAS software.