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) but will be less subject to small sample bias. Further, it is shown how cumulative hazard or survival curves can be computed from case-cohort data and how to accommodate time dependent covariates. 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. ∗ Corresponding author: Phone: [phone], Fax: [phone] Key words: bias, Cox model, cumulative hazard, stratified Cox model, survival curves, time-dependent covariates 0 Abbreviated title: Case-cohort analysis 0 This work was supported by NCI grant CA42949 and NIEH...

• Type: Journal
• Year: 2007
• Where: CSDA
• Authors: Bryan Langholz, Jenny Jiao
• Keywords: Case-cohort Data, CSDA 2007, Cumulative Hazard, Survival Curves