Cox model inference for relative hazard and pure risk from stratified weight-calibrated case-cohort data.

ABSTRACT: The case-cohort design obtains complete covariate data only on cases and on a random sample (the subcohort) of the entire cohort. Subsequent publications described the use of stratification and weight calibration to increase efficiency of estimates of Cox model log-relative hazards, and there has been some work estimating pure risk. Yet there are few examples of these options in the medical literature, and we could not find programs currently online to analyze these various options. We therefore present a unified approach and R software to facilitate such analyses. We used influence functions adapted to the various design and analysis options together with variance calculations that take the two-phase sampling into account. This work clarifies when the widely used "robust" variance estimat

SUBMITTER: Etievant L 

PROVIDER: S-EPMC11420370 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature