Nested Case-Control Sampling for Marginal Estimation in Multiple Event Settings

Music City Center 

The nested case-control (NCC) design is useful for reducing data collection costs in settings where there is a rare event of interest and a covariate that is expensive or burdensome to collect. Instead of using the full cohort for analyses, the NCC design only requires full covariate information from the individuals who experience events (cases) and a subset of the individuals who are still at-risk at each event time (controls). This efficient sampling design has been developed thoroughly in the univariate survival setting; however, there are few examples of its use for multiple event data. We propose a sampling framework and appropriate estimation methods for the multiple event setting that involves implementing the classic NCC design on data stratified by event number. We recommend using this event-specific sampling approach to ensure a balance of controls across event numbers and to allow for the fitting of models with a common or different baseline hazard for each event number.

nested case-control design

survival analysis

recurrent events 

Lifetime Data Science Section