ABSTRACT
In cohort studies, regression methods are commonly applied to assess the influence of risk factors and other covariates on mortality or morbidity; in particular Cox-regression is much
in Cox’s model is based on a partial likelihood, which at each observed death or disease occurrence (“failure”) compares the covariate values of the failing individual to those of all individuals at risk. Thus Cox regression requires collection of covariate information for all individuals in the cohort, even when only a small fraction of these actually get diseased or die. This may be very expensive, or even logistically impossible. Further when covariate measurements are based on biological material stored in biobanks, it will imply a waste of valuable material that one may want to save for future studies.
