the covariate is not measured for all participants, the nested case–control model is both less expensive than a full cohort analysis and more efficient than taking a simple random sample from the full cohort. However, it has been shown that with 4 controls per case and/or stratified sampling of controls, relatively little efficiency may be lost, depending on the method of estimation used. Analysis of nested case–control studies The analysis of a nested case–control model must take into account the way in which controls are sampled from the cohort. Failing to do so, such as by treating the cases and selected controls as the original cohort and performing a logistic regression, which is common, can result in biased estimates whose null distribution is different from what is assumed. Ways to account for the random sampling include conditional logistic regression, and using inverse probability weighting to adjust for missing covariates among those who are not selected into the study. Case–cohort study A case–cohort study is a design in which cases and controls are drawn from within a prospective study. All cases who developed the outcome of interest during the follow-up are selected and compared with a random sample of the cohort. This randomly selected control sample could, by chance, include some cases. Exposure is defined prior to disease development based on data collected at baseline or on assays conducted in biological samples collected at baseline. References Further reading Epidemiological study projects Design of experiments Cohort study methods Nursing research