Outcome-dependent sampling: an efficient sampling and inference procedure for studies with a continuous outcome

To characterize the relation between an exposure and a continuous outcome, the sampling of subjects can be done much as it is in a case-control study, such that the sample is enriched with subjects who are especially informative. In an outcome-dependent sampling design, observations made on a judiciously chosen subset of the base population can provide nearly the same statistical efficiency as observing the entire base population. Reaping the benefits of such sampling, however, requires use of an analysis that accounts for the outcome-dependent sampling. In this report, we examine the statistical efficiency of a plain random sample analyzed with standard methods, compared with that of data collected with outcome-dependent sampling and analyzed by either of 2 appropriate methods. In addition, 3 real datasets were analyzed using an outcome-dependent sampling approach. The results demonstrate the improved statistical efficiency obtained by using an outcome-dependent sampling, and its applicability in a wide range of settings. This design, coupled with an appropriate analysis, offers a cost-efficient approach to studying the determinants of a continuous outcome.