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 (ODS) 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 ODS design. In this report, the authors examined the statistical efficiency of a plain random sample analyzed with standard methods, compared with that of data collected with an ODS design and analyzed by either of two appropriate methods. In addition, three real datasets were analyzed using an ODS approach. The results demonstrate the improved statistical efficiency obtained by using an ODS approach and its applicability in a wide range of settings. An ODS design, coupled with an appropriate analysis, can offer a cost-efficient approach to studying the determinants of a continuous outcome