Inverse sampling of controls in a matched case.control study

A method of inverse sampling of controls in a matched case.control study is described in which, for each case, controls are sampled until a discordant set is achieved.For a binary exposure, inverse sampling is used to determine the number of controls for each case.When most individuals in a population have the same exposure, standard case.control sampling may result in many case.control sets being concordant with respect to exposure and thus uninformative in the conditional logistic analysis.The method using inverse control sampling is proposed as a solution to this problem in situations when it is practically feasible.In many circumstances, inverse control sampling is found to offer improved statistical efficiency relative to a comparable study with a fixed number of controls per case.