Consider a case–control study in which we have a random sample, constructed in such a way that the proportion of cases in our sample is different from that in the general population—for instance, the sample is constructed to achieve a fixed ratio of cases to controls. Imagine that we wish to determine which of the potentially many covariates under study truly influence the response by applying the new model‐X knockoffs approach. This paper demonstrates that it suffices to design knockoff variables using data that may have a different ratio of cases to controls. For example, the knockoff variables can be constructed using the distribution of the original variables under any of the following scenarios: (a) a population of controls only; (b) a population of cases only; and (c) a population of cases and controls mixed in an arbitrary proportion (irrespective of the fraction of cases in the sample at hand). The consequence is that knockoff variables may be constructed using unlabelled data, which are often available more easily than labelled data, while maintaining Type‐I error guarantees.