Confounding by indication is a key challenge for pharmacoepidemiologists. Although self-controlled study designs address time-invariant confounding, indications sometimes vary over time. For example, infection might act as a time-varying confounder in a study of antibiotics and uveitis, because it is time-limited and a direct cause of both receipt of antibiotics and uveitis. Methods for incorporating active comparators in self-controlled studies to address such time-varying confounding by indication have only recently been developed. In this paper, we formalize these methods and provide a detailed description for how the active comparator rate ratio can be derived in a self-controlled case series: either by explicitly comparing the regression coefficients for a drug of interest and an active comparator under certain circumstances using a simple ratio approach or through the use of a nested regression model. The approaches are compared in 2 case studies, one examining the association between thiazolidinedione use and fractures and one examining the association between fluoroquinolone use and uveitis, using the United Kingdom's Clinical Practice Research Datalink. Finally, we provide recommendations for the use of these methods, which we hope will support the design, execution, and interpretation of self-controlled case series using active comparators and thereby increase the robustness of pharmacoepidemiologic studies. This article is part of a Special Collection on Pharmacoepidemiology.