Replication data for: Case Selection via Matching

This paper shows how statistical matching methods can be used to select “most similar” cases for qualitative analysis. I first offer a methodological justification for research designs based on selecting most similar cases. I then discuss the applicability of existing matching methods to the task of selecting most similar cases and propose adaptations to meet the unique requirements of qualitative analysis. Through several applications, I show that matching methods have advantages over traditional selection in most-similar case designs: they ensure that “most-similar” cases are in fact most similar, they make scope conditions, assumptions, and measurement explicit, and they make case selection transparent and replicable.