Analyzing multilevel data with QCA: a straightforward procedure

The social sciences are witnessing a growing body of multilevel theories and debates about the proper methodological tools for the analysis of multilevel data. In a recent contribution to this journal, multilevel Qualitative Comparative Analysis (QCA) was proposed as a new methodological tool for discerning set-relational patterns in multilevel data. I argue that the presentation of multilevel QCA is erroneous in two respects. First, multilevel QCA ignores the fact that equifinal solutions entail diversity and therefore leads one to overestimate the complexity of QCA solutions. Second, the ordinary minimization procedure of truth tables that contain multilevel data yields the same solutions as multilevel QCA, but is much easier to implement. I conclude that the established inventory of QCA does not need to be extended by a special multilevel approach.