Article „Case-to-factor Ratios and Model Specification in Qualitative Comparative Analysis“ published in Field Methods:
Qualitative Comparative Analysis (QCA) is an empirical research method that has gained some popularity in the social sciences. At the same time, the literature has long been convinced that QCA fails in recognizing real data beyond a certain case-to-factor ratio. To reduce that risk, some authors have proposed benchmark tables that put a limit on the number of exogenous factors given a certain number of cases. We demonstrate that these benchmarks induce more fallacious inferences than they prevent. For valid causal inference, researchers are better off relying on the current state of knowledge in their respective fields. The article is available open-access via this link.