• This is an advanced methodologcial course on a set of data analysis techniques that are based on set theory and formal logic, which have become known under the acronym QCA (Qualitative Comparative Analysis), or, most recently under CCM (Configurational Comparative Methods, Rihoux & Ragin 2008). Invented by Charles Ragin (1987), this technique has undergone various modifications, improvements, and ramifications (Ragin 2000, 2008). It currently receives increasing interest in the broader social scientific community, both from its more qualitative and its more quantitative side. This course aims at providing both the mathematical and (set) theoretical underpinnings of QCA and the technical and research practical skills necessary for performing a QCA analysis.

    In order to achieve these aims, we will first look at crisp set QCA (csQCA). We introduce the concepts of causal complexity and of necessity and sufficiency, show how the latter denote subset relations, and then learn how such subset relations can be analyzed with so-called truth tables. In the second part of the course, we extend what we have learned for csQCA to fuzzy set QCA (fsQCA). In a last step we look at advanced moduls for QCA (both crisp and fuzzy) and other extensions of QCA (such as multi-value QCA and time QCA). Throughout the course, we frequently use the computer and enhance our practical QCA skills by performing hands-on analyes.

    A desired (and very likely) side effect of this course will be that we engage into discussions on more general methodological issues of good comparative research, such as case selection, concept formation, measurement validity, and forms of causal relations.