Konstanz Methods Excellence Workshops: Introduction to Qualitative Comparative Analysis (Online Course)
2024-02-26 - 2024-03-01
This 5-day online course introduces Qualitative Comparative Analysis as an approach that enables researchers to model causal complexity by analyzing whether different configurations of conditions are necessary or sufficient for an outcome together with its technical implementation in R.
What Is This Course About?
This 5-day online course introduces Qualitative Comparative Analysis as an approach and a technique, its main assumptions, its standard procedures and operations, and the technical environment (R software and packages) used for its application. QCA enables researchers to model causal complexity by analyzing whether different configurations of conditions are necessary or sufficient for an outcome, based on a formalized comparison of intermediate to large numbers of cases. Throughout the course, emphasis is put on a thorough understanding of the formal logic of set-theoretic methods and QCA, including topics such as Boolean algebra, causal complexity, sets and their calibration, necessity, and sufficiency. The course also discusses the logic and analysis of truth tables and the most important problems that emerge when this analytical tool is used for exploring social science data. Right from the beginning, participants are exposed to performing set-theoretic analyses with the relevant R software packages using data from published applications in the social sciences.

Konstanz Methods Excellence Workshops: Advanced Qualitative Comparative Analysis (Online Course)
2024-02-26 - 2024-03-01 | Online
This 5-day course exposes participants to advanced methodological developments in Qualitative Comparative Analysis (QCA) that allow for further solidifying their results, and enables them to apply state-of-the-art set-theoretic analytic tools in R.
What Is This Course About?
This 5-day course introduces a series of advanced topics in Qualitative Comparative Analysis (QCA) that aim at further solidifying and deepening the understanding of the application of this method and the results produced by it. As QCA continues to evolve, the course exposes participants to its latest methodological developments and enables them to apply state-of-the-art set-theoretic analytic tools in R. The course starts by expanding on the problem of limited empirical diversity (i.e., when not all the configurations of conditions in the analysis are represented empirically) and discusses potential strategies for making good counterfactuals assumptions (within the so-called Enhanced Standard Analysis). Throughout the rest of the course, we discuss advanced analytic tools that can be used after a QCA result has been obtained. Among these, we look at set-theoretic robustness and sensitivity and introduce a QCA robustness check protocol, we discuss strategies for confronting situations when the data at hand contains clusters that are potentially analytically relevant, we discuss the use of set-theoretic theory-evaluation as a way of assessing theoretical hunches based on the results generated by QCA. Finally, we discuss set-theoretic multi-method research introducing guidelines for combining QCA with process-tracing in single or comparative case studies.
