This course introduces you to Qualitative Comparative Analysis and fuzzy sets, and their application in the social sciences, using the R software environment. 

It starts out by familiarising you with the basic concepts of the underlying methodological perspective, including formal logic, Boolean algebra, causal complexity, and calibration. From there, we move to the central notions of necessity and sufficiency, and discuss ways to analyse these using parameters of fit and visualisation techniques.

The core of the course focuses on the logic and analysis of truth tables and discusses the most important problems that emerge when this analytical tool is used for exploring social science data. 

Right from the beginning, you will perform set-theoretic analyses with the relevant R software packages. When discussing set-theoretic methods, our debates will engage on broad, general comparative social research issues, such as case selection principles, concept formation, questions of data aggregation, and the treatment of causally relevant notions of time.

The use of QCA will be practiced based on data from published applications in the social sciences.

This course provides a highly interactive online teaching and learning environment, using state of the art online pedagogical tools. It is designed for a demanding audience (researchers, professional analysts, advanced students) and capped at a maximum of 16 participants so that the teaching team (the Instructor plus one highly qualified Teaching Assistant) can cater to the specific needs of each individual.

Prerequisite Knowledge

You don’t need any prior knowledge of QCA or the R software environment and the package relevant for set-theoretic methods. However, you would profit from prior empirical-comparative training (such as the Comparative Research Designs course on that same week, A:M) and we strongly encourage advance familiarisation with the basic principles of the QCA method by reading the recommended literature.

A previous introduction to the basic functions of R and RStudio would be useful to start working with the software from day 1. We will give you some Intro to R material specific to QCA and we strongly encourage you to practice some of the basics (e.g. loading and manipulating a dataset) beforehand. 

Prior knowledge of the very basics of formal logic and set theory would be very useful but are not expected.