25 August 2023
Qualitative Comparative Analysis (QCA)
This workshop provides participants with a thorough introduction to Qualitative Comparative Analysis (QCA). Since its inception (Ragin 1987), QCA has gained recognition among social scientists as a case-based research method that is ideally suited to capture causal complexity. This essentially describes a situation where an outcome results from multiple pathways and different combinations of conditions. Moreover, QCA entails a rigorous and systematic comparison of selected cases and their configurations through Boolean logic and a software-based analytical protocol. Throughout the workshop, emphasis is placed on research design and practical application so that participants are enabled to work on their own studies.
Throughout the workshop, participants are introduced to the foundations and advanced functions of QCA, while the course structure follows an ideal-typical research process. Starting with empirical illustrations that show how and for what purposes QCA is being used in the social sciences, the workshop proceeds with presenting the method’s core characteristics. This is followed by sessions on causation, causal complexity, and research design to provide a basis for thinking about empirical applications. The ensuing sessions engage with QCA as an analytical approach, starting with set theory and concepts like necessary and sufficient conditions, Boolean algebra, truth tables, and fuzzy sets. In calibrating sets, we look into approaches to transform empirical raw data into crisp and fuzzy sets. Next, the course examines various measures of fit that help in evaluating QCA results. The sessions on set-theoretic analysis put all the elements together and show how empirical data is analysed and interpreted with QCA. During the second half of the workshop, we explore advanced topics, which can be tailored based on participants’ backgrounds and research interests. Potential topics include multi-method research design, QCA variants, robustness tests in QCA, addressing critiques, and recent developments. Participants also have the opportunity to present and discuss their own work within the group. The workshop sessions are complemented by illustrations and exercises from the social sciences, using the R Software environment and relevant R Packages.
The workshop includes dedicated timeslots for individual consultation with the lecturer, group discussions, and networking opportunities.
Course leader
Patrick A. Mello is an Assistant Professor of International Security at the Department of Political Science and Public Administration of the Vrije Universiteit Amsterdam.
Target group
doctoral researchers, early career researchers, experienced researchers
Prerequisites
Course participants are not expected to have any previous knowledge of QCA or the R software environment. Participants will receive preparatory instructions ahead of the summer school, so that they can install the relevant software and familiarize themselves with the environment of R and RStudio. For those new to R, it is recommended to take part in the summer school’s preparatory course on R, which takes place before the start of the workshop.
Credits info
The Summer School cannot grant credits. We only deliver a Certificate of Participation, i.e. we certify your attendance.
If you consider using Summer School workshops to obtain credits (ECTS), you will have to investigate at your home institution (contact the person/institute responsible for your degree) to find out whether they recognise the Summer School, how many credits can be earned from a workshop/course with roughly 35 hours of teaching, no graded work, and no exams.
Make sure to investigate this matter before registering if this is important to you.
Fee info
CHF 700: Reduced fee: 700 Swiss Francs per weekly workshop for students (requires proof of student status).
CHF 1100: Normal fee: 1100 Swiss Francs per weekly workshop for all others.