Lugano, Switzerland

Qualitative Comparative Analysis: Research Design and Application

when 22 August 2022 - 26 August 2022
language English
duration 1 week
fee CHF 700

This workshop gives a thorough introduction to the method of Qualitative Comparative Analysis (QCA), with an emphasis on research design and practical application. 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 this workshop, participants will be introduced to the foundations and advanced functions of QCA, while the course structure follows an ideal-typical research process. The introduction opens with empirical illustrations to show how and for what purposes QCA is being used in various areas of the social sciences, before summarizing the method’s key characteristics. This is followed by concise sessions on causation, causal complexity, and research design, to provide a basis for thinking about empirical applications. The ensuing sessions engage with the use of 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 analyzed and interpreted with QCA.
Towards the end of the workshop, we will look into advanced topics, which can be tailored based on participants’ background and research interests. Potential topics include multi-method research design, QCA variants, robustness tests in QCA, addressing critiques, and recent developments.

The workshop sessions are complemented by illustrations and exercises, using the R Software environment and relevant R Packages.

Requirements

Course participants are not expected to have any previous knowledge of QCA or the R software environment and its relevant packages. 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.

Course leader

Patrick Mello, University of Erfurt

Target group

Everyone who is interested; there are no formal requirement. Note that many workshops have some prerequisites.

The Summer School workshops are conceived for those who need to deepen and widen their methodological knowledge and skills for their work, research projects and (PhD) theses: students, junior and senior researchers, practitioners from academia and outside academia at any stage of their careers whenever the need for further training in methodology arises.

Course aim

Throughout this workshop, participants will be introduced to the building blocks of QCA, while the course structure follows an ideal-typical research process. The introduction opens with empirical illustrations to show how and for what purposes QCA is being used, before summarizing the method’s key characteristics. This is followed by sessions on causation, causal complexity, and research design, to provide a foundation for thinking about empirical applications. The ensuing sessions engage with the use of 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 session on set-theoretic analysis puts all of the elements together and shows how empirical data is analyzed and interpreted with QCA. Finally, the workshop closes with sessions on advanced topics, which can be tailored based on participants’ background and research interests. Potential topics include multi-method research design, QCA variants, addressing critiques, and recent developments.

Credits info

The Summer School cannot grant credits. We only deliver a Certificate of attendance, i.e. we certify your presence

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 recognize 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).
These fees includes also participation in one of the preliminary workshops (two-day workshop preceding the Summer School).
To qualify for the reduced fee, you are required to send a copy of an official document that certifies your current student status or a letter from your supervisor stating your actual position as a doctoral or postdoctoral student. Send this letter/document by e-mail to methodssummerschool@usi.ch.
CHF 1100: Normal fee: 1100 Swiss Francs per weekly workshop for all others.
These fees includes also participation in one of the preliminary workshops (two-day workshop preceding the Summer School).

Scholarships

As the Summer School is financed through participant’s fees alone and has no funds of its own, it cannot offer any scholarship, grants or financial aid.