Qualitative comparative analysis (QCA)

In the academic year 2023-2024 this course will take place offline.

Need to analyse cause-effect relations across multiple cases and not sure how? Qualitative Comparative Analysis (QCA) offers a systematic, transparent, and innovative solution. This method is relevant for both quantitatively and qualitatively oriented researchers.

QCA, introduced by Charles Ragin in the 1980s and developed further since, is gaining prominence in various social sciences, including political science, economics and business, management, pedagogical sciences, health sciences, sociology, and environmental sciences.

Before enrolling, please inform yourself about the aims and setup of the course and the applicability of QCA as described below. Please note that this method cannot be used for the study of one or just a few cases.

This is an introductory course. It is designed for people who have no or limited experience with QCA.

The course is supported by a number of videos that were made for our Massive Open Online Course (MOOC; https://www.coursera.org/learn/qualitative-comparative-analysis). Watching and studying these videos form part of the preparation that is asked from participants.

Participants should not follow our MOOC before attending the course. Instead, the relevant videos will be provided by the lecturer in advance of the course.

Please note that the class sessions comprise exercises that are also offered in our MOOC. Thus the course will be less useful for participants who have already completed our MOOC and done its exercises.

After completing the course participants will:

• know how QCA has historically developed and in which academic context;
• know how a QCA study can be designed, under which conditions, and for what purposes;
• know how to conduct a QCA study and understand the precise logics on which the analyses are based;
• know how to interpret and report the results of a QCA study.

• QCA is relevant for researchers who normally work with qualitative methods and are looking for a more systematic way of comparing and assessing cases.
• QCA is also useful for quantitative researchers who like to assess alternative (more complex) aspects of causation, such as how factors work together in producing an effect.
• QCA can be used for the analysis of cases on all levels: macro (e.g. countries), meso (e.g. organizations) and micro (e.g. individuals).
• QCA is mostly used for research of small- and medium-sized samples and populations (10-100 cases), but it can also be used for larger groups. Ideally, the number of cases is at least 10. The less than 10 cases you have, the less function and added value QCA potentially has. QCA cannot be applied at all if you study just one case.

Session 1
The set-theoretic foundations of QCA and the first research steps (designing a QCA study, calibration, and making a crisp truth table)

Session 2
Making a fuzzy truth table, logical minimization, and the minimal formula

Session 3
Parameters of fit for the solution, using the program fsQCA, and the epistemology of causality in QCA

Session 4
Assessing necessity, the write-up, and your QCA experience (trial of your own model; critical reflection)

Please note that you will need a laptop in all 4 sessions to make notes and assignments.

A syllabus will be provided at the beginning of the course with more details about the course contents and structure.