Exploring Causal Complexity with Qualitative Comparative Analysis (QCA)

Instructor: Patrick A. Mello

Modality: In presence

Week 2: 17-21 August 2026

Workshop Contents and Objectives

Causal complexity is everywhere in the social sciences—yet most researchers lack the systematic tools to capture it rigorously. In this intensive 5-day workshop (28 contact hours) you will learn how to design, apply, and publish empirical research with Qualitative Comparative Analysis (QCA) in the R software environment. The course follows the comprehensive framework developed in Mello (2021, Georgetown University Press), progressing systematically from the foundations of QCA to advanced applications.

The course emphasizes research design alongside analytical techniques, addressing both conceptual foundations and practical application of QCA. You will follow an ideal-typical research process, starting with empirical illustrations of where and how QCA is used in the social sciences. Foundational sessions explore key principles, such as set theory, Boolean algebra, and the calibration of crisp and fuzzy sets, while guiding you through the analytical protocol for identifying patterns of causal complexity using truth tables and Boolean minimization.

The course progresses step by step, from study design to the interpretation of results, incorporating hands-on exercises with examples from published studies and R script templates to adapt for your own purposes. Advanced topics—including multi-method research, robustness tests, and recent developments in QCA—will be tailored to your needs and research interests. Opportunities to present your individual project and explore potential applications further enhance the workshop.

Designed to be inclusive, the workshop welcomes participants at all levels—from PhD students to senior researchers—and strikes a balance between theory, practical exercises, and individualized support. A strong emphasis on collaboration and dialogue in a small group setting ensures ample time for consultation, group discussions, and networking. By the end of the workshop, you will be equipped with the theoretical knowledge and practical skills needed to apply QCA effectively, providing a robust framework for addressing causal complexity in comparative social science research.

Workshop design

Lectures, exercises, participant presentations, individual consultations.

Detailed lecture plan (daily schedule)

A detailed and updated lecture plan will be circulated before the workshop.

Class materials

Presentation slides, R scripts, sample data sets, exercises, published examples.

Prerequisites

While beneficial to gain the most from the course, you are not expected to have prior knowledge of QCA nor the R software environment. Instructions will be circulated ahead of the summer school, so that you can read into the topic, install the relevant software, and familiarize yourself with R. For those new to R it is recommended to take part in the summer school’s preparatory course.

Required reading

Mello, Patrick A. (2021) Qualitative Comparative Analysis: An Introduction to Research Design and Application. Washington, DC: Georgetown University Press.

The workshop follows the structure of this book, with sessions corresponding to individual chapters. To cover the dynamic developments of QCA and related approaches, you will receive a detailed course outline with a current bibliography of recommended readings—updated a few weeks before the workshop.

What our participants appreciated most

"An excellent course — clear, well-documented, and conducted in a way that encouraged questions and productive exchanges."

"This course was excellent! Despite.being completely new for me, it was very understandable. Patrick is an incredible expert, wonderful teacher, and very generous with his time. | found it helpful to read/skim his textbook ahead of time and would encourage future students to do the sameif they have the time. | found it personally helpful (and useful to my career) to do my own parallel analysis on some pilot data."