Qualitative Comparative Analysis: Research Design and Application

Instructor: Patrick A. Mello

Modality: In presence

Week 2: 19-23 August 2024

Workshop Contents and Objectives

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 successfully apply QCA in 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 analyzed and interpreted with QCA. During the second half of the workshop we explore 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. 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.

Workshop design

Lectures, exercises, participant presentations, individual consultations.

Detailed lecture plan (daily schedule)

A detailed lecture plan will be circulated before the event.

Class materials

Presentations slides, scripts, sample data sets.

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.

Recommended readings or preliminary material

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

The course structure follows the outline of the textbook (Mello 2021). Individual sessions will be complemented with additional readings, entailed in the detailed course outline that participants will receive ahead of the summer school. To cover the dynamic development of the literature on QCA and related approaches, the course outline also includes bibliography of recommended readings – which will be updated a few weeks before the workshop.