The Perelman School of Medicine at the University of Pennsylvania has acquired funding from the National Institutes of Health (NIH) for a four-year research project to better understand the complex interplay between contextual and intervention features in care delivery for patients that undergo invasive mechanical ventilation (total budget: USD 2,816,250). The project involves nine researchers across five domains. I will serve as methodological consultant on the QCA component of the multi-method research design.
Month: January 2026
-
Lugano Summer School 2026: Register for Qualitative Comparative Analysis (QCA)
The program for the 30th Summer School in Social Sciences Methods at the Università della Svizzera italiana in Lugano, Switzerland has been announced: I’m offering Exploring Causal Complexity with Qualitative Comparative Analysis (QCA) during the week of August 17-21, 2026. For impressions from previous years, see here. This course provides a complete introduction to QCA, including R software packages (see detailed course description below). For more information, also on registration, please see the USI Summer School Website. If you have any questions about the course, please don’t hesitate to contact me.
From the course description: 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.