Latest Updates

During the week of August 17-21, I taught the course “Exploring Causal Complexity with Qualitative Comparative Analysis (QCA)” at the 30th Summer School in Social Sciences Methods of the Università della Svizzera italiana (USI) in Lugano, Switzerland. This has been the 8th time teaching this course in Lugano, ten years after its first edition in 2016. As in previous years, the intensive one-week course combined lectures with hands-on exercises in R, with dedicated time for participant presentations and individual consultations. The course follows my book Qualitative Comparative Analysis: An Introduction to Research Design and Application (Georgetown University Press, 2021) and the accompanying R Manual for QCA.

It is always a pleasure to see how participants apply QCA to research questions from across the social sciences. Thanks to the organizing team at USI for the smooth running of the summer school and to all participants for a constructive and very engaging week! And many thanks to Johannes Meuer (KLU Hamburg) for an inspiring guest lecture on calibration. We look forward to seeing that paper published!

If you are interested in taking part in 2027, please let me know (registration usually opens in December/January). For impressions from previous years of the USI Summer School, see here.

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The R Manual for QCA has been updated to version 4.1 (August 2026). Among other changes, the manual now includes expanded sections on visualizing QCA results, with templates for creating, customizing, and combining X–Y plots and saving graphics as PDF or PNG files. There are also new sections on cluster analysis and robustness tests. The robustness tests follow the protocol developed by Oana and Schneider (2024), illustrated with replication data from a published study (Meissner and Mello 2022).

While the R Manual is written to get readers started, without assuming prior knowledge of R, it has grown into a 44-page document that provides step-by-step instructions for a complete QCA research cycle, from data management and calibration to necessary conditions, truth table analysis, solution types, and the visualization of results. All code is included in an accompanying R Script that can be adapted for one’s own purposes, complemented by two sample data sets. The analyses draw on the QCA package by Adrian Duşa and the SetMethods package by Ioana-Elena Oana and Carsten Q. Schneider, together with ggplot2 and further packages for visualization. For comprehensive treatments of QCA in R, see Duşa’s QCA with R (Springer, 2019) and Oana, Schneider, and Thomann’s Qualitative Comparative Analysis Using R (Cambridge University Press, 2021).

The R Manual for QCA (PDF file, R Script, and sample data) can be downloaded here and on Harvard Dataverse: https://doi.org/10.7910/DVN/KYF7VJ.

On June 20, Hilde van Meegdenburg (Leiden University) and I presented our co-authored book manuscript “Uncovering Causal Symptoms: Case Study Research, Process Tracing, and Qualitative Comparative Analysis” at the Advances in Qualitative and Multi-Method Research (AQMMR) workshop, held virtually as part of the Institute for Qualitative and Multi-Method Research (IQRM) 2026 at Syracuse University. The manuscript was discussed by James Mahoney (Northwestern University) and Ingo Rohlfing (University of Passau). The workshop was organized by Diana Kapiszewski (Georgetown University) and Sebastian Karcher (Syracuse University), and coordinated with Alan Jacobs (University of British Columbia) and Erica Simmons (University of Wisconsin-Madison) as editors of the Methods for Social Inquiry series published by Cambridge University Press. Many thanks to our discussants and all participants for the constructive and intensive discussion of our manuscript—this has been tremendously helpful.