I am pleased to announce that I will again be teaching a comprehensive five-day QCA course as part of the Global School in Empirical Research Methods (GSERM), hosted by the University of St. Gallen, Switzerland, from June 8-12, 2026.
[Complete course details and application information here]
Course Overview
This intensive workshop provides a thorough introduction to both crisp- and fuzzy-set Qualitative Comparative Analysis (QCA). Participants receive hands-on instruction with the fsQCA software package and develop the skills necessary to design and execute research projects using set-analytic approaches.
Who should attend:
This course is intended for doctoral students, postdoctoral researchers, and faculty across the social sciences who are interested in studying configurational phenomena and causal complexity using set-analytic methods.
About QCA
Qualitative Comparative Analysis combines analytical techniques with a conceptual framework ideal for studying configurational phenomena. It excels at analyzing causally complex situations characterized by multiple, conjunctural causation-where various factors interact in complex ways to produce outcomes.
Developed in the 1980s by sociologist and political scientist Charles Ragin, QCA bridges the gap between primarily qualitative, case-oriented approaches and primarily quantitative, variable-oriented approaches.
QCA employs Boolean algebra to analyze set relations, allowing researchers to formally identify patterns of necessity and sufficiency for outcomes of interest. Since its inception, QCA has evolved into a diverse set of techniques sharing a set-analytic foundation, encompassing both descriptive and inferential methodologies.
Applications
As a formal approach for data analysis, QCA can be applied to essentially any setting, but it is particularly valuable for analyzing datasets with relatively few observations (traditionally 10-50 cases). Recent developments have expanded QCA applications to medium- and large-N situations involving hundreds or even thousands of cases. While these applications require methodological adaptations, they maintain QCA's advantages for analyzing configurational phenomena and causal complexity.
Contact Information
For questions or additional information, please contact me at fiss@marshall.usc.edu.
Peer Fiss
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Peer Fiss
University of Southern California
Los Angeles CA
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