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Crisp and fuzzy set Qualitative Comparative Analysis (QCA) course at GSERM St. Gallen, Switzerland, June 10-14, 2024

  • 1.  Crisp and fuzzy set Qualitative Comparative Analysis (QCA) course at GSERM St. Gallen, Switzerland, June 10-14, 2024

    Posted 18 days ago

    I will again be teaching a five-day QCA course as part of the Global School in Empirical Research Methods (GSERM). It will take place at the University of St. Gallen, Switzerland, from June 10-14, 2024. Information on the course can be found here.

    The goal of this workshop is to provide a ground-up introduction to crisp and fuzzy set Qualitative Comparative Analysis (QCA). Participants will get intensive instruction and hands-on experience with the fsQCA software package and on completion should be prepared to design and execute research projects using the set-analytic approach. 

    Background:

    Qualitative comparative analysis (QCA) is a research approach consisting of both an analytical technique and a conceptual perspective for researchers interested in studying configurational phenomena. QCA is particularly appropriate for the analysis of causally complex phenomena marked by multiple, conjunctural causation where multiple causes combine to bring about outcomes in complex ways.

    QCA was developed in the 1980s by Charles Ragin, a sociologist and political scientist, as an alternative comparative approach that lies midway between the primarily qualitative, case-oriented approach and the primarily quantitative, variable-oriented approach, with the goal of bridging both by combining their advantages and tackling situations where causality is complex and conjunctural. QCA uses Boolean algebra for the analysis of set relations and allows researchers to formally analyze patterns of necessity and sufficiency regarding outcomes of interest. Since its inception, QCA has developed into a broad set of techniques that share their set-analytic nature and include both descriptive and inferential techniques.

    Many researchers have drawn on QCA because it offers a means to systematically analyze data sets with only few observations. In fact, QCA was originally applied to small-n situations of between 10 and 50 cases; situations where there are frequently too many cases to pursue a classical qualitative approach but too few cases for conventional statistical analysis. However, more recently, researchers have also applied QCA to medium- and large-n situations marked by hundreds or thousands of cases. While these applications require some changes to how QCA is applied, they retain many advantages for analyzing situations that are configurational in nature and marked by causal complexity.

    If you have any questions, please feel free to reach out to me. 

    Peer Fiss



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    Peer Fiss
    University of Southern California
    Los Angeles CA
    (213) 821-1471
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