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Working group

Bayesian Inference for Qualitative Evidence

This working group convenes social scientists at all career stages who are interested in using Bayesian reasoning for causation-oriented qualitative research, process tracing, comparative case studies, and multimethod research.  It offers feedback throughout the research process, helping scholars refine hypotheses and systematically evaluate how strongly empirical evidence supports an explanation relative to rivals.

Bayesianism is enjoying a revival across many fields, and it offers a powerful framework for improving inference in qualitative research. Bayesian analysis is an intuitive process that begins by assessing prior odds on rival hypotheses, drawing on any relevant initial knowledge. We gather evidence and evaluate its inferential weight by asking which hypothesis makes that evidence more expected. We then update to obtain posterior odds—following Bayes’ rule, we gain more confidence in whichever hypothesis makes the evidence more expected.

Bayesianism provides a rigorous methodological foundation for inference to best explanation that helps us make more systematic and better reasoned judgements about how strongly evidence supports one hypothesis relative to rivals, while mitigating common cognitive pitfalls like confirmation bias. It also enhances analytic transparency by making it easier for other scholars to evaluate our inferences.

Our workshops range from feedback sessions on preliminary hypotheses, to discussions of conference papers and manuscripts at all stages of the publication pipeline. We invite scholars at the EUI and academics from other universities to participate in our hybrid meetings, with the goal of raising the profile of Bayesianism in the social sciences and expanding the community of scholars who are employing this methodological approach.

Interested members of the EUI community with no previous exposure to Bayesian inference are very welcome to join the working group. Those who would like to learn more about the method are encouraged to consider taking or auditing “Bayesian Inference for Qualitative Research” during the second term (contact Tasha Fairfield for more information).

Watch this video talk to learn about Bayesian reasoning. 

Upcoming Events:

  • Friday, 24 October
    Lukas Hakelberg, Leuphana University of Lüneburg
    “Coalition Formation and the Sovereignty of Tax Havens: A Comparative Historical Analysis of the Bahamas and Bermuda
    ”Discussant: Aaron Schneider, University of Denver

  • Wednesday, 5 November
    Neil Ketchley, Oxford University
    "Death on the Nile: Explaining ‘Ethnic Violence’ During the 1919 Egyptian Revolution
    "Discussant: Natasja Rupesinghe, EUI
     Register here

  • Wednesday, 19 November
    Marius Ghincea, ETH Zurich, and Wolfgang Minatti, Leuphana University
    "Domestic Politics and Military Aid to Ukraine: Explaining Disclosure Policies in France and Germany
    "Discussant: Andrew Bennett, Georgetown
    Register here

External Partners

  • N/A

    Qualitative Bayesian Reasoning Network (QBR-Net)

    The QBR-Net is a googlegroup that disseminates information about training opportunities, conference activities, and virtual research workshops

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