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Understanding Bayesianism: Fundamentals for Process Tracers

Published online by Cambridge University Press:  26 July 2021

Andrew Bennett
Affiliation:
Georgetown University, Washington, DC, USA. Email: bennetta@georgetown.edu
Andrew E. Charman
Affiliation:
University of California–Berkeley, Berkeley, CA, USA. Email: acharman@physics.berkeley.edu
Tasha Fairfield*
Affiliation:
London School of Economics, London, UK. Email: T.A.Fairfield@lse.ac.uk
*
Corresponding author Tasha Fairfield

Abstract

Bayesian analysis has emerged as a rapidly expanding frontier in qualitative methods. Recent work in this journal has voiced various doubts regarding how to implement Bayesian process tracing and the costs versus benefits of this approach. In this response, we articulate a very different understanding of the state of the method and a much more positive view of what Bayesian reasoning can do to strengthen qualitative social science. Drawing on forthcoming research as well as our earlier work, we focus on clarifying issues involving mutual exclusivity of hypotheses, evidentiary import, adjudicating among more than two hypotheses, and the logic of iterative research, with the goal of elucidating how Bayesian analysis operates and pushing the field forward.

Information

Type
Letter
Copyright
© The Author(s) 2021. Published by Cambridge University Press on behalf of the Society for Political Methodology

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Supplementary material: PDF

Bennett et al. supplementary material

Bennett et al. supplementary material

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