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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.

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

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Footnotes

Edited by Jeff Gill

References

Beach, D., and Pedersen, R.. 2016. Causal Case Study Methods. Ann Arbor: University of Michigan Press.CrossRefGoogle Scholar
Bennett, A. 2015. “Disciplining Our Conjectures: Systematizing Process Tracing with Bayesian Analysis.” In Process Tracing in the Social Sciences, edited by Bennett, A., and Checkel, J., 276298. Cambridge: Cambridge University Press.Google Scholar
Cox, R. 1961. The Algebra of Probable Inference. Baltimore: Johns Hopkins University Press.CrossRefGoogle Scholar
Fairfield, T., and Charman, A. E. (F&C). 2017. “Explicit Bayesian Analysis for Process Tracing.” Political Analysis 25(3):363380.CrossRefGoogle Scholar
Fairfield, T., and Charman, A. E. (F&C). 2019. “The Bayesian Foundations of Iterative Research in Qualitative Social Science.” Perspectives on Politics 17(1):154167.CrossRefGoogle Scholar
Fairfield, T., and Charman, A. E. (F&C). 2020. “Reliability of Inference: Analogs of Replication in Qualitative Research.” In The Production of Knowledge, edited by Elman, C., Gerring, J., and Mahoney, J., 301333. Cambridge: Cambridge University Press. URL: https://tashafairfield.wixsite.com/home/bayes-articles.CrossRefGoogle Scholar
Fairfield, T., and Charman, A. E. (F&C). Forthcoming. Social Inquiry and Bayesian Inference: Rethinking Qualitative Research . Cambridge: Cambridge University Press. Chapter 1. https://tashafairfield.wixsite.com/home/bayes-book.Google Scholar
McKeown, T. 1999. “Case Studies and the Statistical Worldview.” International Organization 53(1):161190.CrossRefGoogle Scholar
Ricks, J., and Liu, A.. 2018. “Process-Tracing Research Designs: A Practical Guide.” PS: Political Science & Politics 51(4):842846.Google Scholar
Rohlfing, I. 2014. “Comparative Hypothesis Testing Via Process Tracing.” Sociological Methods & Research 43(4):606642.CrossRefGoogle Scholar
Surowiecki, J. 2004. The Wisdom of Crowds. New York, NY: Doubleday.Google Scholar
Tetlock, P., and Gardner, D.. 2015. Superforecasting: The Art and Science of Prediction. New York, NY: Crown Books.Google Scholar
Zaks, S. (RAR). 2017. “Relationships among Rivals.” Political Analysis 25(3):344362.CrossRefGoogle Scholar
Zaks, S. (UB). 2020. “Updating Bayesian(s): A Critical Evaluation of Bayesian Process Tracing.” Political Analysis 29(1):5874.CrossRefGoogle Scholar
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