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Understanding Bayesianism: fundamentals for process tracers

Bennett, Andrew, Charman, Andrew E. and Fairfield, Tasha (2022) Understanding Bayesianism: fundamentals for process tracers. Political Analysis, 30 (2). 298 - 305. ISSN 1047-1987

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Identification Number: 10.1017/pan.2021.23

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.

Item Type: Article
Official URL: https://www.cambridge.org/core/journals/political-...
Additional Information: © 2021 The Authors
Divisions: International Development
Subjects: Q Science > Q Science (General)
H Social Sciences > H Social Sciences (General)
Date Deposited: 01 Feb 2022 12:24
Last Modified: 07 Apr 2022 09:54
URI: http://eprints.lse.ac.uk/id/eprint/113589

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