Understanding Bayesianism: Fundamentals for Process Tracers

IF 4.7 2区 社会学 Q1 POLITICAL SCIENCE Political Analysis Pub Date : 2021-07-26 DOI:10.1017/pan.2021.23
Andrew Bennett, A. Charman, Tasha Fairfield
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引用次数: 2

Abstract

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.
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理解贝叶斯主义:过程跟踪的基础
摘要贝叶斯分析已成为定性方法中一个迅速发展的前沿领域。该杂志最近的工作对如何实现贝叶斯过程跟踪以及这种方法的成本与收益提出了各种各样的质疑。在这个回应中,我们阐述了一种对方法状态的非常不同的理解,以及一种更积极的观点,即贝叶斯推理可以做些什么来加强定性社会科学。借鉴即将开展的研究以及我们早期的工作,我们专注于澄清涉及假设的互斥性,证据进口,在两个以上的假设之间进行裁决,以及迭代研究的逻辑等问题,目的是阐明贝叶斯分析如何运作并推动该领域向前发展。
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来源期刊
Political Analysis
Political Analysis POLITICAL SCIENCE-
CiteScore
8.80
自引率
3.70%
发文量
30
期刊介绍: Political Analysis chronicles these exciting developments by publishing the most sophisticated scholarship in the field. It is the place to learn new methods, to find some of the best empirical scholarship, and to publish your best research.
期刊最新文献
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