A Set-Theoretic Approach to Bayesian Process Tracing

Rodrigo Barrenechea, James L Mahoney*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

This article develops a set-theoretic approach to Bayes’s theorem and Bayesian process tracing. In the approach, hypothesis testing is the procedure whereby one updates beliefs by narrowing the range of states of the world that are regarded as possible, thus diminishing the domain in which the actual world can reside. By explicitly connecting Bayesian analysis to its set-theoretic foundations, the approach makes process tracing more intuitive and thus easier to apply for qualitative researchers. Moreover, the set-theoretic approach provides new tools for assessing both the consequentialness and expectedness of evidence when conducting process tracing. It also provides a new way to classify and interpret process-tracing tests, such as hoop tests and smoking gun tests, by viewing them as zones in a continuous space whose dimensions reflect the magnitude of changes in sets. The article shows that Bayesian process tracing and set-theoretic process tracing are not alternatives to each other but rather two sides of the same coin.

Original languageEnglish (US)
Pages (from-to)451-484
Number of pages34
JournalSociological Methods and Research
Volume48
Issue number3
DOIs
StatePublished - Aug 1 2019

Keywords

  • Bayesian analysis
  • hypothesis testing
  • possible worlds
  • process tracing
  • set theory

ASJC Scopus subject areas

  • Social Sciences (miscellaneous)
  • Sociology and Political Science

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