Cited by 1,101Statistical Methods and Bayesian InferenceMeta-analysis and systematic reviewsBayesian Modeling and Causal Inference

What are the odds? A practical guide to computing and reporting Bayes factors

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Jarosz, Andrew F., Wiley, Jennifer·2014·The Journal of Problem Solving

Abstract

The purpose of this paper is to provide an easy template for the inclusion of the Bayes factor in reporting experimental results, particularly as a recommendation for articles in the Journal of Problem Solving. The Bayes factor provides information with a similar purpose to the p-value – to allow the researcher to make statistical inferences from data provided by experiments. While the p-value is widely used, the Bayes factor provides several advantages, particularly in that it allows the researcher to make a statement about the alternative hypothesis, rather than just the null hypothesis. In addition, it provides a clearer estimate of the amount of evidence present in the data. Building on previous work by authors such as Wagenmakers (2007), Rouder et al. (2009), and Masson (2011), this article provides a short introduction to Bayes factors, before providing a practical guide to their computation using examples from published work on problem solving.

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Crossref · 10.7771/1932-6246.1167

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Authors
Jarosz, A. F., & Wiley, J.
Affiliations
University of Illinois Chicago (US)
Venue
The Journal of Problem Solving
Published
2014-11-07
Volume
7
Issue
1
ISSN
1932-6246 (ISSN-L)
OpenAlex
W2029705137
Cited by
1,101
References
23
Citations by year
2026: 47 · 2025: 59 · 2024: 85 · 2023: 80 · 2022: 123 · 2021: 164 · 2020: 174 · 2019: 137 · 2018: 109 · 2017: 68 · 2016: 36 · 2015: 14 · 2014: 2
FWCI
42.23
Type
journal article
Language
en
Open access
Locations
  • The Journal of Problem Solving (publishedVersion)
  • Purdue e-Pubs (Purdue University System) (submittedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
  • Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
  • Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Modeling and Causal Inference
Keywords
Bayes factor, p-values, alternative hypothesis, problem-solving research, statistical inference

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