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Bayes Factors From Pooled Data Are No Substitute for Bayesian Meta-Analysis: Commentary on Scheibehenne, Jamil, and Wagenmakers (2016)
Linnaeus University, Faculty of Health and Life Sciences, Department of Psychology.ORCID iD: 0000-0002-6456-5735
University of Toronto Mississauga, Canada.
University of California Davis, USA.
University of Münster, Germany.
2017 (English)In: Psychological Science, ISSN 0956-7976, E-ISSN 1467-9280, Vol. 28, no 11, p. 1694-1697Article in journal, Letter (Refereed) Published
Abstract [en]

Scheibehenne, Jamil, and Wagenmakers (2016; SJW) recently introduced Bayesian evidence synthesis (BES). They used it to combine evidence from seven published studies that examined the influence of social-norm messages on hotel towel reuse rates. Although most of the original studies provided non-significant results (p-value > .05), BES provided strong support for the effect (Bayes factor = 37). We think that this conclusion is wrong. We demonstrate that BES is inherently flawed because it pools data in a way that is vulnerable to a Simpson’s paradox, and that a Bayesian meta-analysis that avoids this problem produces weaker evidence. 

Place, publisher, year, edition, pages
Sage Publications, 2017. Vol. 28, no 11, p. 1694-1697
Keywords [en]
Meta-analysis, Bayesian, Social norms
National Category
Psychology (excluding Applied Psychology)
Research subject
Social Sciences, Psychology
Identifiers
URN: urn:nbn:se:lnu:diva-59448DOI: 10.1177/0956797616684682ISI: 000414656900014PubMedID: 28910202OAI: oai:DiVA.org:lnu-59448DiVA, id: diva2:1058859
Available from: 2016-12-21 Created: 2016-12-21 Last updated: 2018-05-31Bibliographically approved

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Carlsson, Rickard

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CiteExportLink to record
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Citation style
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  • Other locale
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