Cited by 654Statistical Methods and Bayesian InferenceMeta-analysis and systematic reviewsStatistical Methods in Clinical Trials

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Using Bayes factor hypothesis testing in neuroscience to establish evidence of absence

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Keysers, Christian, Gazzola, Valeria, Wagenmakers, Eric-Jan·2020·Nature Neuroscience

DOI 10.1038/s41593-020-0660-4PMC PMC7610527

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Abstract

Most neuroscientists would agree that for brain research to progress, we have to know which experimental manipulations have no effect as much as we must identify those that do have an effect. The dominant statistical approaches used in neuroscience rely on P values and can establish the latter but not the former. This makes non-significant findings difficult to interpret: do they support the null hypothesis or are they simply not informative? Here we show how Bayesian hypothesis testing can be used in neuroscience studies to establish both whether there is evidence of absence and whether there is absence of evidence. Through simple tutorial-style examples of Bayesian t-tests and ANOVA using the open-source project JASP, this article aims to empower neuroscientists to use this approach to provide compelling and rigorous evidence for the absence of an effect.

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Self-citation

Authors: Keysers, C., Gazzola, V., & Wagenmakers, E.-J.
Affiliations: Netherlands Institute for Neuroscience (NL)
University of Amsterdam (NL)
Corresponding author: Keysers, Christian
ORCID: Keysers, Christian
Gazzola, Valeria
Wagenmakers, Eric-Jan
Venue: Nature Neuroscience
Publisher: Springer Science and Business Media LLC
Published: 2020-06-29
Volume: 23
Issue: 7
Pages: 788-799
ISSN: 1097-6256 (ISSN-L)
1546-1726
DOI: 10.1038/s41593-020-0660-4
PMC: PMC7610527
OpenAlex: W3037007306
Cited by: 654
References: 41
Citations by year: 2026: 69 · 2025: 92 · 2024: 127 · 2023: 118 · 2022: 118 · 2021: 98 · 2020: 29
FWCI: 14.74
Type: journal article
Language: en
Update notices: correction (2020-10-06)
Open access: green
pure.knaw.nl
Licence: other-oa
www.springer.com/tdm (tdm)
www.springer.com/tdm (vor)
Locations: Nature Neuroscience (publishedVersion)
PubMed (publishedVersion)
KNAW research portal (Royal Academy of Art and Sciences (KNAW)) (publishedVersion, other-oa)
PubMed Central (acceptedVersion)
UvA-DARE (University of Amsterdam) (submittedVersion, cc-by)
KNAW Research Portal (The Royal Netherlands Academy of Arts and Sciences) (submittedVersion, cc-by)
Data Archiving and Networked Services (DANS) (submittedVersion, cc-by)
Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
Funders: Nederlandse Organisatie voor Wetenschappelijk Onderzoek (453-15-009, 452-14-015)
H2020 European Research Council (758703)
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 › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Keywords: Bayes factor, evidence of absence, absence of evidence, Bayesian hypothesis testing, null hypothesis, p-values, Bayesian t-test, JASP
MeSH terms: Animals, Bayes Theorem, Brain, Humans, Neurosciences, Research Design

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Using Bayes factor hypothesis testing in neuroscience to establish evidence of absence

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