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Mac Giolla, E. & Ly, A. (2020). What to do with all these Bayes factors: How to make Bayesian reports in deception research more informative. Legal and Criminological Psychology
Open this publication in new window or tab >>What to do with all these Bayes factors: How to make Bayesian reports in deception research more informative
2020 (English)In: Legal and Criminological Psychology, ISSN 1355-3259, E-ISSN 2044-8333Article in journal (Refereed) Epub ahead of print
Abstract [en]

Bayes factors quantify the evidence in support of the null (absence of an effect) or the alternative hypothesis (presence of an effect). Based on commonly used cut-offs, Bayes factors between 1/3 and 3 are interpreted as evidentially weak, and one typically concludes there is an absence of evidence. In this commentary on Warmelink, Subramanian, Tkacheva, and McLatchie (Legal Criminol Psychol 24, 2019, 258), we discuss how a Bayesian report can be made more informative. Firstly, this implies a departure from the labels provided by commonly used cut-offs when reporting Bayes factors. Instead, we encourage researchers to report the value of the Bayes factors, or to convert these values into nominal support for the hypotheses. Secondly, researchers can provide recommendations to design follow-up studies by examining the posterior distribution of the magnitude of the effect size. Lastly, we show how individual Bayes factors can be evaluated in the context of large-scale meta-analyses.

Keywords
Bayes factors, deception detection, sample size
National Category
Applied Psychology
Research subject
SOCIAL SCIENCE, Psychology
Identifiers
urn:nbn:se:hv:diva-14747 (URN)10.1111/lcrp.12162 (DOI)000501173900001 ()
Note

First published: 05 December 2019

Available from: 2020-02-24 Created: 2020-02-24 Last updated: 2020-03-02Bibliographically approved
Mac Giolla, E. & Ly, A. (2019). What to do with all these Bayes factors: How to make Bayesian reports in deception research more informative. Legal and Criminological Psychology
Open this publication in new window or tab >>What to do with all these Bayes factors: How to make Bayesian reports in deception research more informative
2019 (English)In: Legal and Criminological Psychology, ISSN 1355-3259, E-ISSN 2044-8333Article in journal (Refereed) Epub ahead of print
Abstract [en]

Bayes factors quantify the evidence in support of the null (absence of an effect) or the alternative hypothesis (presence of an effect). Based on commonly used cut-offs, Bayes factors between 1/3 and 3 are interpreted as evidentially weak, and one typically concludes there is an absence of evidence. In this commentary on Warmelink, Subramanian, Tkacheva, and McLatchie (Legal Criminol Psychol 24, 2019, 258), we discuss how a Bayesian report can be made more informative. Firstly, this implies a departure from the labels provided by commonly used cut-offs when reporting Bayes factors. Instead, we encourage researchers to report the value of the Bayes factors, or to convert these values into nominal support for the hypotheses. Secondly, researchers can provide recommendations to design follow-up studies by examining the posterior distribution of the magnitude of the effect size. Lastly, we show how individual Bayes factors can be evaluated in the context of large-scale meta-analyses. © 2019 British Psychological Society

Keywords
deception; effect size; follow up; human; meta analysis; note; sample size
National Category
Applied Psychology
Research subject
SOCIAL SCIENCE, Psychology
Identifiers
urn:nbn:se:hv:diva-14915 (URN)10.1111/lcrp.12162 (DOI)2-s2.0-85076291391 (Scopus ID)
Available from: 2020-01-29 Created: 2020-01-29 Last updated: 2020-01-29Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-5285-5321

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