Bayes Factors for Mixed Models: Perspective on Responses.

Bayes factors Mixed effects Mixed models Random effects

Journal

Computational brain & behavior
ISSN: 2522-087X
Titre abrégé: Comput Brain Behav
Pays: Switzerland
ID NLM: 101728813

Informations de publication

Date de publication:
2023
Historique:
accepted: 09 10 2022
entrez: 7 3 2023
pubmed: 8 3 2023
medline: 8 3 2023
Statut: ppublish

Résumé

In van Doorn et al. (2021), we outlined a series of open questions concerning Bayes factors for mixed effects model comparison, with an emphasis on the impact of aggregation, the effect of measurement error, the choice of prior distributions, and the detection of interactions. Seven expert commentaries (partially) addressed these initial questions. Surprisingly perhaps, the experts disagreed (often strongly) on what is best practice-a testament to the intricacy of conducting a mixed effect model comparison. Here, we provide our perspective on these comments and highlight topics that warrant further discussion. In general, we agree with many of the commentaries that in order to take full advantage of Bayesian mixed model comparison, it is important to be aware of the specific assumptions that underlie the to-be-compared models.

Identifiants

pubmed: 36879767
doi: 10.1007/s42113-022-00158-x
pii: 158
pmc: PMC9981503
doi:

Types de publication

Journal Article

Langues

eng

Pagination

127-139

Informations de copyright

© The Author(s) 2023.

Déclaration de conflit d'intérêts

Competing interestsThe authors declare no competing interests.

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Auteurs

Johnny van Doorn (J)

Department of Psychological Methods, University of Amsterdam, Valckeniersstraat 59, 1018 XA Amsterdam, the Netherlands.

Frederik Aust (F)

Department of Psychological Methods, University of Amsterdam, Valckeniersstraat 59, 1018 XA Amsterdam, the Netherlands.

Julia M Haaf (JM)

Department of Psychological Methods, University of Amsterdam, Valckeniersstraat 59, 1018 XA Amsterdam, the Netherlands.

Angelika M Stefan (AM)

Department of Psychological Methods, University of Amsterdam, Valckeniersstraat 59, 1018 XA Amsterdam, the Netherlands.

Eric-Jan Wagenmakers (EJ)

Department of Psychological Methods, University of Amsterdam, Valckeniersstraat 59, 1018 XA Amsterdam, the Netherlands.

Classifications MeSH