Bayes Factors for Mixed Models: a Discussion

Johnny van Doorn; Julia M. Haaf; Angelika M. Stefan; Eric-Jan Wagenmakers; Gregory Edward Cox; Clintin P. Davis-Stober; Andrew Heathcote; Daniel W. Heck; Michael Kalish; David Kellen; Dora Matzke; Richard D. Morey; Bruno Nicenboim; Don van Ravenzwaaij; Jeffrey N. Rouder; Daniel J. Schad; Richard M. Shiffrin; Henrik Singmann; Shravan Vasishth; João Veríssimo; Florence Bockting; Suyog Chandramouli; John C. Dunn; Quentin F. Gronau; Maximilian Linde; Sara D. McMullin; Danielle Navarro; Martin Schnuerch; Himanshu Yadav; Frederik Aust

doi:10.1007/s42113-022-00160-3

Bayes Factors for Mixed Models: a Discussion

Johnny van Doorn, Julia M. Haaf, Angelika M. Stefan, Eric-Jan Wagenmakers, Gregory Edward Cox, Clintin P. Davis-Stober, Andrew Heathcote, Daniel W. Heck, Michael Kalish, David Kellen, Dora Matzke, Richard D. Morey, Bruno Nicenboim, Don van Ravenzwaaij, Jeffrey N. Rouder, Daniel J. Schad, Richard M. Shiffrin, Henrik Singmann, Shravan Vasishth, João VeríssimoFlorence Bockting, Suyog Chandramouli, John C. Dunn, Quentin F. Gronau, Maximilian Linde, Sara D. McMullin, Danielle Navarro, Martin Schnuerch, Himanshu Yadav, Frederik Aust

Cognitive Science and AI

Research output: Contribution to journal › Article › Scientific › peer-review

2 Citations (Scopus)

Abstract

van Doorn et al. (2021) outlined various questions that arise when conducting Bayesian model comparison for mixed effects models. Seven response articles offered their own perspective on the preferred setup for mixed model comparison, on the most appropriate specification of prior distributions, and on the desirability of default recommendations. This article presents a round-table discussion that aims to clarify outstanding issues, explore common ground, and outline practical considerations for any researcher wishing to conduct a Bayesian mixed effects model comparison.

Original language	English
Pages (from-to)	140-158
Number of pages	19
Journal	Computational Brain & Behavior
Volume	6
DOIs	https://doi.org/10.1007/s42113-022-00160-3
Publication status	Published - Mar 2023

Keywords

Bayes factors
Mixed effects
Mixed models
Random effects

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10.1007/s42113-022-00160-3

Cite this

Doorn, J. V., Haaf, J. M., Stefan, A. M., Wagenmakers, E.-J., Cox, G. E., Davis-Stober, C. P., Heathcote, A., Heck, D. W., Kalish, M., Kellen, D., Matzke, D., Morey, R. D., Nicenboim, B., Ravenzwaaij, D. V., Rouder, J. N., Schad, D. J., Shiffrin, R. M., Singmann, H., Vasishth, S., ... Aust, F. (2023). Bayes Factors for Mixed Models: a Discussion. Computational Brain & Behavior, 6, 140-158. https://doi.org/10.1007/s42113-022-00160-3

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title = "Bayes Factors for Mixed Models: a Discussion",

abstract = "van Doorn et al. (2021) outlined various questions that arise when conducting Bayesian model comparison for mixed effects models. Seven response articles offered their own perspective on the preferred setup for mixed model comparison, on the most appropriate specification of prior distributions, and on the desirability of default recommendations. This article presents a round-table discussion that aims to clarify outstanding issues, explore common ground, and outline practical considerations for any researcher wishing to conduct a Bayesian mixed effects model comparison.",

keywords = "Bayes factors, Mixed effects, Mixed models, Random effects",

author = "Doorn, {Johnny van} and Haaf, {Julia M.} and Stefan, {Angelika M.} and Eric-Jan Wagenmakers and Cox, {Gregory Edward} and Davis-Stober, {Clintin P.} and Andrew Heathcote and Heck, {Daniel W.} and Michael Kalish and David Kellen and Dora Matzke and Morey, {Richard D.} and Bruno Nicenboim and Ravenzwaaij, {Don van} and Rouder, {Jeffrey N.} and Schad, {Daniel J.} and Shiffrin, {Richard M.} and Henrik Singmann and Shravan Vasishth and Jo{\~a}o Ver{\'i}ssimo and Florence Bockting and Suyog Chandramouli and Dunn, {John C.} and Gronau, {Quentin F.} and Maximilian Linde and McMullin, {Sara D.} and Danielle Navarro and Martin Schnuerch and Himanshu Yadav and Frederik Aust",

note = "Publisher Copyright: {\textcopyright} 2023, The Author(s).",

year = "2023",

month = mar,

doi = "10.1007/s42113-022-00160-3",

language = "English",

volume = "6",

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Doorn, JV, Haaf, JM, Stefan, AM, Wagenmakers, E-J, Cox, GE, Davis-Stober, CP, Heathcote, A, Heck, DW, Kalish, M, Kellen, D, Matzke, D, Morey, RD, Nicenboim, B, Ravenzwaaij, DV, Rouder, JN, Schad, DJ, Shiffrin, RM, Singmann, H, Vasishth, S, Veríssimo, J, Bockting, F, Chandramouli, S, Dunn, JC, Gronau, QF, Linde, M, McMullin, SD, Navarro, D, Schnuerch, M, Yadav, H & Aust, F 2023, 'Bayes Factors for Mixed Models: a Discussion', Computational Brain & Behavior, vol. 6, pp. 140-158. https://doi.org/10.1007/s42113-022-00160-3

TY - JOUR

T1 - Bayes Factors for Mixed Models: a Discussion

AU - Doorn, Johnny van

AU - Haaf, Julia M.

AU - Stefan, Angelika M.

AU - Wagenmakers, Eric-Jan

AU - Cox, Gregory Edward

AU - Davis-Stober, Clintin P.

AU - Heathcote, Andrew

AU - Heck, Daniel W.

AU - Kalish, Michael

AU - Kellen, David

AU - Matzke, Dora

AU - Morey, Richard D.

AU - Nicenboim, Bruno

AU - Ravenzwaaij, Don van

AU - Rouder, Jeffrey N.

AU - Schad, Daniel J.

AU - Shiffrin, Richard M.

AU - Singmann, Henrik

AU - Vasishth, Shravan

AU - Veríssimo, João

AU - Bockting, Florence

AU - Chandramouli, Suyog

AU - Dunn, John C.

AU - Gronau, Quentin F.

AU - Linde, Maximilian

AU - McMullin, Sara D.

AU - Navarro, Danielle

AU - Schnuerch, Martin

AU - Yadav, Himanshu

AU - Aust, Frederik

PY - 2023/3

Y1 - 2023/3

N2 - van Doorn et al. (2021) outlined various questions that arise when conducting Bayesian model comparison for mixed effects models. Seven response articles offered their own perspective on the preferred setup for mixed model comparison, on the most appropriate specification of prior distributions, and on the desirability of default recommendations. This article presents a round-table discussion that aims to clarify outstanding issues, explore common ground, and outline practical considerations for any researcher wishing to conduct a Bayesian mixed effects model comparison.

AB - van Doorn et al. (2021) outlined various questions that arise when conducting Bayesian model comparison for mixed effects models. Seven response articles offered their own perspective on the preferred setup for mixed model comparison, on the most appropriate specification of prior distributions, and on the desirability of default recommendations. This article presents a round-table discussion that aims to clarify outstanding issues, explore common ground, and outline practical considerations for any researcher wishing to conduct a Bayesian mixed effects model comparison.

KW - Bayes factors

KW - Mixed effects

KW - Mixed models

KW - Random effects

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U2 - 10.1007/s42113-022-00160-3

DO - 10.1007/s42113-022-00160-3

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VL - 6

SP - 140

EP - 158

JO - Computational Brain & Behavior

JF - Computational Brain & Behavior

ER -

Bayes Factors for Mixed Models: a Discussion

Abstract

Keywords

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