Bayes Factors for Mixed Models: a Discussion
Doorn,Johnny van Haaf,Julia M. Stefan,Angelika M. Wagenmakers,Eric-Jan Cox,Gregory Edward Davis-Stober,Clintin P. Heathcote,Andrew Heck,Daniel W. Kalish,Michael Kellen,David
Doorn,Johnny van
Haaf,Julia M.
Stefan,Angelika M.
Wagenmakers,Eric-Jan
Cox,Gregory Edward
Davis-Stober,Clintin P.
Heathcote,Andrew
Heck,Daniel W.
Kalish,Michael
Kellen,David
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.
Description
Publisher Copyright: © 2023, The Author(s).
Date
2023-03
Journal Title
Journal ISSN
Volume Title
Publisher
Research Projects
Organizational Units
Journal Issue
Keywords
Bayes factors, Mixed effects, Mixed models, Random effects
Citation
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, Veríssimo, J, Bockting, F, Chandramouli, S, Dunn, J C, Gronau, Q F, Linde, M, McMullin, S D, 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