- Title
- Bayes Factors for Mixed Models: a Discussion
- Creator
- van Doorn, Johnny; Haaf, Julia M.; Matzke, Dora; Morey, Richard D.; Nicenboim, Bruno; van Ravenzwaaij, Don; Rouder, Jeffrey N.; Schad, Daniel J.; Shiffrin, Richard M.; Singmann, Henrik; Vasishth, Shravan; Veríssimo, João; Stefan, Angelika M.; Bockting, Florence; Chandramouli, S; Dunn, JC; Gronau, Quentin F.; Linde, M; McMullin, SD; Navarro, D; Schnuerch, M; Yadav, H; Aust, F; Wagenmakers, Eric-Jan; Cox, Gregory Edward; Davis-Stober, Clintin P.; Heathcote, Andrew; Heck, Daniel W.; Kalish, Michael; Kellen, David
- Relation
- Computational Brain and Behavior Vol. 6, Issue 16 February 2023, p. 140-158
- Publisher Link
- http://dx.doi.org/10.1007/s42113-022-00160-3
- Publisher
- Springer
- Resource Type
- journal article
- Date
- 2023
- Description
- 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.
- Subject
- Bayes factors; mixed effects; mixed models; random effects
- Identifier
- http://hdl.handle.net/1959.13/1485254
- Identifier
- uon:51524
- Identifier
- ISSN:2522-087X
- Rights
- x
- Language
- eng
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