Bayes Factors for Mixed Models: a Discussion

Author:

van Doorn JohnnyORCID,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,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,Bockting Florence,Chandramouli Suyog,Dunn John C.,Gronau Quentin F.,Linde Maximilian,McMullin Sara D.,Navarro Danielle,Schnuerch Martin,Yadav Himanshu,Aust Frederik

Abstract

Abstractvan 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.

Funder

Nederlandse Organisatie voor Wetenschappelijk Onderzoek

H2020 European Research Council

National Science Foundation

Fundação para a Ciência e a Tecnologia

Deutsche Forschungsgemeinschaft

Publisher

Springer Science and Business Media LLC

Subject

Developmental and Educational Psychology,Neuropsychology and Physiological Psychology

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