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Media type:
E-Article
Title:
Sample Size Determination for Bayesian Hierarchical Models Commonly Used in Psycholinguistics
Contributor:
Vasishth, Shravan;
Yadav, Himanshu;
Schad, Daniel J.;
Nicenboim, Bruno
Published:
Springer Science and Business Media LLC, 2023
Published in:
Computational Brain & Behavior, 6 (2023) 1, Seite 102-126
Language:
English
DOI:
10.1007/s42113-021-00125-y
ISSN:
2522-0861;
2522-087X
Origination:
Footnote:
Description:
AbstractWe discuss an important issue that is not directly related to the main theses of the van Doorn et al. (Computational Brain and Behavior, 2021) paper, but which frequently comes up when using Bayesian linear mixed models: how to determine sample size in advance of running a study when planning a Bayes factor analysis. We adapt a simulation-based method proposed by Wang and Gelfand (Statistical Science193–208, 2002) for a Bayes factor-based design analysis, and demonstrate how relatively complex hierarchical models can be used to determine approximate sample sizes for planning experiments.