Using GAMMs to model trial-by-trial fluctuations in experimental data: more risks but hardly any benefit

Thul, R., Conklin, K. and Barr, D. J. (2021) Using GAMMs to model trial-by-trial fluctuations in experimental data: more risks but hardly any benefit. Journal of Memory and Language, 120, 104247. (doi: 10.1016/j.jml.2021.104247)

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Data from each subject in a repeated-measures experiment form a time series, which may include trial-by-trial fluctuations arising from human factors such as practice or fatigue. Concerns about the statistical implications of such effects have increased the popularity of Generalized Additive Mixed Models (GAMMs), a powerful technique for modeling wiggly patterns. We question these statistical concerns and investigate the costs and benefits of using GAMMs relative to linear mixed-effects models (LMEMs). In two sets of Monte Carlo simulations, LMEMs that ignored time-varying effects were no more prone to false positives than GAMMs. Although GAMMs generally boosted power for within-subject effects, they reduced power for between-subject effects, sometimes to a severe degree. Our results signal the importance of proper subject-level randomization as the main defense against statistical artifacts due to by-trial fluctuations.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Barr, Dr Dale
Authors: Thul, R., Conklin, K., and Barr, D. J.
College/School:College of Medical Veterinary and Life Sciences > School of Psychology & Neuroscience
Journal Name:Journal of Memory and Language
ISSN (Online):1096-0821
Published Online:20 April 2021
Copyright Holders:Copyright © 2021 Elsevier Inc.
First Published:First published in Journal of Memory and Language 120: 104247
Publisher Policy:Reproduced in accordance with the publisher copyright policy
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