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Model comparison in ANOVA

Rouder J, Engelhardt C, McCabe S & Morey R (2016) Model comparison in ANOVA, Psychonomic Bulletin and Review, 23 (6), pp. 1779-1786.

Analysis of variance (ANOVA), the workhorse analysis of experimental designs, consists of F-tests of main effects and interactions. Yet, testing, including traditional ANOVA, has been recently critiqued on a number of theoretical and practical grounds. In light of these critiques, model comparison and model selection serve as an attractive alternative. Model comparison differs from testing in that one can support a null or nested model vis-a-vis a more general alternative by penalizing more flexible models. We argue this ability to support more simple models allows for more nuanced theoretical conclusions than provided by traditional ANOVA F-tests. We provide a model comparison strategy and show how ANOVA models may be reparameterized to better address substantive questions in data analysis.

ANOVA; Statistical models; Interactions; Model comparison; Order-restricted inference

AuthorsRouder Jeffrey, Engelhardt Christopher, McCabe Simon, Morey Richard
Publication date12/2016
Publication date online11/04/2016
Date accepted by journal03/03/2016
ISSN 1069-9384

Psychonomic Bulletin and Review: Volume 23, Issue 6

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