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Model comparison in ANOVA

Rouder, Jeffrey N., Engelhardt, Christopher R., McCabe, Simon and Morey, Richard D. 2016. Model comparison in ANOVA. Psychonomic Bulletin & Review 23 (6) , pp. 1779-1786. 10.3758/s13423-016-1026-5

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Abstract

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.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Psychology
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Uncontrolled Keywords: ANOVA; Statistical models; Interactions; Model comparison; Order-restricted inference
Publisher: Springer
ISSN: 1069-9384
Date of First Compliant Deposit: 21 July 2017
Date of Acceptance: 27 August 2016
Last Modified: 19 Oct 2019 13:48
URI: http://orca.cf.ac.uk/id/eprint/102830

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