- Title
- The Limits of Marginality
- Creator
- Heathcote, Andrew; Matzke, Dora
- Relation
- Computational Brain and Behavior Vol. 6, Issue 1, p. 28-34
- Publisher Link
- http://dx.doi.org/10.1007/s42113-021-00120-3
- Publisher
- Springer
- Resource Type
- journal article
- Date
- 2023
- Description
- The “marginality principle” for linear regression models states that when a higher order term is included, its constituent terms must also be included. The target article relies on this principle for the fixed-effects part of linear mixed models of ANOVA designs and considers the implication that if extended to combined fixed-and-random-effects models, model selection tests specific to some fixed-effects ANOVA terms are not possible. We review the basis for this principle for fixed-effects models and delineate its limits. We then consider its extension to combined fixed-and-random-effects models. We conclude that we have been unable to find in the literature, including the target article, and have ourselves been unable to construct any satisfactory argument against the use of incomplete ANOVA models. The only basis we could find requires one to assume that it is not possible to test point-null hypotheses, something we disagree with, and which we believe is incompatible with the Bayesian model-selection methods that are the basis of the target article.
- Subject
- linear mixed models; response surface models; ANOVA models; literature
- Identifier
- http://hdl.handle.net/1959.13/1478300
- Identifier
- uon:50151
- Identifier
- ISSN:2522-087X
- Rights
- x
- Language
- eng
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