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Recovering Crossed Random Effects in Mixed-Effects Models Using Model Averaging

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dc.contributor.authorOlmos, Ricardo
dc.contributor.authorMartínez Huertas, José Ángel
dc.date.accessioned2024-05-20T11:49:24Z
dc.date.available2024-05-20T11:49:24Z
dc.date.issued2022-12-22
dc.description.abstractRandom effects contain crucial information to understand the variability of the processes under study in mixed-effects models with crossed random effects (MEMs-CR). Given that model selection makes all-or-nothing decisions regarding to the inclusion of model parameters, we evaluated if model averaging could deal with model uncertainty to recover random effects of MEMs-CR. Specifically, we analyzed the bias and the root mean squared error (RMSE) of the estimations of the variances of random effects using model averaging with Akaike weights and Bayesian model averaging with BIC posterior probabilities, comparing them with two alternative analytical strategies as benchmarks: AIC and BIC model selection, and fitting a full random structure. A simulation study was conducted manipulating sample sizes for subjects and items, and the variance of random effects. Results showed that model averaging, especially Akaike weights, can adequately recover random variances, given a minimum sample size in the modeled clusters. Thus, we endorse using model averaging to deal with model uncertainty in MEMs-CR. An empirical illustration is provided to ease the usability of model averaging.en
dc.description.versionversión publicada
dc.identifier.doihttps://doi.org/10.5964/meth.9597
dc.identifier.issn1614-1881; eISSN 1614-2241
dc.identifier.urihttps://hdl.handle.net/20.500.14468/12598
dc.journal.issue4
dc.journal.titleMethodology
dc.journal.volume18
dc.language.isoen
dc.publisherPsychOpen
dc.relation.centerFacultad de Psicología
dc.relation.departmentMetodología de las Ciencias del Comportamiento
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/4.0
dc.subject.keywordsmixed-effects models
dc.subject.keywordscrossed random effects
dc.subject.keywordsrandom effects
dc.subject.keywordsmodel averaging
dc.subject.keywordsAkaike weights
dc.subject.keywordsBayesian model averaging
dc.subject.keywordsAIC
dc.subject.keywordsBIC
dc.titleRecovering Crossed Random Effects in Mixed-Effects Models Using Model Averaginges
dc.typejournal articleen
dc.typeartículoes
dspace.entity.typePublication
relation.isAuthorOfPublicationca510876-0be8-438a-a565-ac5f8953fb78
relation.isAuthorOfPublication.latestForDiscoveryca510876-0be8-438a-a565-ac5f8953fb78
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