Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/35872
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dc.contributor.authorAriyo, Oludare-
dc.contributor.authorLESAFFRE, Emmanuel-
dc.contributor.authorVERBEKE, Geert-
dc.contributor.authorHuisman, Martijn-
dc.contributor.authorHeymans, Martijn-
dc.contributor.authorTwisk, Jos-
dc.date.accessioned2021-11-24T16:34:10Z-
dc.date.available2021-11-24T16:34:10Z-
dc.date.issued2022-
dc.date.submitted2021-11-19T09:16:53Z-
dc.identifier.citationStatistica Neerlandica 2021, 76 (2) , p. 219-235-
dc.identifier.issn0039-0402-
dc.identifier.urihttp://hdl.handle.net/1942/35872-
dc.description.abstractMediation analysis is often used to explore the complex relationship between two variables through a third mediating variable. This paper aims to illustrate the performance of the deviance information criterion, the pseudo-Bayes factor, and the Watanabe-Akaike information criterion in selecting the appropriate multilevel mediation model. Our focus will be on comparing the conditional criteria (given random effects) versus the marginal criteria (averaged over random effects) in this respect. Most of the previous work on the multilevel mediation models fails to report the poor behavior of the conditional criteria. We demonstrate here the superiority of the marginal version of the selection criteria over their conditional counterpart in the mediated longitudinal settings through simulation studies and via an application to data from the Longitudinal Aging Study of the Amsterdam study. In addition, we demonstrate the usefulness of our self-written R function for multilevel mediation models.-
dc.description.sponsorshipThe research of the first author was funded by Tertiary Education Trust Fund (TETFund) - AS&D grant of the Federal University of Agriculture, Abeokuta, Nigeria.-
dc.language.isoen-
dc.publisherWILEY-
dc.rights2021 Netherlands Society for Statistics and Operations Research. Free access-
dc.subject.otherdeviance information criterion-
dc.subject.othermarginalized likelihood-
dc.subject.othermultilevel mediation models-
dc.subject.otherpseudo Bayes factor-
dc.subject.otherWatanabe-Akaike information criterion-
dc.titleBayesian model selection for multilevel mediation models-
dc.typeJournal Contribution-
dc.identifier.epage235-
dc.identifier.issue2-
dc.identifier.spage219-
dc.identifier.volume76-
local.format.pages17-
local.bibliographicCitation.jcatA1-
dc.description.notesAriyo, O (corresponding author), Katholieke Univ Leuven, Interuniv Inst Biostat & Stat Bioinformat I BioSt, Leuven, Belgium.-
dc.description.notesariyoso@funaab.edu.ng-
local.publisher.place111 RIVER ST, HOBOKEN 07030-5774, NJ USA-
local.type.refereedRefereed-
local.type.specifiedArticle-
dc.identifier.doi10.1111/stan.12256-
dc.identifier.isi000715136600001-
dc.identifier.eissn1467-9574-
local.provider.typewosris-
local.uhasselt.uhpubyes-
local.description.affiliation[Ariyo, Oludare; Lesaffre, Emmanuel; Verbeke, Geert] Katholieke Univ Leuven, Interuniv Inst Biostat & Stat Bioinformat I BioSt, Leuven, Belgium.-
local.description.affiliation[Ariyo, Oludare] Fed Univ Agr, Dept Stat, Abeokuta, Nigeria.-
local.description.affiliation[Huisman, Martijn; Heymans, Martijn; Twisk, Jos] Amsterdam UMC, Amsterdam Publ Hlth Res Inst, Dept Epidemiol & Data Sci, Amsterdam, Netherlands.-
local.description.affiliation[Heymans, Martijn] Vrije Univ Amsterdam, Dept Sociol, Amsterdam, Netherlands.-
local.uhasselt.internationalyes-
item.fullcitationAriyo, Oludare; LESAFFRE, Emmanuel; VERBEKE, Geert; Huisman, Martijn; Heymans, Martijn & Twisk, Jos (2022) Bayesian model selection for multilevel mediation models. In: Statistica Neerlandica 2021, 76 (2) , p. 219-235.-
item.fulltextWith Fulltext-
item.contributorAriyo, Oludare-
item.contributorLESAFFRE, Emmanuel-
item.contributorVERBEKE, Geert-
item.contributorHuisman, Martijn-
item.contributorHeymans, Martijn-
item.contributorTwisk, Jos-
item.accessRightsOpen Access-
crisitem.journal.issn0039-0402-
crisitem.journal.eissn1467-9574-
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