Comparing Methods for Multilevel Moderated Mediation: A Decomposed-first Strategy
DC Field | Value | Language |
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dc.contributor.author | Kim, Soyoung | - |
dc.contributor.author | Hong, Sehee | - |
dc.date.accessioned | 2021-08-30T15:04:21Z | - |
dc.date.available | 2021-08-30T15:04:21Z | - |
dc.date.created | 2021-06-19 | - |
dc.date.issued | 2020-09-02 | - |
dc.identifier.issn | 1070-5511 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/53195 | - |
dc.description.abstract | The purpose of this study is to propose a decomposed-first strategy for multilevel moderated mediation and to compare the performance of three moderated mediation approaches in multilevel structural equation modeling. The following approaches were compared in simulations to test coefficients that were decomposed level by level: orthogonal partitioning with centering within cluster, random coefficient prediction, and latent moderated structural equations. The manipulated conditions for the simulation analysis were the analysis method, the number of groups, group size, and intraclass correlation. The results showed that, for samples consisting of a large number of groups, a large average group size and a large intraclass correlation, LMS had the strongest performance. This study is meaningful in that it produces interpretable coefficients by applying a decomposed-first strategy in multilevel moderated mediation and extends a basic moderated mediation model to include more specific research questions in multilevel structural equation modeling. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD | - |
dc.subject | STRUCTURAL EQUATION MODELS | - |
dc.subject | MAXIMUM-LIKELIHOOD-ESTIMATION | - |
dc.subject | SAMPLE-SIZE | - |
dc.subject | SCHOOL | - |
dc.subject | LEVEL | - |
dc.subject | VARIABLES | - |
dc.subject | FRAMEWORK | - |
dc.subject | ISSUES | - |
dc.subject | POWER | - |
dc.title | Comparing Methods for Multilevel Moderated Mediation: A Decomposed-first Strategy | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Soyoung | - |
dc.contributor.affiliatedAuthor | Hong, Sehee | - |
dc.identifier.doi | 10.1080/10705511.2019.1683015 | - |
dc.identifier.scopusid | 2-s2.0-85075064067 | - |
dc.identifier.wosid | 000495197400001 | - |
dc.identifier.bibliographicCitation | STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL, v.27, no.5, pp.661 - 677 | - |
dc.relation.isPartOf | STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL | - |
dc.citation.title | STRUCTURAL EQUATION MODELING-A MULTIDISCIPLINARY JOURNAL | - |
dc.citation.volume | 27 | - |
dc.citation.number | 5 | - |
dc.citation.startPage | 661 | - |
dc.citation.endPage | 677 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | ssci | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalResearchArea | Mathematical Methods In Social Sciences | - |
dc.relation.journalWebOfScienceCategory | Mathematics, Interdisciplinary Applications | - |
dc.relation.journalWebOfScienceCategory | Social Sciences, Mathematical Methods | - |
dc.subject.keywordPlus | STRUCTURAL EQUATION MODELS | - |
dc.subject.keywordPlus | MAXIMUM-LIKELIHOOD-ESTIMATION | - |
dc.subject.keywordPlus | SAMPLE-SIZE | - |
dc.subject.keywordPlus | SCHOOL | - |
dc.subject.keywordPlus | LEVEL | - |
dc.subject.keywordPlus | VARIABLES | - |
dc.subject.keywordPlus | FRAMEWORK | - |
dc.subject.keywordPlus | ISSUES | - |
dc.subject.keywordPlus | POWER | - |
dc.subject.keywordAuthor | Multilevel moderated mediation | - |
dc.subject.keywordAuthor | decomposed-first strategy | - |
dc.subject.keywordAuthor | latent moderated structural equations | - |
dc.subject.keywordAuthor | random coefficient prediction | - |
dc.subject.keywordAuthor | orthogonal partitioning with centering within cluster | - |
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