Comparing Methods for Multilevel Moderated Mediation: A Decomposed-first Strategy

  • Soyoung Kim
  • , Sehee Hong*
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)661-677
Number of pages17
JournalStructural Equation Modeling
Volume27
Issue number5
DOIs
Publication statusPublished - 2020 Sept 2

Bibliographical note

Publisher Copyright:
© 2019 Taylor & Francis Group, LLC.

Keywords

  • Decomposed-first strategy
  • latent moderated structural equations
  • multilevel moderated mediation
  • orthogonal partitioning with centering within cluster
  • random coefficient prediction

ASJC Scopus subject areas

  • General Decision Sciences
  • Modelling and Simulation
  • Sociology and Political Science
  • General Economics,Econometrics and Finance

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