Mediation from multilevel to structural equation modeling

David Mackinnon, Matthew J. Valente

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


Background/Aims: The purpose of this article is to outline multilevel structural equation modeling (MSEM) for mediation analysis of longitudinal data. The introduction of mediating variables can improve experimental and nonexperimental studies of child growth in several ways as discussed throughout this article. Single-mediator individual-level and multilevel mediation models illustrate several current issues in the estimation of mediation with longitudinal data. The strengths of incorporating structural equation modeling (SEM) with multilevel mediation modeling are described.

Summary and Key Messages: Longitudinal mediation models are pervasive in many areas of research including child growth. Longitudinal mediation models are ideally modeled as repeated measurements clustered within individuals. Further, the combination of MSEM and SEM provides an ideal approach for several reasons, including the ability to assess effects at different levels of analysis, incorporation of measurement error and possible random effects that vary across individuals.

Original languageEnglish (US)
Pages (from-to)198-204
Number of pages7
JournalAnnals of Nutrition and Metabolism
StatePublished - Nov 27 2014


  • Mediation
  • Multilevel mediation
  • Multilevel structural equation modeling

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Nutrition and Dietetics


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