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Exploratory structural equation modeling : an integration of the best features of exploratory and confirmatory factor analysis

  • Herbert W. Marsh
  • , Alexandre J. S. Morin
  • , Philip D. Parker
  • , Gurvinder Kaur

    Research output: Contribution to journalArticlepeer-review

    1569 Citations (Scopus)

    Abstract

    Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), path analysis, and structural equation modeling (SEM) have long histories in clinical research. Although CFA has largely erseded EFA, CFAs of multidimensional constructs typically fail to meet standards of good measurement: goodness of fit, measurement invariance, lack of differential item functioning, and well-differentiated factors in port of discriminant validity. Part of the problem is undue reliance on overly restrictive CFAs in which each item loads on only one factor. Exploratory SEM (ESEM), an overarching integration of the best aspects of CFA/SEM and traditional EFA, provides confirmatory tests of a priori factor structures, relations between latent factors and multigroup/multioccasion tests of full (mean structure) measurement invariance. It incorporates all combinations of CFA factors, ESEM factors, covariates, grouping/multiple-indicator multiple-cause (MIMIC) variables, latent growth, and complex structures that typically have required CFA/SEM. ESEM has broad applicability to clinical studies that are not appropriately addressed either by traditional EFA or CFA/SEM.
    Original languageEnglish
    Pages (from-to)85-110
    Number of pages26
    JournalAnnual Review of Clinical Psychology
    Volume10
    DOIs
    Publication statusPublished - 2014

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