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Related Experiment Videos

Potential problems with "well fitting" models.

Andrew J Tomarken1, Niels G Waller

  • 1Department of Psychology, Vanderbilt University, Nashville, TN 37203, USA. andrew.j.tomarken@vanderbilt.edu

Journal of Abnormal Psychology
|December 17, 2003
PubMed
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Structural equation modeling (SEM) fit assessment is complex. Researchers must recognize potential ambiguities in SEM models, even those with good statistical fit, to avoid misinterpretations.

Area of Science:

  • Psychometrics
  • Statistical Modeling

Background:

  • Structural equation modeling (SEM) is widely used in psychological research.
  • Assessing the fit of SEM models is crucial for valid interpretation.
  • Current fit assessment practices may overlook significant model ambiguities.

Purpose of the Study:

  • To highlight the complexities and indeterminate nature of model fit assessment in SEM.
  • To identify and discuss common pitfalls that can lead to erroneous conclusions.
  • To provide guidance for researchers, particularly in psychopathology, conducting SEM analyses.

Main Methods:

  • Conceptual analysis of structural equation modeling fit assessment.
  • Identification and discussion of seven common problems in SEM fit assessment.
  • Illustrative examples provided for each identified problem.

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Main Results:

  • Models with good statistical fit can still exhibit significant problems.
  • Seven key issues can compromise the interpretation of SEM fit indices.
  • These issues include model equivalence, omitted variables, and partitioning failures.

Conclusions:

  • Researchers should exercise caution when interpreting SEM model fit.
  • Awareness of potential ambiguities is essential for robust SEM application.
  • Recommendations are offered to improve SEM analysis practices in psychopathology.