Abstract
For structural equation models, a huge variety of fit indices has been developed. These indices, however, can point to conflicting conclusions about the extent to which a model actually matches the observed data. The present article provides some guidelines that should help applied researchers to evaluate the adequacy of a given structural equation model. First, as goodness-of-fit measures depend on the method used for parameter estimation, maximum likelihood (ML) and weighted least squares (WLS) methods are introduced in the context of structural equation modeling. Then, the most common goodness-of-fit indices are discussed and some recommendations for practitioners given. Finally, we generated an artificial data set according to a "true" model and analyzed two misspecified and two correctly specified models as examples of poor model fit, adequate fit, and good fit.
Keywords
Goodness of fitStructural equation modelingContext (archaeology)StatisticsMathematicsEconometrics
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Publication Info
- Year
- 2003
- Type
- article
- Volume
- 8
- Pages
- 23-74
- Citations
- 8898
- Access
- Closed
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Cite This
Karin Schermelleh-Engel,
Helfried Moosbrugger,
H. G. Müller
(2003).
Evaluating the Fit of Structural Equation Models: Tests of Significance and Descriptive Goodness-of-Fit Measures.
Psychology Archives
, 8
, 23-74.
https://doi.org/10.23668/psycharchives.12784
Identifiers
- DOI
- 10.23668/psycharchives.12784