On Specifying the Null Model for Incremental Fit Indices in Structural Equation Modeling

In structural equation modeling, incremental fit indices are based on the comparison of the fit of a substantive model to that of a null model. The standard null model yields unconstrained estimates of the variance (and mean, if included) of each manifest variable. For many models, however, the stan...

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Bibliographic Details
Published in:Psychological methods 2003-03, Vol.8 (1), p.16-37
Main Authors: Widaman, Keith F, Thompson, Jane S
Format: Article
Language:English
Subjects:
Biological and medical sciences
Data Interpretation, Statistical
Fundamental and applied biological sciences. Psychology
Goodness of Fit
Human
Humans
Mathematical Computing
Models, Statistical
Null Hypothesis Testing
Psychological Tests - statistics & numerical data
Psychology. Psychoanalysis. Psychiatry
Psychology. Psychophysiology
Psychometrics - statistics & numerical data
Psychometrics. Statistics. Methodology
Reproducibility of Results
Software
Statistics. Mathematics
Structural Equation Modeling
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Description
Summary:In structural equation modeling, incremental fit indices are based on the comparison of the fit of a substantive model to that of a null model. The standard null model yields unconstrained estimates of the variance (and mean, if included) of each manifest variable. For many models, however, the standard null model is an improper comparison model. In these cases, incremental fit index values reported automatically by structural modeling software have no interpretation and should be disregarded. The authors explain how to formulate an acceptable, modified null model, predict changes in fit index values accompanying its use, provide examples illustrating effects on fit index values when using such a model, and discuss implications for theory and practice of structural equation modeling.
ISSN:1082-989X
1939-1463
DOI:10.1037/1082-989X.8.1.16