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Influence of Sample Size, Estimation Method, and Model Specification on Goodness-of-Fit Assessments in Structural Equation Models
The problem of assessing fit of structural equation models is reviewed, and two sampling studies are reported that examine the effects of sample size, estimation method, and model misspecification on fit indices. In the first study, the behavior of indices in a known-population confirmatory factor a...
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Published in: | Journal of applied psychology 1989-08, Vol.74 (4), p.625-635 |
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description | The problem of assessing fit of structural equation models is reviewed, and two sampling studies are reported that examine the effects of sample size, estimation method, and model misspecification on fit indices. In the first study, the behavior of indices in a known-population confirmatory factor analysis model is considered. In the second study, the same problem in an empirical data set is examined by looking at antecedents and consequences of work motivation. The findings across the two studies suggest that, (a) as might be expected, sample size is an important determinant in assessing model fit; (b) estimator-specific, as opposed to estimator-general, fit indices provide more accurate indications of model fit; and (c) the studied fit indices are differentially sensitive to model misspecification. Some recommendations for the use of structural equation model fit indices are given. |
doi_str_mv | 10.1037/0021-9010.74.4.625 |
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subjects | Biological and medical sciences Estimation Fundamental and applied biological sciences. Psychology Goodness of Fit Human Mathematical Modeling Psychology. Psychoanalysis. Psychiatry Psychology. Psychophysiology Psychometrics. Statistics. Methodology Statistical Sample Parameters Statistics. Mathematics |
title | Influence of Sample Size, Estimation Method, and Model Specification on Goodness-of-Fit Assessments in Structural Equation Models |
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