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Effects of sample size, estimation methods, and model specification on structural equation modeling fit indexes

Fan, Xitao, Thompson, Bruce, Wang, Lin·1999·Structural Equation Modeling: A Multidisciplinary Journal

Abstract

A Monte Carlo simulation study was conducted to investigate the effects on structural equation modeling (SEM) fit indexes of sample size, estimation method, and model specification. Based on a balanced experimental design, samples were generated from a prespecified population covariance matrix and fitted to structural equation models with different degrees of model misspecification. Ten SEM fit indexes were studied. Two primary conclusions were suggested: (a) some fit indexes appear to be noncomparable in terms of the information they provide about model fit for misspecified models and (b) estimation method strongly influenced almost all the fit indexes examined, especially for misspecified models. These 2 issues do not seem to have drawn enough attention from SEM practitioners. Future research should study not only different models vis‐à‐vis model complexity, but a wider range of model specification conditions, including correctly specified models and models specified incorrectly to varying degrees.

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Metadata

Authors
Fan, X., Thompson, B., & Wang, L.
Venue
Structural Equation Modeling: A Multidisciplinary Journal
Published
1999-01
Volume
6
Issue
1
Pages
56-83
ISSN
  • 1070-5511 (ISSN-L)
  • 1532-8007
OpenAlex
W2072787586
Cited by
1,663
References
3
FWCI
21.70
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Effects of sample size, estimation methods, and model specification on structural equation modeling fit indexes. https://app.cochat.ai/papers/10.1080/10705519909540119
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Fan, X., Thompson, B., & Wang, L. (1999). Effects of sample size, estimation methods, and model specification on structural equation modeling fit indexes. Structural Equation Modeling: A Multidisciplinary Journal. https://doi.org/10.1080/10705519909540119

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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