Journal ArticleDOI
Goodness-of-fit indexes in confirmatory factor analysis : The effect of sample size
TLDR
In this paper, the influence of sample size on different goodness-of-fit indices used in confirmatory factor analysis (CFA) was examined and the results are consistent with the observation that the amount of random, unexplained variance varies inversely with sample size.Abstract:
This investigation examined the influence of sample size on different goodness-of-fit indices used in confirmatory factor analysis (CFA). The first two data sets were derived from large normative samples of responses to a multidimensional self-concept instrument and to a multidimensional instrument used to assess students' evaluations of teaching effectiveness. In the third set, data were simulated and generated according to the model to be tested. In the fourth, data were simulated and generated according to a three-factor model that did not have a simple structure. Twelve fit indicators were used to assess goodness-offit in all CFAs. All analyses were conducted with the LISREL V package. One-way ANOVAs and a visual inspection of graphs were used to assess the sample size effect on each index for the four data sets. Despite the inconsistency of the findings with previous claims, the results are consistent with the observation that the amount of random, unexplained variance varies inversely with sample size. Appendices include a set of computed statements, an explanation and listing of the 12 goodness-of-fit indicators, a bibliography, a table of results, and figures showing sample size effect. (Author/LMO) *********************************************************************** Reproductions supplied by EDRS are the best that can be made from the original document. ***********************************************************************read more
Citations
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Journal ArticleDOI
Cutoff criteria for fit indexes in covariance structure analysis : Conventional criteria versus new alternatives
Li-tze Hu,Peter M. Bentler +1 more
TL;DR: In this article, the adequacy of the conventional cutoff criteria and several new alternatives for various fit indexes used to evaluate model fit in practice were examined, and the results suggest that, for the ML method, a cutoff value close to.95 for TLI, BL89, CFI, RNI, and G...
Journal ArticleDOI
Comparative fit indexes in structural models
TL;DR: A new coefficient is proposed to summarize the relative reduction in the noncentrality parameters of two nested models and two estimators of the coefficient yield new normed (CFI) and nonnormed (FI) fit indexes.
Journal ArticleDOI
Evaluating Goodness-of-Fit Indexes for Testing Measurement Invariance
TL;DR: In this paper, the authors examined the change in the goodness-of-fit index (GFI) when cross-group constraints are imposed on a measurement model and found that the change was independent of both model complexity and sample size.
Journal ArticleDOI
Fit indices in covariance structure modeling : Sensitivity to underparameterized model misspecification
Li-tze Hu,Peter M. Bentler +1 more
TL;DR: In this article, the sensitivity of maximum likelihood (ML), generalized least squares (GLS), and asymptotic distribution-free (ADF)-based fit indices to model misspecification, under conditions that varied sample size and distribution.
Journal ArticleDOI
Power analysis and determination of sample size for covariance structure modeling.
TL;DR: In this article, a framework for hypothesis testing and power analysis in the assessment of fit of covariance structure models is presented, where the value of confidence intervals for fit indices is emphasized.
References
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TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
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TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
Journal ArticleDOI
Significance tests and goodness of fit in the analysis of covariance structures
TL;DR: In this article, a general null model based on modified independence among variables is proposed to provide an additional reference point for the statistical and scientific evaluation of covariance structure models, and the importance of supplementing statistical evaluation with incremental fit indices associated with the comparison of hierarchical models.
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A reliability coefficient for maximum likelihood factor analysis
Ledyard R Tucker,Charles Lewis +1 more
TL;DR: In this paper, a reliability coefficient is proposed to indicate quality of representation of interrelations among attributes in a battery by a maximum likelihood factor analysis, which can indicate that an otherwise acceptable factor model does not exactly represent the interrelations between the attributes for a population.
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