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Comparison of model fit indices used in structural equation modeling under multivariate normality

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Wayne State Univ Press

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The purpose of this study is to investigate the impact of estimation techniques and sample sizes on model fit indices in structural equation models constructed according to the number of exogenous latent variables under multivariate normality. The performances of fit indices are compared by considering effects of related factors. The Ratio Chi-square Test Statistic to Degree of Freedom, Root Mean Square Error of Approximation, and Comparative Fit Index are the least affected indices by estimation technique and sample size under multivariate normality, especially with large sample size.

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Goodness-of-fit, Confirmatory factor-analysis, Sample-size, Number, Sensitivity, Parameter, Variables, Criteria, Search, Structural equation modeling, Multivariate normality, Science & technology, Physical sciences, Statistics & probability, Mathematics

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