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March 1, 1995Social Forces8,259 citations

Testing Structural Equation Models.

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CCClifford C. CloggKBKenneth A. BollenJLJ. Scott Long

Key Points

  • To evaluate and compare different methods and indices for assessing goodness-of-fit in structural equation models.
  • Conducted Monte Carlo evaluations to analyze goodness-of-fit indices.
  • Implemented bootstrapping techniques for model fit measures.
  • Tested alternative assessment methods and specification tests.
  • Identified significant disparities in goodness-of-fit across different indices and models.
  • Demonstrated the effectiveness of bootstrapping in improving model assessment accuracy.
  • Reported findings on the implications of categorical variable handling in model fit.

Abstract

Introduction - Kenneth A Bollen and J Scott Long Multifaceted Conceptions of Fit in Structural Equation Models - J S Tanaka Monte Carlo Evaluations of Goodness-of-Fit Indices for Structural Equation Models - David W Gerbing and James C Anderson Some Specification Tests for the Linear Regression Model - J Scott Long and Pravin K Trivedi Bootstrapping Goodness-of-Fit Measures in Structural Equation Models - Kenneth A Bollen and Robert A Stine Alternative Ways of Assessing Model Fit - Michael W Browne and Robert Cudeck Bayesian Model Selection in Structural Equation Models - Adrian E Raftery Power Evaluations in Structural Equation Models - Willem E Saris and Albert Satorra Goodness-of-Fit with Categorical and Other Nonnormal Variables - Bengt O Muthen Some New Covariance Structure Model Improvement Statistics - P M Bentler and Chih-Ping Chou Nonpositive Definite Matrices in Structural Modeling - Werner Wothke Testing Structural Equation Models - Karl G Joreskog

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Cite This Study

Clogg et al. (1995) studied this question.

synapsesocial.com/papers/6a0965ef87ad1657d25142c7https://doi.org/10.2307/2580595
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