Structural Equations Modeling: Fit Indices, Sample Size, and Advanced Topics
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- Type
- article
- Published
- 2010-01-01
- Cited by
- 2,286
- References
- 45
- OpenAlex
- https://openalex.org/W2038318317
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:3941857
Keywords
Structural equation modeling, Mediation, Sample (material), Psychology, Econometrics
References
- Principles and Practice of Structural Equation Modeling
- A general structural equation model with dichotomous, ordered categorical, and continuous latent variable indicators
- Advanced structural equation modeling : issues and techniques
- On the meaning of formative measurement and how it differs from reflective measurement: comment on Howell, Breivik, and Wilcox (2007).
- Overall Fit in Covariance Structure Models: Two Types of Sample Size Effects
- Fit indices in covariance structure modeling : Sensitivity to underparameterized model misspecification
- Goodness-of-fit indexes in confirmatory factor analysis : The effect of sample size
- Point Estimation, Hypothesis Testing, and Interval Estimation Using the RMSEA: Some Comments and a Reply to Hayduk and Glaser
- Analysis of covariance structures
- Monte Carlo Evaluations of Goodness of Fit Indices for Structural Equation Models
- Revisiting Sample Size and Number of Parameter Estimates: Some Support for the N:q Hypothesis
- Comparative fit indexes in structural models.
- The Performance of ML, GLS, and WLS Estimation in Structural Equation Modeling Under Conditions of Misspecification and Nonnormality
- CFI versus RMSEA: A comparison of two fit indexes for structural equation modeling
- In Search of Golden Rules: Comment on Hypothesis-Testing Approaches to Setting Cutoff Values for Fit Indexes and Dangers in Overgeneralizing Hu and Bentler's (1999) Findings
- Reconsidering formative measurement.
- Predicting the performance of measures in a confirmatory factor analysis with a pretest assessment of their substantive validities.
- Testing differences between nested covariance structure models: Power analysis and null hypotheses.
- Effect of the Number of Variables on Measures of Fit in Structural Equation Modeling
- On the Meaning of Within-Factor Correlated Measurement Errors
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