Reporting practices in confirmatory factor analysis: an overview and some recommendations.
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Summary
Results indicate some positive findings with respect to reporting practices including proposing multiple models a priori and near universal reporting of the chi-square significance test, but many deficiencies were found such as lack of information regarding missing data and assessment of normality.
- Type
- review
- Published
- 2009-03-01
- Cited by
- 2,184
- References
- 94
- OpenAlex
- https://openalex.org/W2129748849
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:8595994
Keywords
Confirmatory factor analysis, Checklist, Psychology, Normality, Structural equation modeling
References
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- Principles and Practice of Structural Equation Modeling
- Confirmatory Factor Analysis for Applied Research
- Reporting Structural Equation Modeling and Confirmatory Factor Analysis Results: A Review
- An index of goodness-of-fit based on noncentrality
- The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis.
- Applications of structural equation modeling in marketing and consumer research: A review
- Power analysis and determination of sample size for covariance structure modeling.
- Use of Structural Equation Modeling in Counseling Psychology Research.
- Analysis of correlation matrices using covariance structure models.
- Structural equation modeling made difficult
- Effects of Potential Confounding Factors on Fit Indices and Parameter Estimates for True and Misspecified SEM Models
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- Postpartum Depression in the NICU: An Examination of the Factor Structure of the Postpartum Depression Screening Scale
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- The Development and Validation of the Empathy Components Questionnaire (ECQ)
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- Evidence for two distinct domains of negative symptoms: Confirming the factorial structure of the CAINS.
- Cloud Computing : The Adoption of Cloud Computing for Small and Medium Enterprises
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