Reporting Structural Equation Modeling and Confirmatory Factor Analysis Results: A Review

ABSTRACT The authors provide a basic set of guidelines and recommendations for information that should be included in any manuscript that has confirmatory factor analysis or structural equation modeling as the primary statistical analysis technique. The authors provide an introduction to both techni...

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Bibliographic Details
Published in:The Journal of educational research (Washington, D.C.) D.C.), 2006-07, Vol.99 (6), p.323-338
Main Authors: Schreiber, James B., Nora, Amaury, Stage, Frances K., Barlow, Elizabeth A., King, Jamie
Format: Article
Language:English
Subjects:
Academic achievement
Biological and medical sciences
Changes
Coefficients
Computer processing
confirmatory factor analysis
Educational research
Factor Analysis
Fundamental and applied biological sciences. Psychology
Guidelines
Mathematical Models
Maximum likelihood estimation
Measurement errors
Methodology. Experimentation
Missing data
Modeling
Modifications
Observational research
Parametric models
Path Analysis
Psychology. Psychoanalysis. Psychiatry
Psychology. Psychophysiology
Psychometrics. Statistics. Methodology
R&D
reports statistical results
Research & development
Research Methodology
research methods
Researchers
Sample size
Statistical Analysis
Structural equation modeling
Structural Equation Models
Studies
Variables
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Summary:ABSTRACT The authors provide a basic set of guidelines and recommendations for information that should be included in any manuscript that has confirmatory factor analysis or structural equation modeling as the primary statistical analysis technique. The authors provide an introduction to both techniques, along with sample analyses, recommendations for reporting, evaluation of articles in The Journal of Educational Research using these techniques, and concluding remarks.
ISSN:0022-0671
1940-0675
DOI:10.3200/JOER.99.6.323-338