Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Analiza factoriala confirmativa multi-grup (MG-CFA)× | Analiza factoriala confirmatorie (CFA)× | |
|---|---|---|
| Domeniu | Psihometrie | Psihometrie |
| Familie | Latent structure | Latent structure |
| Anul apariției≠ | 1971 | 1969 |
| Autorul original≠ | Karl Jöreskog | Karl Gustav Jöreskog |
| Tip≠ | Measurement model / invariance test | Hypothesis-testing latent variable model |
| Sursa seminală≠ | Vandenberg, R. J. & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–70. DOI ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Denumiri alternative | MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Înrudite≠ | 6 | 4 |
| Rezumat≠ | Multi-group confirmatory factor analysis tests whether a measurement model holds equivalently across two or more groups — such as cultures, genders, or time points. By imposing increasingly stringent equality constraints and comparing model fit, it determines whether comparisons of latent mean scores are justified. | Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing. |
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