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| Tests d'invariance de mesure multigroupe× | Analyse factorielle confirmatoire multi-groupes (AFC-MG)× | |
|---|---|---|
| Domaine | Psychométrie | Psychométrie |
| Famille | Latent structure | Latent structure |
| Année d'origine≠ | 1971–1993 | 1971 |
| Auteur d'origine≠ | Jöreskog, K. G. (1971); Meredith, W. (1993) | Karl Jöreskog |
| Type≠ | Model comparison / hypothesis testing | Measurement model / invariance test |
| Source fondatrice | 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 ↗ | 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 ↗ |
| Alias | measurement invariance, factorial invariance, cross-group invariance, MI testing | MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA |
| Apparentées | 6 | 6 |
| Résumé≠ | Multi-group measurement invariance testing examines whether a latent construct is measured in the same way across two or more distinct groups — such as cultures, genders, or age cohorts. It is a prerequisite for meaningful group comparisons of latent means or relationships, ensuring that observed score differences reflect true differences rather than measurement artifacts. | 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. |
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