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| Testowanie niezmienniczości pomiaru w wielu grupach× | Wielogrupowa konfirmacyjna analiza czynnikowa (MG-CFA)× | |
|---|---|---|
| Dziedzina | Psychometria | Psychometria |
| Rodzina | Latent structure | Latent structure |
| Rok powstania≠ | 1971–1993 | 1971 |
| Twórca≠ | Jöreskog, K. G. (1971); Meredith, W. (1993) | Karl Jöreskog |
| Typ≠ | Model comparison / hypothesis testing | Measurement model / invariance test |
| Źródło pierwotne | 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 ↗ |
| Inne nazwy | measurement invariance, factorial invariance, cross-group invariance, MI testing | MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA |
| Pokrewne | 6 | 6 |
| Podsumowanie≠ | 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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