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| Многогрупова теория на обобщаемостта× | Многогрупов конфирматорен факторен анализ (MG-CFA)× | |
|---|---|---|
| Област | Психометрия | Психометрия |
| Семейство | Latent structure | Latent structure |
| Година на възникване≠ | 1963–2001 | 1971 |
| Създател≠ | Lee J. Cronbach and colleagues (Cronbach, Gleser, Nanda, Rajaratnam), extended to multi-group contexts by Brennan and others | Karl Jöreskog |
| Тип≠ | Variance component / reliability generalization | Measurement model / invariance test |
| Основополагащ източник≠ | Brennan, R. L. (2001). Generalizability Theory. Springer. ISBN: 978-0387952826 | 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 ↗ |
| Други названия | MG G-theory, multi-group G-theory, generalizability theory across groups, cross-group G-study | MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA |
| Свързани | 6 | 6 |
| Резюме≠ | Multi-group generalizability theory (MG G-theory) extends classical generalizability theory to estimate and compare variance components — attributable to persons, items, raters, occasions, and their interactions — simultaneously across two or more defined groups. It reveals whether a measurement procedure is equally reliable and generalizable for every group studied, supporting fair and equitable score interpretation. | 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. |
| ScholarGateНабор от данни ↗ |
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