Сравнение методов

	Многогрупповая модель Раша	Многогрупповой конфирматорный факторный анализ (MG-CFA)
Область	Психометрия	Психометрия
Семейство	Latent structure	Latent structure
Год появления	1960 (Rasch); 1980s–1990s (multi-group extensions)	1971
Автор метода	Georg Rasch (single-group); extended to multi-group applications by Fischer, Molenaar, and others	Karl Jöreskog
Тип	Item response model / measurement invariance test	Measurement model / invariance test
Основополагающий источник	Fischer, G. H. & Molenaar, I. W. (Eds.) (1995). Rasch Models: Foundations, Recent Developments, and Applications. Springer. ISBN: 978-0387944296	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.
Другие названия	MG-Rasch, Rasch measurement invariance, multi-group 1PL IRT, cross-group Rasch analysis	MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA
Связанные	6	6
Сводка	The multi-group Rasch model fits the one-parameter logistic item response model simultaneously across two or more distinct groups, testing whether item difficulty parameters are invariant across groups. It is the primary psychometric tool for establishing that a scale measures the same latent trait with the same metric in each group, a prerequisite for meaningful score comparisons.	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.