Сравнение методов

	Многогрупповой анализ надежности	Многогрупповой конфирматорный факторный анализ (MG-CFA)
Область	Психометрия	Психометрия
Семейство	Latent structure	Latent structure
Год появления	1990s–2000s	1971
Автор метода	Classical test theory traditions; synthesized in modern practice by Vandenberg & Lance (2000) and Sijtsma (2009)	Karl Jöreskog
Тип	Reliability estimation and comparison	Measurement model / invariance test
Основополагающий источник	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.	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	reliability comparison across groups, group-specific reliability estimation, multi-sample reliability analysis, cross-group internal consistency	MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA
Связанные	4	6
Сводка	Multi-group reliability analysis estimates internal consistency or stability coefficients separately within each group and then formally compares them to determine whether a scale functions with equal precision across populations. It is a foundational step in cross-group measurement research, typically carried out alongside or prior to measurement invariance testing.	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.