Comparer des méthodes

	Théorie de la généralisabilité multi-groupes	Modèle de Rasch multigroupe
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1963–2001	1960 (Rasch); 1980s–1990s (multi-group extensions)
Auteur d'origine	Lee J. Cronbach and colleagues (Cronbach, Gleser, Nanda, Rajaratnam), extended to multi-group contexts by Brennan and others	Georg Rasch (single-group); extended to multi-group applications by Fischer, Molenaar, and others
Type	Variance component / reliability generalization	Item response model / measurement invariance test
Source fondatrice	Brennan, R. L. (2001). Generalizability Theory. Springer. ISBN: 978-0387952826	Fischer, G. H. & Molenaar, I. W. (Eds.) (1995). Rasch Models: Foundations, Recent Developments, and Applications. Springer. ISBN: 978-0387944296
Alias	MG G-theory, multi-group G-theory, generalizability theory across groups, cross-group G-study	MG-Rasch, Rasch measurement invariance, multi-group 1PL IRT, cross-group Rasch analysis
Apparentées	6	6
Résumé	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.	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.