Σύγκριση μεθόδων

	Γενικευσιμότητα Πολλαπλών Ομάδων	Έλεγχος Αναλλοιότητας Μετρήσεων Πολλαπλών Ομάδων
Πεδίο	Ψυχομετρία	Ψυχομετρία
Οικογένεια	Latent structure	Latent structure
Έτος προέλευσης	1963–2001	1971–1993
Δημιουργός	Lee J. Cronbach and colleagues (Cronbach, Gleser, Nanda, Rajaratnam), extended to multi-group contexts by Brennan and others	Jöreskog, K. G. (1971); Meredith, W. (1993)
Τύπος	Variance component / reliability generalization	Model comparison / hypothesis testing
Θεμελιώδης πηγή	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.
Εναλλακτικές ονομασίες	MG G-theory, multi-group G-theory, generalizability theory across groups, cross-group G-study	measurement invariance, factorial invariance, cross-group invariance, MI testing
Συναφείς	6	6
Σύνοψη	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 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.