Comparer des méthodes

	Développement d'échelles multiniveaux	Invariance de mesure multiniveaux
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1990s–2000s	2000s
Auteur d'origine	Raudenbush, Bryk, Hox and colleagues	Muthén, Asparouhov, and colleagues
Type	Hierarchical measurement / scale construction	Measurement model evaluation
Source fondatrice	Hox, J. J. (2010). Multilevel Analysis: Techniques and Applications (2nd ed.). Routledge. ISBN: 978-1848728462	Muthén, B. O., & Asparouhov, T. (2009). Multilevel factor analysis of class and student achievement components. Journal of Educational and Behavioral Statistics, 34(2), 250–270.
Alias	multilevel measurement modeling, hierarchical scale development, MLSEM scale construction, nested data scale development	MLMI, multilevel factorial invariance, cross-level measurement invariance, multilevel CFA invariance
Apparentées	5	3
Résumé	Multilevel scale development constructs and validates measurement instruments for data collected from individuals nested within higher-level units such as classrooms, organizations, or clinics. It partitions item variance into within-group and between-group components, ensuring that reliability and factor structure are evaluated at both levels simultaneously.	Multilevel measurement invariance testing evaluates whether a latent construct is measured equivalently both within clusters (e.g., individuals within teams) and between clusters (e.g., team-level aggregates). It extends standard measurement invariance procedures to nested data structures commonly encountered in organisational, educational, and cross-cultural research.