Comparer des méthodes

	Développement d'échelles multiniveaux	Analyse Factorielle Confirmatoire (AFC)
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1990s–2000s	1969
Auteur d'origine	Raudenbush, Bryk, Hox and colleagues	Karl Gustav Jöreskog
Type	Hierarchical measurement / scale construction	Hypothesis-testing latent variable model
Source fondatrice	Hox, J. J. (2010). Multilevel Analysis: Techniques and Applications (2nd ed.). Routledge. ISBN: 978-1848728462	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.
Alias	multilevel measurement modeling, hierarchical scale development, MLSEM scale construction, nested data scale development	CFA, confirmatory FA, measurement model, restricted factor analysis
Apparentées	5	4
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.	Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing.