Σύγκριση μεθόδων

	Πολυεπίπεδη αμεταβλητότητα μέτρησης	Επαληθευτική Παραγοντική Ανάλυση (Confirmatory Factor Analysis - CFA)
Πεδίο	Ψυχομετρία	Ψυχομετρία
Οικογένεια	Latent structure	Latent structure
Έτος προέλευσης	2000s	1969
Δημιουργός	Muthén, Asparouhov, and colleagues	Karl Gustav Jöreskog
Τύπος	Measurement model evaluation	Hypothesis-testing latent variable model
Θεμελιώδης πηγή	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.	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.
Εναλλακτικές ονομασίες	MLMI, multilevel factorial invariance, cross-level measurement invariance, multilevel CFA invariance	CFA, confirmatory FA, measurement model, restricted factor analysis
Συναφείς	3	4
Σύνοψη	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.	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.