Salīdzināt metodes

	Daudzlīmeņu skalas izstrāde	Daudzlīmeņu mērījumu ekvitāte
Nozare	Psihometrija	Psihometrija
Saime	Latent structure	Latent structure
Izcelsmes gads	1990s–2000s	2000s
Autors	Raudenbush, Bryk, Hox and colleagues	Muthén, Asparouhov, and colleagues
Tips	Hierarchical measurement / scale construction	Measurement model evaluation
Pirmavots	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.
Citi nosaukumi	multilevel measurement modeling, hierarchical scale development, MLSEM scale construction, nested data scale development	MLMI, multilevel factorial invariance, cross-level measurement invariance, multilevel CFA invariance
Saistītās	5	3
Kopsavilkums	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.