विधियों की तुलना करें

	बहुस्तरीय पैमाना विकास	बहुस्तरीय मापन निश्चरता (Multilevel Measurement Invariance)
क्षेत्र	मनोमिति	मनोमिति
परिवार	Latent structure	Latent structure
उद्भव वर्ष	1990s–2000s	2000s
प्रवर्तक	Raudenbush, Bryk, Hox and colleagues	Muthén, Asparouhov, and colleagues
प्रकार	Hierarchical measurement / scale construction	Measurement model evaluation
मौलिक स्रोत	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.
उपनाम	multilevel measurement modeling, hierarchical scale development, MLSEM scale construction, nested data scale development	MLMI, multilevel factorial invariance, cross-level measurement invariance, multilevel CFA invariance
संबंधित	5	3
सारांश	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.