Salīdzināt metodes

	Daudzlīmeņu diskriminējošā validitāte	Daudzlīmeņu mērījumu ekvitāte
Nozare	Psihometrija	Psihometrija
Saime	Latent structure	Latent structure
Izcelsmes gads	2005	2000s
Autors	Dyer, Hanges, & Hall; Chen, Sousa, & West	Muthén, Asparouhov, and colleagues
Tips	Validity evaluation within multilevel CFA	Measurement model evaluation
Pirmavots	Dyer, N. G., Hanges, P. J., & Hall, R. J. (2005). Applying multilevel confirmatory factor analysis techniques to the study of leadership. Leadership Quarterly, 16(1), 149–167.	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 DV, cross-level discriminant validity, hierarchical discriminant validity, ML-DV	MLMI, multilevel factorial invariance, cross-level measurement invariance, multilevel CFA invariance
Saistītās	5	3
Kopsavilkums	Multilevel discriminant validity evaluates whether theoretically distinct constructs are empirically separable when data are nested within higher-level units such as teams, schools, or organizations. It extends single-level discriminant validity checks into a multilevel confirmatory factor analysis framework, verifying that constructs are distinguishable both within and between 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.