Salīdzināt metodes

	Daudzlīmeņu nomoloģiskā validitāte	Apstiprinošā faktoru analīze (AFA)
Nozare	Psihometrija	Psihometrija
Saime	Latent structure	Latent structure
Izcelsmes gads	2005	1969
Autors	Chen, Bliese & Mathieu (building on Cronbach & Meehl)	Karl Gustav Jöreskog
Tips	Validity assessment / construct validation	Hypothesis-testing latent variable model
Pirmavots	Chen, G., Bliese, P. D. & Mathieu, J. E. (2005). Conceptual framework and statistical procedures for delineating and testing multilevel theories of homology. Organizational Research Methods, 8(4), 375–409.	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.
Citi nosaukumi	cross-level construct validity, multilevel construct validation, MNV, nomological validity across levels	CFA, confirmatory FA, measurement model, restricted factor analysis
Saistītās	4	4
Kopsavilkums	Multilevel nomological validity evaluates whether a psychological construct and its network of theoretical relationships hold consistently across multiple levels of analysis — such as individual, team, and organization. It extends classical construct validation to nested data structures, ensuring that a measure means the same thing and behaves as theory predicts at each level.	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.