Salīdzināt metodes

	Robustas diskriminantās validitātes pārbaude	Apstiprinošā faktoru analīze (AFA)
Nozare	Psihometrija	Psihometrija
Saime	Latent structure	Latent structure
Izcelsmes gads	1959 (foundational); 2015 (HTMT criterion)	1969
Autors	Henseler, Ringle & Sarstedt (HTMT); Campbell & Fiske (foundational framework)	Karl Gustav Jöreskog
Tips	Validity assessment / measurement quality criterion	Hypothesis-testing latent variable model
Pirmavots	Henseler, J., Ringle, C. M. & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135.	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.
Citi nosaukumi	HTMT criterion, heterotrait-monotrait ratio, discriminant validity testing, RDV	CFA, confirmatory FA, measurement model, restricted factor analysis
Saistītās	4	4
Kopsavilkums	Robust discriminant validity assessment determines whether distinct latent constructs in a measurement model are sufficiently different from one another. Unlike traditional AVE-based approaches, robust methods such as the Heterotrait-Monotrait (HTMT) ratio use the pattern of inter-indicator correlations to provide a more sensitive and simulation-validated criterion for judging discriminant validity in structural equation modeling contexts.	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.