Σύγκριση μεθόδων

	Αξιολόγηση Εγκυρότητας Κατασκευής κατά Bayes	Επαληθευτική Παραγοντική Ανάλυση (Confirmatory Factor Analysis - CFA)
Πεδίο	Ψυχομετρία	Ψυχομετρία
Οικογένεια	Latent structure	Latent structure
Έτος προέλευσης	1955 / 2012	1969
Δημιουργός	Cronbach & Meehl (validity framework); Muthén & Asparouhov (Bayesian SEM extension)	Karl Gustav Jöreskog
Τύπος	Validity assessment / Bayesian inference	Hypothesis-testing latent variable model
Θεμελιώδης πηγή	Muthén, B. & Asparouhov, T. (2012). Bayesian structural equation modeling: A more flexible representation of substantive theory. Psychological Methods, 17(3), 313–335.	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.
Εναλλακτικές ονομασίες	Bayesian validity analysis, Bayesian CFA-based validity, Bayesian structural validity, posterior construct validity	CFA, confirmatory FA, measurement model, restricted factor analysis
Συναφείς	6	4
Σύνοψη	Bayesian construct validity assessment uses Bayesian confirmatory factor analysis and related Bayesian structural equation models to evaluate whether a scale or test measures the intended latent construct. It yields full posterior distributions for factor loadings, structural coefficients, and model-fit indices rather than single point estimates, enabling more nuanced and uncertainty-aware validity conclusions.	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.