Σύγκριση μεθόδων

	Επαληθευτική Παραγοντική Ανάλυση (Confirmatory Factor Analysis - CFA)	Διερευνητική Ανάλυση Παραγόντων (EFA)	Ανάλυση Διαμεσολάβησης
Πεδίο	Ψυχομετρία	Στατιστική	Στατιστική
Οικογένεια	Latent structure	Latent structure	Hypothesis test
Έτος προέλευσης	1969	—	1986
Δημιουργός	Karl Gustav Jöreskog	—	Baron & Kenny
Τύπος	Hypothesis-testing latent variable model	Latent variable / dimension reduction	Indirect effects / path test
Θεμελιώδης πηγή	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.	Fabrigar, L. R., Wegener, D. T., MacCallum, R. C. & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299.	Baron, R. M. & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research. Journal of Personality and Social Psychology, 51(6), 1173–1182.
Εναλλακτικές ονομασίες	CFA, confirmatory FA, measurement model, restricted factor analysis	common factor analysis, açımlayıcı faktör analizi, factor analysis	indirect effects analysis, path-based mediation, PROCESS macro mediation, Aracılık Analizi (Mediation / PROCESS)
Συναφείς	4	4	5
Σύνοψη	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.	Exploratory factor analysis reduces a large set of observed variables into a smaller number of latent common factors. It is widely used in scale development and psychometrics to uncover the dimensional structure that underlies a set of correlated items, without specifying that structure in advance.	Mediation analysis is a statistical procedure that tests whether the effect of an independent variable X on an outcome Y operates wholly or partly through a third variable M, called the mediator. Formalised by Baron and Kenny in 1986, it decomposes the total effect of X on Y into a direct path (c′) and an indirect path (a × b), quantifying how much of the relationship is carried by the mediating mechanism.