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Teoria generalizowalności (G-Theory)×Kwantitativna analiza czynnikowa (CFA)×
DziedzinaPsychometriaPsychometria
RodzinaLatent structureLatent structure
Rok powstania1963–19721969
TwórcaLee J. Cronbach, Goldine Gleser, Harinder Nanda, Nageswari RajaratnamKarl Gustav Jöreskog
TypVariance-components reliability modelHypothesis-testing latent variable model
Źródło pierwotneCronbach, L. J., Gleser, G. C., Nanda, H. & Rajaratnam, N. (1972). The Dependability of Behavioral Measurements: Theory of Generalizability for Scores and Profiles. Wiley. link ↗Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗
Inne nazwyG-theory, G-study / D-study framework, variance components reliabilityCFA, confirmatory FA, measurement model, restricted factor analysis
Pokrewne44
PodsumowanieGeneralizability Theory is a psychometric framework that decomposes observed score variance into multiple sources — persons, items, raters, occasions, and their interactions — using analysis of variance. It replaces the single reliability coefficient of classical test theory with a family of coefficients that tell researchers how well scores generalize across different measurement conditions.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.
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ScholarGatePorównaj metody: Generalizability Theory · Confirmatory factor analysis. Pobrano 2026-06-18 z https://scholargate.app/pl/compare