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Bayesiansk konfirmatorisk faktoranalyse (BCFA)×Generaliserbarhetsteori (G-teori)×
FagfeltPsykometriPsykometri
FamilieLatent structureLatent structure
Opprinnelsesår2007–20121963–1972
OpphavspersonSik-Yum Lee; Bengt Muthén and Tihomir AsparouhovLee J. Cronbach, Goldine Gleser, Harinder Nanda, Nageswari Rajaratnam
TypeBayesian latent variable modelVariance-components reliability model
Opprinnelig kildeLee, S.-Y. (2007). Structural Equation Modeling: A Bayesian Approach. Wiley. ISBN: 978-0470024232Cronbach, L. J., Gleser, G. C., Nanda, H. & Rajaratnam, N. (1972). The Dependability of Behavioral Measurements: Theory of Generalizability for Scores and Profiles. Wiley. link ↗
AliasBCFA, Bayesian CFA, Bayesian structural equation measurement model, Bayes-CFAG-theory, G-study / D-study framework, variance components reliability
Relaterte44
SammendragBayesian confirmatory factor analysis tests a pre-specified factor structure using Bayesian inference. Instead of point estimates with p-values, it produces full posterior distributions for loadings, factor correlations, and residual variances, allowing the researcher to incorporate prior knowledge and propagate parameter uncertainty naturally.Generalizability 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.
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ScholarGateSammenlign metoder: Bayesian Confirmatory Factor Analysis · Generalizability Theory. Hentet 2026-06-18 fra https://scholargate.app/no/compare