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Байесовский конфирматорный факторный анализ (BCFA)×Теория обобщаемости (G-теория)×
ОбластьПсихометрияПсихометрия
СемействоLatent structureLatent structure
Год появления2007–20121963–1972
Автор методаSik-Yum Lee; Bengt Muthén and Tihomir AsparouhovLee J. Cronbach, Goldine Gleser, Harinder Nanda, Nageswari Rajaratnam
ТипBayesian latent variable modelVariance-components reliability model
Основополагающий источникLee, 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 ↗
Другие названияBCFA, Bayesian CFA, Bayesian structural equation measurement model, Bayes-CFAG-theory, G-study / D-study framework, variance components reliability
Связанные44
СводкаBayesian 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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ScholarGateСравнение методов: Bayesian Confirmatory Factor Analysis · Generalizability Theory. Получено 2026-06-18 из https://scholargate.app/ru/compare