পদ্ধতির তুলনা করুন

	Bayesian Confirmatory Factor Analysis	Generalizability Theory (G-Theory)
ক্ষেত্র	মনোমিতি	মনোমিতি
পরিবার	Latent structure	Latent structure
উদ্ভবের বছর	2007–2012	1963–1972
প্রবর্তক	Sik-Yum Lee; Bengt Muthén and Tihomir Asparouhov	Lee J. Cronbach, Goldine Gleser, Harinder Nanda, Nageswari Rajaratnam
ধরন	Bayesian latent variable model	Variance-components reliability model
মৌলিক উৎস	Lee, S.-Y. (2007). Structural Equation Modeling: A Bayesian Approach. Wiley. ISBN: 978-0470024232	Cronbach, L. J., Gleser, G. C., Nanda, H. & Rajaratnam, N. (1972). The Dependability of Behavioral Measurements: Theory of Generalizability for Scores and Profiles. Wiley.
অপর নাম	BCFA, Bayesian CFA, Bayesian structural equation measurement model, Bayes-CFA	G-theory, G-study / D-study framework, variance components reliability
সম্পর্কিত	4	4
সারসংক্ষেপ	Bayesian 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.