विधियों की तुलना करें

	Bayesian Hierarchical Model	पुष्टिकारीय कारक विश्लेषण (CFA)
क्षेत्र	बायेसियन	सांख्यिकी
परिवार	Bayesian methods	Latent structure
उद्भव वर्ष	2006	1969
प्रवर्तक	Gelman & Hill (2006); Bayesian multilevel tradition	Karl Jöreskog
प्रकार	hierarchical probabilistic model	Confirmatory latent variable model
मौलिक स्रोत	Gelman, A. & Hill, J. (2006). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press.	Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research (2nd ed.). The Guilford Press. ISBN: 978-1462515363
उपनाम	multilevel Bayes, Bayesian multilevel model, Bayesian HLM, partial pooling model	Doğrulayıcı Faktör Analizi (CFA), confirmatory factor analysis, measurement model
संबंधित	4	4
सारांश	Bayesian hierarchical modelling, popularised by Gelman and Hill (2006), is a Bayesian approach to nested data structures — such as students within schools within districts — that estimates separate parameters at each level while allowing those levels to share statistical strength through a mechanism called partial pooling. Where a classical hierarchical linear model treats group means as fixed unknown quantities, the Bayesian version places hyperprior distributions on those group means so that information flows freely across levels, producing more reliable group-level estimates whenever any individual group has few observations.	Confirmatory factor analysis tests whether a researcher-specified factor structure fits the observed data. Formalised by Karl Jöreskog in 1969, it is the measurement-model step within structural equation modelling and is the standard tool for validating the factorial structure of scales and questionnaires before comparing groups or estimating latent relationships.