Porównaj metody

	Regresja bayesowska	Konfirmacyjna Analiza Czynnikowa (CFA)	Model krzywej wzrostu utajonego (LGC)
Dziedzina	Statystyka bayesowska	Statystyka	Statystyka
Rodzina	Bayesian methods	Latent structure	Latent structure
Rok powstania	—	1969	1990
Twórca	—	Karl Jöreskog	Meredith & Tisak
Typ	Bayesian linear model	Confirmatory latent variable model	Latent variable / longitudinal growth model
Źródło pierwotne	Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A. & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955	Brown, T. A. (2015). Confirmatory Factor Analysis for Applied Research (2nd ed.). The Guilford Press. ISBN: 978-1462515363	Meredith, W. & Tisak, J. (1990). Latent Curve Analysis. Psychometrika, 55(1), 107–122.
Inne nazwy	bayesian linear regression, probabilistic regression, bayesian regresyon	Doğrulayıcı Faktör Analizi (CFA), confirmatory factor analysis, measurement model	latent growth model, LGC, growth curve model, Gizil Büyüme Eğrisi Modeli
Pokrewne	2	4	5
Podsumowanie	Bayesian regression is a probabilistic version of linear regression that treats the model parameters as uncertain quantities. Instead of returning a single best-fit estimate, it combines prior knowledge with the observed data to produce a full posterior probability distribution for each parameter, from which credible intervals and predictions are read off.	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.	The latent growth curve model is a structural equation modelling approach introduced by Meredith and Tisak (1990) for analysing change over time. It treats each individual's starting point (intercept) and rate of change (slope) as latent variables, simultaneously estimating the average trajectory across the sample and the extent to which individuals differ in their own trajectories.