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Bayesiansk regresjon×Latent Growth Curve Model (LGC)×
FagfeltBayesianskStatistikk
FamilieBayesian methodsLatent structure
Opprinnelsesår1990
OpphavspersonMeredith & Tisak
TypeBayesian linear modelLatent variable / longitudinal growth model
Opprinnelig kildeGelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A. & Rubin, D. B. (2013). Bayesian Data Analysis (3rd ed.). CRC Press. ISBN: 978-1439840955Meredith, W. & Tisak, J. (1990). Latent Curve Analysis. Psychometrika, 55(1), 107–122. DOI ↗
Aliasbayesian linear regression, probabilistic regression, bayesian regresyonlatent growth model, LGC, growth curve model, Gizil Büyüme Eğrisi Modeli
Relaterte25
SammendragBayesian 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.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.
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ScholarGateSammenlign metoder: Bayesian Regression · LGC Model. Hentet 2026-06-19 fra https://scholargate.app/no/compare