Porovnat metody

	Bayesovský hierarchický model s chybějícími daty	Vícestupňová bayesovská inference
Obor	Bayesovská statistika	Bayesovská statistika
Rodina	Bayesian methods	Bayesian methods
Rok vzniku	1990s–2000s	1980s–2000s
Tvůrce	Gelman, Rubin, Little (and collaborators)	Gelman, Hill, Raudenbush, Bryk
Typ	Bayesian hierarchical model with missing-data integration	Bayesian hierarchical model
Původní zdroj	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	Gelman, A., & Hill, J. (2007). Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press. ISBN: 978-0521686891
Další názvy	BHM missing data, multilevel Bayesian missing data model, hierarchical Bayesian imputation, Bayesian multilevel model with incomplete data	Bayesian multilevel model, Bayesian hierarchical model, Bayesian mixed-effects model, Bayesian random-effects model
Příbuzné	5	6
Shrnutí	A Bayesian hierarchical model with missing data treats unobserved values as additional unknowns and samples them jointly with all model parameters from the posterior. The nested structure of the hierarchy borrows strength across groups, while the Bayesian framework naturally propagates uncertainty from missingness through every estimate and prediction.	Multilevel Bayesian inference combines Bayesian probability with hierarchical data structures, treating group-level parameters as drawn from a common population distribution. It simultaneously estimates unit-level effects and the hyperparameters governing their variation, propagating full uncertainty through every level of the hierarchy via posterior sampling.