Comparer des méthodes

	Simulation de bootstrap hiérarchique	Simulation de bootstrap multiniveau
Domaine	Bayésien	Bayésien
Famille	Bayesian methods	Bayesian methods
Année d'origine	1997-2008	1979 (bootstrap); multilevel variants c.1990s
Auteur d'origine	Davison & Hinkley; Cameron, Gelbach & Miller	Efron (1979); multilevel extensions developed through 1980s–2000s
Type	resampling simulation	resampling / simulation
Source fondatrice	Davison, A. C. & Hinkley, D. V. (1997). Bootstrap Methods and their Application. Cambridge University Press. ISBN: 978-0521574716	Efron, B. (1979). Bootstrap methods: Another look at the jackknife. The Annals of Statistics, 7(1), 1–26.
Alias	cluster bootstrap, multilevel bootstrap, nested bootstrap resampling, hierarchical resampling	hierarchical bootstrap, cluster bootstrap, stratified bootstrap for multilevel data, multilevel resampling
Apparentées	5	6
Résumé	Hierarchical bootstrap simulation is a resampling technique designed for data with nested or clustered structure — students within schools, patients within hospitals, repeated measures within subjects. It preserves the natural grouping of the data by resampling at each level of the hierarchy in sequence, producing a sampling distribution that correctly reflects both between-group and within-group variability.	Multilevel bootstrap simulation is a resampling technique designed for clustered or hierarchically structured data. It preserves the nested data structure by resampling at each level independently — first drawing clusters (e.g., schools, hospitals), then drawing observations within each sampled cluster — so that bootstrap replicate datasets reflect the same multilevel organisation as the original data.