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Symulacja metodą wielopoziomowego bootstrapu×Symulacja bootstrapowa z brakującymi danymi×
DziedzinaStatystyka bayesowskaStatystyka bayesowska
RodzinaBayesian methodsBayesian methods
Rok powstania1979 (bootstrap); multilevel variants c.1990s1979–1990s
TwórcaEfron (1979); multilevel extensions developed through 1980s–2000sBradley Efron (bootstrap); missing-data extensions by Efron, Little, Rubin and others
Typresampling / simulationResampling simulation
Źródło pierwotneEfron, B. (1979). Bootstrap methods: Another look at the jackknife. The Annals of Statistics, 7(1), 1–26. DOI ↗Efron, B. & Tibshirani, R. J. (1993). An Introduction to the Bootstrap. Chapman and Hall/CRC. ISBN: 978-0412042317
Inne nazwyhierarchical bootstrap, cluster bootstrap, stratified bootstrap for multilevel data, multilevel resamplingbootstrap with missing data, bootstrap imputation simulation, resampling under missingness, bootstrap MI
Pokrewne65
PodsumowanieMultilevel 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.Bootstrap simulation with missing data combines resampling-based variance estimation with principled handling of incomplete observations. Rather than deleting cases or assuming complete data, the method integrates imputation or weighting directly into the bootstrap loop, propagating the additional uncertainty due to missingness into the final standard errors and confidence intervals.
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ScholarGatePorównaj metody: Multilevel Bootstrap Simulation · Bootstrap Simulation with Missing Data. Pobrano 2026-06-15 z https://scholargate.app/pl/compare