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Многоуровневое бутстреп-моделирование×Бутстреп-симуляция при наличии пропущенных данных×
ОбластьБайесовские методыБайесовские методы
СемействоBayesian methodsBayesian methods
Год появления1979 (bootstrap); multilevel variants c.1990s1979–1990s
Автор методаEfron (1979); multilevel extensions developed through 1980s–2000sBradley Efron (bootstrap); missing-data extensions by Efron, Little, Rubin and others
Типresampling / simulationResampling simulation
Основополагающий источникEfron, 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
Другие названияhierarchical bootstrap, cluster bootstrap, stratified bootstrap for multilevel data, multilevel resamplingbootstrap with missing data, bootstrap imputation simulation, resampling under missingness, bootstrap MI
Связанные65
СводкаMultilevel 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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ScholarGateСравнение методов: Multilevel Bootstrap Simulation · Bootstrap Simulation with Missing Data. Получено 2026-06-15 из https://scholargate.app/ru/compare