Comparar métodos

	Simulação Bootstrap Multinível	Simulação Bootstrap com Dados Faltantes
Área	Bayesiano	Bayesiano
Família	Bayesian methods	Bayesian methods
Ano de origem	1979 (bootstrap); multilevel variants c.1990s	1979–1990s
Autor original	Efron (1979); multilevel extensions developed through 1980s–2000s	Bradley Efron (bootstrap); missing-data extensions by Efron, Little, Rubin and others
Tipo	resampling / simulation	Resampling simulation
Fonte seminal	Efron, B. (1979). Bootstrap methods: Another look at the jackknife. The Annals of Statistics, 7(1), 1–26.	Efron, B. & Tibshirani, R. J. (1993). An Introduction to the Bootstrap. Chapman and Hall/CRC. ISBN: 978-0412042317
Outros nomes	hierarchical bootstrap, cluster bootstrap, stratified bootstrap for multilevel data, multilevel resampling	bootstrap with missing data, bootstrap imputation simulation, resampling under missingness, bootstrap MI
Relacionados	6	5
Resumo	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.	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.