方法对比
并排查看您选择的方法;存在差异的行会高亮显示。
| 多层自助法模拟× | 缺失数据时的自助法模拟× | |
|---|---|---|
| 领域 | 贝叶斯 | 贝叶斯 |
| 方法族 | Bayesian methods | Bayesian methods |
| 起源年份≠ | 1979 (bootstrap); multilevel variants c.1990s | 1979–1990s |
| 提出者≠ | Efron (1979); multilevel extensions developed through 1980s–2000s | Bradley Efron (bootstrap); missing-data extensions by Efron, Little, Rubin and others |
| 类型≠ | resampling / simulation | Resampling simulation |
| 开创性文献≠ | Efron, 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 |
| 别名 | hierarchical bootstrap, cluster bootstrap, stratified bootstrap for multilevel data, multilevel resampling | bootstrap with missing data, bootstrap imputation simulation, resampling under missingness, bootstrap MI |
| 相关≠ | 6 | 5 |
| 摘要≠ | 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. |
| ScholarGate数据集 ↗ |
|
|