Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Hierarchical Bootstrap Simulation× | Daudzlīmeņu Bootstrap simulācija× | |
|---|---|---|
| Nozare | Bajesa metodes | Bajesa metodes |
| Saime | Bayesian methods | Bayesian methods |
| Izcelsmes gads≠ | 1997-2008 | 1979 (bootstrap); multilevel variants c.1990s |
| Autors≠ | Davison & Hinkley; Cameron, Gelbach & Miller | Efron (1979); multilevel extensions developed through 1980s–2000s |
| Tips≠ | resampling simulation | resampling / simulation |
| Pirmavots≠ | 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. DOI ↗ |
| Citi nosaukumi | cluster bootstrap, multilevel bootstrap, nested bootstrap resampling, hierarchical resampling | hierarchical bootstrap, cluster bootstrap, stratified bootstrap for multilevel data, multilevel resampling |
| Saistītās≠ | 5 | 6 |
| Kopsavilkums≠ | 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. |
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