Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Адаптивная многоступенчатая выборка× | Многоступенчатая выборка× | |
|---|---|---|
| Область | Методология опросов | Методология опросов |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1977 (multistage base); 1990-1992 (adaptive extensions by Thompson) | 1950s–1960s (formalized in Kish 1965 and Cochran 1977) |
| Автор метода≠ | Steven K. Thompson (adaptive principles); William G. Cochran (multistage framework) | Leslie Kish; William G. Cochran |
| Тип≠ | Probability-based adaptive sampling design | Probability sampling design |
| Основополагающий источник≠ | Thompson, S. K. (1992). Sampling. Wiley. ISBN: 978-0471548850 | Kish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471109495 |
| Другие названия | AMS, adaptive multi-phase sampling, sequential multistage sampling, adaptive hierarchical sampling | multistage cluster sampling, multi-stage sampling, nested sampling, hierarchical sampling |
| Связанные | 5 | 5 |
| Сводка≠ | Adaptive multistage sampling combines the hierarchical efficiency of multistage designs with adaptive decision rules that adjust which units are sampled at later stages based on what is observed at earlier stages. It is used when a target characteristic is rare, clustered, or spatially heterogeneous and a fixed design would waste resources on uninformative areas of the population. | Multistage sampling is a probability-based design that selects a sample by working through two or more successive levels of a population hierarchy — for example, first selecting regions, then districts within those regions, then households within those districts. It makes large-scale surveys practical when a complete population list is unavailable or when the population is geographically dispersed, by concentrating fieldwork within a manageable number of sampled units at each stage. |
| ScholarGateНабор данных ↗ |
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