Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Пропорциональная многоступенчатая выборка× | Многоступенчатая выборка× | |
|---|---|---|
| Область | Методология опросов | Методология опросов |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | 1950s–1960s | 1950s–1960s (formalized in Kish 1965 and Cochran 1977) |
| Автор метода≠ | Leslie Kish; William G. Cochran (theoretical foundations) | Leslie Kish; William G. Cochran |
| Тип | Probability sampling design | Probability sampling design |
| Основополагающий источник≠ | Kish, L. (1965). Survey Sampling. John Wiley & Sons. (Chapters 6–7 on multistage and PPS designs.) ISBN: 978-0471489009 | Kish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471109495 |
| Другие названия | proportional PPS multistage sampling, multistage probability proportional to size sampling, proportionate multistage cluster sampling, PPS multistage sampling | multistage cluster sampling, multi-stage sampling, nested sampling, hierarchical sampling |
| Связанные≠ | 6 | 5 |
| Сводка≠ | Proportional multistage sampling is a probability sampling design that selects units across two or more hierarchical stages — for example, regions, then districts, then households — where the number of units drawn at each stage is proportional to the size of each higher-level unit. By weighting selection probabilities to match cluster size, it produces self-weighting samples that closely mirror the population structure and simplify variance estimation. | 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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