Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Кластерная выборка× | Ранжированная выборка (Ranked Set Sampling)× | |
|---|---|---|
| Область≠ | Методология опросов | Выборка |
| Семейство | Process / pipeline | Process / pipeline |
| Год появления≠ | Early-to-mid 20th century; canonical treatment 1953/1977 | 1952 |
| Автор метода≠ | Formalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice | Glenn A. McIntyre |
| Тип≠ | Probability sampling design | Sampling design methodology |
| Основополагающий источник≠ | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407 | McIntyre, G. A. (1952). A method for unbiased selective sampling using ranked sets. Australian Journal of Agricultural Research, 3(4), 385–390. DOI ↗ |
| Другие названия≠ | cluster random sampling, area sampling, one-stage cluster sampling | RSS |
| Связанные≠ | 5 | 4 |
| Сводка≠ | Cluster sampling is a probability sampling technique in which the population is divided into naturally occurring groups (clusters), a random sample of clusters is selected, and all — or a random subset of — members within each selected cluster are studied. It is especially practical when a complete population list is unavailable or when units are geographically dispersed, making individual random selection prohibitively expensive. One-stage cluster sampling surveys every member of selected clusters; two-stage designs add a second random draw within clusters. | Ranked Set Sampling (RSS) is a data collection method introduced by G. A. McIntyre in 1952 that improves estimation efficiency when visual ranking of units is easier or cheaper than actual measurement. By deliberately selecting and measuring units that are ranked as most likely to yield desired outcomes, RSS reduces variance compared to simple random sampling while maintaining unbiasedness. |
| ScholarGateНабор данных ↗ |
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