Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Échantillonnage par ensembles classés× | Échantillonnage en grappes× | |
|---|---|---|
| Domaine≠ | Échantillonnage | Méthodologie d'enquête |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | 1952 | Early-to-mid 20th century; canonical treatment 1953/1977 |
| Auteur d'origine≠ | Glenn A. McIntyre | Formalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice |
| Type≠ | Sampling design methodology | Probability sampling design |
| Source fondatrice≠ | McIntyre, G. A. (1952). A method for unbiased selective sampling using ranked sets. Australian Journal of Agricultural Research, 3(4), 385–390. DOI ↗ | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407 |
| Alias≠ | RSS | cluster random sampling, area sampling, one-stage cluster sampling |
| Apparentées≠ | 4 | 5 |
| Résumé≠ | 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. | 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. |
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