Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Échantillonnage en grappes multi-niveaux× | Échantillonnage systématique× | |
|---|---|---|
| Domaine | Méthodologie d'enquête | Méthodologie d'enquête |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | 1950s-1970s (cluster sampling); multilevel extension formalized 1980s-1990s | Mid-20th century (Cochran 1953; Kish 1965) |
| Auteur d'origine≠ | W. G. Cochran (cluster sampling foundations); extended into multilevel contexts by survey methodologists | William G. Cochran; formalized in survey sampling theory |
| Type | Probability sampling design | Probability sampling design |
| Source fondatrice≠ | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407 | Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407 |
| Alias | hierarchical cluster sampling, nested cluster sampling, multi-stage cluster sampling, clustered multilevel sampling | interval sampling, systematic random sampling, equal-interval sampling, fixed-interval sampling |
| Apparentées≠ | 6 | 5 |
| Résumé≠ | Multi-level cluster sampling is a probability sampling design for hierarchically structured populations — such as students nested within classrooms within schools within districts. Clusters are randomly selected at each level of the hierarchy before individual units are sampled within the final-level clusters. The design mirrors the natural nesting of real-world populations and enables efficient large-scale data collection while supporting multilevel statistical analysis. | Systematic sampling is a probability sampling technique in which every k-th element is selected from an ordered list of the population after a random starting point. With population size N and desired sample size n, the sampling interval k = N/n is computed and one unit is chosen at random from the first interval; all subsequent units are selected by adding k repeatedly. The method is operationally simple, yields a spread-out sample, and often achieves lower variance than simple random sampling when the list has no harmful periodicity. |
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