Comparer des méthodes

	Échantillonnage à plusieurs degrés	Échantillonnage en grappes
Domaine	Méthodologie d'enquête	Méthodologie d'enquête
Famille	Process / pipeline	Process / pipeline
Année d'origine	1950s–1960s (formalized in Kish 1965 and Cochran 1977)	Early-to-mid 20th century; canonical treatment 1953/1977
Auteur d'origine	Leslie Kish; William G. Cochran	Formalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice
Type	Probability sampling design	Probability sampling design
Source fondatrice	Kish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471109495	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407
Alias	multistage cluster sampling, multi-stage sampling, nested sampling, hierarchical sampling	cluster random sampling, area sampling, one-stage cluster sampling
Apparentées	5	5
Résumé	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.	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.