Comparer des méthodes

	Échantillonnage en grappes proportionnel	Échantillonnage à plusieurs degrés
Domaine	Méthodologie d'enquête	Méthodologie d'enquête
Famille	Process / pipeline	Process / pipeline
Année d'origine	1950s–1960s	1950s–1960s (formalized in Kish 1965 and Cochran 1977)
Auteur d'origine	Formalized by William G. Cochran and Leslie Kish	Leslie Kish; William G. Cochran
Type	Probability sampling design	Probability sampling design
Source fondatrice	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). John Wiley & Sons. ISBN: 978-0471162407	Kish, L. (1965). Survey Sampling. John Wiley & Sons. ISBN: 978-0471109495
Alias	PPS cluster sampling, proportional-to-size cluster sampling, size-proportional cluster sampling, probability proportional to size sampling	multistage cluster sampling, multi-stage sampling, nested sampling, hierarchical sampling
Apparentées	6	5
Résumé	Proportional cluster sampling selects naturally occurring groups (clusters) from a population with probability proportional to each cluster's size, so that larger clusters have a higher chance of selection while every individual element retains an equal overall inclusion probability. This design efficiently handles large, geographically dispersed populations and is the backbone of national health, education, and social surveys worldwide.	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.