Comparer des méthodes

	Échantillonnage pondéré proportionnel	Échantillonnage à plusieurs degrés
Domaine	Méthodologie d'enquête	Méthodologie d'enquête
Famille	Process / pipeline	Process / pipeline
Année d'origine	Mid-20th century (formalized 1950s–1960s)	1950s–1960s (formalized in Kish 1965 and Cochran 1977)
Auteur d'origine	William G. Cochran; 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	proportional probability weighting, proportional weight sampling, probability proportional to size sampling, PPS sampling	multistage cluster sampling, multi-stage sampling, nested sampling, hierarchical sampling
Apparentées	6	5
Résumé	Proportional weighted sampling is a probability-based survey design in which each subgroup (stratum or cluster) of the population is sampled and weighted in proportion to its true size in the population. By assigning sampling weights that mirror the actual composition of the population, the method ensures unbiased estimates without the need for post-hoc reweighting, and produces efficient estimates when variance within subgroups is relatively homogeneous.	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.