Comparer des méthodes

	Échantillonnage en grappes multi-niveaux	Échantillonnage aléatoire simple
Domaine	Méthodologie d'enquête	Méthodologie d'enquête
Famille	Process / pipeline	Process / pipeline
Année d'origine	1950s-1970s (cluster sampling); multilevel extension formalized 1980s-1990s	Early 20th century; systematized by Cochran 1953/1977
Auteur d'origine	W. G. Cochran (cluster sampling foundations); extended into multilevel contexts by survey methodologists	William Gosset, Jerzy Neyman, and formalized by William Cochran
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	SRS, unrestricted random sampling, equal-probability sampling, EPSEM
Apparentées	6	6
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.	Simple random sampling (SRS) is the foundational probability sampling method in which every unit in the population has an equal and independent chance of being selected. Because selection is governed purely by chance, SRS eliminates systematic bias, supports unbiased estimation of population parameters, and provides the statistical baseline against which all more complex probability designs are evaluated.