Comparer des méthodes

	Échantillonnage en grappes	Analyse factorielle exploratoire (AFE)
Domaine	Méthodologie d'enquête	Statistique
Famille	Process / pipeline	Latent structure
Année d'origine	Early-to-mid 20th century; canonical treatment 1953/1977	—
Auteur d'origine	Formalized by William G. Cochran; roots in early 20th-century U.S. Census Bureau survey practice	—
Type	Probability sampling design	Latent variable / dimension reduction
Source fondatrice	Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley. ISBN: 978-0471162407	Fabrigar, L. R., Wegener, D. T., MacCallum, R. C. & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299.
Alias	cluster random sampling, area sampling, one-stage cluster sampling	common factor analysis, açımlayıcı faktör analizi, factor analysis
Apparentées	5	4
Résumé	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.	Exploratory factor analysis reduces a large set of observed variables into a smaller number of latent common factors. It is widely used in scale development and psychometrics to uncover the dimensional structure that underlies a set of correlated items, without specifying that structure in advance.