Comparer des méthodes

	Cultural Consensus Model	Analyse factorielle
Domaine	Anthropology	Statistiques de recherche
Famille	Latent structure	Process / pipeline
Année d'origine	1986	1931
Auteur d'origine	A. Kimball Romney, Susan C. Weller & William H. Batchelder	Louis Leon Thurstone
Type	Latent-structure measurement model for shared cultural knowledge	Method
Source fondatrice	Romney, A. K., Weller, S. C., & Batchelder, W. H. (1986). Culture as consensus: A theory of culture and informant accuracy. American Anthropologist, 88(2), 313–338.	Thurstone, L. L. (1947). Multiple Factor Analysis. University of Chicago Press.
Alias	Cultural Consensus Theory, CCT, Consensus Analysis, Informant Accuracy Model	EFA, CFA, latent variable modeling
Apparentées	4	3
Résumé	The cultural consensus model is a latent-structure measurement framework that estimates the culturally shared answers to a set of questions and, simultaneously, how much each informant knows, without the researcher knowing the correct answers in advance. Introduced by Romney, Weller and Batchelder in 1986, it treats agreement among informants as evidence of shared knowledge and uses a factor-analytic (or, in modern variants, Bayesian) decomposition to recover both a single 'answer key' and an informant-specific competence score.	Factor analysis is a statistical technique for identifying latent (unobserved) dimensions underlying observed variables, developed by Louis Leon Thurstone in the 1930s and formalized by Jöreskog (1969). Exploratory factor analysis (EFA) discovers unknown factor structure from data; confirmatory factor analysis (CFA) tests hypothesized relationships between observed and latent variables. Essential in psychometrics (test development), organizational research (measuring constructs like leadership style), and biomedicine (identifying disease subtypes), factor analysis reduces dimensionality while revealing conceptual organization in multivariate data.