ScholarGate
Assistant

Comparer des méthodes

Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.

Analyse Factorielle Confirmatoire (AFC)×Alpha de Cronbach (Analyse de fiabilité)×Analyse factorielle exploratoire (AFE)×
DomaineStatistiqueStatistiqueStatistique
FamilleLatent structureLatent structureLatent structure
Année d'origine19691951
Auteur d'origineKarl JöreskogLee J. Cronbach
TypeConfirmatory latent variable modelReliability / internal consistency coefficientLatent variable / dimension reduction
Source fondatriceBrown, T. A. (2015). Confirmatory Factor Analysis for Applied Research (2nd ed.). The Guilford Press. ISBN: 978-1462515363Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297–334. DOI ↗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. DOI ↗
AliasDoğrulayıcı Faktör Analizi (CFA), confirmatory factor analysis, measurement modelcoefficient alpha, alpha reliability, internal consistency reliability, Güvenilirlik Analizi (Cronbach Alpha)common factor analysis, açımlayıcı faktör analizi, factor analysis
Apparentées444
RésuméConfirmatory factor analysis tests whether a researcher-specified factor structure fits the observed data. Formalised by Karl Jöreskog in 1969, it is the measurement-model step within structural equation modelling and is the standard tool for validating the factorial structure of scales and questionnaires before comparing groups or estimating latent relationships.Cronbach's alpha is a coefficient of internal consistency that quantifies the degree to which a set of items on a scale measures the same underlying construct. Introduced by Lee J. Cronbach in 1951, it remains the most widely reported reliability index in social-science, health, and educational research.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.
ScholarGateJeu de données
  1. v1
  2. 2 Sources
  3. PUBLISHED
  1. v1
  2. 2 Sources
  3. PUBLISHED
  1. v2
  2. 2 Sources
  3. PUBLISHED

Aller à la recherche Télécharger les diapositives

ScholarGateComparer des méthodes: CFA · Cronbach's Alpha · EFA. Consulté le 2026-06-18 sur https://scholargate.app/fr/compare