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Théorie de la généralisabilité appliquée aux tests adaptatifs informatisés×Analyse de fiabilité multiniveau×
DomainePsychométriePsychométrie
FamilleLatent structureLatent structure
Année d'origine1972 (G-theory); CAT application 1990s–2000s2014
Auteur d'origineLee J. Cronbach (G-theory); applied to CAT by Brennan and othersGeldhof, Preacher & Zyphur
TypeReliability / generalizability analysisReliability estimation / psychometric modeling
Source fondatriceBrennan, R. L. (2001). Generalizability Theory. Springer. ISBN: 978-0387952826Geldhof, G. J., Preacher, K. J., & Zyphur, M. J. (2014). Reliability estimation in a multilevel confirmatory factor analysis framework. Psychological Methods, 19(1), 72–91. DOI ↗
AliasCAT G-theory, adaptive test generalizability, G-theory in CAT, computerized adaptive generalizability analysismultilevel omega, within-group reliability, between-group reliability, hierarchical reliability
Apparentées63
RésuméGeneralizability theory (G-theory) applied to computerized adaptive testing (CAT) evaluates the dependability of adaptive test scores by decomposing score variance across measurement facets such as persons, items, and occasions. Unlike classical test theory, G-theory quantifies multiple simultaneous sources of measurement error, offering a richer reliability picture for adaptively administered assessments.Multilevel reliability analysis estimates the internal consistency of scale scores separately at the within-group (individual) and between-group (cluster) levels. It corrects the bias that arises when ordinary alpha or omega is applied to hierarchically nested data, such as employees within organizations or students within classrooms.
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ScholarGateComparer des méthodes: CAT Generalizability Theory · Multilevel Reliability Analysis. Consulté le 2026-06-17 sur https://scholargate.app/fr/compare