Comparer des méthodes

	Théorie de la généralisabilité ordinale	Théorie de la Réponse à l'Item Ordinal
Domaine	Psychométrie	Psychométrie
Famille	Latent structure	Latent structure
Année d'origine	1963–2001	1969
Auteur d'origine	Lee J. Cronbach and Robert L. Brennan	Fumiko Samejima (Graded Response Model, 1969); Gerhard Fischer & Georg Rasch lineage for partial credit
Type	Reliability / generalizability analysis	Probabilistic latent trait model for ordered polytomous responses
Source fondatrice	Brennan, R. L. (2001). Generalizability Theory. Springer. ISBN: 978-0387952826	Samejima, F. (1969). Estimation of latent ability using a response pattern of graded scores. Psychometrika Monograph Supplement, 34(4, Pt. 2), 1–97.
Alias	Ordinal G-theory, G-theory for ordinal data, ordinal variance component analysis, G-study for ordered categorical data	polytomous IRT, ordinal IRT models, graded response models, ordinal latent trait models
Apparentées	5	6
Résumé	Ordinal generalizability theory extends classical G-theory to the analysis of reliability and measurement error when item responses are ordered categorical (e.g., Likert-type) rather than continuous. It partitions score variance into components attributable to persons, facets, and their interactions, while accounting for the discrete, bounded nature of ordinal rating scales.	Ordinal item response theory (ordinal IRT) comprises a family of probabilistic models — most notably the Graded Response Model and the Partial Credit Model — that relate a respondent's standing on a latent trait to the probability of choosing each ordered response category on a polytomous item. It extends classical IRT beyond dichotomous items to the Likert-type and rating-scale items that dominate psychometric measurement.