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Ordinal Generalizability Theory×Ordinal Item Response Theory×
FagområdePsykometriPsykometri
FamilieLatent structureLatent structure
Oprindelsesår1963–20011969
OphavspersonLee J. Cronbach and Robert L. BrennanFumiko Samejima (Graded Response Model, 1969); Gerhard Fischer & Georg Rasch lineage for partial credit
TypeReliability / generalizability analysisProbabilistic latent trait model for ordered polytomous responses
Oprindelig kildeBrennan, R. L. (2001). Generalizability Theory. Springer. ISBN: 978-0387952826Samejima, F. (1969). Estimation of latent ability using a response pattern of graded scores. Psychometrika Monograph Supplement, 34(4, Pt. 2), 1–97. link ↗
AliasserOrdinal G-theory, G-theory for ordinal data, ordinal variance component analysis, G-study for ordered categorical datapolytomous IRT, ordinal IRT models, graded response models, ordinal latent trait models
Relaterede56
ResuméOrdinal 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.
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ScholarGateSammenlign metoder: Ordinal Generalizability Theory · Ordinal IRT. Hentet 2026-06-19 fra https://scholargate.app/da/compare