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Ordinal Item Response Theory×Partial Credit Model (PCM / GPCM)×
ÄmnesområdePsykometriPsykometri
FamiljLatent structureLatent structure
Ursprungsår19691982
UpphovspersonFumiko Samejima (Graded Response Model, 1969); Gerhard Fischer & Georg Rasch lineage for partial creditGeoff N. Masters (PCM, 1982); Eiji Muraki (GPCM, 1992)
TypProbabilistic latent trait model for ordered polytomous responsesItem Response Theory / Polytomous IRT
UrsprungskällaSamejima, F. (1969). Estimation of latent ability using a response pattern of graded scores. Psychometrika Monograph Supplement, 34(4, Pt. 2), 1–97. link ↗Masters, G. N. (1982). A Rasch model for partial credit scoring. Psychometrika, 47(2), 149–174. DOI ↗
Aliaspolytomous IRT, ordinal IRT models, graded response models, ordinal latent trait modelsKısmi Kredi Modeli (PCM / GPCM), Generalized Partial Credit Model, GPCM, PCM
Närliggande65
SammanfattningOrdinal 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.The Partial Credit Model is an extension of the Rasch measurement framework designed for ordered polytomous items — items whose responses fall into more than two ordered categories, such as partial-credit tasks in performance assessment or open-ended scoring rubrics. Proposed by Geoff Masters in 1982 and later generalised by Eiji Muraki in 1992, the model estimates a separate threshold (step) parameter for each adjacent-category transition within every item, allowing fine-grained calibration of how much each additional credit level contributes to locating a person on the latent trait.
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ScholarGateJämför metoder: Ordinal IRT · PCM / GPCM. Hämtad 2026-06-19 från https://scholargate.app/sv/compare