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Many-Facet Rasch Measurement×Generalisoitavuusteoria (G-teoria)×
TieteenalaEducationPsykometriikka
MenetelmäperheLatent structureLatent structure
Syntyvuosi19891963–1972
KehittäjäJohn Michael LinacreLee J. Cronbach, Goldine Gleser, Harinder Nanda, Nageswari Rajaratnam
TyyppiRasch model extension adding rater and other facets to person and itemVariance-components reliability model
AlkuperäislähdeLinacre, J. M. (1989). Many-Facet Rasch Measurement. MESA Press. ISBN: 9780941938020Cronbach, L. J., Gleser, G. C., Nanda, H. & Rajaratnam, N. (1972). The Dependability of Behavioral Measurements: Theory of Generalizability for Scores and Profiles. Wiley. link ↗
RinnakkaisnimetMFRM, Many-Faceted Rasch Model, Facets Model, Linacre Facets ModelG-theory, G-study / D-study framework, variance components reliability
Liittyvät44
TiivistelmäMany-facet Rasch measurement (MFRM) extends the basic Rasch model to assessments mediated by raters. Beyond examinee ability and item difficulty, it adds explicit parameters for rater severity and for any other facet of the rating situation — task, occasion, rating criterion — placing them all on one common logit scale. Developed by John Michael Linacre, MFRM lets analysts estimate and adjust for the fact that some raters are systematically harsh and others lenient, producing 'fair' ability estimates that do not penalize an examinee for happening to draw a severe judge.Generalizability Theory is a psychometric framework that decomposes observed score variance into multiple sources — persons, items, raters, occasions, and their interactions — using analysis of variance. It replaces the single reliability coefficient of classical test theory with a family of coefficients that tell researchers how well scores generalize across different measurement conditions.
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ScholarGateVertaile menetelmiä: Many-Facet Rasch Measurement · Generalizability Theory. Haettu 2026-06-25 osoitteesta https://scholargate.app/fi/compare