ScholarGate
دستیار

مقایسهٔ روش‌ها

روش‌های انتخابی خود را کنار هم مرور کنید؛ ردیف‌های متفاوت برجسته شده‌اند.

نظریه پاسخ آیت ترتیبی×نظریه پاسخ به سنجش (IRT)×
حوزهروان‌سنجیروان‌سنجی
خانوادهLatent structureLatent structure
سال پیدایش19691952–1968
پدیدآورFumiko Samejima (Graded Response Model, 1969); Gerhard Fischer & Georg Rasch lineage for partial creditFrederic M. Lord (and Allan Birnbaum for the 2PL/3PL models)
نوعProbabilistic latent trait model for ordered polytomous responsesProbabilistic measurement model
منبع بنیادینSamejima, F. (1969). Estimation of latent ability using a response pattern of graded scores. Psychometrika Monograph Supplement, 34(4, Pt. 2), 1–97. link ↗Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗
نام‌های دیگرpolytomous IRT, ordinal IRT models, graded response models, ordinal latent trait modelsIRT, latent trait theory, item characteristic curve theory, modern test theory
مرتبط65
خلاصهOrdinal 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.Item response theory models the probability that a respondent answers an item correctly (or endorses it) as a function of the respondent's latent trait level and the item's own statistical properties — difficulty, discrimination, and guessing. Unlike classical test theory, IRT places persons and items on the same scale, yielding measurement that is sample-independent for items and test-independent for persons.
ScholarGateمجموعه‌داده
  1. v1
  2. 2 منابع
  3. PUBLISHED
  1. v1
  2. 2 منابع
  3. PUBLISHED

رفتن به جست‌وجو دریافت اسلایدها

ScholarGateمقایسهٔ روش‌ها: Ordinal IRT · Item Response Theory. بازیابی‌شده در 2026-06-19 از https://scholargate.app/fa/compare