विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| आंशिक क्रेडिट मॉडल (PCM / GPCM)× | आइटम रिस्पांस थ्योरी (IRT)× | |
|---|---|---|
| क्षेत्र | मनोमिति | मनोमिति |
| परिवार | Latent structure | Latent structure |
| उद्भव वर्ष≠ | 1982 | 1952–1968 |
| प्रवर्तक≠ | Geoff N. Masters (PCM, 1982); Eiji Muraki (GPCM, 1992) | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| प्रकार≠ | Item Response Theory / Polytomous IRT | Probabilistic measurement model |
| मौलिक स्रोत≠ | Masters, G. N. (1982). A Rasch model for partial credit scoring. Psychometrika, 47(2), 149–174. DOI ↗ | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| उपनाम | Kısmi Kredi Modeli (PCM / GPCM), Generalized Partial Credit Model, GPCM, PCM | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| संबंधित | 5 | 5 |
| सारांश≠ | 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. | 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. |
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