Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Политомическая валидность конструкта× | Модель частичного зачёта (PCM / GPCM)× | |
|---|---|---|
| Область | Психометрия | Психометрия |
| Семейство | Latent structure | Latent structure |
| Год появления≠ | 1992–2000 | 1982 |
| Автор метода≠ | Building on Messick (1989) and IRT extensions by Masters, Muraki, and Samejima | Geoff N. Masters (PCM, 1982); Eiji Muraki (GPCM, 1992) |
| Тип≠ | Psychometric validity framework | Item Response Theory / Polytomous IRT |
| Основополагающий источник≠ | Muraki, E. (1992). A generalized partial credit model: Application of an EM algorithm. Applied Psychological Measurement, 16(2), 159–176. DOI ↗ | Masters, G. N. (1982). A Rasch model for partial credit scoring. Psychometrika, 47(2), 149–174. DOI ↗ |
| Другие названия | polytomous item construct validity, ordered-category construct validity, polytomous measurement validity, multi-category scale validity | Kısmi Kredi Modeli (PCM / GPCM), Generalized Partial Credit Model, GPCM, PCM |
| Связанные≠ | 6 | 5 |
| Сводка≠ | Polytomous construct validity refers to the evaluation of whether a scale composed of ordered, multi-category items (e.g., Likert or rating-scale items) genuinely measures the intended latent construct. It extends classical validity frameworks to polytomous measurement models — such as the Graded Response Model or Generalized Partial Credit Model — ensuring that ordered response categories function as designed and that the resulting scores reflect the target construct. | 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. |
| ScholarGateНабор данных ↗ |
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