Compara mètodes
Revisa els mètodes seleccionats l'un al costat de l'altre; les files que difereixen es ressalten.
| Multilevel Item Response Theory× | Teoria de Resposta a l'Ítem (TRI)× | |
|---|---|---|
| Camp≠ | Education | Psicometria |
| Família | Latent structure | Latent structure |
| Any d'origen≠ | 2010 | 1952–1968 |
| Autor original≠ | Adams, Wilson & Wu; Fox & Glas; De Boeck & Wilson | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| Tipus≠ | Item response models with a multilevel structure on the latent ability | Probabilistic measurement model |
| Font seminal≠ | Fox, J.-P. (2010). Bayesian Item Response Modeling: Theory and Applications. Springer. DOI ↗ | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| Àlies | Multilevel IRT, MLIRT, Hierarchical IRT, Explanatory Item Response Models | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| Relacionats≠ | 4 | 5 |
| Resum≠ | Multilevel item response theory (MLIRT) joins two powerful frameworks: an IRT measurement model that turns item responses into a latent ability, and a multilevel structural model that explains how that ability varies across nested groups such as classrooms, schools, or countries. Instead of first scoring a test and then running a multilevel regression on the scores, MLIRT does both at once, so that measurement error in ability is properly carried into the group-level analysis. It is the rigorous way to study how student and school characteristics relate to a latent trait measured by a test. | 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. |
| ScholarGateConjunt de dades ↗ |
|
|