विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| बहु-समूह राश मॉडल× | आइटम रिस्पांस थ्योरी (IRT)× | |
|---|---|---|
| क्षेत्र | मनोमिति | मनोमिति |
| परिवार | Latent structure | Latent structure |
| उद्भव वर्ष≠ | 1960 (Rasch); 1980s–1990s (multi-group extensions) | 1952–1968 |
| प्रवर्तक≠ | Georg Rasch (single-group); extended to multi-group applications by Fischer, Molenaar, and others | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| प्रकार≠ | Item response model / measurement invariance test | Probabilistic measurement model |
| मौलिक स्रोत≠ | Fischer, G. H. & Molenaar, I. W. (Eds.) (1995). Rasch Models: Foundations, Recent Developments, and Applications. Springer. ISBN: 978-0387944296 | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| उपनाम | MG-Rasch, Rasch measurement invariance, multi-group 1PL IRT, cross-group Rasch analysis | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| संबंधित≠ | 6 | 5 |
| सारांश≠ | The multi-group Rasch model fits the one-parameter logistic item response model simultaneously across two or more distinct groups, testing whether item difficulty parameters are invariant across groups. It is the primary psychometric tool for establishing that a scale measures the same latent trait with the same metric in each group, a prerequisite for meaningful score comparisons. | 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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