विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| बहु-समूह विभेदक मद कार्यप्रणाली (MG-DIF)× | आइटम रिस्पांस थ्योरी (IRT)× | |
|---|---|---|
| क्षेत्र | मनोमिति | मनोमिति |
| परिवार | Latent structure | Latent structure |
| उद्भव वर्ष≠ | 1980s-1990s | 1952–1968 |
| प्रवर्तक≠ | Shealy & Stout (SIBTEST framework); Lord (IRT-based DIF) | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| प्रकार≠ | Measurement bias detection | Probabilistic measurement model |
| मौलिक स्रोत≠ | Millsap, R. E. (2012). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936 | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| उपनाम | MG-DIF, multi-group DIF, differential item functioning across groups, multiple-group DIF analysis | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| संबंधित≠ | 6 | 5 |
| सारांश≠ | Multi-group differential item functioning examines whether test or scale items function equivalently across three or more distinct groups — such as gender, ethnicity, or country — after matching respondents on the underlying trait being measured. Items that behave differently across groups threaten fair measurement and valid 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. |
| ScholarGateडेटासेट ↗ |
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