विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| बहुस्तरीय विभेदक आइटम कार्यप्रणाली (Multilevel DIF)× | बहुस्तरीय मापन निश्चरता (Multilevel Measurement Invariance)× | |
|---|---|---|
| क्षेत्र | मनोमिति | मनोमिति |
| परिवार | Latent structure | Latent structure |
| उद्भव वर्ष≠ | 2001 | 2000s |
| प्रवर्तक≠ | Kamata (2001) and subsequent multilevel IRT/DIF literature | Muthén, Asparouhov, and colleagues |
| प्रकार≠ | Bias detection / multilevel measurement model | Measurement model evaluation |
| मौलिक स्रोत≠ | French, B. F., & Finch, W. H. (2008). Multigroup confirmatory factor analysis: Locating the invariant referent sets. Structural Equation Modeling: A Multidisciplinary Journal, 15(1), 96–113. DOI ↗ | Muthén, B. O., & Asparouhov, T. (2009). Multilevel factor analysis of class and student achievement components. Journal of Educational and Behavioral Statistics, 34(2), 250–270. link ↗ |
| उपनाम | multilevel DIF, hierarchical DIF analysis, cross-level DIF, ML-DIF | MLMI, multilevel factorial invariance, cross-level measurement invariance, multilevel CFA invariance |
| संबंधित≠ | 5 | 3 |
| सारांश≠ | Multilevel DIF analysis detects whether individual test or survey items function differently across groups when respondents are clustered within higher-level units — such as students nested in schools, employees in organizations, or patients in clinics. By accounting for hierarchical data structure, it separates genuine item bias from artificial DIF signals caused by ignoring clustering. | Multilevel measurement invariance testing evaluates whether a latent construct is measured equivalently both within clusters (e.g., individuals within teams) and between clusters (e.g., team-level aggregates). It extends standard measurement invariance procedures to nested data structures commonly encountered in organisational, educational, and cross-cultural research. |
| ScholarGateडेटासेट ↗ |
|
|