विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| बहु-समूह विभेदक मद कार्यप्रणाली (MG-DIF)× | पुष्टिकारीय कारक विश्लेषण (CFA)× | |
|---|---|---|
| क्षेत्र | मनोमिति | मनोमिति |
| परिवार | Latent structure | Latent structure |
| उद्भव वर्ष≠ | 1980s-1990s | 1969 |
| प्रवर्तक≠ | Shealy & Stout (SIBTEST framework); Lord (IRT-based DIF) | Karl Gustav Jöreskog |
| प्रकार≠ | Measurement bias detection | Hypothesis-testing latent variable model |
| मौलिक स्रोत≠ | Millsap, R. E. (2012). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936 | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| उपनाम | MG-DIF, multi-group DIF, differential item functioning across groups, multiple-group DIF analysis | CFA, confirmatory FA, measurement model, restricted factor analysis |
| संबंधित≠ | 6 | 4 |
| 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. | Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing. |
| ScholarGateडेटासेट ↗ |
|
|