विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| बहु-समूह मापन निश्चरता परीक्षण× | बहु-समूह पुष्टिकारी कारक विश्लेषण (MG-CFA)× | |
|---|---|---|
| क्षेत्र | मनोमिति | मनोमिति |
| परिवार | Latent structure | Latent structure |
| उद्भव वर्ष≠ | 1971–1993 | 1971 |
| प्रवर्तक≠ | Jöreskog, K. G. (1971); Meredith, W. (1993) | Karl Jöreskog |
| प्रकार≠ | Model comparison / hypothesis testing | Measurement model / invariance test |
| मौलिक स्रोत | Vandenberg, R. J. & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–70. DOI ↗ | Vandenberg, R. J. & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–70. DOI ↗ |
| उपनाम | measurement invariance, factorial invariance, cross-group invariance, MI testing | MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA |
| संबंधित | 6 | 6 |
| सारांश≠ | Multi-group measurement invariance testing examines whether a latent construct is measured in the same way across two or more distinct groups — such as cultures, genders, or age cohorts. It is a prerequisite for meaningful group comparisons of latent means or relationships, ensuring that observed score differences reflect true differences rather than measurement artifacts. | Multi-group confirmatory factor analysis tests whether a measurement model holds equivalently across two or more groups — such as cultures, genders, or time points. By imposing increasingly stringent equality constraints and comparing model fit, it determines whether comparisons of latent mean scores are justified. |
| ScholarGateडेटासेट ↗ |
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