विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| बहुस्तरीय अभिसारी वैधता× | पुष्टिकारीय कारक विश्लेषण (CFA)× | |
|---|---|---|
| क्षेत्र | मनोमिति | मनोमिति |
| परिवार | Latent structure | Latent structure |
| उद्भव वर्ष≠ | 2005 | 1969 |
| प्रवर्तक≠ | Dyer, Hanges & Hall; Chen, Bliese & Mathieu | Karl Gustav Jöreskog |
| प्रकार≠ | Measurement validity evaluation | Hypothesis-testing latent variable model |
| मौलिक स्रोत≠ | Dyer, N. G., Hanges, P. J. & Hall, R. J. (2005). Applying multilevel confirmatory factor analysis techniques to the study of leadership. Leadership Quarterly, 16(1), 149–167. DOI ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| उपनाम≠ | cross-level convergent validity, multilevel measurement validity, between-level convergent validity | CFA, confirmatory FA, measurement model, restricted factor analysis |
| संबंधित | 4 | 4 |
| सारांश≠ | Multilevel convergent validity evaluates whether items or scales intended to measure the same construct show coherent, strong associations at each level of a nested data structure — within individuals, within groups, and between groups. It extends classical convergent validity from single-level measurement models into the multilevel confirmatory factor analysis (ML-CFA) framework. | 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. |
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