विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| अनुदैर्ध्य अन्वेषी कारक विश्लेषण (Longitudinal EFA)× | पुष्टिकारीय कारक विश्लेषण (CFA)× | |
|---|---|---|
| क्षेत्र | मनोमिति | मनोमिति |
| परिवार | Latent structure | Latent structure |
| उद्भव वर्ष≠ | 1970s–1983 | 1969 |
| प्रवर्तक≠ | John R. Nesselroade and colleagues (lifespan developmental tradition) | Karl Gustav Jöreskog |
| प्रकार≠ | Latent variable / dimension reduction across time | Hypothesis-testing latent variable model |
| मौलिक स्रोत≠ | Nesselroade, J. R. (1983). Temporal selection and factor invariance in the study of development and change. In P. B. Baltes & O. G. Brim (Eds.), Life-Span Development and Behavior (Vol. 5, pp. 59–87). Academic Press. link ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| उपनाम | LEFA, longitudinal factor analysis, repeated-measures EFA, panel EFA | CFA, confirmatory FA, measurement model, restricted factor analysis |
| संबंधित≠ | 6 | 4 |
| सारांश≠ | Longitudinal EFA applies exploratory factor analysis separately at each measurement occasion — or jointly across occasions — to discover whether the same latent factor structure emerges over time and whether factor loadings remain stable across waves. It is the foundational data-driven approach for examining structural change and continuity in panel and developmental research. | 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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