विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| अनुदैर्ध्य सामान्यीकरण सिद्धांत× | अन्वेषणात्मक कारक विश्लेषण (EFA)× | |
|---|---|---|
| क्षेत्र≠ | मनोमिति | सांख्यिकी |
| परिवार | Latent structure | Latent structure |
| उद्भव वर्ष≠ | 1990s–2000s | — |
| प्रवर्तक≠ | Webb, Shavelson, and colleagues, building on Cronbach et al. (1963) G-theory foundations | — |
| प्रकार≠ | Variance components / reliability estimation | Latent variable / dimension reduction |
| मौलिक स्रोत≠ | Webb, N. M., Shavelson, R. J., & Harrigan, E. H. (2007). Generalizability theory: Overview. In C. R. Rao & S. Sinharay (Eds.), Handbook of Statistics, Vol. 26: Psychometrics (pp. 1–43). Elsevier. link ↗ | Fabrigar, L. R., Wegener, D. T., MacCallum, R. C. & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299. DOI ↗ |
| उपनाम≠ | longitudinal G-theory, longitudinal GT, repeated-measures generalizability theory, G-theory for longitudinal designs | common factor analysis, açımlayıcı faktör analizi, factor analysis |
| संबंधित | 4 | 4 |
| सारांश≠ | Longitudinal generalizability theory extends classical G-theory to repeated-measures and longitudinal designs, decomposing score variance across persons, measurement occasions, raters, and items simultaneously. It quantifies how reliably scores can be generalized across time points, evaluators, and conditions — information that is invisible to cross-sectional reliability indices. | Exploratory factor analysis reduces a large set of observed variables into a smaller number of latent common factors. It is widely used in scale development and psychometrics to uncover the dimensional structure that underlies a set of correlated items, without specifying that structure in advance. |
| ScholarGateडेटासेट ↗ |
|
|