विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| बाइफैक्टर मॉडल (सामान्य और विशिष्ट कारक)× | अन्वेषणात्मक कारक विश्लेषण (EFA)× | |
|---|---|---|
| क्षेत्र≠ | मनोमिति | सांख्यिकी |
| परिवार | Latent structure | Latent structure |
| उद्भव वर्ष≠ | 1937 | — |
| प्रवर्तक≠ | Holzinger & Swineford (1937); modern revival by Reise (2012) | — |
| प्रकार≠ | Confirmatory latent variable model | Latent variable / dimension reduction |
| मौलिक स्रोत≠ | Reise, S. P. (2012). The Rediscovery of Bifactor Measurement Models. Multivariate Behavioral Research, 47(5), 667–696. DOI ↗ | 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≠ | Bifaktör Modeli — Genel ve Spesifik Faktörler, hierarchical factor model, general-specific factor model, Schmid-Leiman model | common factor analysis, açımlayıcı faktör analizi, factor analysis |
| संबंधित≠ | 6 | 4 |
| सारांश≠ | The bifactor measurement model specifies that every indicator loads simultaneously on a single general factor and on one of several specific (group) factors. Formally introduced by Holzinger and Swineford in 1937 and brought into mainstream psychometrics by Reise (2012), it is now the standard tool for evaluating whether a multidimensional scale can legitimately yield a single composite score. | 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. |
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