विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| स्केल विकास के लिए अन्वेषणात्मक कारक विश्लेषण (EFA)× | पुष्टिकारीय कारक विश्लेषण (CFA)× | |
|---|---|---|
| क्षेत्र | मनोमिति | मनोमिति |
| परिवार | Latent structure | Latent structure |
| उद्भव वर्ष≠ | 1904 (foundational); contemporary scale-development practice from 1990s onward | 1969 |
| प्रवर्तक≠ | Primarily Spearman (1904); psychometric scale application formalised by Thurstone (1930s) | Karl Gustav Jöreskog |
| प्रकार≠ | Latent variable / dimension reduction | Hypothesis-testing latent variable model |
| मौलिक स्रोत≠ | Costello, A. B. & Osborne, J. W. (2005). Best practices in exploratory factor analysis: Four recommendations for getting the most from your analysis. Practical Assessment, Research & Evaluation, 10(7), 1–9. link ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| उपनाम≠ | Açımlayıcı Faktör Analizi — Ölçek Geliştirme (EFA), psychometric EFA, scale construction factor analysis | CFA, confirmatory FA, measurement model, restricted factor analysis |
| संबंधित≠ | 5 | 4 |
| सारांश≠ | Exploratory Factor Analysis for Scale Development is the psychometric application of EFA in which an item pool is administered and the resulting response data are analysed to discover the latent factor structure underlying the items. Originating with Spearman's (1904) factor theory and formalised for applied scale construction by Costello and Osborne (2005) and Fabrigar and colleagues (1999), this variant imposes a stricter sample requirement (n ≥ 100, subject-to-item ratio ≥ 5) and a higher loading threshold (≥ 0.40) than general EFA, and it treats the recovered factor structure as a draft to be subsequently validated by confirmatory analysis. | 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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