विधियों की तुलना करें

	बायेसियन स्केल डेवलपमेंट	अन्वेषणात्मक कारक विश्लेषण (EFA)
क्षेत्र	मनोमिति	सांख्यिकी
परिवार	Latent structure	Latent structure
उद्भव वर्ष	1990s–2000s	—
प्रवर्तक	Harold Jeffreys, expanded into psychometrics by Mislevy and colleagues	—
प्रकार	Bayesian probabilistic scale construction	Latent variable / dimension reduction
मौलिक स्रोत	De Ayala, R. J. (2009). The Theory and Practice of Item Response Theory. Guilford Press. ISBN: 978-1593858698	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.
उपनाम	Bayesian psychometric scale construction, Bayesian measurement modeling, Bayesian item development, BSD	common factor analysis, açımlayıcı faktör analizi, factor analysis
संबंधित	5	4
सारांश	Bayesian scale development applies Bayesian statistical inference to the construction and evaluation of psychometric scales. Rather than relying on single point estimates of item and person parameters, it produces full posterior distributions that quantify uncertainty, incorporate prior knowledge, and support principled decisions about item retention, reliability, and validity in small or complex samples.	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.