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	ベイジアン尺度開発	因子分析（EFA）
分野	心理測定学	統計学
系統	Latent structure	Latent structure
提唱年	1990s–2000s	—
提唱者	Harold Jeffreys, expanded into psychometrics by Mislevy and colleagues	—
種類	Bayesian probabilistic scale construction	Latent variable / dimension reduction
原典	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.
別名	Bayesian psychometric scale construction, Bayesian measurement modeling, Bayesian item development, BSD	common factor analysis, açımlayıcı faktör analizi, factor analysis
関連	5	4
概要	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.