方法对比

	贝叶斯量表开发	项目反应理论 (IRT)
领域	心理测量学	心理测量学
方法族	Latent structure	Latent structure
起源年份	1990s–2000s	1952–1968
提出者	Harold Jeffreys, expanded into psychometrics by Mislevy and colleagues	Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models)
类型	Bayesian probabilistic scale construction	Probabilistic measurement model
开创性文献	De Ayala, R. J. (2009). The Theory and Practice of Item Response Theory. Guilford Press. ISBN: 978-1593858698	Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley.
别名	Bayesian psychometric scale construction, Bayesian measurement modeling, Bayesian item development, BSD	IRT, latent trait theory, item characteristic curve theory, modern test theory
相关	5	5
摘要	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.	Item response theory models the probability that a respondent answers an item correctly (or endorses it) as a function of the respondent's latent trait level and the item's own statistical properties — difficulty, discrimination, and guessing. Unlike classical test theory, IRT places persons and items on the same scale, yielding measurement that is sample-independent for items and test-independent for persons.