方法对比

	贝叶斯调节分析	贝叶斯调节中介
领域	统计学	统计学
方法族	Latent structure	Latent structure
起源年份	2000s–2010s	2009–2013
提出者	Bayesian framework applied to moderation by Kruschke, Gelman and colleagues	Yuan & MacKinnon (Bayesian mediation); Hayes (conditional process framework)
类型	Interaction / moderator test	Conditional indirect effect model
开创性文献	Hayes, A. F. (2018). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (2nd ed.). Guilford Press. ISBN: 978-1462534654	Yuan, Y. & MacKinnon, D. P. (2009). Bayesian mediation analysis. Psychological Methods, 14(4), 301–322.
别名	Bayesian interaction analysis, Bayesian moderated regression, Bayesian moderator testing, BMA	Bayesian conditional process analysis, Bayesian mediated moderation, Bayesian PROCESS model, Bayesian conditional indirect effect
相关	2	4
摘要	Bayesian moderation analysis tests whether the relationship between a predictor and an outcome changes depending on the value of a third variable (the moderator). By placing prior distributions on all model parameters and updating them with observed data, it yields full posterior distributions for the interaction effect — enabling direct probability statements about the moderation rather than binary significance decisions.	Bayesian moderated mediation estimates how a mediator transmits the effect of a predictor onto an outcome, and whether that indirect effect varies in size depending on a moderator variable — all within a Bayesian framework that quantifies uncertainty via posterior distributions rather than p-values and confidence intervals.