Сравнение методов

	Байесовская модерируемая медиация	Байесовский анализ модерации
Область	Статистика	Статистика
Семейство	Latent structure	Latent structure
Год появления	2009–2013	2000s–2010s
Автор метода	Yuan & MacKinnon (Bayesian mediation); Hayes (conditional process framework)	Bayesian framework applied to moderation by Kruschke, Gelman and colleagues
Тип	Conditional indirect effect model	Interaction / moderator test
Основополагающий источник	Yuan, Y. & MacKinnon, D. P. (2009). Bayesian mediation analysis. Psychological Methods, 14(4), 301–322.	Hayes, A. F. (2018). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (2nd ed.). Guilford Press. ISBN: 978-1462534654
Другие названия	Bayesian conditional process analysis, Bayesian mediated moderation, Bayesian PROCESS model, Bayesian conditional indirect effect	Bayesian interaction analysis, Bayesian moderated regression, Bayesian moderator testing, BMA
Связанные	4	2
Сводка	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.	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.