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	Analiza moderacji bayesowskiej	Bayesowska moderowana mediacja	Analiza mediacji moderowanej
Dziedzina	Statystyka	Statystyka	Statystyka
Rodzina	Latent structure	Latent structure	Latent structure
Rok powstania	2000s–2010s	2009–2013	2007
Twórca	Bayesian framework applied to moderation by Kruschke, Gelman and colleagues	Yuan & MacKinnon (Bayesian mediation); Hayes (conditional process framework)	Preacher, Rucker & Hayes
Typ	Interaction / moderator test	Conditional indirect effect model	Conditional process model
Źródło pierwotne	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.	Hayes, A. F. (2018). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (2nd ed.). Guilford Press. ISBN: 978-1462534654
Inne nazwy	Bayesian interaction analysis, Bayesian moderated regression, Bayesian moderator testing, BMA	Bayesian conditional process analysis, Bayesian mediated moderation, Bayesian PROCESS model, Bayesian conditional indirect effect	conditional process analysis, moderated mediation model, first-stage moderated mediation, second-stage moderated mediation
Pokrewne	2	4	4
Podsumowanie	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.	Moderated mediation tests whether the indirect effect of an independent variable on an outcome — transmitted through a mediator — differs in strength depending on the level of a moderator variable. It answers the question: for whom, or under what conditions, does the mediated pathway operate most strongly?