Σύγκριση μεθόδων

	Μπεϋζιανή Ανάλυση Μετριασμού	Μπεϋζιανή Μετριαζόμενη Διαμεσολάβηση	Ανώμαλη Ανάλυση Διαμεσολάβησης
Πεδίο	Στατιστική	Στατιστική	Στατιστική
Οικογένεια	Latent structure	Latent structure	Latent structure
Έτος προέλευσης	2000s–2010s	2009–2013	2007
Δημιουργός	Bayesian framework applied to moderation by Kruschke, Gelman and colleagues	Yuan & MacKinnon (Bayesian mediation); Hayes (conditional process framework)	Preacher, Rucker & Hayes
Τύπος	Interaction / moderator test	Conditional indirect effect model	Conditional process model
Θεμελιώδης πηγή	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
Εναλλακτικές ονομασίες	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
Συναφείς	2	4	4
Σύνοψη	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?