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| 베이즈 중재 분석× | 베이지안 조절된 매개× | |
|---|---|---|
| 분야 | 통계학 | 통계학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 2000s–2010s | 2009–2013 |
| 창시자≠ | Bayesian framework applied to moderation by Kruschke, Gelman and colleagues | Yuan & MacKinnon (Bayesian mediation); Hayes (conditional process framework) |
| 유형≠ | Interaction / moderator test | Conditional indirect effect model |
| 원전≠ | 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. DOI ↗ |
| 별칭 | Bayesian interaction analysis, Bayesian moderated regression, Bayesian moderator testing, BMA | Bayesian conditional process analysis, Bayesian mediated moderation, Bayesian PROCESS model, Bayesian conditional indirect effect |
| 관련≠ | 2 | 4 |
| 요약≠ | 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. |
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