Vertaile menetelmiä
Tarkastele valitsemiasi menetelmiä rinnakkain; eroavat rivit korostetaan.
| Robustinen mediaatioanalyysi× | Moderoitu välitysanalyysi× | |
|---|---|---|
| Tieteenala | Tilastotiede | Tilastotiede |
| Menetelmäperhe | Latent structure | Latent structure |
| Syntyvuosi≠ | 2008–2014 | 2007 |
| Kehittäjä≠ | Yuan & MacKinnon (median-regression formulation, 2014); robust bootstrap variants popularised by Hayes (2013) and Preacher & Hayes (2008) | Preacher, Rucker & Hayes |
| Tyyppi≠ | Causal inference / indirect effects | Conditional process model |
| Alkuperäislähde≠ | Yuan, Y., & MacKinnon, D. P. (2014). Robust mediation analysis based on median regression. Psychological Methods, 19(1), 1–20. DOI ↗ | Hayes, A. F. (2018). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (2nd ed.). Guilford Press. ISBN: 978-1462534654 |
| Rinnakkaisnimet≠ | robust indirect effects, outlier-resistant mediation, robust causal mediation | conditional process analysis, moderated mediation model, first-stage moderated mediation, second-stage moderated mediation |
| Liittyvät≠ | 5 | 4 |
| Tiivistelmä≠ | Robust mediation analysis estimates the indirect effect of an independent variable on an outcome through one or more mediators using estimators that resist the influence of outliers and non-normal error distributions. By combining robust regression (such as median or M-estimation) with percentile or bias-corrected bootstrap confidence intervals, it yields trustworthy conclusions when standard ordinary-least-squares mediation would be distorted by extreme observations. | 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? |
| ScholarGateAineisto ↗ |
|
|