방법 비교
선택한 방법을 나란히 검토하세요. 서로 다른 행은 강조 표시됩니다.
| 강건 조절된 매개 분석× | 조절된 매개 분석× | |
|---|---|---|
| 분야 | 통계학 | 통계학 |
| 계열 | Latent structure | Latent structure |
| 기원 연도≠ | 2007–2013 | 2007 |
| 창시자≠ | Hayes, A. F.; building on Preacher, Rucker & Hayes (2007) for moderated mediation and robust bootstrap inference | Preacher, Rucker & Hayes |
| 유형≠ | Conditional indirect effect model with robust inference | Conditional process model |
| 원전≠ | Hayes, A. F. (2022). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (3rd ed.). Guilford Press. ISBN: 978-1462549030 | Hayes, A. F. (2018). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (2nd ed.). Guilford Press. ISBN: 978-1462534654 |
| 별칭 | robust conditional process analysis, robust mediated moderation, robust moderated indirect effects, robust conditional indirect effects | conditional process analysis, moderated mediation model, first-stage moderated mediation, second-stage moderated mediation |
| 관련≠ | 5 | 4 |
| 요약≠ | Robust moderated mediation tests whether the indirect effect of X on Y through a mediator M varies as a function of a moderator W, while using robust estimation (percentile or bias-corrected bootstrap, heteroscedasticity-consistent standard errors, or M-estimation) to protect inference against non-normality, outliers, and heteroscedasticity in the data. | 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? |
| ScholarGate데이터셋 ↗ |
|
|