方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 多层次中介分析× | 有条件过程分析（有调节的中介）× | |
|---|---|---|
| 领域≠ | 统计学 | 因果推断 |
| 方法族≠ | Hypothesis test | Regression model |
| 起源年份≠ | 2003 | 2018 |
| 提出者≠ | Kenny, Korchmaros & Bolger | Andrew F. Hayes (PROCESS framework); Preacher, Rucker & Hayes (moderated mediation) |
| 类型≠ | Multilevel structural model | Regression-based conditional process model |
| 开创性文献≠ | Kenny, D. A., Korchmaros, J. D., & Bolger, N. (2003). Lower level mediation in multilevel models. Psychological Methods, 8(2), 115–128. DOI ↗ | Hayes, A. F. (2018). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (2nd ed.). The Guilford Press. ISBN: 978-1462534654 |
| 别名≠ | multilevel mediation, hierarchical mediation, cross-level mediation, 1-1-1 mediation | moderated mediation, moderated mediation analysis, PROCESS model, Hayes PROCESS conditional process model |
| 相关≠ | 8 | 5 |
| 摘要≠ | Multilevel mediation analysis is a parametric structural method that estimates indirect (mediated) effects within hierarchically nested data, such as students within schools or employees within organisations. Formalised for lower-level mediation in multilevel models by Kenny, Korchmaros and Bolger (2003), it simultaneously handles individual-level (1-1-1) and group-level (2-2-1 or 2-1-1) mediation pathways in a single coherent framework. | Conditional process analysis is Andrew F. Hayes's regression-based PROCESS framework (2018) that combines mediation and moderation in a single model, testing how an indirect effect changes across levels of a moderator. It quantifies conditional indirect and conditional direct effects and tests them with bootstrap confidence intervals. |
| ScholarGate数据集 ↗ |
|
|