विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| कारण मध्यस्थता विश्लेषण (प्राकृतिक प्रत्यक्ष और अप्रत्यक्ष प्रभाव)× | सशर्त प्रक्रिया विश्लेषण (मध्यस्थता का मॉडरेशन)× | |
|---|---|---|
| क्षेत्र | कारणात्मक अनुमान | कारणात्मक अनुमान |
| परिवार | Regression model | Regression model |
| उद्भव वर्ष≠ | 2010 | 2018 |
| प्रवर्तक≠ | Pearl (2001); general framework by Imai, Keele & Tingley (2010) | Andrew F. Hayes (PROCESS framework); Preacher, Rucker & Hayes (moderated mediation) |
| प्रकार≠ | Counterfactual causal decomposition | Regression-based conditional process model |
| मौलिक स्रोत≠ | Pearl, J. (2001). Direct and Indirect Effects. In Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI), 411-420. link ↗ | Hayes, A. F. (2018). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (2nd ed.). The Guilford Press. ISBN: 978-1462534654 |
| उपनाम | natural direct effect, natural indirect effect, NDE / NIE decomposition, counterfactual mediation | moderated mediation, moderated mediation analysis, PROCESS model, Hayes PROCESS conditional process model |
| संबंधित | 5 | 5 |
| सारांश≠ | Causal mediation analysis is a counterfactual framework that splits a treatment's total effect into a Natural Direct Effect (NDE) and a Natural Indirect Effect (NIE) that runs through a mediator. The modern general approach was formalised by Pearl (2001) and Imai, Keele and Tingley (2010), giving the decomposition a precise causal interpretation. | 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. |
| ScholarGateडेटासेट ↗ |
|
|