Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| Kondicionālās procesa analīze (moderētā mediācija)× | Dizains ar regresijas pārtraukumu (RDD)× | |
|---|---|---|
| Nozare | Cēloņsakarību secināšana | Cēloņsakarību secināšana |
| Saime | Regression model | Regression model |
| Izcelsmes gads≠ | 2018 | 2008 |
| Autors≠ | Andrew F. Hayes (PROCESS framework); Preacher, Rucker & Hayes (moderated mediation) | Imbens & Lemieux (guide to practice); Cattaneo, Idrobo & Titiunik (practical introduction) |
| Tips≠ | Regression-based conditional process model | Quasi-experimental causal design |
| Pirmavots≠ | Hayes, A. F. (2018). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (2nd ed.). The Guilford Press. ISBN: 978-1462534654 | Imbens, G. W., & Lemieux, T. (2008). Regression Discontinuity Designs: A Guide to Practice. Journal of Econometrics, 142(2), 615-635. DOI ↗ |
| Citi nosaukumi | moderated mediation, moderated mediation analysis, PROCESS model, Hayes PROCESS conditional process model | RDD, regression discontinuity design, sharp RDD, fuzzy RDD |
| Saistītās | 5 | 5 |
| Kopsavilkums≠ | 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. | Regression Discontinuity Design is a quasi-experimental method that identifies a causal effect by locally comparing units just above and just below a cutoff on a continuous assignment (running) variable. Formalised for applied work by Imbens and Lemieux (2008) and developed as a practical framework by Cattaneo, Idrobo, and Titiunik (2020), it estimates a local average treatment effect (LATE) at the threshold. |
| ScholarGateDatu kopa ↗ |
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