Módszerek összehasonlítása

	Placebo tesztek kauzális következtetésekhez	Regressziós diszkontinuitási dizájn (RDD)
Tudományterület	Oksági következtetés	Oksági következtetés
Módszercsalád	Regression model	Regression model
Keletkezés éve	2010	2008
Megalkotó	Abadie, Diamond & Hainmueller (synthetic control placebos); Imbens & Lemieux (RDD validity)	Imbens & Lemieux (guide to practice); Cattaneo, Idrobo & Titiunik (practical introduction)
Típus	Falsification / robustness test family for causal inference	Quasi-experimental causal design
Alapmű	Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic Control Methods for Comparative Case Studies: Estimating the Effect of California's Tobacco Control Program. Journal of the American Statistical Association, 105(490), 493-505.	Imbens, G. W., & Lemieux, T. (2008). Regression Discontinuity Designs: A Guide to Practice. Journal of Econometrics, 142(2), 615-635.
Alternatív nevek	falsification tests, placebo checks, refutation tests, Plasebo Testleri — Nedensel Çıkarım Doğrulama	RDD, regression discontinuity design, sharp RDD, fuzzy RDD
Kapcsolódó	5	5
Összefoglaló	Placebo tests are a family of falsification checks that probe the credibility of a causal claim by re-running the analysis on a fake treatment, a false intervention date, or an outcome that should not have been affected. The approach was popularised through the synthetic control work of Abadie, Diamond and Hainmueller (2010) and the regression-discontinuity validity checks of Imbens and Lemieux (2008).	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.