Módszerek összehasonlítása

	Fuzzy regressziós diszkontinuitás-tervezés az oktatáskutatásban	A különbség-különbségek (Diff-in-Diff) módszer
Tudományterület	Oksági következtetés	Ökonometria
Módszercsalád	Regression model	Regression model
Keletkezés éve	Late 1990s–2000s	1994
Megalkotó	Imbens & Lemieux (2008); applied in education by Jacob & Lefgren (2004) and Angrist & Lavy (1999)	Card & Krueger (canonical 1994 application); Angrist & Pischke (textbook treatment)
Típus	Quasi-experimental / causal inference	Causal inference / panel regression
Alapmű	Imbens, G. W., & Lemieux, T. (2008). Regression discontinuity designs: A guide to practice. Journal of Econometrics, 142(2), 615-635.	Angrist, J. D., & Pischke, J.-S. (2009). Mostly Harmless Econometrics: An Empiricist's Companion. Princeton University Press. ISBN: 978-0691120355
Alternatív nevek	Fuzzy RDD, Fuzzy RD, Imperfect RDD, Non-sharp RD	diff-in-diff, DiD, Farkların Farkı (Diff-in-Diff)
Kapcsolódó	4	5
Összefoglaló	Fuzzy Regression Discontinuity Design (Fuzzy RDD) is a quasi-experimental causal method that exploits a known score threshold — such as a test cutoff — to estimate the effect of a program or intervention when assignment is imperfect. Widely used in education research to evaluate summer school, remedial programs, scholarships, and class-size rules, it uses two-stage least squares to recover a local average treatment effect for students near the threshold.	Difference-in-Differences is a causal-inference method that estimates the effect of an intervention by comparing how a treatment group and a control group change over time. Made famous by Card and Krueger's 1994 minimum-wage study and developed in Angrist and Pischke's Mostly Harmless Econometrics, it isolates the treatment effect as the difference between the two groups' before-after changes.