Methoden vergleichen

	Fuzzy Regression Discontinuity Design in der Bildungsforschung	Lokaler durchschnittlicher Behandlungseffekt (LATE / CACE)
Fachgebiet	Kausale Inferenz	Kausale Inferenz
Familie	Regression model	Regression model
Entstehungsjahr	Late 1990s–2000s	1994
Urheber	Imbens & Lemieux (2008); applied in education by Jacob & Lefgren (2004) and Angrist & Lavy (1999)	Imbens & Angrist (1994); Angrist, Imbens & Rubin (1996)
Typ	Quasi-experimental / causal inference	Instrumental-variable causal estimand
Wegweisende Quelle	Imbens, G. W., & Lemieux, T. (2008). Regression discontinuity designs: A guide to practice. Journal of Econometrics, 142(2), 615-635.	Imbens, G. W., & Angrist, J. D. (1994). Identification and Estimation of Local Average Treatment Effects. Econometrica, 62(2), 467-475.
Aliasnamen	Fuzzy RDD, Fuzzy RD, Imperfect RDD, Non-sharp RD	LATE, CACE, complier average causal effect, Yerel Ortalama Tedavi Etkisi (LATE / CACE)
Verwandt	4	5
Zusammenfassung	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.	The Local Average Treatment Effect is an instrumental-variable estimand, introduced by Imbens and Angrist (1994) and formalised with Rubin (1996), that recovers the average treatment effect for the subpopulation of compliers — units whose treatment status is actually moved by the instrument. It is closely tied to compliance analysis.