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Fuzzy regressionskontinuitetsdesign inom utbildningsforskning×Lokal genomsnittlig behandlingseffekt (LATE / CACE)×
ÄmnesområdeKausal inferensKausal inferens
FamiljRegression modelRegression model
UrsprungsårLate 1990s–2000s1994
UpphovspersonImbens & Lemieux (2008); applied in education by Jacob & Lefgren (2004) and Angrist & Lavy (1999)Imbens & Angrist (1994); Angrist, Imbens & Rubin (1996)
TypQuasi-experimental / causal inferenceInstrumental-variable causal estimand
UrsprungskällaImbens, G. W., & Lemieux, T. (2008). Regression discontinuity designs: A guide to practice. Journal of Econometrics, 142(2), 615-635. DOI ↗Imbens, G. W., & Angrist, J. D. (1994). Identification and Estimation of Local Average Treatment Effects. Econometrica, 62(2), 467-475. DOI ↗
AliasFuzzy RDD, Fuzzy RD, Imperfect RDD, Non-sharp RDLATE, CACE, complier average causal effect, Yerel Ortalama Tedavi Etkisi (LATE / CACE)
Närliggande45
SammanfattningFuzzy 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.
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ScholarGateJämför metoder: Fuzzy Regression Discontinuity in Education Research · Local Average Treatment Effect. Hämtad 2026-06-20 från https://scholargate.app/sv/compare