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| 교육 연구에서의 퍼지 회귀 불연속 설계× | 국소 평균 처리 효과 (LATE / CACE)× | |
|---|---|---|
| 분야 | 인과추론 | 인과추론 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | Late 1990s–2000s | 1994 |
| 창시자≠ | Imbens & Lemieux (2008); applied in education by Jacob & Lefgren (2004) and Angrist & Lavy (1999) | Imbens & Angrist (1994); Angrist, Imbens & Rubin (1996) |
| 유형≠ | Quasi-experimental / causal inference | Instrumental-variable causal estimand |
| 원전≠ | Imbens, 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 ↗ |
| 별칭 | Fuzzy RDD, Fuzzy RD, Imperfect RDD, Non-sharp RD | LATE, CACE, complier average causal effect, Yerel Ortalama Tedavi Etkisi (LATE / CACE) |
| 관련≠ | 4 | 5 |
| 요약≠ | 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. |
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