השוואת שיטות

	רגרסיית אי-רציפות להערכת השפעות טיפול הטרוגניות (HTE-RDD)	אפקט הטיפול הממוצע המקומי (LATE / CACE)
תחום	הסקה סיבתית	הסקה סיבתית
משפחה	Regression model	Regression model
שנת המקור	2015	1994
הוגה השיטה	Dong & Lewbel (2015); Chiang, Hsu & Sasaki (2019)	Imbens & Angrist (1994); Angrist, Imbens & Rubin (1996)
סוג	Quasi-experimental causal inference with effect heterogeneity	Instrumental-variable causal estimand
מקור מכונן	Dong, Y., & Lewbel, A. (2015). Identifying the Effect of Changing the Policy Threshold in Regression Discontinuity Models. Review of Economics and Statistics, 97(5), 1081-1092.	Imbens, G. W., & Angrist, J. D. (1994). Identification and Estimation of Local Average Treatment Effects. Econometrica, 62(2), 467-475.
כינויים	HTE-RDD, heterogeneous RDD, subgroup RDD, effect heterogeneity RD	LATE, CACE, complier average causal effect, Yerel Ortalama Tedavi Etkisi (LATE / CACE)
קשורות	4	5
תקציר	Heterogeneous Treatment Effect RDD extends the classic regression discontinuity framework to detect and estimate how the causal effect of crossing an assignment cutoff varies across subgroups or along covariates. Rather than reporting a single local average treatment effect at the threshold, HTE-RDD maps how treatment impact differs by individual characteristics, enabling richer policy conclusions about who benefits most or least from a threshold-based intervention.	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.