手法を比較

	フロントドア調整（フロントドア基準）	回帰不連続デザイン（Regression Discontinuity Design, RDD）
分野	因果推論	因果推論
系統	Regression model	Regression model
提唱年	1995	2008
提唱者	Judea Pearl	Imbens & Lemieux (guide to practice); Cattaneo, Idrobo & Titiunik (practical introduction)
種類	Causal identification (graphical adjustment)	Quasi-experimental causal design
原典	Pearl, J. (1995). Causal Diagrams for Empirical Research. Biometrika, 82(4), 669-688.	Imbens, G. W., & Lemieux, T. (2008). Regression Discontinuity Designs: A Guide to Practice. Journal of Econometrics, 142(2), 615-635.
別名	frontdoor criterion, Pearl's frontdoor adjustment, frontdoor formula, Ön Kapı Düzenlemesi (Frontdoor Adjustment)	RDD, regression discontinuity design, sharp RDD, fuzzy RDD
関連	4	5
概要	Frontdoor adjustment is Judea Pearl's graphical identification strategy, introduced in 1995, that recovers the causal effect of a treatment on an outcome through a fully mediating variable even when an unobserved confounder sits between the treatment and the outcome. It is the go-to tool when the backdoor criterion cannot be satisfied because the confounder is unmeasured.	Regression Discontinuity Design is a quasi-experimental method that identifies a causal effect by locally comparing units just above and just below a cutoff on a continuous assignment (running) variable. Formalised for applied work by Imbens and Lemieux (2008) and developed as a practical framework by Cattaneo, Idrobo, and Titiunik (2020), it estimates a local average treatment effect (LATE) at the threshold.