Usporedite metode

	Frontdoor prilagodba (Frontdoor kriterij)	Identifikacija uzročnosti pomoću usmjerenih acikličkih grafova (do-račun)
Područje	Uzročno zaključivanje	Uzročno zaključivanje
Obitelj	Regression model	Regression model
Godina nastanka	1995	2009
Tvorac	Judea Pearl	Judea Pearl
Vrsta	Causal identification (graphical adjustment)	Causal identification framework
Temeljni izvor	Pearl, J. (1995). Causal Diagrams for Empirical Research. Biometrika, 82(4), 669-688.	Pearl, J. (2009). Causality: Models, Reasoning, and Inference (2nd ed.). Cambridge University Press. ISBN: 978-0521895606
Drugi nazivi	frontdoor criterion, Pearl's frontdoor adjustment, frontdoor formula, Ön Kapı Düzenlemesi (Frontdoor Adjustment)	do-calculus, backdoor adjustment, Pearl causal identification, DAG ile Nedensel Tanımlama (do-calculus)
Srodne	4	5
Sažetak	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.	DAG causal identification is a framework, developed by Judea Pearl (2009), that encodes causal assumptions as a directed acyclic graph and uses the do-calculus rules to determine whether and how a causal effect can be identified from observational data. It systematically handles confounders, instrumental variables, and backdoor paths.