השוואת שיטות

	ניתוח תיווך סיבתי (אפקטים ישירים ועקיפים טבעיים)	זיהוי סיבתי באמצעות גרפי ייחוס מכוונים (do-calculus)
תחום	הסקה סיבתית	הסקה סיבתית
משפחה	Regression model	Regression model
שנת המקור	2010	2009
הוגה השיטה	Pearl (2001); general framework by Imai, Keele & Tingley (2010)	Judea Pearl
סוג	Counterfactual causal decomposition	Causal identification framework
מקור מכונן	Pearl, J. (2001). Direct and Indirect Effects. In Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI), 411-420.	Pearl, J. (2009). Causality: Models, Reasoning, and Inference (2nd ed.). Cambridge University Press. ISBN: 978-0521895606
כינויים	natural direct effect, natural indirect effect, NDE / NIE decomposition, counterfactual mediation	do-calculus, backdoor adjustment, Pearl causal identification, DAG ile Nedensel Tanımlama (do-calculus)
קשורות	5	5
תקציר	Causal mediation analysis is a counterfactual framework that splits a treatment's total effect into a Natural Direct Effect (NDE) and a Natural Indirect Effect (NIE) that runs through a mediator. The modern general approach was formalised by Pearl (2001) and Imai, Keele and Tingley (2010), giving the decomposition a precise causal interpretation.	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.