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Analiza kauzalne medijacije (prirodni direktni i indirektni efekti)×Kauzalna identifikacija pomoću usmerenih acikličnih grafova (do-račun)×
OblastKauzalno zaključivanjeKauzalno zaključivanje
PorodicaRegression modelRegression model
Godina nastanka20102009
TvoracPearl (2001); general framework by Imai, Keele & Tingley (2010)Judea Pearl
TipCounterfactual causal decompositionCausal identification framework
Temeljni izvorPearl, J. (2001). Direct and Indirect Effects. In Proceedings of the Seventeenth Conference on Uncertainty in Artificial Intelligence (UAI), 411-420. link ↗Pearl, J. (2009). Causality: Models, Reasoning, and Inference (2nd ed.). Cambridge University Press. ISBN: 978-0521895606
Drugi nazivinatural direct effect, natural indirect effect, NDE / NIE decomposition, counterfactual mediationdo-calculus, backdoor adjustment, Pearl causal identification, DAG ile Nedensel Tanımlama (do-calculus)
Srodne55
SažetakCausal 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.
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ScholarGateUporedite metode: Causal Mediation Analysis · DAG Causal Identification. Preuzeto 2026-06-18 sa https://scholargate.app/sr/compare