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تعديل الباب الأمامي (معيار الباب الأمامي)×التعرف السببي باستخدام الرسوم البيانية الموجهة غير الدورية (حسابات do)×
المجالالاستدلال السببيالاستدلال السببي
العائلةRegression modelRegression model
سنة النشأة19952009
صاحب الطريقةJudea PearlJudea Pearl
النوعCausal identification (graphical adjustment)Causal identification framework
المصدر التأسيسيPearl, J. (1995). Causal Diagrams for Empirical Research. Biometrika, 82(4), 669-688. DOI ↗Pearl, J. (2009). Causality: Models, Reasoning, and Inference (2nd ed.). Cambridge University Press. ISBN: 978-0521895606
الأسماء البديلةfrontdoor 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)
ذات صلة45
الملخصFrontdoor 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.
ScholarGateمجموعة البيانات
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ScholarGateقارن الطرق: Frontdoor Adjustment · DAG Causal Identification. استُرجع بتاريخ 2026-06-18 من https://scholargate.app/ar/compare