Rekodi ya ushahidi wa mbinu

DAG Causal Identification

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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Causal Identification with Directed Acyclic Graphs (do-calculus)

Rekodi ya mbinu ya kiajenda · regression-model / causal-inference

Pearl, J. (2009). Causality: Models, Reasoning, and Inference (2nd ed.). Cambridge University Press. · ISBN 978-0521895606
Pearl, J., Glymour, M., & Jewell, N. P. (2016). Causal Inference in Statistics: A Primer. Wiley. · ISBN 978-1119186847

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