Ways to close backdoors in DAGs
Read OriginalThis technical article details practical methods for closing confounding backdoors in Directed Acyclic Graphs (DAGs) to establish causal relationships from observational data. It covers techniques such as regression, inverse probability weighting, and matching, framed within the context of modern causal inference and do-calculus. Aimed at practitioners, it includes resources for learning DAGs and is implemented with R and related tools.
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