Graphical Models, Causality, and Intervention

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The Mediation Formula: A Guide to the Assessment of Causal Pathways in Nonlinear Models (2011, background): “(See (Pearl, 2011) for in depth discussion of these issues.)”
Thinking Clearly About Correlations and Causation: Graphical Causal Models for Observational Data (2017, methodology): “Thoemmes and Mohan (2015) used DAGs based on formalizations by Mohan, Pearl, and Tian (2013) to provide visual representations of missing- data scenarios.”
CAUSALITY FROM A DISTRIBUTIONAL ROBUSTNESS POINT OF VIEW (2018, methodology): “To simplify the discussion, only linear SEMs will be discussed here as causal structural models for Z [7, 8].”
Minimal sufficient causation and directed acyclic graphs (2009, methodology): “Note that this is a graphical generalization of Theorem 4 of Rosenbaum and Rubin [31] and of the g-formula [27, 28, 36, 22].”