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arXiv · 2008.06017

Multivariate Counterfactual Systems And Causal Graphical Models

Ilya Shpitser·Thomas S. Richardson·James M. Robins
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Abstract

Among Judea Pearl's many contributions to Causality and Statistics, the graphical d-separation} criterion, the do-calculus and the mediation formula stand out. In this chapter we show that d-separation} provides direct insight into an earlier causal model originally described in terms of potential outcomes and event trees. In turn, the resulting synthesis leads to a simplification of the do-calculus that clarifies and separates the underlying concepts, and a simple counterfactual formulation of a complete identification algorithm in causal models with hidden variables.

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Ilya Shpitser, Thomas S. Richardson, James M. Robins. 2020-08-13. Multivariate Counterfactual Systems And Causal Graphical Models. https://arxiv.org/abs/2008.06017

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