Interpretable Causal Graphical Models for Equilibrium Systems with Confounding

Fuente: arXiv
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Main Authors: Teh, Kai Z., Sadeghi, Kayvan, Soo, Terry
Format: Preprint
Published: 2026
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author Teh, Kai Z.
Sadeghi, Kayvan
Soo, Terry
author_facet Teh, Kai Z.
Sadeghi, Kayvan
Soo, Terry
contents In applications, quantities of interest are often modelled in equilibrium or an equilibrium solution is sought. The presence of confounding makes causal inference in this setting challenging. We provide interpretable graphical models for equilibrium systems with confounding using anterial graphs (Lauritzen and Sadeghi, 2018), a class of graphs containing directed acyclic graphs, ancestral graphs, and chain graphs. In this setting, we provide valid graphical representations of both counterfactual variables and observational variables, which we relate to counterfactual graphs (Shpitser and Pearl, 2007) and single-world intervention graphs (Richardson and Robins,2013). As an application of this graphical representation, we provide an element-wise procedure of selecting adjustment sets that flexibly include and exclude given covariates.
format Preprint
id arxiv_https___arxiv_org_abs_2603_24859
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Interpretable Causal Graphical Models for Equilibrium Systems with Confounding
Teh, Kai Z.
Sadeghi, Kayvan
Soo, Terry
Methodology
Statistics Theory
In applications, quantities of interest are often modelled in equilibrium or an equilibrium solution is sought. The presence of confounding makes causal inference in this setting challenging. We provide interpretable graphical models for equilibrium systems with confounding using anterial graphs (Lauritzen and Sadeghi, 2018), a class of graphs containing directed acyclic graphs, ancestral graphs, and chain graphs. In this setting, we provide valid graphical representations of both counterfactual variables and observational variables, which we relate to counterfactual graphs (Shpitser and Pearl, 2007) and single-world intervention graphs (Richardson and Robins,2013). As an application of this graphical representation, we provide an element-wise procedure of selecting adjustment sets that flexibly include and exclude given covariates.
title Interpretable Causal Graphical Models for Equilibrium Systems with Confounding
topic Methodology
Statistics Theory
url https://arxiv.org/abs/2603.24859