Note on the identification of total effect in Cluster-DAGs with cycles

2025/04/10 by Yvernes, Clément · 2 citations
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #FOS: Mathematics #Statistics Theory (math.ST)

paper · doi:10.48550/arxiv.2504.07921

Abstract

In this note, we discuss the identifiability of a total effect in cluster-DAGs, allowing for cycles within the cluster-DAG (while still assuming the associated underlying DAG to be acyclic). This is presented into two key results: first, restricting the cluster-DAG to clusters containing at most four nodes; second, adapting the notion of d-separation. We provide a graphical criterion to address the identifiability problem.

Citations

• Identifying Macro Conditional Independencies and Macro Total Effects in Summary Causal Graphs with Latent Confounding
• Complete Graphical Characterization and Construction of Adjustment Sets in Markov Equivalence Classes of Ancestral Graphs

Cited by

• Cluster-Dags as Powerful Background Knowledge For Causal Discovery
• Identifying Macro Causal Effects in C-DMGs over DMGs

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