Local Markov Equivalence for PC-style Local Causal Discovery and Identification of Controlled Direct Effects

ArXi:2505.02781v4 Announce Type: replace Identifying controlled direct effects (CDEs) is crucial across numerous scientific domains. While existing methods can identify these effects from causal directed acyclic graphs (DAGs), the true DAG is often unknown in practice. Essential graphs, which represent a Marko equivalence class of DAGs characterized by the same set of conditional independencies, provide a practical and realistic alternative, and the PC algorithm is one of the most widely used method to learn them using conditional independence tests.