Identifiability of path-specific effects

Authors:
Chen Avin;Ilya Shpitser;Judea Pearl
Affiliations:
Cognitive Systems Laboratory, Department of Computer Science, University of California, Los Angeles, Los Angeles, CA;Cognitive Systems Laboratory, Department of Computer Science, University of California, Los Angeles, Los Angeles, CA;Cognitive Systems Laboratory, Department of Computer Science, University of California, Los Angeles, Los Angeles, CA
Venue:
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Year:
2005

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Abstract

Counterfactual quantities representing path-specific effects arise in cases where we are interested in computing the effect of one variable on another only along certain causal paths in the graph (in other words by excluding a set of edges from consideration). A recent paper [Pearl, 2001] details a method by which such an exclusion can be specified formally by fixing the value of the parent node of each excluded edge. In this paper we derive simple, graphical conditions for experimental identifiability of path-specific effects, namely, conditions under which path-specific effects can be estimated consistently from data obtained from controlled experiments.