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.
|Number of pages||7|
|Journal||IJCAI International Joint Conference on Artificial Intelligence|
|State||Published - 1 Dec 2005|
|Event||19th International Joint Conference on Artificial Intelligence, IJCAI 2005 - Edinburgh, United Kingdom|
Duration: 30 Jul 2005 → 5 Aug 2005
ASJC Scopus subject areas
- Artificial Intelligence