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The extension of counterfactual causal graphic model with three variables ofvertex set in directed acyclic graph (DAG) is discussed in this paper byextending two- value distribution to three-value distribution of the variablesinvolved in DAG. Using the conditional independence as ancillary information, 6kinds of extension counterfactual causal graphic models with some variables areextended from two-value distribution to three-value distribution and thesufficient conditions of identifiability are derived.

Extension of Three-Variable Counterfactual Casual Graphic Model: from Two-Value to Three-Value Random Variable