Graphical models, potential outcomes and causal inference: comment on Linquist and Sobel.

摘要

Dear Editor,I read with interest the comment by Lindquist and Sobel (2011) (L&S) entitled: "Graphical models, potential outcomes and causal inference" (Neurolmage, 2011) in which they advocate the use of counterfactual language to explicate causal assumptions, and raise doubts on whether graphical models are generally useful for estimating causal effects. Their comment creates the impression, perhaps unintentionally, that counterfactual language is somehow superior, more rigorous or more principled than the graphical language used by structural equation modelers (SEM) in fMRl research. The purpose of this communication is to correct any such impression and to supplement L&S comment with proven mathematical results regarding the relations between the two notational systems.