Counterfactuals, graphical causal models and potential outcomes: Response to Lindquist and Sobel
نویسنده
چکیده
Lindquist and Sobel claim that the graphical causal models they call "agnostic" do not imply any counterfactual conditionals. They doubt that "causal effects" can be discovered using graphical causal models typical of SEMs, DCMs, Bayes nets, Granger causal models, etc. Each of these claims is false or exaggerated. They recommend instead that investigators adopt the "potential outcomes" framework. The potential outcomes framework is an obstacle rather than an aid to discovering causal relations in fMRI contexts.
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Graphical models, potential outcomes and causal inference: Comment on Linquist and Sobel
Dear Editor, I read with interest the comment by Lindquist and Sobel (L&S) entitled: “Graphical models, potential outcomes and causal inference” (NeuroImage, 2010) 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...
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ورودعنوان ژورنال:
- NeuroImage
دوره 76 شماره
صفحات -
تاریخ انتشار 2013