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Counterfactuals, graphical causal models and potential outcomes: Response to Lindquist and Sobel

机译:反事实,图形化因果模型和潜在结果:对Lindquist和Sobel的回应

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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.
机译:Lindquist和Sobel声称他们称之为“不可知论”的图形因果模型并不暗示任何反事实条件。他们怀疑可以使用SEM,DCM,贝叶斯网络,格兰杰因果模型等典型的图形因果模型来发现“因果效应”。这些主张中的每一项都是错误的或夸大的。他们建议调查人员采用“潜在结果”框架。潜在结果框架是在功能磁共振成像环境中发现因果关系的障碍而不是帮助。

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