Department of Philosophy, Carnegie Mellon University, Pittsburgh, PA 15213, Florida Institute for Human and Machine Cognition, Pensacola, Florida, 32507, USA.
Neuroimage. 2013 Aug 1;76:450-1. doi: 10.1016/j.neuroimage.2011.07.071. Epub 2011 Jul 30.
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.
林奎斯特和索贝尔声称，他们所谓的“非干预性”图形因果模型并不意味着任何反事实条件。他们怀疑使用 SEM、DCM、贝叶斯网络、格兰杰因果模型等典型的图形因果模型是否可以发现“因果效应”。这些说法要么是错误的，要么是夸大其词的。他们建议研究人员采用“潜在结果”框架。在 fMRI 背景下，潜在结果框架是发现因果关系的障碍，而不是帮助。
