In 2 recent communications, Cole and Frangakis (Epidemiology. 2009;20:3-5) and VanderWeele (Epidemiology. 2009;20:880-883) conclude that the consistency rule used in causal inference is an assumption that precludes any side-effects of treatment/exposure on the outcomes of interest. They further develop auxiliary notation to make this assumption formal and explicit. I argue that the consistency rule is a theorem in the logic of counterfactuals and need not be altered. Instead, warnings of potential side-effects should be embodied in standard modeling practices that make causal assumptions explicit and transparent.
CITATION STYLE
Pearl, J. (2010). On the Consistency Rule in Causal Inference. Epidemiology, 21(6), 872–875. https://doi.org/10.1097/ede.0b013e3181f5d3fd
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