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. © 2010 by Lippincott Williams & Wilkins.
CITATION STYLE
Pearl, J. (2010). On the consistency rule in causal inference: Axiom, definition, assumption, or theorem? Epidemiology, 21(6), 872–875. https://doi.org/10.1097/EDE.0b013e3181f5d3fd
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