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Epidemiology. 2010 Nov;21(6):872-5. doi: 10.1097/EDE.0b013e3181f5d3fd.

On the consistency rule in causal inference: axiom, definition, assumption, or theorem?

Author information

  • 1Department of Computer Science, University of California, Los Angeles, CA 90095-1596, USA. judea@cs.ucla.edu

Erratum in

  • Epidemiology. 2011 Mar;22(2):285.

Abstract

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.

PMID:
20864888
DOI:
10.1097/EDE.0b013e3181f5d3fd
[PubMed - indexed for MEDLINE]
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