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. 2017 Jun 1;185(11):1048-1050.
doi: 10.1093/aje/kwx077.

Invited Commentary: Selection Bias Without Colliders

Invited Commentary: Selection Bias Without Colliders

Miguel A Hernán. Am J Epidemiol. .

Abstract

In causal analyses, conditioning on a collider generally results in selection bias. Conditioning on a prognostic factor that is independent of the exposure-and therefore is not a collider-can also result in selection bias when 1) the exposure has a non-null effect on the outcome and 2) the association between the noncollider and the outcome is heterogenous across levels of the exposure. This result was empirically demonstrated by Greenland in 1977 (Am J Epidemiol. 1977;106(3):184-187).

Keywords: causal diagrams; collider; loss to follow-up; selection bias.

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Figures

Figure
1.
Figure 1.
Causal directed acyclic graph off the null where E is exposure, D is disease, C is censoring, and U is the unmeasured common causes of C and D. The box around C indicates that the analysis is conditional on being uncensored.
Figure 2.
Figure 2.
Causal directed acyclic graph under the null where E is exposure, D is disease, C is censoring, and U is the unmeasured common causes of C and D. The box around C indicates that the analysis is conditional on being uncensored.

References

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    1. Hernán MA. Discussion on the paper by Keiding and Louis. J R Stat Soc Ser A Stat Soc. 2016;179(part 2):346–347.
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    1. Greenland S, Pearl J. Adjustments and their consequences-collapsibility analysis using graphical models. Int Stat Rev. 2011;79(3):401–426.

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