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Updated: Aug 6, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Survival as a source of confounding, selection bias, and effect modification
C Mary Schooling1,2, Guoyi Yang2
1Graduate School of Public Health and Health Policy, City University of New York, New York, NY, United States.
Background:
Survival is a long-standing source of confounding, selection bias, and effect modification that is often overlooked. Here, we describe how it can occur and when it can be averted.
Methods:
Directed acyclic graphs were used to illustrate how survival could cause confounding and selection bias. Selection diagrams were used to illustrate how survival could cause effect modification by factors such as age or health status.
Results:
Survival can be a confounder that biases towards favouring the exposure when exposure allocation starts or changes after recruitment. Survival can be a source of Type 1 selection bias that attenuates or reverses estimates when the exposure and outcome, or the exposure and a competing risk of the outcome, affect survival before recruitment. Confounding and selection bias by survival can largely be averted by ensuring exposure allocation coincides with recruitment. Given survival is usually most relevant to older or sicker people, confounding and selection bias due to survival are likely more evident with advancing age or poorer health status.
Conclusions:
Confounding by survival should be considered when exposure allocation starts or changes after recruitment. Type 1 selection bias from survival should be considered when the exposure starts before recruitment. Given that long-term exposures are often of interest, and confounding as well as selection bias are difficult to address, study designs less open to these biases might be preferable.
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