Skip to main content
. Author manuscript; available in PMC: 2023 Feb 1.
Published in final edited form as: J Clin Epidemiol. 2021 Aug 8;142:264–267. doi: 10.1016/j.jclinepi.2021.08.001

Figure 2:

Figure 2:

Examples of settings in which controlling for or restricting on a variable can introduce bias. A box around a variable denotes conditioning on that variable.

Panel a) Depiction of controlling for a mediating variable. Stroke severity is a consequence of stroke and adjusting for it blocks one pathway through which stroke causes functional decline, attenuating the estimated effect size.

Panel b) Depiction of selection bias in a study estimating the effect of the number of sexual partners on cervical cancer. Here, to be included in the study, participants had to have sought care at an STI clinic. Because seeking care at an STI clinic is influenced by both the exposure and the outcome (i.e., it is a collider), the estimate of the causal effect of interest will be biased.