Selection bias due to conditioning on a collider

Definition of a colliderIn a causal graph, a collider is a variable that is affected by two or more variables on the graph.12 For example, suppose a causal diagram has three variables: vaccine V (yes or no) at baseline, infection I (yes or no) during the subsequent six months, and individual, pre-baseline susceptibility S to infection (high, medium, low) (fig 1, top graph). There would be an arrow from V to I because the vaccine lowers the risk of infection, and an arrow from S to I because susceptibility increases the risk of infection. Therefore, the variable I is a collider because arrows go into it from two other variables: the arrows from V and S “collide” into I. Identifying colliders is important because conditioning on colliders is expected to lead to selection bias.13bmj;381/jun07_6/p1135/F1F1f1Fig 1Three types of causal graphs. I=infection; J=fourth variable; S=susceptibility to infection; V=vaccineColliders and selection biasSuppose that…
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