Selection Bias Requires Selection: The Case of Collider Stratification Bias

• Published in: American journal of epidemiology 2024-02, Vol.193 (3), p.407-409
• Main Authors: Lu, Haidong, Gonsalves, Gregg S, Westreich, Daniel
• Format: Article
• Language: English
• Subjects: Bias; Causality; Humans; Selection Bias
• ISSN: 0002-9262; 1476-6256; 1476-6256
• DOI: 10.1093/aje/kwad213

Abstract In epidemiology, collider stratification bias, the bias resulting from conditioning on a common effect of two causes, is oftentimes considered a type of selection bias, regardless of the conditioning methods employed. In this commentary, we distinguish between two types of collider stratification bias: collider restriction bias due to restricting to one level of a collider (or a descendant of a collider) and collider adjustment bias through inclusion of a collider (or a descendant of a collider) in a regression model. We argue that categorizing collider adjustment bias as a form of selection bias may lead to semantic confusion, as adjustment for a collider in a regression model does not involve selecting a sample for analysis. Instead, we propose that collider adjustment bias can be better viewed as a type of overadjustment bias. We further provide two distinct causal diagram structures to distinguish collider restriction bias and collider adjustment bias. We hope that such a terminological distinction can facilitate easier and clearer communication.