JAMAevidence JAMA Guide to Statistics and Methods JAMA Guide to Statistics and Methods: Collider Bias With Dr Andersen
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Jun 5, 2025 
In this engaging discussion, Lars W. Andersen, a professor at Aarhus University Hospital renowned for his work in acute care, delves into the intricate world of collider bias with statistical editor Roger J. Lewis. They clarify its critical importance in ensuring accurate treatment effect estimates in research. Lars illustrates collider bias using examples from diet and cognitive assessments and discusses its implications in COVID-19 medication studies. He emphasizes the need for rigorous study designs and thoughtful population selection to mitigate this pervasive bias.
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Understanding Bias
- Bias is a systematic, non-random error that causes incorrect estimates in studies.
- Distinguish bias from random error, which arises from insufficient sample size.
Collider Bias Explained
- Collider bias is a type of selection bias occurring due to selection in a study.
- It biases cause-effect inference by conditioning on a variable influenced by both exposure and outcome.
Diet Study Example of Collider Bias
- In a diet and cognitive decline study, restricting to those with follow-up can create collider bias.
- Loss to follow-up depends on diet and cognitive function, biasing outcome comparisons.