Overadjustment – an important bias hiding in plain sight

Anita van Zwieten, Fiona M Blyth, Germaine Wong and Saman Khalatbari-Soltani

Epidemiologists are generally well equipped to design and conduct studies that minimise various types of bias, so as to obtain the most accurate estimates possible and therefore high-quality evidence. In observational studies, some types of bias, like confounding, have received a lot of attention, while others have been overlooked. One that has been neglected is overadjustment bias, which occurs when researchers adjust for an explanatory variable on the causal pathway from exposure to outcome when seeking to estimate the total effect.

Continue reading “Overadjustment – an important bias hiding in plain sight”