Revisiting Overadjustment Bias

Affiliations

¹ Public Health Modeling Unit and Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT.
² Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC.
³ Departments of Pediatrics and Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada.
⁴ Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD.

Haidong Lu et al. Epidemiology. 2021.

. 2021 Sep 1;32(5):e22-e23.

doi: 10.1097/EDE.0000000000001377.

¹ Public Health Modeling Unit and Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT.
² Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC.
³ Departments of Pediatrics and Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada.
⁴ Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD.

No abstract available

Conflict of interest statement

The authors report no funding and conflicts of interest.

1. Schisterman EF, Cole SR, Platt RW. Overadjustment bias and unnecessary adjustment in epidemiologic studies. Epidemiology. 2009;20:488–495.
1. VanderWeele TJ. On the relative nature of overadjustment and unnecessary adjustment. Epidemiology. 2009;20:496–499.
1. Cole SR, Platt RW, Schisterman EF, et al. Illustrating bias due to conditioning on a collider. Int J Epidemiol. 2010;39:417–420.
1. Greenland S. Quantifying biases in causal models: classical confounding vs collider-stratification bias. Epidemiology. 2003;14:300–306.
1. Greenland S. An introduction to instrumental variables for epidemiologists. Int J Epidemiol. 2000;29:722–729.