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Implications of M bias in epidemiologic studies: a simulation study.

Publication ,  Journal Article
Liu, W; Brookhart, MA; Schneeweiss, S; Mi, X; Setoguchi, S
Published in: Am J Epidemiol
November 15, 2012

Collider-stratification bias arises from conditioning on a variable (collider) which opens a path from exposure to outcome. M bias occurs when the collider-stratification bias is transmitted through ancestors of exposure and outcome. Previous theoretical work, but not empirical data, has demonstrated that M bias is smaller than confounding bias. The authors simulated data for large cohort studies with binary exposure, an outcome, a collider, and 2 predictors of the collider. They created 178 scenarios by changing the frequencies of variables and/or the magnitudes of associations among the variables. They calculated the effect estimate, percentage bias, and mean squared error. M bias in these realistic scenarios ranged from -2% to -5%. When the authors increased one or both relative risks for the relation between the collider and unmeasured factors to ≥8, the negative bias was more substantial (>15%). The result was substantially biased (e.g., >20%) if an unmeasured confounder that was also a collider was not adjusted to avoid M bias. In scenarios resembling those the authors examined, M bias had a small impact unless associations between the collider and unmeasured confounders were very large (relative risk > 8). When a collider is itself an important confounder, controlling for confounding would take precedence over avoiding M bias.

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Published In

Am J Epidemiol

DOI

EISSN

1476-6256

Publication Date

November 15, 2012

Volume

176

Issue

10

Start / End Page

938 / 948

Location

United States

Related Subject Headings

  • Risk Factors
  • Risk
  • Models, Theoretical
  • Humans
  • Epidemiology
  • Epidemiologic Methods
  • Cohort Studies
  • Causality
  • Bias
  • 11 Medical and Health Sciences
 

Citation

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Liu, W., Brookhart, M. A., Schneeweiss, S., Mi, X., & Setoguchi, S. (2012). Implications of M bias in epidemiologic studies: a simulation study. Am J Epidemiol, 176(10), 938–948. https://doi.org/10.1093/aje/kws165
Liu, Wei, M Alan Brookhart, Sebastian Schneeweiss, Xiaojuan Mi, and Soko Setoguchi. “Implications of M bias in epidemiologic studies: a simulation study.Am J Epidemiol 176, no. 10 (November 15, 2012): 938–48. https://doi.org/10.1093/aje/kws165.
Liu W, Brookhart MA, Schneeweiss S, Mi X, Setoguchi S. Implications of M bias in epidemiologic studies: a simulation study. Am J Epidemiol. 2012 Nov 15;176(10):938–48.
Liu, Wei, et al. “Implications of M bias in epidemiologic studies: a simulation study.Am J Epidemiol, vol. 176, no. 10, Nov. 2012, pp. 938–48. Pubmed, doi:10.1093/aje/kws165.
Liu W, Brookhart MA, Schneeweiss S, Mi X, Setoguchi S. Implications of M bias in epidemiologic studies: a simulation study. Am J Epidemiol. 2012 Nov 15;176(10):938–948.
Journal cover image

Published In

Am J Epidemiol

DOI

EISSN

1476-6256

Publication Date

November 15, 2012

Volume

176

Issue

10

Start / End Page

938 / 948

Location

United States

Related Subject Headings

  • Risk Factors
  • Risk
  • Models, Theoretical
  • Humans
  • Epidemiology
  • Epidemiologic Methods
  • Cohort Studies
  • Causality
  • Bias
  • 11 Medical and Health Sciences