Invited commentary: Understanding bias amplification

  • Pearl J
  • 68

    Readers

    Mendeley users who have this article in their library.
  • 47

    Citations

    Citations of this article.

Abstract

In choosing covariates for adjustment or inclusion in propensity score analysis, researchers must weigh the benefit of reducing confounding bias carried by those covariates against the risk of amplifying residual bias carried by unmeasured confounders. The latter is characteristic of covariates that act like instrumental variables-that is, variables that are more strongly associated with the exposure than with the outcome. In this issue of the Journal (Am J Epidemiol. 2011;174(11):1213-1222), Myers et al. compare the bias amplification of a near-instrumental variable with its bias-reducing potential and suggest that, in practice, the latter outweighs the former. The author of this commentary sheds broader light on this comparison by considering the cumulative effects of conditioning on multiple covariates and showing that bias amplification may build up at a faster rate than bias reduction. The author further derives a partial order on sets of covariates which reveals preference for conditioning on outcome-related, rather than exposure-related, confounders

Author-supplied keywords

  • Bias (epidemiology)
  • Confounding factors (epidemiology)
  • Epidemiologic methods
  • Instrumental variable
  • Precision
  • Simulation
  • Variable selection

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

Get full text

Authors

  • Judea Pearl

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free