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Bias testing, bias correction, and confounder selection using an instrumental variable model.

Publication ,  Journal Article
Yeob Choi, B; Fine, JP; Alan Brookhart, M
Published in: Stat Med
December 20, 2020

Instrumental variable (IV) analysis can be used to address bias due to unobserved confounding when estimating the causal effect of a treatment on an outcome of interest. However, if a proposed IV is correlated with unmeasured confounders and/or weakly correlated with the treatment, the standard IV estimator may be more biased than an ordinary least squares (OLS) estimator. Several methods have been proposed that compare the bias of the IV and OLS estimators relying on the belief that measured covariates can be used as proxies for the unmeasured confounder. Despite these developments, there is lack of discussion about approaches that can be used to formally test whether the IV estimator may be less biased than the OLS estimator. Thus, we have developed a testing framework to compare the bias and a criterion to select informative measured covariates for bias comparison and regression adjustment. We also have developed a bias-correction method, which allows one to use an invalid IV to correct the bias of the OLS or IV estimator. Numerical studies demonstrate that the proposed methods perform well with realistic sample sizes.

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Published In

Stat Med

DOI

EISSN

1097-0258

Publication Date

December 20, 2020

Volume

39

Issue

29

Start / End Page

4386 / 4404

Location

England

Related Subject Headings

  • Statistics & Probability
  • Sample Size
  • Models, Statistical
  • Least-Squares Analysis
  • Humans
  • Causality
  • Bias
  • 4905 Statistics
  • 4202 Epidemiology
  • 1117 Public Health and Health Services
 

Citation

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Yeob Choi, B., Fine, J. P., & Alan Brookhart, M. (2020). Bias testing, bias correction, and confounder selection using an instrumental variable model. Stat Med, 39(29), 4386–4404. https://doi.org/10.1002/sim.8730
Yeob Choi, Byeong, Jason P. Fine, and M. Alan Brookhart. “Bias testing, bias correction, and confounder selection using an instrumental variable model.Stat Med 39, no. 29 (December 20, 2020): 4386–4404. https://doi.org/10.1002/sim.8730.
Yeob Choi B, Fine JP, Alan Brookhart M. Bias testing, bias correction, and confounder selection using an instrumental variable model. Stat Med. 2020 Dec 20;39(29):4386–404.
Yeob Choi, Byeong, et al. “Bias testing, bias correction, and confounder selection using an instrumental variable model.Stat Med, vol. 39, no. 29, Dec. 2020, pp. 4386–404. Pubmed, doi:10.1002/sim.8730.
Yeob Choi B, Fine JP, Alan Brookhart M. Bias testing, bias correction, and confounder selection using an instrumental variable model. Stat Med. 2020 Dec 20;39(29):4386–4404.
Journal cover image

Published In

Stat Med

DOI

EISSN

1097-0258

Publication Date

December 20, 2020

Volume

39

Issue

29

Start / End Page

4386 / 4404

Location

England

Related Subject Headings

  • Statistics & Probability
  • Sample Size
  • Models, Statistical
  • Least-Squares Analysis
  • Humans
  • Causality
  • Bias
  • 4905 Statistics
  • 4202 Epidemiology
  • 1117 Public Health and Health Services