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Sharp sensitivity bounds for mediation under unmeasured mediator-outcome confounding

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  • Peng Ding
  • Tyler J. Vanderweele

Abstract

It is often of interest to decompose the total effect of an exposure into a component that acts on the outcome through some mediator and a component that acts independently through other pathways. Said another way, we are interested in the direct and indirect effects of the exposure on the outcome. Even if the exposure is randomly assigned, it is often infeasible to randomize the mediator, leaving the mediator-outcome confounding not fully controlled. We develop a sensitivity analysis technique that can bound the direct and indirect effects without parametric assumptions about the unmeasured mediator-outcome confounding.

Suggested Citation

  • Peng Ding & Tyler J. Vanderweele, 2016. "Sharp sensitivity bounds for mediation under unmeasured mediator-outcome confounding," Biometrika, Biometrika Trust, vol. 103(2), pages 483-490.
    • Handle: RePEc:oup:biomet:v:103:y:2016:i:2:p:483-490.
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    File URL: http://hdl.handle.net/10.1093/biomet/asw012
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    Cited by:

    1. Emma Gearon & Anna Peeters & Winda Ng & Allison Hodge & Kathryn Backholer, 2018. "Diet and physical activity as possible mediators of the association between educational attainment and body mass index gain among Australian adults," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 63(7), pages 883-893, September.
    2. Leah Comment & Brent A. Coull & Corwin Zigler & Linda Valeri, 2022. "Bayesian data fusion: Probabilistic sensitivity analysis for unmeasured confounding using informative priors based on secondary data," Biometrics, The International Biometric Society, vol. 78(2), pages 730-741, June.
    3. Jiang, Zhichao & Ding, Peng, 2017. "The directions of selection bias," Statistics & Probability Letters, Elsevier, vol. 125(C), pages 104-109.
    4. Kai Wang, 2019. "Maximum Likelihood Analysis of Linear Mediation Models with Treatment–Mediator Interaction," Psychometrika, Springer;The Psychometric Society, vol. 84(3), pages 719-748, September.

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