Simple yet Sharp Sensitivity Analysis for Unmeasured Confounding
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Abstract (arXiv)
We present a method for assessing the sensitivity of the true causal effect to unmeasured confounding. The method requires the analyst to set two intuitive parameters. Otherwise, the method is assumption-free. The method returns an interval that contains the true causal effect, and whose bounds are arbitrarily sharp, i.e. practically attainable. We show experimentally that our bounds can be tighter than those obtained by the method of Ding and VanderWeele (2016a) which, moreover, requires to set one more parameter than our method. Finally, we extend our method to bound the natural direct and indirect effects when there are measured mediators and unmeasured exposure-outcome confounding.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 2 of its 15 references that are in the map. First posted on arXiv 27 Apr 2021.
Builds on
2 of 15 references.
References · 2
- 2013Direct and Indirect Effectscited by 276
- 2016Sharp sensitivity bounds for mediation under unmeasured mediator-outcome confoundingcited by 2
Built on by
Citing papers per year: 2022: 2; 2023: 1; 2024: 1; 2025: 1.
5 papers.
- 2022ρ-GNF: A Copula-based Sensitivity Analysis to Unobserved Confounding Using Normalizing Flowscited by 2
- 2023Bounding the Probabilities of Benefit and Harm Through Sensitivity Parameters and Proxiescited by 2
- 2022A Consistent Estimator for Confounding Strengthcited by 1
- 2025Sensitivity Analysis to Unobserved Confounding with Copula-based Normalizing Flowscited by 1
- 2024Simple yet Sharp Sensitivity Analysis for Any Contrast Under Unmeasured Confoundingcited by 0
- 2025Sensitivity Analysis to Unobserved Confounding with Copula-based Normalizing Flows12 Aug 2025
- 2024Simple yet Sharp Sensitivity Analysis for Any Contrast Under Unmeasured Confounding12 Jun 2024
- 2023Bounding the Probabilities of Benefit and Harm Through Sensitivity Parameters and Proxies8 Mar 2023
- 2022A Consistent Estimator for Confounding Strength3 Nov 2022
- 2022ρ-GNF: A Copula-based Sensitivity Analysis to Unobserved Confounding Using Normalizing Flows15 Sep 2022