On the Monotonicity of a Nondifferentially Mismeasured Binary Confounder
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Abstract (arXiv)
Suppose that we are interested in the average causal effect of a binary treatment on an outcome when this relationship is confounded by a binary confounder. Suppose that the confounder is unobserved but a nondifferential proxy of it is observed. We show that, under certain monotonicity assumption that is empirically verifiable, adjusting for the proxy produces a measure of the effect that is between the unadjusted and the true measures.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 May 2020.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 2; 2024: 1.
6 papers.
- 2022Conceptualizing Treatment Leakage in Text-based Causal Inferencecited by 14
- 2023Integrating Earth Observation Data into Causal Inference: Challenges and Opportunitiescited by 8
- 2022Estimating Causal Effects Under Image Confounding Bias with an Application to Poverty in Africacited by 4
- 2023Bounding the Probabilities of Benefit and Harm Through Sensitivity Parameters and Proxiescited by 2
- 2021On the Non-Monotonicity of a Non-Differentially Mismeasured Binary Confoundercited by 0
- 2024Simple yet Sharp Sensitivity Analysis for Any Contrast Under Unmeasured Confoundingcited by 0
- 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
- 2023Integrating Earth Observation Data into Causal Inference: Challenges and Opportunities30 Jan 2023
- 2022Estimating Causal Effects Under Image Confounding Bias with an Application to Poverty in Africa13 Jun 2022
- 2022Conceptualizing Treatment Leakage in Text-based Causal Inference1 May 2022
- 2021On the Non-Monotonicity of a Non-Differentially Mismeasured Binary Confounder20 Jan 2021