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Identifying causal effects with proxy variables of an unmeasured confounder

Citations

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Cited by:

  1. Rahul Singh & Moses Stewart, 2025. "Placebo Discontinuity Design," Papers 2507.12693, arXiv.org.
  2. Kirill Borusyak & Jiafeng Chen & Peter Hull & Lihua Lei, 2025. "Nonparametric Identification of Demand without Exogenous Product Characteristics," Papers 2512.23211, arXiv.org, revised Feb 2026.
  3. Zhongren Chen & Siyu Chen & Zhengling Qi & Xiaohong Chen & Zhuoran Yang, 2025. "Quantile-Optimal Policy Learning under Unmeasured Confounding," Papers 2506.07140, arXiv.org.
  4. AmirEmad Ghassami & Andrew Ying & Ilya Shpitser & Eric Tchetgen Tchetgen, 2021. "Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal Inference," Papers 2104.02929, arXiv.org, revised Mar 2022.
  5. Zihan Zhang & Lianyan Fu & Dehui Wang, 2026. "Difference-in-Differences using Double Negative Controls and Graph Neural Networks for Unmeasured Network Confounding," Papers 2601.00603, arXiv.org.
  6. Gaoming Lin & Xin Zhang & Zhonghao Ren & Quan Zou & Prayag Tiwari & Changjun Zhou & Yijie Ding, 2025. "TAPB: an interventional debiasing framework for alleviating target prior bias in drug-target interaction prediction," Nature Communications, Nature, vol. 16(1), pages 1-16, December.
  7. AmirEmad Ghassami & Chang Liu & Alan Yang & David Richardson & Ilya Shpitser & Eric Tchetgen Tchetgen, 2022. "Combining Experimental and Observational Data for Identification and Estimation of Long-Term Causal Effects," Papers 2201.10743, arXiv.org, revised Sep 2025.
  8. AmirEmad Ghassami & James M. Robins & Andrea Rotnitzky, 2025. "Debiased Ill-Posed Regression," Papers 2505.20787, arXiv.org.
  9. Crucinio, Francesca R. & De Bortoli, Valentin & Doucet, Arnaud & Johansen, Adam M., 2024. "Solving a class of Fredholm integral equations of the first kind via Wasserstein gradient flows," Stochastic Processes and their Applications, Elsevier, vol. 173(C).
  10. Zhongren Chen & Siyu Chen & Zhengling Qi & Xiaohong Chen & Zhuoran Yang, 2025. "Quantile-Optimal Policy Learning under Unmeasured Confounding," Cowles Foundation Discussion Papers 2469, Cowles Foundation for Research in Economics, Yale University.
  11. Rahul Singh, 2020. "Kernel Methods for Unobserved Confounding: Negative Controls, Proxies, and Instruments," Papers 2012.10315, arXiv.org, revised Mar 2023.
  12. Peña Jose M., 2020. "On the Monotonicity of a Nondifferentially Mismeasured Binary Confounder," Journal of Causal Inference, De Gruyter, vol. 8(1), pages 150-163, January.
  13. Jiawei Fu & Donald P. Green, 2026. "Nonparametric Identification and Estimation of Causal Effects on Latent Outcomes," Papers 2604.08681, arXiv.org, revised Apr 2026.
  14. Claudia Shi & Dhanya Sridhar & Vishal Misra & David M. Blei, 2021. "On the Assumptions of Synthetic Control Methods," Papers 2112.05671, arXiv.org, revised Dec 2021.
  15. Guido Imbens & Nathan Kallus & Xiaojie Mao, 2021. "Controlling for Unmeasured Confounding in Panel Data Using Minimal Bridge Functions: From Two-Way Fixed Effects to Factor Models," Papers 2108.03849, arXiv.org.
  16. Pengzhou Wu & Kenji Fukumizu, 2021. "Towards Principled Causal Effect Estimation by Deep Identifiable Models," Papers 2109.15062, arXiv.org, revised Nov 2021.
  17. Ben Deaner, 2022. "Controlling for Latent Confounding with Triple Proxies," Papers 2204.13815, arXiv.org, revised May 2023.
  18. Adel Daoud & Richard Johansson & Connor T. Jerzak, 2025. "Detecting and Mitigating Treatment Leakage in Text-Based Causal Inference: Distillation and Sensitivity Analysis," Papers 2601.02400, arXiv.org.
  19. Rahul Singh, 2021. "Kernel Ridge Riesz Representers: Generalization, Mis-specification, and the Counterfactual Effective Dimension," Papers 2102.11076, arXiv.org, revised Jul 2024.
  20. Zikai Shen & Nathan Kallus & Dimitri Meunier & Houssam Zenati & Arthur Gretton & Aur'elien Bibaut, 2026. "Nonparametric Instrumental Variable Analysis Without Structural Equations: Debiased Inference on Functionals of Inverse Problems with No Solutions," Papers 2604.24660, arXiv.org, revised May 2026.
  21. Ting-Chih Hung & Yu-Chang Chen, 2026. "The Proximal Surrogate Index: Long-Term Treatment Effects under Unobserved Confounding," Papers 2601.17712, arXiv.org.
  22. Andrew Bennett & Nathan Kallus & Xiaojie Mao & Whitney Newey & Vasilis Syrgkanis & Masatoshi Uehara, 2022. "Inference on Strongly Identified Functionals of Weakly Identified Functions," Papers 2208.08291, arXiv.org, revised Jun 2023.
  23. Ben Deaner, 2021. "Many Proxy Controls," Papers 2110.03973, arXiv.org.
  24. Zhang, Jeffrey & Li, Wei & Miao, Wang & Tchetgen Tchetgen, Eric, 2023. "Proximal causal inference without uniqueness assumptions," Statistics & Probability Letters, Elsevier, vol. 198(C).
  25. Liu, Lin & Mukherjee, Rajarshi & Robins, James M., 2024. "Assumption-lean falsification tests of rate double-robustness of double-machine-learning estimators," Journal of Econometrics, Elsevier, vol. 240(2).
  26. Peña Jose M., 2020. "On the Monotonicity of a Nondifferentially Mismeasured Binary Confounder," Journal of Causal Inference, De Gruyter, vol. 8(1), pages 150-163, January.
  27. Ziyu Wang & Yucen Luo & Yueru Li & Jun Zhu & Bernhard Scholkopf, 2022. "Spectral Representation Learning for Conditional Moment Models," Papers 2210.16525, arXiv.org, revised Dec 2022.
  28. Yilin Li & Wang Miao & Ilya Shpitser & Eric J. Tchetgen Tchetgen, 2023. "A self‐censoring model for multivariate nonignorable nonmonotone missing data," Biometrics, The International Biometric Society, vol. 79(4), pages 3203-3214, December.
  29. Abhinandan Dalal & Eric J. Tchetgen Tchetgen, 2025. "Partial Identification of Causal Effects for Endogenous Continuous Treatments," Papers 2508.13946, arXiv.org.
  30. Christian Tien, 2022. "Instrumented Common Confounding," Papers 2206.12919, arXiv.org, revised Sep 2022.
  31. Shuyuan Chen & Peng Zhang & Yifan Cui, 2025. "Identification and Debiased Learning of Causal Effects with General Instrumental Variables," Papers 2510.20404, arXiv.org, revised Feb 2026.
  32. Yue Hu & Yuanshan Gao & Minhao Qi, 2025. "Proximal Causal Inference for Censored Data with an Application to Right Heart Catheterization Data," Stats, MDPI, vol. 8(3), pages 1-22, July.
  33. Lan Liu & Eric Tchetgen Tchetgen, 2022. "Regression‐based negative control of homophily in dyadic peer effect analysis," Biometrics, The International Biometric Society, vol. 78(2), pages 668-678, June.
  34. Isaac Meza & Rahul Singh, 2021. "Nested Nonparametric Instrumental Variable Regression," Papers 2112.14249, arXiv.org, revised May 2025.
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