Identifying causal effects with proxy variables of an unmeasured confounder

Citations

Cited by:

1. Rahul Singh, 2021. "Kernel Ridge Riesz Representers: Generalization, Mis-specification, and the Counterfactual Effective Dimension," Papers 2102.11076, arXiv.org, revised Jul 2024.
2. Rahul Singh & Moses Stewart, 2025. "Placebo Discontinuity Design," Papers 2507.12693, arXiv.org.
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. 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.
6. 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.
7. Ben Deaner, 2021. "Many Proxy Controls," Papers 2110.03973, arXiv.org.
8. Zhang, Jeffrey & Li, Wei & Miao, Wang & Tchetgen Tchetgen, Eric, 2023. "Proximal causal inference without uniqueness assumptions," Statistics & Probability Letters, Elsevier, vol. 198(C).
9. AmirEmad Ghassami & James M. Robins & Andrea Rotnitzky, 2025. "Debiased Ill-Posed Regression," Papers 2505.20787, arXiv.org.
10. 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).
11. 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.
12. 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.
13. 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).
14. 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.
15. Abhinandan Dalal & Eric J. Tchetgen Tchetgen, 2025. "Partial Identification of Causal Effects for Endogenous Continuous Treatments," Papers 2508.13946, arXiv.org.
16. Rahul Singh, 2020. "Kernel Methods for Unobserved Confounding: Negative Controls, Proxies, and Instruments," Papers 2012.10315, arXiv.org, revised Mar 2023.
17. 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.
18. Christian Tien, 2022. "Instrumented Common Confounding," Papers 2206.12919, arXiv.org, revised Sep 2022.
19. 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.
20. 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.
21. Shuyuan Chen & Peng Zhang & Yifan Cui, 2025. "Identification and Debiased Learning of Causal Effects with General Instrumental Variables," Papers 2510.20404, arXiv.org.
22. Pengzhou Wu & Kenji Fukumizu, 2021. "Towards Principled Causal Effect Estimation by Deep Identifiable Models," Papers 2109.15062, arXiv.org, revised Nov 2021.
23. 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.
24. Ben Deaner, 2022. "Controlling for Latent Confounding with Triple Proxies," Papers 2204.13815, arXiv.org, revised May 2023.
25. 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.
26. Isaac Meza & Rahul Singh, 2021. "Nested Nonparametric Instrumental Variable Regression," Papers 2112.14249, arXiv.org, revised May 2025.