References

Chernozhukov, Victor, Whitney K Newey, Victor Quintas-Martinez, and Vasilis Syrgkanis. 2021. “Automatic Debiased Machine Learning via Riesz Regression.” arXiv Preprint arXiv:2104.14737.

Dı́az, Iván, and Nima S Hejazi. 2020. “Causal Mediation Analysis for Stochastic Interventions.” Journal of the Royal Statistical Society: Series B (Statistical Methodology) 82 (3): 661–83.

Hejazi, Nima S, Kara E Rudolph, Mark J van der Laan, and Iván Dı́az. 2022. “Nonparametric Causal Mediation Analysis for Stochastic Interventional (in) Direct Effects.” Biostatistics (in press). https://doi.org/10.1093/biostatistics/kxac002.

Kennedy, Edward H. 2018. “Nonparametric Causal Effects Based on Incremental Propensity Score Interventions.” Journal of the American Statistical Association, no. just-accepted.

Liu, Richard, Nicholas T Williams, Kara E Rudolph, and Iván Dı́az. 2024. “General Targeted Machine Learning for Modern Causal Mediation Analysis.” arXiv Preprint arXiv:2408.14620.

Miles, Caleb H. 2022. “On the Causal Interpretation of Randomized Interventional Indirect Effects.” arXiv Preprint arXiv:2203.00245. https://arxiv.org/abs/2203.00245.

Rudolph, Kara E, Shodai Inose, Nicholas T Williams, Katherine L Hoffman, Sarah E Forrest, Rachael K Ross, Floriana Milazzo, et al. 2025. “Mediation of Chronic Pain and Disability on Opioid Use Disorder Risk by Pain Management Practices Among Adult Medicaid Patients, 2016-2019.” American Journal of Epidemiology, kwaf093.

Tchetgen Tchetgen, Eric J, and Tyler J VanderWeele. 2014. “On Identification of Natural Direct Effects When a Confounder of the Mediator Is Directly Affected by Exposure.” Epidemiology 25 (2): 282.

van der Laan, Mark J, Eric C Polley, and Alan E Hubbard. 2007. “Super Learner.” Statistical Applications in Genetics and Molecular Biology 6 (1).

Vo, Tat-Thang, Nicholas Williams, Richard Liu, Kara E Rudolph, and Ivan Dıaz. 2024. “Recanting Twins: Addressing Intermediate Confounding in Mediation Analysis.” arXiv Preprint arXiv:2401.04450.