GitHub

References

Bibliographic keys match the CDCS book file references.bib where possible, so chapters and package docs stay aligned. Prefer DOIs when citing externally.

Mediation (natural, interventional, stochastic)

  • Robins, J. M., & Greenland, S. (1992). Identifiability and exchangeability for direct and indirect effects. Epidemiology, 3(2), 143–155. — key robins1992estimation

  • Pearl, J. (2001). Direct and indirect effects. In UAI. — key pearl2001direct

  • VanderWeele, T. J. (2015). Explanation in Causal Inference: Methods for Mediation and Interaction. Oxford University Press. — key vanderweele2015explanation

  • Vansteelandt, S., & Daniel, R. M. (2017). Interventional effects for mediation analysis with multiple mediators. Epidemiology, 28(2), 258–265. doi:10.1097/EDE.0000000000000596 — key vansteelandt2017interventional

  • Díaz, I., & Hejazi, N. S. (2020). Causal mediation analysis for stochastic interventions. Journal of the Royal Statistical Society: Series B, 82(3), 661–683. doi:10.1111/rssb.12362 — key diaz2020mediation

  • Hejazi, N. S., Rudolph, K. E., van der Laan, M. J., & Díaz, I. (2023). Nonparametric causal mediation analysis for stochastic interventional (in)direct effects. Biostatistics, 24(3), 686–707. doi:10.1093/biostatistics/kxac002 — key hejazi2023stochastic

  • Liu, R., Williams, N. T., Rudolph, K. E., & Díaz, I. (2024). General targeted machine learning for modern causal mediation analysis. arXiv:2408.14620. doi:10.48550/arXiv.2408.14620 — key liu2024mediation

  • Liu, R., Williams, N. T., Rudolph, K. E., & Díaz, I. (2025). crumble: A comprehensive framework for modern causal mediation analysis with intermediate confounding. arXiv:2604.09902. doi:10.48550/arXiv.2604.09902 — key liu2025crumble

Organic effects and recanting twins

  • Lok, J. J. (2015). Organic direct and indirect effects with multiple mediators. Statistics in Medicine (and related Lok papers). — cite via book bibliography when key is present

  • Vo, T. T., & Díaz, I. (and related Vo–Díaz work on recanting twins / path-specific effects). — see CDCS references.bib for the keyed entry used in the book

Modified treatment policies (shared with CausalTargeted)

  • Díaz Muñoz, I., & van der Laan, M. J. (2012). Population intervention causal effects based on stochastic interventions. Biometrics, 68(2), 541–549. doi:10.1111/j.1541-0420.2011.01685.x — key diaz2012stochastic

  • Díaz, I., Williams, N., Hoffman, K. L., & Schenck, E. J. (2023). Nonparametric causal effects based on longitudinal modified treatment policies. Journal of the American Statistical Association, 118(542), 846–857. doi:10.1080/01621459.2021.1955691 — key diaz2023lmtp

Targeted learning and Super Learner

  • van der Laan, M. J., & Rubin, D. (2006). Targeted maximum likelihood learning. The International Journal of Biostatistics, 2(1). — key vanderlaan2006targeted

  • van der Laan, M. J., Polley, E. C., & Hubbard, A. E. (2007). Super learner. Statistical Applications in Genetics and Molecular Biology, 6(1). — key vanderlaan2007super

  • van der Laan, M. J., & Rose, S. (2011). Targeted Learning. Springer. — key vanderlaan2011targeted

  • Zheng, W., & van der Laan, M. J. (2011). Cross-validated targeted minimum-loss-based estimation. In van der Laan & Rose (2011). — key zheng2011crossfitting

Identification and target trials (upstream)

  • Pearl, J. (2009). Causality (2nd ed.). Cambridge University Press. — key pearl2009causality

  • Hernán, M. A., & Robins, J. M. (2020). Causal Inference: What If. Chapman & Hall/CRC. — key hernan2020causal