References in zbMATH (referenced in 49 articles )

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  1. Ertefaie, Ashkan; McKay, James R.; Oslin, David; Strawderman, Robert L.: Robust Q-learning (2021)
  2. Benkeser, David; Cai, Weixin; van der Laan, Mark J.: Rejoinder: A nonparametric superefficient estimator of the average treatment effect (2020)
  3. Boehmke, Brad; Greenwell, Brandon M.: Hands-on machine learning with R (2020)
  4. Chi Zhang, Jennifer Ahern, Mark J. van der Laan, Oleg Sofrygin: tmleCommunity: A R Package Implementing Target Maximum Likelihood Estimation for Community-level Data (2020) arXiv
  5. Ertefaie, Ashkan; Johnson, Brent A.: Comment: Outcome-wide individualized treatment strategies (2020)
  6. Li, Meng; Dunson, David B.: Comparing and weighting imperfect models using D-probabilities (2020)
  7. Orhobor, Oghenejokpeme I.; Alexandrov, Nickolai N.; King, Ross D.: Predicting Rice phenotypes with meta and multi-target learning (2020)
  8. Papadogeorgou, Georgia; Dominici, Francesca: A causal exposure response function with local adjustment for confounding: estimating health effects of exposure to low levels of ambient fine particulate matter (2020)
  9. Rauschenberger, Armin; Ciocănea-Teodorescu, Iuliana; Jonker, Marianne A.; Menezes, Renée X.; van de Wiel, Mark A.: Sparse classification with paired covariates (2020)
  10. Schomaker, Michael; Heumann, Christian: When and when not to use optimal model averaging (2020)
  11. Westling, Ted; Carone, Marco: A unified study of nonparametric inference for monotone functions (2020)
  12. Antonelli, Joseph; Daniels, Michael J.: Discussion of PENCOMP (2019)
  13. Díaz, Iván; Colantuoni, Elizabeth; Hanley, Daniel F.; Rosenblum, Michael: Improved precision in the analysis of randomized trials with survival outcomes, without assuming proportional hazards (2019)
  14. Gruber, Susan; van der Laan, Mark J.: Comment on “Automated versus do-it-yourself methods for causal inference: lessons learned from a data analysis competition” (2019)
  15. Kennedy, Edward H.: Nonparametric causal effects based on incremental propensity score interventions (2019)
  16. Luedtke, Alex; Carone, Marco; Van der Laan, Mark J.: An omnibus non-parametric test of equality in distribution for unknown functions (2019)
  17. Duroux, Roxane; Scornet, Erwan: Impact of subsampling and tree depth on random forests (2018)
  18. Rudolph, Kara E.; Sofrygin, Oleg; Zheng, Wenjing; van der Laan, Mark J.: Robust and flexible estimation of stochastic mediation effects: a proposed method and example in a randomized trial setting (2018)
  19. Scharfstein, Daniel; McDermott, Aidan; Díaz, Iván; Carone, Marco; Lunardon, Nicola; Turkoz, Ibrahim: Global sensitivity analysis for repeated measures studies with informative drop-out: a semi-parametric approach (2018)
  20. Van der Laan, Mark J.; Rose, Sherri: Targeted learning in data science. Causal inference for complex longitudinal studies (2018)

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