Rejoinder: On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning
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Abstract (arXiv)
This is the rejoinder to the discussion by Kennedy, Balakrishnan and Wasserman on the paper "On nearly assumption-free tests of nominal confidence interval coverage for causal parameters estimated by machine learning" published in Statistical Science.
Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 Aug 2020.
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Citing papers per year: 2022: 1; 2023: 4; 2024: 0; 2025: 1; 2026: 1.
7 papers.
- 2023The Fundamental Limits of Structure-Agnostic Functional Estimationcited by 12
- 2022DeepMed: Semiparametric Causal Mediation Analysis with Debiased Deep Learningcited by 10
- 2023Efficient and Multiply Robust Risk Estimation under General Forms of Dataset Shiftcited by 5
- 2026On the Asymptotic Inadmissibility of Double Machine Learning Estimators Under Structure-Agnostic Modelscited by 3
- 2023Assumption-lean falsification tests of rate double-robustness of double-machine-learning estimatorscited by 2
- 2023New √n-consistent, numerically stable higher-order influence function estimatorscited by 1
- 2025Penalized Empirical Likelihood for Doubly Robust Causal Inference under Contamination in High Dimensionscited by 0
- 2026On the Asymptotic Inadmissibility of Double Machine Learning Estimators Under Structure-Agnostic Models21 Jun 2026
- 2025Penalized Empirical Likelihood for Doubly Robust Causal Inference under Contamination in High Dimensions23 Jul 2025
- 2023Efficient and Multiply Robust Risk Estimation under General Forms of Dataset Shift28 Jun 2023
- 2023Assumption-lean falsification tests of rate double-robustness of double-machine-learning estimators18 Jun 2023
- 2023The Fundamental Limits of Structure-Agnostic Functional Estimation6 May 2023
- 2023New √n-consistent, numerically stable higher-order influence function estimators16 Feb 2023
- 2022DeepMed: Semiparametric Causal Mediation Analysis with Debiased Deep Learning10 Oct 2022