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Discussion on “Instrumental variable estimation of the causal hazard ratio,” by Linbo Wang, Eric Tchetgen Tchetgen, Torben Martinussen, and Stijn Vansteelandt

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  • Benjamin R. Baer
  • Robert L. Strawderman
  • Ashkan Ertefaie

Abstract

We propose and study an augmented variant of the estimator proposed by Wang, Tchetgen Tchetgen, Martinussen, and Vansteelandt.

Suggested Citation

  • Benjamin R. Baer & Robert L. Strawderman & Ashkan Ertefaie, 2023. "Discussion on “Instrumental variable estimation of the causal hazard ratio,” by Linbo Wang, Eric Tchetgen Tchetgen, Torben Martinussen, and Stijn Vansteelandt," Biometrics, The International Biometric Society, vol. 79(2), pages 554-558, June.
  • Handle: RePEc:bla:biomet:v:79:y:2023:i:2:p:554-558
    DOI: 10.1111/biom.13790
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    References listed on IDEAS

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    1. Oliver Hines & Oliver Dukes & Karla Diaz-Ordaz & Stijn Vansteelandt, 2022. "Demystifying Statistical Learning Based on Efficient Influence Functions," The American Statistician, Taylor & Francis Journals, vol. 76(3), pages 292-304, July.
    2. Zhichao Jiang & Shu Yang & Peng Ding, 2022. "Multiply robust estimation of causal effects under principal ignorability," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1423-1445, September.
    3. Yifan Cui & Eric Tchetgen Tchetgen, 2021. "A Semiparametric Instrumental Variable Approach to Optimal Treatment Regimes Under Endogeneity," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 116(533), pages 162-173, January.
    4. Linbo Wang & Eric Tchetgen Tchetgen, 2018. "Bounded, efficient and multiply robust estimation of average treatment effects using instrumental variables," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 80(3), pages 531-550, June.
    5. Torben Martinussen & Stijn Vansteelandt & Per Kragh Andersen, 2020. "Subtleties in the interpretation of hazard contrasts," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(4), pages 833-855, October.
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