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Sharp bounds on the causal effects in randomized experiments with "truncation-by-death"

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Cited by:

  1. Halloran M. Elizabeth & Hudgens Michael G., 2012. "Causal Inference for Vaccine Effects on Infectiousness," The International Journal of Biostatistics, De Gruyter, vol. 8(2), pages 1-40, January.
  2. Bartalotti, Otávio & Kédagni, Désiré & Possebom, Vitor, 2023. "Identifying marginal treatment effects in the presence of sample selection," Journal of Econometrics, Elsevier, vol. 234(2), pages 565-584.
  3. Wei Yan & Yaqin Hu & Zhi Geng, 2012. "Identifiability of Causal Effects for Binary Variables with Baseline Data Missing Due to Death," Biometrics, The International Biometric Society, vol. 68(1), pages 121-128, March.
  4. Phillip Heiler & Asbj{o}rn Kaufmann & Bezirgen Veliyev, 2024. "Treatment Evaluation at the Intensive and Extensive Margins," Papers 2412.11179, arXiv.org.
  5. Markus Frölich & Martin Huber, 2014. "Treatment Evaluation With Multiple Outcome Periods Under Endogeneity and Attrition," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1697-1711, December.
  6. Hans Fricke & Markus Frölich & Martin Huber & Michael Lechner, 2020. "Endogeneity and non‐response bias in treatment evaluation – nonparametric identification of causal effects by instruments," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(5), pages 481-504, August.
  7. Sooahn Shin, 2024. "Difference-in-differences Design with Outcomes Missing Not at Random," Papers 2411.18772, arXiv.org.
  8. Huber, Martin & Meier, Jonas & Wallimann, Hannes, 2022. "Business analytics meets artificial intelligence: Assessing the demand effects of discounts on Swiss train tickets," Transportation Research Part B: Methodological, Elsevier, vol. 163(C), pages 22-39.
  9. Martin Huber & Giovanni Mellace, 2015. "Sharp Bounds on Causal Effects under Sample Selection," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 77(1), pages 129-151, February.
  10. Linbo Wang & Thomas S. Richardson & Xiao-Hua Zhou, 2017. "Causal analysis of ordinal treatments and binary outcomes under truncation by death," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(3), pages 719-735, June.
  11. Martin Huber & Giovanni Mellace, 2010. "Sharp IV bounds on average treatment effects under endogeneity and noncompliance," University of St. Gallen Department of Economics working paper series 2010 2010-31, Department of Economics, University of St. Gallen.
  12. Michela Bia & German Blanco & Marie Valentova, 2021. "The Causal Impact of Taking Parental Leave on Wages: Evidence from 2005 to 2015," LISER Working Paper Series 2021-08, Luxembourg Institute of Socio-Economic Research (LISER).
  13. Gayani Rathnayake & Akanksha Negi & Otavio Bartalotti & Xueyan Zhao, 2024. "Difference-in-Differences with Sample Selection," Papers 2411.09221, arXiv.org, revised Dec 2024.
  14. Alessandra Mattei & Fabrizia Mealli & Barbara Pacini, 2014. "Identification of causal effects in the presence of nonignorable missing outcome values," Biometrics, The International Biometric Society, vol. 70(2), pages 278-288, June.
  15. Gilbert Peter B. & Blette Bryan S. & Shepherd Bryan E. & Hudgens Michael G., 2020. "Post-randomization Biomarker Effect Modification Analysis in an HIV Vaccine Clinical Trial," Journal of Causal Inference, De Gruyter, vol. 8(1), pages 54-69, January.
  16. Ting Ye & Luke Keele & Raiden Hasegawa & Dylan S. Small, 2020. "A Negative Correlation Strategy for Bracketing in Difference-in-Differences," Papers 2006.02423, arXiv.org, revised Jun 2022.
  17. 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.
  18. Kosuke Imai & Zhichao Jiang, 2020. "Identification and sensitivity analysis of contagion effects in randomized placebo‐controlled trials," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(4), pages 1637-1657, October.
  19. Mealli Fabrizia & Mattei Alessandra, 2012. "A Refreshing Account of Principal Stratification," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-19, April.
  20. Simon Calmar Andersen & Louise Beuchert & Phillip Heiler & Helena Skyt Nielsen, 2023. "A Guide to Impact Evaluation under Sample Selection and Missing Data: Teacher's Aides and Adolescent Mental Health," Papers 2308.04963, arXiv.org.
  21. Fan Yang & Dylan S. Small, 2016. "Using post-outcome measurement information in censoring-by-death problems," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(1), pages 299-318, January.
  22. Phillip Heiler, 2022. "Heterogeneous Treatment Effect Bounds under Sample Selection with an Application to the Effects of Social Media on Political Polarization," Papers 2209.04329, arXiv.org, revised Jul 2024.
  23. VanderWeele Tyler J, 2011. "Principal Stratification -- Uses and Limitations," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-14, July.
  24. Shanshan Luo & Wei Li & Yangbo He, 2023. "Causal inference with outcomes truncated by death in multiarm studies," Biometrics, The International Biometric Society, vol. 79(1), pages 502-513, March.
  25. Gilbert Peter B. & Blette Bryan S. & Hudgens Michael G. & Shepherd Bryan E., 2020. "Post-randomization Biomarker Effect Modification Analysis in an HIV Vaccine Clinical Trial," Journal of Causal Inference, De Gruyter, vol. 8(1), pages 54-69, January.
  26. Kosuke Imai & Teppei Yamamoto, 2010. "Causal Inference with Differential Measurement Error: Nonparametric Identification and Sensitivity Analysis," American Journal of Political Science, John Wiley & Sons, vol. 54(2), pages 543-560, April.
  27. Peter Z. Schochet, 2013. "Student Mobility, Dosage, and Principal Stratification in School-Based RCTs," Journal of Educational and Behavioral Statistics, , vol. 38(4), pages 323-354, August.
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