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Improving efficiency and robustness of the doubly robust estimator for a population mean with incomplete data

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  1. Anastasios A. Tsiatis & Marie Davidian & Weihua Cao, 2011. "Improved Doubly Robust Estimation When Data Are Monotonely Coarsened, with Application to Longitudinal Studies with Dropout," Biometrics, The International Biometric Society, vol. 67(2), pages 536-545, June.
  2. Gruber Susan & van der Laan Mark J., 2012. "Targeted Minimum Loss Based Estimator that Outperforms a given Estimator," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-22, May.
  3. Bryan S. Graham & Keisuke Hirano, 2011. "Robustness to Parametric Assumptions in Missing Data Models," American Economic Review, American Economic Association, vol. 101(3), pages 538-543, May.
  4. Słoczyński, Tymon & Wooldridge, Jeffrey M., 2018. "A General Double Robustness Result For Estimating Average Treatment Effects," Econometric Theory, Cambridge University Press, vol. 34(1), pages 112-133, February.
  5. Rashid Javed & Mazhar Mughal, 2022. "Changing patterns of son preference and fertility in Pakistan," Journal of International Development, John Wiley & Sons, Ltd., vol. 34(6), pages 1086-1109, August.
  6. AmirEmad Ghassami & Andrew Ying & Ilya Shpitser & Eric Tchetgen Tchetgen, 2021. "Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal Inference," Papers 2104.02929, arXiv.org, revised Mar 2022.
  7. Baojiang Chen & Jing Qin, 2014. "Test the reliability of doubly robust estimation with missing response data," Biometrics, The International Biometric Society, vol. 70(2), pages 289-298, June.
  8. Peisong Han & Linglong Kong & Jiwei Zhao & Xingcai Zhou, 2019. "A general framework for quantile estimation with incomplete data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 81(2), pages 305-333, April.
  9. Weibin Mo & Yufeng Liu, 2022. "Efficient learning of optimal individualized treatment rules for heteroscedastic or misspecified treatment‐free effect models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(2), pages 440-472, April.
  10. Anna Garriga & Fulvia Pennoni, 2022. "The Causal Effects of Parental Divorce and Parental Temporary Separation on Children’s Cognitive Abilities and Psychological Well-being According to Parental Relationship Quality," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 161(2), pages 963-987, June.
  11. Chaudhuri, Saraswata & Renault, Eric, 2023. "Efficient estimation of regression models with user-specified parametric model for heteroskedasticty," The Warwick Economics Research Paper Series (TWERPS) 1473, University of Warwick, Department of Economics.
  12. Mohamed Abdallah Ali & Mazhar Mughal & Charles Kodjo Mawusi, 2021. "Does Khat Consumption Affect Work Performance ? A Micro-Perspective from Djibouti," Working papers of Transitions Energétiques et Environnementales (TREE) hal-03375659, HAL.
  13. Jie Zhou & Zhiwei Zhang & Zhaohai Li & Jun Zhang, 2015. "Coarsened Propensity Scores and Hybrid Estimators for Missing Data and Causal Inference," International Statistical Review, International Statistical Institute, vol. 83(3), pages 449-471, December.
  14. Rong Fu & Peter B. Gilbert, 2017. "Joint modeling of longitudinal and survival data with the Cox model and two-phase sampling," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(1), pages 136-159, January.
  15. Vermeulen Karel & Vansteelandt Stijn, 2016. "Data-Adaptive Bias-Reduced Doubly Robust Estimation," The International Journal of Biostatistics, De Gruyter, vol. 12(1), pages 253-282, May.
  16. Ito, Junichi & Feuer, Hart N. & Kitano, Shinichi & Asahi, Haruka, 2019. "Assessing the effectiveness of Japan's community-based direct payment scheme for hilly and mountainous areas," Ecological Economics, Elsevier, vol. 160(C), pages 62-75.
  17. Michal Juraska & Peter B. Gilbert, 2016. "Mark-specific hazard ratio model with missing multivariate marks," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 22(4), pages 606-625, October.
  18. Lan Wen & Miguel A. Hernán & James M. Robins, 2022. "Multiply robust estimators of causal effects for survival outcomes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(3), pages 1304-1328, September.
  19. Peisong Han, 2014. "Multiply Robust Estimation in Regression Analysis With Missing Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1159-1173, September.
  20. Sho Komukai & Satoshi Hattori, 2017. "Doubly robust estimator for net survival rate in analyses of cancer registry data," Biometrics, The International Biometric Society, vol. 73(1), pages 124-133, March.
  21. Luo, Yu & Graham, Daniel J. & McCoy, Emma J., 2023. "Semiparametric Bayesian doubly robust causal estimation," LSE Research Online Documents on Economics 117944, London School of Economics and Political Science, LSE Library.
  22. Li Liang & Greene Tom, 2013. "A Weighting Analogue to Pair Matching in Propensity Score Analysis," The International Journal of Biostatistics, De Gruyter, vol. 9(2), pages 215-234, July.
  23. Helene Boistard & Guillaume Chauvet & David Haziza, 2016. "Doubly Robust Inference for the Distribution Function in the Presence of Missing Survey Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(3), pages 683-699, September.
  24. Porter Kristin E. & Gruber Susan & van der Laan Mark J. & Sekhon Jasjeet S., 2011. "The Relative Performance of Targeted Maximum Likelihood Estimators," The International Journal of Biostatistics, De Gruyter, vol. 7(1), pages 1-34, August.
  25. Brian J. Reich & Shu Yang & Yawen Guan & Andrew B. Giffin & Matthew J. Miller & Ana Rappold, 2021. "A Review of Spatial Causal Inference Methods for Environmental and Epidemiological Applications," International Statistical Review, International Statistical Institute, vol. 89(3), pages 605-634, December.
  26. Mohamed Abdallah Ali & Mazhar Mughal & Dina Chhorn, 2022. "Microfinance and poverty reduction: Evidence from Djibouti," Review of Development Economics, Wiley Blackwell, vol. 26(2), pages 1189-1224, May.
  27. Su, Miaomiao & Wang, Ruoyu & Wang, Qihua, 2022. "A two-stage optimal subsampling estimation for missing data problems with large-scale data," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
  28. Radice Rosalba & Ramsahai Roland & Grieve Richard & Kreif Noemi & Sadique Zia & Sekhon Jasjeet S., 2012. "Evaluating treatment effectiveness in patient subgroups: a comparison of propensity score methods with an automated matching approach," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-45, August.
  29. Satoshi Hattori & Masayuki Henmi, 2014. "Stratified doubly robust estimators for the average causal effect," Biometrics, The International Biometric Society, vol. 70(2), pages 270-277, June.
  30. Lee, Myoung-jae & Lee, Sanghyeok, 2019. "Double robustness without weighting," Statistics & Probability Letters, Elsevier, vol. 146(C), pages 175-180.
  31. Wang, Qihua & Su, Miaomiao & Wang, Ruoyu, 2021. "A beyond multiple robust approach for missing response problem," Computational Statistics & Data Analysis, Elsevier, vol. 155(C).
  32. Ruoyao Shi, 2021. "An Averaging Estimator for Two Step M Estimation in Semiparametric Models," Working Papers 202105, University of California at Riverside, Department of Economics.
  33. Sun Hao & Ertefaie Ashkan & Lu Xin & Johnson Brent A., 2020. "Improved Doubly Robust Estimation in Marginal Mean Models for Dynamic Regimes," Journal of Causal Inference, De Gruyter, vol. 8(1), pages 300-314, January.
  34. Ao Yuan & Anqi Yin & Ming T. Tan, 2021. "Enhanced Doubly Robust Procedure for Causal Inference," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 13(3), pages 454-478, December.
  35. Guo, Xu & Fang, Yun & Zhu, Xuehu & Xu, Wangli & Zhu, Lixing, 2018. "Semiparametric double robust and efficient estimation for mean functionals with response missing at random," Computational Statistics & Data Analysis, Elsevier, vol. 128(C), pages 325-339.
  36. Sean Yiu & Li Su, 2022. "Joint calibrated estimation of inverse probability of treatment and censoring weights for marginal structural models," Biometrics, The International Biometric Society, vol. 78(1), pages 115-127, March.
  37. Michael Zimmert, 2018. "The Finite Sample Performance of Treatment Effects Estimators based on the Lasso," Papers 1805.05067, arXiv.org.
  38. Jianxuan Liu & Yanyuan Ma & Lan Wang, 2018. "An alternative robust estimator of average treatment effect in causal inference," Biometrics, The International Biometric Society, vol. 74(3), pages 910-923, September.
  39. Li, Wei & Luo, Shanshan & Xu, Wangli, 2024. "Calibrated regression estimation using empirical likelihood under data fusion," Computational Statistics & Data Analysis, Elsevier, vol. 190(C).
  40. Qi Long & Xiaoxi Zhang & Brent A. Johnson, 2011. "Robust Estimation of Area Under ROC Curve Using Auxiliary Variables in the Presence of Missing Biomarker Values," Biometrics, The International Biometric Society, vol. 67(2), pages 559-567, June.
  41. Xinyu Li & Wang Miao & Fang Lu & Xiao‐Hua Zhou, 2023. "Improving efficiency of inference in clinical trials with external control data," Biometrics, The International Biometric Society, vol. 79(1), pages 394-403, March.
  42. Garriga, Anna & Pennoni, Fulvia, 2017. "The influence of parental divorce, parental temporary separation and parental relationship quality on children’s school readiness," MPRA Paper 82892, University Library of Munich, Germany.
  43. Guo, Donglin & Xue, Liugen & Hu, Yuqin, 2017. "Covariate-balancing-propensity-score-based inference for linear models with missing responses," Statistics & Probability Letters, Elsevier, vol. 123(C), pages 139-145.
  44. Peisong Han, 2016. "Combining Inverse Probability Weighting and Multiple Imputation to Improve Robustness of Estimation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(1), pages 246-260, March.
  45. Baqun Zhang & Anastasios A. Tsiatis & Eric B. Laber & Marie Davidian, 2012. "A Robust Method for Estimating Optimal Treatment Regimes," Biometrics, The International Biometric Society, vol. 68(4), pages 1010-1018, December.
  46. Dridi, Ichrak & Boughrara, Adel, 2023. "Flexible inflation targeting and stock market volatility: Evidence from emerging market economies," Economic Modelling, Elsevier, vol. 126(C).
  47. M. Hristache & V. Patilea, 2017. "Conditional moment models with data missing at random," Biometrika, Biometrika Trust, vol. 104(3), pages 735-742.
  48. Matthew Cefalu & Francesca Dominici & Nils Arvold & Giovanni Parmigiani, 2017. "Model averaged double robust estimation," Biometrics, The International Biometric Society, vol. 73(2), pages 410-421, June.
  49. Stijn Vansteelandt & Oliver Dukes, 2022. "Authors' reply to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(3), pages 729-739, July.
  50. Hao Cheng & Ying Wei, 2018. "A fast imputation algorithm in quantile regression," Computational Statistics, Springer, vol. 33(4), pages 1589-1603, December.
  51. Karel Vermeulen & Stijn Vansteelandt, 2015. "Bias-Reduced Doubly Robust Estimation," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(511), pages 1024-1036, September.
  52. Ashkan Ertefaie & Nima S. Hejazi & Mark J. van der Laan, 2023. "Nonparametric inverse‐probability‐weighted estimators based on the highly adaptive lasso," Biometrics, The International Biometric Society, vol. 79(2), pages 1029-1041, June.
  53. Su, Miaomiao & Wang, Qihua, 2022. "A convex programming solution based debiased estimator for quantile with missing response and high-dimensional covariables," Computational Statistics & Data Analysis, Elsevier, vol. 168(C).
  54. Iván Díaz & Elizabeth Colantuoni & Daniel F. Hanley & Michael Rosenblum, 2019. "Improved precision in the analysis of randomized trials with survival outcomes, without assuming proportional hazards," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 25(3), pages 439-468, July.
  55. Xiaogang Duan & Guosheng Yin, 2017. "Ensemble Approaches to Estimating the Population Mean with Missing Response," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(4), pages 899-917, December.
  56. Kwun Chuen Gary Chan & Sheung Chi Phillip Yam & Zheng Zhang, 2016. "Globally efficient non-parametric inference of average treatment effects by empirical balancing calibration weighting," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 673-700, June.
  57. Haight, Thaddeus J. & Wang, Yue & van der Laan, Mark J. & Tager, Ira B., 2010. "A cross-validation deletion-substitution-addition model selection algorithm: Application to marginal structural models," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3080-3094, December.
  58. Benjamin Gochanour & Sixia Chen & Laura Beebe & David Haziza, 2023. "A semiparametric multiply robust multiple imputation method for causal inference," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(5), pages 517-542, July.
  59. Zhiwei Zhang & Zhen Chen & James F. Troendle & Jun Zhang, 2012. "Causal Inference on Quantiles with an Obstetric Application," Biometrics, The International Biometric Society, vol. 68(3), pages 697-706, September.
  60. Chen, Sixia & Haziza, David, 2018. "Jackknife empirical likelihood method for multiply robust estimation with missing data," Computational Statistics & Data Analysis, Elsevier, vol. 127(C), pages 258-268.
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