Empirical Efficiency Maximization: Improved Locally Efficient Covariate Adjustment in Randomized Experiments and Survival Analysis
Author
Abstract
Suggested Citation
DOI: 10.2202/1557-4679.1084
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Daniel O. Scharfstein, 2002. "Estimation of the failure time distribution in the presence of informative censoring," Biometrika, Biometrika Trust, vol. 89(3), pages 617-634, August.
- Satten, Glen A. & Datta, Somnath & Robins, James, 2001. "Estimating the marginal survival function in the presence of time dependent covariates," Statistics & Probability Letters, Elsevier, vol. 54(4), pages 397-403, October.
- David Clayton & David Spiegelhalter & Graham Dunn & Andrew Pickles, 1998. "Analysis of longitudinal binary data from multiphase sampling," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 60(1), pages 71-87.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- 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.
- van der Laan Mark J., 2010. "Targeted Maximum Likelihood Based Causal Inference: Part I," The International Journal of Biostatistics, De Gruyter, vol. 6(2), pages 1-45, February.
- Wang, Qihua & Su, Miaomiao & Wang, Ruoyu, 2021. "A beyond multiple robust approach for missing response problem," Computational Statistics & Data Analysis, Elsevier, vol. 155(C).
- Peisong Han, 2016. "Intrinsic efficiency and multiple robustness in longitudinal studies with drop-out," Biometrika, Biometrika Trust, vol. 103(3), pages 683-700.
- 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.
- van der Laan Mark J. & Gruber Susan, 2010. "Collaborative Double Robust Targeted Maximum Likelihood Estimation," The International Journal of Biostatistics, De Gruyter, vol. 6(1), pages 1-71, May.
- 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.
- 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.
- 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.
- Rubin Daniel B. & van der Laan Mark J., 2012. "Statistical Issues and Limitations in Personalized Medicine Research with Clinical Trials," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-20, July.
- David Benkeser & Iván Díaz & Alex Luedtke & Jodi Segal & Daniel Scharfstein & Michael Rosenblum, 2021. "Improving precision and power in randomized trials for COVID‐19 treatments using covariate adjustment, for binary, ordinal, and time‐to‐event outcomes," Biometrics, The International Biometric Society, vol. 77(4), pages 1467-1481, December.
- 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.
- 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.
- Han, Peisong, 2012. "A note on improving the efficiency of inverse probability weighted estimator using the augmentation term," Statistics & Probability Letters, Elsevier, vol. 82(12), pages 2221-2228.
- 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.
- Rosenblum Michael & van der Laan Mark J., 2010. "Simple, Efficient Estimators of Treatment Effects in Randomized Trials Using Generalized Linear Models to Leverage Baseline Variables," The International Journal of Biostatistics, De Gruyter, vol. 6(1), pages 1-44, April.
- Edwards, Ben & Yu, Maggie, 2018. "The influence of child care on the behavior problems of children of teenage mothers," Children and Youth Services Review, Elsevier, vol. 94(C), pages 96-104.
- Wei Zhang & Zhiwei Zhang & Aiyi Liu, 2023. "Optimizing treatment allocation in randomized clinical trials by leveraging baseline covariates," Biometrics, The International Biometric Society, vol. 79(4), pages 2815-2829, December.
- Tan, Zhiqiang, 2014. "Second-order asymptotic theory for calibration estimators in sampling and missing-data problems," Journal of Multivariate Analysis, Elsevier, vol. 131(C), pages 240-253.
- 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.
- 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.
- Giorgio Brunello & Lorenzo Rocco, 2017. "The Labor Market Effects of Academic and Vocational Education over the Life Cycle: Evidence Based on a British Cohort," Journal of Human Capital, University of Chicago Press, vol. 11(1), pages 106-166.
- 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.
- Nicholas Williams & Michael Rosenblum & Iván Díaz, 2022. "Optimising precision and power by machine learning in randomised trials with ordinal and time‐to‐event outcomes with an application to COVID‐19," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(4), pages 2156-2178, October.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Richard J. Cook & Jerald F. Lawless, 2020. "Failure time studies with intermittent observation and losses to follow‐up," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(4), pages 1035-1063, December.
- Greg DiRienzo, 2004. "Nonparametric Comparison of Two Survival-Time Distributions in the Presence of Dependent Censoring," Harvard University Biostatistics Working Paper Series 1000, Berkeley Electronic Press.
- A. G. DiRienzo, 2003. "Nonparametric Comparison of Two Survival-Time Distributions in the Presence of Dependent Censoring," Biometrics, The International Biometric Society, vol. 59(3), pages 497-504, September.
- Tchetgen Tchetgen, Eric J. & Robins, James, 2012. "On parametrization, robustness and sensitivity analysis in a marginal structural Cox proportional hazards model for point exposure," Statistics & Probability Letters, Elsevier, vol. 82(5), pages 907-915.
- Miran A. Jaffa & Ayad A. Jaffa, 2019. "A Likelihood-Based Approach with Shared Latent Random Parameters for the Longitudinal Binary and Informative Censoring Processes," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 11(3), pages 597-613, December.
- Fotios Siannis, 2004. "Applications of a Parametric Model for Informative Censoring," Biometrics, The International Biometric Society, vol. 60(3), pages 704-714, September.
- Maja Pohar Perme & Janez Stare & Jacques Estève, 2012. "On Estimation in Relative Survival," Biometrics, The International Biometric Society, vol. 68(1), pages 113-120, March.
- Xuelin Huang & Nan Zhang, 2008. "Regression Survival Analysis with an Assumed Copula for Dependent Censoring: A Sensitivity Analysis Approach," Biometrics, The International Biometric Society, vol. 64(4), pages 1090-1099, December.
- Shu Yang & Yilong Zhang & Guanghan Frank Liu & Qian Guan, 2023. "SMIM: A unified framework of survival sensitivity analysis using multiple imputation and martingale," Biometrics, The International Biometric Society, vol. 79(1), pages 230-240, March.
- Subramanian, Sundarraman & Bandyopadhyay, Dipankar, 2010. "Doubly robust semiparametric estimation for the missing censoring indicator model," Statistics & Probability Letters, Elsevier, vol. 80(7-8), pages 621-630, April.
- Richard M. Golden & Steven S. Henley & Halbert White & T. Michael Kashner, 2019. "Consequences of Model Misspecification for Maximum Likelihood Estimation with Missing Data," Econometrics, MDPI, vol. 7(3), pages 1-27, September.
- Yuhyun Park & Lu Tian & L. J. Wei, 2004. "One- and Two-Sample Nonparametric Inference Procedures in the Presence of Dependent Censoring," Harvard University Biostatistics Working Paper Series 1012, Berkeley Electronic Press.
- Oliver Dukes & Torben Martinussen & Eric J. Tchetgen Tchetgen & Stijn Vansteelandt, 2019. "On doubly robust estimation of the hazard difference," Biometrics, The International Biometric Society, vol. 75(1), pages 100-109, March.
- Pablo Gonzalez Ginestet & Ales Kotalik & David M. Vock & Julian Wolfson & Erin E. Gabriel, 2021. "Stacked inverse probability of censoring weighted bagging: A case study in the InfCareHIV Register," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(1), pages 51-65, January.
- Karen Lostritto & Robert L. Strawderman & Annette M. Molinaro, 2012. "A Partitioning Deletion/Substitution/Addition Algorithm for Creating Survival Risk Groups," Biometrics, The International Biometric Society, vol. 68(4), pages 1146-1156, December.
- James R. Carpenter & Michael G. Kenward & Stijn Vansteelandt, 2006. "A comparison of multiple imputation and doubly robust estimation for analyses with missing data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(3), pages 571-584, July.
- Daniel O. Scharfstein & Rafael A. Irizarry, 2003. "Generalized Additive Selection Models for the Analysis of Studies with Potentially Nonignorable Missing Outcome Data," Biometrics, The International Biometric Society, vol. 59(3), pages 601-613, September.
- Sedigheh Mirzaei Salehabadi & Debasis Sengupta & Rituparna Das, 2015. "Parametric Estimation of Menarcheal Age Distribution Based on Recall Data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 290-305, March.
- repec:jss:jstsof:43:i13 is not listed on IDEAS
- Shen, Pao-sheng, 2010. "Semiparametric estimation of survival function when data are subject to dependent censoring and left truncation," Statistics & Probability Letters, Elsevier, vol. 80(3-4), pages 161-168, February.
- Fan, Jie & Datta, Somnath, 2011. "Fitting marginal accelerated failure time models to clustered survival data with potentially informative cluster size," Computational Statistics & Data Analysis, Elsevier, vol. 55(12), pages 3295-3303, December.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bpj:ijbist:v:4:y:2008:i:1:n:5. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Peter Golla (email available below). General contact details of provider: https://www.degruyter.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.