Discussion of “Improving precision and power in randomized trials for COVID‐19 treatments using covariate adjustment, for binary, ordinal, and time‐to‐event outcomes”
Author
Abstract
Suggested Citation
DOI: 10.1111/biom.13492
Download full text from publisher
References listed on IDEAS
- Min Zhang & Anastasios A. Tsiatis & Marie Davidian, 2008. "Improving Efficiency of Inferences in Randomized Clinical Trials Using Auxiliary Covariates," Biometrics, The International Biometric Society, vol. 64(3), pages 707-715, September.
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.- 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.
- Jiang, Liang & Phillips, Peter C.B. & Tao, Yubo & Zhang, Yichong, 2023.
"Regression-adjusted estimation of quantile treatment effects under covariate-adaptive randomizations,"
Journal of Econometrics, Elsevier, vol. 234(2), pages 758-776.
- Liang Jiang & Xiaobin Liu & Peter C.B. Phillips & Yichong Zhang, 2021. "Regression-Adjusted Estimation of Quantile Treatment Effects under Covariate-Adaptive Randomizations," Cowles Foundation Discussion Papers 2288, Cowles Foundation for Research in Economics, Yale University.
- Liang Jiang & Peter C. B. Phillips & Yubo Tao & Yichong Zhang, 2021. "Regression-Adjusted Estimation of Quantile Treatment Effects under Covariate-Adaptive Randomizations," Papers 2105.14752, arXiv.org, revised Sep 2022.
- Yuehao Bai & Jizhou Liu & Azeem M. Shaikh & Max Tabord-Meehan, 2023. "On the Efficiency of Finely Stratified Experiments," Papers 2307.15181, arXiv.org, revised Aug 2024.
- Paul Frédéric Blanche & Anders Holt & Thomas Scheike, 2023. "On logistic regression with right censored data, with or without competing risks, and its use for estimating treatment effects," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 29(2), pages 441-482, April.
- Hennessy Jonathan & Dasgupta Tirthankar & Miratrix Luke & Pattanayak Cassandra & Sarkar Pradipta, 2016. "A Conditional Randomization Test to Account for Covariate Imbalance in Randomized Experiments," Journal of Causal Inference, De Gruyter, vol. 4(1), pages 61-80, March.
- Lola Etievant & Joshua N. Sampson & Mitchell H. Gail, 2023. "Increasing efficiency and reducing bias when assessing HPV vaccination efficacy by using nontargeted HPV strains," Biometrics, The International Biometric Society, vol. 79(2), pages 1534-1545, June.
- Tianchen Qian & Constantine Frangakis & Constantin Yiannoutsos, 2020. "Deductive Semiparametric Estimation in Double-Sampling Designs with Application to PEPFAR," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(3), pages 417-445, December.
- Yuanyuan Shen & Tianxi Cai, 2016. "Identifying predictive markers for personalized treatment selection," Biometrics, The International Biometric Society, vol. 72(4), pages 1017-1025, December.
- 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.
- Paola Berchialla & Veronica Sciannameo & Sara Urru & Corrado Lanera & Danila Azzolina & Dario Gregori & Ileana Baldi, 2021. "Adjustment for Baseline Covariates to Increase Efficiency in RCTs with Binary Endpoint: A Comparison of Bayesian and Frequentist Approaches," IJERPH, MDPI, vol. 18(15), pages 1-9, July.
- Jingxuan Guo & Fuguo Liu & Wolfgang Karl Härdle & Xueliang Zhang & Kai Wang & Ting Zeng & Liping Yang & Maozai Tian, 2023. "Sampling Importance Resampling Algorithm with Nonignorable Missing Response Variable Based on Smoothed Quantile Regression," Mathematics, MDPI, vol. 11(24), pages 1-30, December.
- 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.
- Layla Parast & Beth Ann Griffin, 2017. "Landmark estimation of survival and treatment effects in observational studies," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(2), pages 161-182, April.
- Wang, Qihua & Su, Miaomiao & Wang, Ruoyu, 2021. "A beyond multiple robust approach for missing response problem," Computational Statistics & Data Analysis, Elsevier, vol. 155(C).
- 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.
- Zhiwei Zhang & Wei Li & Hui Zhang, 2020. "Efficient Estimation of Mann–Whitney-Type Effect Measures for Right-Censored Survival Outcomes in Randomized Clinical Trials," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 12(2), pages 246-262, July.
- 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.
- Michael J. Martens & Brent R. Logan, 2020. "Group sequential tests for treatment effect on survival and cumulative incidence at a fixed time point," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(3), pages 603-623, July.
- Zhao, Anqi & Ding, Peng, 2021. "Covariate-adjusted Fisher randomization tests for the average treatment effect," Journal of Econometrics, Elsevier, vol. 225(2), pages 278-294.
- Yuan, Ao & Zheng, Yanxun & Huang, Peng & Tan, Ming T., 2016. "A nonparametric test for the evaluation of group sequential clinical trials with covariate information," Journal of Multivariate Analysis, Elsevier, vol. 152(C), pages 82-99.
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:bla:biomet:v:77:y:2021:i:4:p:1485-1488. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0006-341X .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.