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Related papers: CBARA: Covariate-Balanced-and-Adjusted Response-Ad…

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In clinical trials, a covariate-adjusted response-adaptive (CARA) design allows a subject newly entering a trial a better chance of being allocated to a superior treatment regimen based on cumulative information from previous subjects, and…

Applications · Statistics 2011-06-21 Yuan-chin Ivan Chang , Eunsik Park

Covariate adaptive randomization (CAR) procedures are extensively used to reduce the likelihood of covariate imbalances occurring in clinical trials. In literatures, a lot of CAR procedures have been proposed so that the specified…

Statistics Theory · Mathematics 2026-03-10 Zhang Li-Xin

There has been a split in the statistics community about the need for taking covariates into account in the design phase of a clinical trial. There are many advocates of using stratification and covariate-adaptive randomization to promote…

Methodology · Statistics 2011-02-21 William F. Rosenberger , Oleksandr Sverdlov

Emerging applications increasingly demand flexible covariate adaptive randomization (CAR) methods that support unequal targeted allocation ratios. While existing procedures can achieve covariate balance, they often suffer from the shift…

Methodology · Statistics 2026-02-27 Hengjia Fang , Wei Ma

Covariate-adjusted response-adaptive (CARA) designs have gained widespread adoption for their clear benefits in enhancing experimental efficiency and participant welfare. These designs dynamically adjust treatment allocations during interim…

Methodology · Statistics 2025-12-10 Xinwei Ma , Jingshen Wang , Waverly Wei

Covariate-adaptive randomization (CAR) procedures are frequently used in comparative studies to increase the covariate balance across treatment groups. However, because randomization inevitably uses the covariate information when forming…

Statistics Theory · Mathematics 2022-07-08 Wei Ma , Yichen Qin , Yang Li , Feifang Hu

It is often important to incorporating covariate information in the design of clinical trials. In literature, there are many designs of using stratification and covariate-adaptive randomization to balance on certain known covariate.…

Methodology · Statistics 2009-08-30 Li-Xin Zhang , Feifang Hu

Applications of CAR for balancing continuous covariates remain comparatively rare, especially in multi-treatment clinical trials, and the theoretical properties of multi-treatment CAR have remained largely elusive for decades. In this…

Statistics Theory · Mathematics 2026-02-17 Li-Xin Zhang

Response-adaptive designs have been extensively studied and used in clinical trials. However, there is a lack of a comprehensive study of response-adaptive designs that include covariates, despite their importance in clinical experiments.…

Statistics Theory · Mathematics 2008-12-26 Li-Xin Zhang , Feifang Hu , Siu Hung Cheung , Wai Sum Chan

This paper focuses on the estimation of distributional treatment effects in randomized experiments that use covariate-adaptive randomization (CAR). These include designs such as Efron's biased-coin design and stratified block randomization,…

Econometrics · Economics 2025-06-09 Undral Byambadalai , Tomu Hirata , Tatsushi Oka , Shota Yasui

Balancing influential covariates is crucial for valid treatment comparisons in clinical studies. While covariate-adaptive randomization is commonly used to achieve balance, its performance can be inadequate when the number of baseline…

Methodology · Statistics 2024-12-30 Ziqing Guo , Yang Liu , Lucy Xia

In this paper we propose a general class of covariate-adjusted response-adaptive (CARA) designs based on a new functional urn model. We prove strong consistency concerning the functional urn proportion and the proportion of subjects…

Methodology · Statistics 2019-09-27 Giacomo Aletti , Andrea Ghiglietti , William F. Rosenberger

In the context of precision medicine, covariate-adjusted response-adaptive randomization (CARA) has garnered much attention from both academia and industry due to its benefits in providing ethical and tailored treatment assignments based on…

Methodology · Statistics 2024-11-26 Jiahui Xin , Wei Ma

In modern randomized experiments, large-scale data collection increasingly yields rich baseline covariates and auxiliary information from multiple sources. Such information offers opportunities for more precise treatment effect estimation,…

Methodology · Statistics 2026-03-10 Wei Ma , Zeqi Wu , Zheng Zhang

Multi-arm randomization has increasingly widespread applications recently and it is also crucial to ensure that the distributions of important observed covariates as well as the potential unobserved covariates are similar and comparable…

Applications · Statistics 2024-12-20 Xingjian Ma , Yang Liu

We investigate how to improve efficiency using regression adjustments with covariates in covariate-adaptive randomizations (CARs) with imperfect subject compliance. Our regression-adjusted estimators, which are based on the doubly robust…

Econometrics · Economics 2023-06-19 Liang Jiang , Oliver B. Linton , Haihan Tang , Yichong Zhang

Covariate-adjusted randomization (CAR) can reduce the risk of covariate imbalance and, when accounted for in analysis, increase the power of a trial. Despite CAR advances, stratified randomization remains the most common CAR method. Matched…

Methodology · Statistics 2023-07-13 Jonathan J. Chipman , Lindsay Mayberry , Robert A. Greevy

Response adaptive randomization (RAR) is appealing from methodological, ethical, and pragmatic perspectives in the sense that subjects are more likely to be randomized to better performing treatment groups based on accumulating data.…

Methodology · Statistics 2022-08-03 Tianyu Zhan , Lu Cui , Ziqian Geng , Lanju Zhang , Yihua Gu , Ivan S. F. Chan

In most clinical trials, patients are randomized with equal probability among treatments to obtain an unbiased estimate of the treatment effect. Response-adaptive randomization (RAR) has been proposed for ethical reasons, where the…

Applications · Statistics 2019-09-16 Thevaa Chandereng , Rick Chappell

This paper studies inference in a randomized controlled trial (RCT) with covariate-adaptive randomization (CAR) and imperfect compliance of a binary treatment. In this context, we study inference on the LATE. As in Bugni et al. (2018,2019),…

Econometrics · Economics 2023-07-25 Federico A. Bugni , Mengsi Gao
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