Literature DB >> 16918921

Response-adaptive randomization for clinical trials with continuous outcomes.

Lanju Zhang1, William F Rosenberger.   

Abstract

We provide an explicit asymptotic method to evaluate the performance of different response-adaptive randomization procedures in clinical trials with continuous outcomes. We use this method to investigate four different response-adaptive randomization procedures. Their performance, especially in power and treatment assignment skewing to the better treatment, is thoroughly evaluated theoretically. These results are then verified by simulation. Our analysis concludes that the doubly adaptive biased coin design procedure targeting optimal allocation is the best one for practical use. We also consider the effect of delay in responses and nonstandard responses, for example, Cauchy distributed response. We illustrate our procedure by redesigning a real clinical trial.

Mesh:

Year:  2006        PMID: 16918921     DOI: 10.1111/j.1541-0420.2005.00496.x

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  7 in total

1.  A surrogate-primary replacement algorithm for response-adaptive randomization in stroke clinical trials.

Authors:  Amy S Nowacki; Wenle Zhao; Yuko Y Palesch
Journal:  Stat Methods Med Res       Date:  2015-01-12       Impact factor: 3.021

2.  Implementing Optimal Allocation in Clinical Trials with Multiple Endpoints.

Authors:  Lu Wang; Yong Chen; Hongjian Zhu
Journal:  J Stat Plan Inference       Date:  2016-10-07       Impact factor: 1.111

3.  A Unified Family of Covariate-Adjusted Response-Adaptive Designs Based on Efficiency and Ethics.

Authors:  Jianhua Hu; Hongjian Zhu; Feifang Hu
Journal:  J Am Stat Assoc       Date:  2015-04-22       Impact factor: 5.033

4.  A simulation study for comparing testing statistics in response-adaptive randomization.

Authors:  Xuemin Gu; J Jack Lee
Journal:  BMC Med Res Methodol       Date:  2010-06-05       Impact factor: 4.615

5.  The Method of Randomization for Cluster-Randomized Trials: Challenges of Including Patients with Multiple Chronic Conditions.

Authors:  Denise Esserman; Heather G Allore; Thomas G Travison
Journal:  Int J Stat Med Res       Date:  2016-01-08

6.  A response-adaptive randomization procedure for multi-armed clinical trials with normally distributed outcomes.

Authors:  S Faye Williamson; Sofía S Villar
Journal:  Biometrics       Date:  2019-09-19       Impact factor: 2.571

7.  Some performance considerations when using multi-armed bandit algorithms in the presence of missing data.

Authors:  Xijin Chen; Kim May Lee; Sofia S Villar; David S Robertson
Journal:  PLoS One       Date:  2022-09-12       Impact factor: 3.752

  7 in total

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