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Robertson, David S. ; Burnett, Thomas ; Choodari‐Oskooei, Babak ; Dimairo, Munya ; Grayling, Michael ; Pallmann, Philip ; Jaki, Thomas

Confidence Intervals for Adaptive Trial Designs II: Case Study and Practical Guidance

Robertson, David S., Burnett, Thomas, Choodari‐Oskooei, Babak, Dimairo, Munya, Grayling, Michael, Pallmann, Philip and Jaki, Thomas (2025) Confidence Intervals for Adaptive Trial Designs II: Case Study and Practical Guidance. Statistics in Medicine 44 (18-19), e70202.

Date of publication of this fulltext: 22 Sep 2025 04:47
Article
DOI to cite this document: 10.5283/epub.77709


Abstract

In adaptive clinical trials, the conventional confidence interval (CI) for a treatment effect is prone to undesirable properties such as undercoverage and potential inconsistency with the final hypothesis testing decision. Accordingly, as is stated in recent regulatory guidance on adaptive designs, there is the need for caution in the interpretation of CIs constructed during and after an adaptive ...

In adaptive clinical trials, the conventional confidence interval (CI) for a treatment effect is prone to undesirable properties such as undercoverage and potential inconsistency with the final hypothesis testing decision. Accordingly, as is stated in recent regulatory guidance on adaptive designs, there is the need for caution in the interpretation of CIs constructed during and after an adaptive clinical trial. However, it may be unclear which of the available CIs in the literature are preferable. This paper is the second in a two-part series that explores CIs for adaptive trials. Part I provided a methodological review of approaches to construct CIs for adaptive designs. In this paper (Part II), we present an extended case study based around a two-stage group sequential trial, including a comprehensive simulation study of the proposed CIs for this setting. This facilitates an expanded description of considerations around what makes for an effective CI procedure following an adaptive trial. We show that the CIs can have notably different properties. Finally, we propose a set of guidelines for researchers around the choice of CIs and the reporting of CIs following an adaptive design.



Involved Institutions


Details

Item typeArticle
Journal or Publication TitleStatistics in Medicine
Publisher:Wiley
Volume:44
Number of Issue or Book Chapter:18-19
Page Range:e70202
Date8 August 2025
InstitutionsInformatics and Data Science > Department Machine Learning & Data Science > Lehrstuhl für Computational Statistics (Prof. Dr. Thomas Jaki)
Identification Number
ValueType
10.1002/sim.70202DOI
Keywordsadaptive design bootstrap conditional inference coverage estimation group sequential interim analyses
Dewey Decimal Classification000 Computer science, information & general works > 004 Computer science
StatusPublished
RefereedYes, this version has been refereed
Created at the University of RegensburgPartially
URN of the UB Regensburgurn:nbn:de:bvb:355-epub-777093
Item ID77709

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