D-optimal designs for multiarm trials with dropouts

Lee, Kim May, Biedermann, Stefanie and Mitra, Robin ORCID: https://orcid.org/0000-0001-9584-8044 2019. D-optimal designs for multiarm trials with dropouts. Statistics in Medicine 38 (15) , pp. 2749-2766. 10.1002/sim.8148

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Abstract

Multiarm trials with follow-up on participants are commonly implemented to assess treatment effects on a population over the course of the studies. Dropout is an unavoidable issue especially when the duration of the multiarm study is long. Its impact is often ignored at the design stage, which may lead to less accurate statistical conclusions. We develop an optimal design framework for trials with repeated measurements, which takes potential dropouts into account, and we provide designs for linear mixed models where the presence of dropouts is noninformative and dependent on design variables. Our framework is illustrated through redesigning a clinical trial on Alzheimer's disease, whereby the benefits of our designs compared with standard designs are demonstrated through simulations. © 2019 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Mathematics
Publisher:	John Wiley and Sons
ISSN:	0277-6715
Date of First Compliant Deposit:	11 January 2022
Last Modified:	08 May 2023 10:48
URI:	https://orca.cardiff.ac.uk/id/eprint/146470

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