@article{7e8c900110a343c294da190854eff944,
title = "D-optimal designs for multiarm trials with dropouts",
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.",
keywords = "available case analysis, design of experiments, linear mixed models, noninformative dropouts",
author = "Lee, {Kim May} and S Biedermann and R Mitra",
note = "Funding Information: We would like to thank two unknown reviewers for their careful reading of our work and for useful suggestions that led to substantial improvements of our paper. The first author's research has been funded by the Institute for Life Sciences at the University of Southampton and by the Medical Research Council (grants MR/N028171 and MC_UP_1302/4). We would like to acknowledge Clive Holmes, Robert Howard, and Patrick Philips for supplying us with the data from the DOMINO study RCTN49545035, which was funded by the MRC and Alzheimer's Society, UK. Funding Information: We would like to thank two unknown reviewers for their careful reading of our work and for useful suggestions that led to substantial improvements of our paper. The first author's research has been funded by the Institute for Life Sciences at the University of Southampton and by the Medical Research Council (grants MR/N028171 and MC_UP_1302/4). We would like to acknowledge Clive Holmes, Robert Howard, and Patrick Philips for supplying us with the data from the DOMINO study RCTN49545035, which was funded by the MRC and Alzheimer's Society, UK. The authors declare no potential conflict of interests. Funding Information: Institute for Life Sciences at the University of Southampton; Medical Research Council, Grant/Award Number: MR/N028171 and MC_UP_1302/4; MRC and Alzheimer's Society UK, Grant/Award Number: RCTN49545035 Publisher Copyright: {\textcopyright} 2019 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. Copyright: Copyright 2019 Elsevier B.V., All rights reserved.",
year = "2019",
month = jul,
day = "10",
doi = "10.1002/sim.8148",
language = "English",
volume = "38",
pages = "2749--2766",
journal = "Statistics in Medicine",
issn = "0277-6715",
publisher = "Wiley-Blackwell",
number = "15",
}