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A hybrid procedure for detecting global treatment effects in multivariate clinical trials : theory and applications to fMRI studies
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Minas, Giorgos, Rigat, Fabio, Nichols, Thomas E., Aston, John A. D. and Stallard, Nigel (2012) A hybrid procedure for detecting global treatment effects in multivariate clinical trials : theory and applications to fMRI studies. Statistics in Medicine, Vol.31 (No.3). pp. 253-268. doi:10.1002/sim.4395 ISSN 0277-6715.
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Official URL: http://dx.doi.org/10.1002/sim.4395
Abstract
In multivariate clinical trials, a key research endpoint is ascertaining whether a candidate treatment is more efficacious than an established alternative. This global endpoint is clearly of high practical value for studies, such as those arising from neuroimaging, where the outcome dimensions are not only numerous but they are also highly correlated and the available sample sizes are typically small. In this paper, we develop a two-stage procedure testing the null hypothesis of global equivalence between treatments effects and demonstrate its application to analysing phase II neuroimaging trials. Prior information such as suitable statistics of historical data or suitably elicited expert clinical opinions are combined with data collected from the first stage of the trial to learn a set of optimal weights. We apply these weights to the outcome dimensions of the second-stage responses to form the linear combination z and t tests statistics while controlling the test's false positive rate. We show that the proposed tests hold desirable asymptotic properties and characterise their power functions under wide conditions. In particular, by comparing the power of the proposed tests with that of Hotelling's T2, we demonstrate their advantages when sample sizes are close to the dimension of the multivariate outcome. We apply our methods to fMRI studies, where we find that, for sufficiently precise first stage estimates of the treatment effect, standard single-stage testing procedures are outperformed. Copyright © 2011 John Wiley & Sons, Ltd.
Item Type: | Journal Article | ||||
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Subjects: | Q Science > QA Mathematics R Medicine > R Medicine (General) |
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Divisions: | Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School > Health Sciences Faculty of Science, Engineering and Medicine > Science > Statistics Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School Faculty of Science, Engineering and Medicine > Engineering > WMG (Formerly the Warwick Manufacturing Group) |
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Library of Congress Subject Headings (LCSH): | Multivariate analysis, Statistical hypothesis testing, Magnetic resonance imaging, Clinical trials | ||||
Journal or Publication Title: | Statistics in Medicine | ||||
Publisher: | John Wiley & Sons Ltd. | ||||
ISSN: | 0277-6715 | ||||
Official Date: | 10 February 2012 | ||||
Dates: |
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Volume: | Vol.31 | ||||
Number: | No.3 | ||||
Page Range: | pp. 253-268 | ||||
DOI: | 10.1002/sim.4395 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access | ||||
Funder: | University of Warwick. Centre for Analytical Science | ||||
Grant number: | EP/F034210/1 (UoW) |
Data sourced from Thomson Reuters' Web of Knowledge
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