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Lookup NU author(s): Dr Jian Shi,
Professor Janet Eyre
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© 2018 John Wiley & Sons, Ltd. In this paper, we propose a large-scale multiple testing procedure to find the significant sub-areas between two samples of curves automatically. The procedure is optimal in that it controls the directional false discovery rate at any specified level on a continuum asymptotically. By introducing a nonparametric Gaussian process regression model for the two-sided multiple test, the procedure is computationally inexpensive. It can cope with problems with multidimensional covariates and accommodate different sampling designs across the samples. We further propose the significant curve/surface, giving an insight on dynamic significant differences between two curves. Simulation studies demonstrate that the proposed procedure enjoys superior performance with strong power and good directional error control. The procedure is also illustrated with the application to two executive function studies in hemiplegia.
Author(s): Xu P, Lee Y, Shi JQ, Eyre J
Publication type: Article
Publication status: Published
Journal: Statistics in Medicine
Print publication date: 10/02/2019
Online publication date: 17/09/2018
Acceptance date: 22/08/2018
ISSN (print): 0277-6715
ISSN (electronic): 1097-0258
Publisher: John Wiley and Sons Ltd
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