Multiple testing correction over contrasts for brain imaging
Abstract
The multiple testing problem arises not only when there are many voxels or vertices in an image representation of the brain, but also when multiple contrasts of parameter estimates (that represent hypotheses) are tested in the same general linear model. We argue that a correction for this multiplicity must be performed to avoid excess of false positives. Various methods for correction have been proposed in the literature, but few have been...
Paper Details
Title
Multiple testing correction over contrasts for brain imaging
Published Date
Aug 1, 2020
Journal
Volume
216
Pages
116760 - 116760
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