# Permutation-based true discovery proportions for fMRI cluster analysis.

@article{Andreella2020PermutationbasedTD, title={Permutation-based true discovery proportions for fMRI cluster analysis.}, author={Angela Andreella and Jesse Hemerik and Wouter D. Weeda and Livio Finos and Jelle J. Goeman}, journal={arXiv: Applications}, year={2020} }

We develop a general permutation-based closed testing method to compute a simultaneous lower confidence bound for the true discovery proportions of all possible subsets of a hypothesis testing problem. It is particularly useful in functional Magnetic Resonance Imaging cluster analysis, where it is of interest to select a cluster of voxels and to provide a confidence statement on the percentage of truly activated voxels within that cluster, avoiding the well-known spatial specificity paradox. We…

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