GraphMM, a graph-based empirical Bayes mixture model, controls false discovery rates and improves power for detecting spatially coherent effects in large-scale brain-imaging tests.
and Frazier, Peter I
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Dimension constraints improve hypothesis testing for large-scale, graph-associated, brain-image data
GraphMM, a graph-based empirical Bayes mixture model, controls false discovery rates and improves power for detecting spatially coherent effects in large-scale brain-imaging tests.