A rank-based graph test detects whether within-group similarity improves prediction of Y from X, with asymptotic normality claimed under permutation of group labels.
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Graph-theoretic Inference for Random Effects in High-dimensional Studies
A rank-based graph test detects whether within-group similarity improves prediction of Y from X, with asymptotic normality claimed under permutation of group labels.