BIRS Workshop Lecture Videos
Two-Sample Tests for Connectomes using Distance Statistics Shinohara, Russell
We propose statistical methods for quantifying variability in a population of connectomes using general representations. While the graphical model literature is growing, little work has been done comprehensively studying populations of graphs in without distributional assumptions. To study this, we use generalized variances for complex objects based on distance statistics. We further develop methods for two-sample testing at the whole connectome and the subnetwork levels and study the asymptotic properties of the test statistics. We demonstrate the utility of these methods in a connectomic study of autism spectrum disorders using diffusion tensor imaging.
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