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Inference for Heterogeneous Graphical Models using Doubly High-Dimensional Linear-Mixed Models

2024 · arXiv (Cornell University)

Motivated by the problem of inferring the graph structure of functional connectivity networks from multi-level functional magnetic resonance imaging data, we develop a valid inference framework for high-dimensional graphical models that accounts for group-level heterogeneity. …