Nevin Manimala Statistics

Evidence for embracing normative modeling

Elife. 2023 Mar 13;12:e85082. doi: 10.7554/eLife.85082. Online ahead of print.


In this work, we expand the normative model repository introduced in (Rutherford, Fraza, et al., 2022) to include normative models charting lifespan trajectories of structural surface area and brain functional connectivity, measured using two unique resting-state network atlases (Yeo-17 and Smith-10), and an updated online platform for transferring these models to new data sources. We showcase the value of these models with a head-to-head comparison between the features output by normative modeling and raw data features in several benchmarking tasks: mass univariate group difference testing (schizophrenia versus control), classification (schizophrenia versus control), and regression (predicting general cognitive ability). Across all benchmarks, we show the advantage of using normative modeling features, with the strongest statistically significant results demonstrated in the group difference testing and classification tasks. We intend for these accessible resources to facilitate wider adoption of normative modeling across the neuroimaging community.

PMID:36912775 | DOI:10.7554/eLife.85082

By Nevin Manimala

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