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Spatial-extent inference for testing variance components in reliability and heritability studies
Ruyi Pan1,2, Erin W Dickie2,3, Colin Hawco2,3
1Department of Statistical Sciences, University of Toronto, Toronto, ON, M5G 1Z5, Canada.
Biorxiv : the Preprint Server for Biology
|May 3, 2023
Summary
We developed CLEAN-V, a powerful statistical test for variance components in neuroimaging. This method enhances the detection of heritability and reliability, outperforming existing approaches with improved statistical power.
Area of Science:
- Neuroimaging
- Statistical Genetics
- Brain Imaging Analysis
Background:
- Clusterwise inference is common in neuroimaging for sensitivity but limited to General Linear Model (GLM) for mean parameters.
- Statistical methods for variance components, crucial for heritability and reliability, are underdeveloped and often lack power due to computational challenges.
Conclusions:
- CLEAN-V offers a computationally efficient and practically useful tool for analyzing variance components in neuroimaging.
- The method significantly enhances the power to detect heritability and reliability, outperforming current techniques.
Keywords:
clusterwise inferenceheritabilityspatial autocorrelationtask-fMRItest-retest reliabilityvariance componentMore Related Videos
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