New Results
Mixed Effects Models for Resampled Network Statistics Improves Statistical Power to Find Differences in Multi-Subject Functional Connectivity
View ORCID ProfileManjari Narayan, Genevera I. Allen
doi: https://doi.org/10.1101/027516
Manjari Narayan
1Department of Electrical and Computer Engineering,
Genevera I. Allen
1Department of Electrical and Computer Engineering,
2Department of Statistics, Rice University, Houston, TX, USA
3Jan and Dan Duncan Neurological Research Institute, Houston, TX, USA
Article usage
Posted March 28, 2016.
Mixed Effects Models for Resampled Network Statistics Improves Statistical Power to Find Differences in Multi-Subject Functional Connectivity
Manjari Narayan, Genevera I. Allen
bioRxiv 027516; doi: https://doi.org/10.1101/027516
Subject Area
Subject Areas
- Biochemistry (11697)
- Bioengineering (8714)
- Bioinformatics (29118)
- Biophysics (14924)
- Cancer Biology (12047)
- Cell Biology (17347)
- Clinical Trials (138)
- Developmental Biology (9405)
- Ecology (14138)
- Epidemiology (2067)
- Evolutionary Biology (18260)
- Genetics (12214)
- Genomics (16759)
- Immunology (11838)
- Microbiology (27986)
- Molecular Biology (11545)
- Neuroscience (60780)
- Paleontology (450)
- Pathology (1864)
- Pharmacology and Toxicology (3228)
- Physiology (4937)
- Plant Biology (10381)
- Synthetic Biology (2876)
- Systems Biology (7332)
- Zoology (1642)