Bootstrap Enhanced Penalized Regression for Variable Selection with Neuroimaging Data

Bootstrap Enhanced Penalized Regression for Variable Selection with Neuroimaging Data

Recent advances in fMRI research highlight the use of multivariate methods for examining whole-brain connectivity. Complementary data-driven methods are needed for determining the subset of predictors related to individual differences. Although commonly used for this purpose, ordinary least squares...

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Bibliographic Details
Main Authors: Samantha Valerie Abram, Nathaniel Helwig, Craig Moodie, Colin G DeYoung, Angus W MacDonald III, Niels Waller
Format: Article
Language:English
Published: Frontiers Media S.A. 2016-07-01
Series:Frontiers in Neuroscience
Subjects:
fMRI
individual differences
functional connectivity
Independent Component Analysis
Bootstrap
penalized regression
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnins.2016.00344/full

Internet

http://journal.frontiersin.org/Journal/10.3389/fnins.2016.00344/full

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