Dear AFNI experts,
my aim is to run a multiple linear regression on resting state functional connectivity maps from 17 subjects.
Predictors are represented by a 10-dimensional questionnaire.
I'm particularly interested in obtaining R
2 coefficient, for each predictor, for each voxel. It is clear that I need to take in account dependencies between predictors, in this analysis.
I'm aware that a PCA can help solve this problem, but there is a way to take into account multicollinearity in 3dRegAna (or other programs) in multiple regression?
A related question: is there a method that allows to use independent bootstrapped regressions on input data (something similar to random trees generation)?
