AFNI Message Board

Dear AFNI users-

We are very pleased to announce that the new AFNI Message Board framework is up! Please join us at:

https://discuss.afni.nimh.nih.gov

Existing user accounts have been migrated, so returning users can login by requesting a password reset. New users can create accounts, as well, through a standard account creation process. Please note that these setup emails might initially go to spam folders (esp. for NIH users!), so please check those locations in the beginning.

The current Message Board discussion threads have been migrated to the new framework. The current Message Board will remain visible, but read-only, for a little while.

Sincerely, AFNI HQ

History of AFNI updates  

Previous Message Next Message
Message List New Topic Print View
|
swijeakumar
February 27, 2014 03:04AM
Hi all

I have question about multicollinearity issues.

I have data from 10 subjects and 3 runs each. There are 12 regressors (two types of trials x hit or misses x 3 stages in a trial). 1dplot.py on the xmat design matrix tells me that the last two stages of each trial are correlated (>0.7). I used 3dDeconvolve.

If I was interested in closely examining the contributions of these two regressors (last two stages of the trials) at certain brain areas more closely, am I right in following what Erdinez et al did (see attached)?
i.e...
I can pull out my two regressors in question, orthogonalize one with respect to the other in matlab, for instance (with function qr or gram-schmidt orthogonalization) and then use them in GLM models like he/she did to study the contributions of these regressors to common areas in the brain?

OR

Is there another straightforward way to go about this?

Thank you!

Sobana
Reply Quote
RSS
Subject Author Posted

Mutlicollinearity Issues

swijeakumar February 27, 2014 03:04AM

Re: Mutlicollinearity Issues

swijeakumar February 27, 2014 03:05AM

Re: Mutlicollinearity Issues

gang February 28, 2014 10:31AM

Re: Mutlicollinearity Issues

swijeakumar March 03, 2014 03:38PM