Thanks Anderson,I
see.
For the 1st
question,did I need demean behavior data when I used -D option?
For the 2nd
question,what I think below are appropriate?
1,Output of randomise
is an inference based on non-paramatric method, and result from FEAT is an
inference based on paramatric method.
2,For VBM and TBSS(for
gray matter and white matter respectively),can I use the same GLM setup which is
used for randomise previously to perform paramatric inference by FEAT at the
end(not by randomise)? That is to say, I want to use FEAT not randomise to
perform paramatric inference.
Thanks again,
Anderson.
All the
best.
Rujing Zha
2014-02-07
charujing123
发送时间：2014-02-07 17:45
主题：Re: [FSL] question about
"randomise -D option" and "GLM design in Two-Group Difference"
抄送：
Hi,
The -D option in recent versions of FSL removes the mean from both the data
and the design matrix EVs.
Permutations and t-tests are not mutually exclusive. You are still
using t-tests (or F-tests if you combine t-tests) in randomise, but the method
by which it performs inference (calculating probabilities) uses a
permutation-based non-parameteric method, as opposed to tools like FEAT where
parametric methods are used. This is totally separate from the fact that
you are performing a t-test.
All the best,
Mark
Hi Anderson and other FSL
experts,
I have a two
questions about FSL statistics.
1,As we know, there
is a -D option in randomise,which is "demeaning data temporally before model
fitting". What I wonder is -D option demean what data, either only MR data or
both for MR data and behavior data?
Thanks Anderson and
others.
All the
best.
Rujing Zha
2014-02-07
charujing123