You would do a first level fixed effects analysis for each subject. If you did three runs for each subject then go ahead and treat as three sessions of non-repeated conditions. This will add some extra regressors of no interest "session regressors". You can then create a contrast for each subject that is then used for the random effects analysis (2nd level).
If you had 2 conditions A and B, and occuring in each session then your contrast for A-B would be "1 -1 1 -1 1 -1" right padded with zeros for the regressors of no interest. This will produce a single contrast image that is used for the random effects analysis.
Robert Welsh
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Robert C. Welsh, PhD
Research Investigator
Department of Radiology
University of Michigan
(734) - 764 - 2412 (fax)
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>>> "<Eric> <Long>" <[log in to unmask]> 06/03/02 05:23PM >>>
An fMRI story---
for each subject we performed three runs- each run was essentially
the same except for the order of conditions (blocks) was
counterbalanced. I used Roger Woods tools to do my data pre-
processing and now have everything in 'analyze formate' -- I'm
intending to eventually do a random effects analysis but understand I
must first generate a fixed effects model --- QUESTION: Should I
concatinate runs so that I have one long session for each subject or
should I treat each run as a single session in my fixed effects model?
(for random effects)
If I treat each run as a single session ......
I have 12 subjects - - I end up with 36 sessions - is there any way to
create 'true' single subject contrast (incorporating the 3 runs) within
the fixed effect model or do I creat a single contrast for each of the 36
sessions that will then be used in the random effects analysis? If I
end up with 36 single 'session' contrast' do I need to then specify in
my random effects model that session 1,2,3 all correspond to subject
one or do I just work with the 36 contrast as independent measures?
Thank YOU - Thank YOU - THANK YOU - to whomever can help me
resolve these issues----
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