Dear SPMers,
we are looking for a solution that might also be of interest
for other people doing imaging studies.
We need an appropriate model for group comparisons in SPM.
When going through the SPM email archives we found several entries which seem
to be more or less close to the problem. However, we are still not convinced
to have a valid solution. Also a discussion with people who are relatively
familiar with SPM did not yield a definite answer. Therefore, we pose our
question here.
==============================
Our fMRI studies included
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- groups of
patients and control subjects (each with n > 12) in different ranges of
age
- 4 'activation' conditions (A1, .., A4) and a control condition
(C)
We have obtained contrast images for each subject from a
first level analysis (A1-C, A2-C, ..., A1-A2, ...).
Now, we are looking for
an appropriate model for a second level analysis.
It is clear what a one or two sample t-test or a one way
ANOVA do, and it is also clear, in principle, how to configure these methods
using SPM's Basic Models.
==============================
We have been recommended not to cut the negative contrast
values, but to mask with another contrast and specifying an appropriate
p-value. For example, we assume that it may be needed to mask the group
contrast (A1-C) - (A2-C) by a positive (p-thresholded) group contrast (A1-C)
and/or (A2-C).
In order to have an elegant way to model any group
comparison for any contrast of interest, we have been recommended to use one
of the larger models which are available under the PET option, e.g.
Multi-group conditions & covariates. This would also give the opportunity
to model covariate(s) and/or nuisance variable(s), which will become a
relevant topic in our study.
However, after entering the images and other parameters, our
attempts to implement group comparisons provided 'invalid contrast' messages.
===========================
Example:
----------------------------------------------
We entered 2 groups, and
for each subject 4 contrast images A1-C, .., A4-C (now called
A1,...A4).
The design matrix had 8+N columns:
contrast A1 A2 A3 A4
(group 1),
contrast A1 A2 A3 A4
(group 2),
and a constant for each of the N subjects.
Now we tried to specify, e.g. where group 1 activated more
than group 2 with respect to A1 by entering
1 0 0 0 -1
However, this
provided an 'invalid contrast' message, whereas an intra-group comparison of
the type
1 -1 ...
was termed
valid.
===========================
Was there a mistake in our modelling considerations or in
the use of the SPM tool?
We would greatly appreciate some advice in
choosing an effective and efficient model and masking method.
Best
regards
Ulrich
***************************
Dr.-Ing. Ulrich
Moeller
Institute of Medical Statistics, Computer Sciences and
Documentation,
Clinic for Child and Adolescents Psychiatry
Friedrich
Schiller University Jena
Philosophenweg 3/5, D-07740 Jena
Email: [log in to unmask]
