Dear Freesurfer Experts,
We are analysing longitudinal data - the difference between 2 groups (P and M) [19 and 17 subjects] with 2 time points for each group (A, B).
We are using the example of "Repeated Measures Anova" (http://surfer.nmr.mgh.harvard.edu/fswiki/RepeatedMeasuresAnova)
For our first approach - we took all the subjects - 36 classes, and tried to create the contrast for:
P(B-A) - M(B-A) 2 within subject factors, and 2 inter-subject
We considered the recent explanations (http://www.mail-archive.com/freesurfer@nmr.mgh.harvard.edu/msg25459.html), and, as we understood, our null hypothesis is:
PB-PA=0 AND MB-MA=0 -> Combining: PB-PA-MB+MA=0
and the matrix seems to be: 0 0 0 .... (36 zeros) -1 0 0 0 .... (36 zeros) 1 0 0 0 .... (36 zeros) 1 0 0 0 .... (36 zeros) -1
but we still get a dimension mismatch between X and C: X has 72, C has 37.
The fsgd file is like this: Class subject 1 . . . Class subject 36 Variables TP1-vs-TP2 Input groupPsubj1-A Subject1 -1 Input groupPsubj1- B Subject1 1 Input groupPsubj2-A Subject2 -1 . . . Input groupMsubj35-A Subject35 1 Input groupMsubj35-B Subject35 -1 Input groupMsubj36-A Subject36 1 Input groupMsubj36-B Subject36 -1
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Our second approach - we run mris_glmfit for each group separately and then we wanted to use mris_calc to compute the difference:
mris_calc -o avg.mgh groupP/glm-dir/Contrast/sig.mgh add groupM/glm-dir/Contrast/sig.mgh
though the sig.mgh for each group shows significant results, the avg.mgh reveals no effect.
Can you please help with this analysis ?
Thanks!
Sincerely, Alex.