dear fsl experts
I have a very general and important question, which i think disturb whichever researcher dreams.
are there any rules to define the GLM model when i have several variables and i want to correlate my MRI images to (FA, MD, VBM, RS, Tracto..or whichever measure). how do i have to arrange my parameters ??
consider for example a disease investigation, just the patient group correlation with several scores.
demographic values, like age,gender, education...etc (D1, D2,.., Dy)
clinical scores (C1, C2,..Cn),
neuronal integrity marker like NNA/Cr or NAA/Cho..etc.....(S1, S2,..Sm)
Neurophysiology scores (N1, N2, ..., Nx).
these values may few (6,7) but also many (20,30,40).
assuming Z the number of mandatory covariates to correct for (like age for example), and W the number of scores of interest
we all know that there is a dramatic difference in performing W analyses with Z+2 columns (mean, the score and Z covariates) or one analysis with W+Z+1 columns (mean, Z cov, W variables of interest)
we also know that we are free to declare how many scores we calculated and/or investigated. for example for spectroscopy parameters, we can calculate whichever score we want NNA, Cr, Cho, mI, H2O, NNA/Cr, NAA/Cho, NNA/Cho+Cr, NAA/mI, etc....
so we can play with this....but we don't like to play with this.
of course there is a plenty of physiological reason to couple variables, for example, when you suspect a relationship between two variables, in order to separate their contribute to the investigated MRI voxel property, you should put them in a same GLM.
but if you find, when making single score analyses, that some scores all correlates with a voxel, untill you are not interested in assess to which score your voxel correlates more/less, can you also report the results of the separated analyses, reporting only those voxel with a p value corrected by the number of scores tested (e.g. you make five 1-score analyses, you report only voxels < 0.01, or > 0.99 if tfce_corrp) ??is it ok ??.
when you want to compare their relation,
if you declare that you investigated 5 scores, 3 do not correlate at all, is it ok if you declare that, and then make a 2-scores GLM with only the two scores correlating.
and if, finally, you find that only one (A) of the two scores correlated, you may declare that, although both A and B singularly correlated, a more precise analysis revealed that actually such correlation was due to the A score.
but, importantly, also B correlated, before considering A also.
to conclude, can i preliminary correlation analyses of the scores itself (without GLM with MRI voxel data) guides us in coupling variables ?
is it correct to perform several 1-score GLMs to reduce the dimensions of the final GLM matrix, that is exclude scores from further analyses?
should all these steps carefully reported in a paper ??
well I could go on with several other examples and questions but, surely, some of you, much more expert, can formalize my problem in a more concise and better form.
thanks in advance
regards
Alberto
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