Dear Jesper,
I followed the procedure you outlined below, but the outcome leaves me
more confused. The output of the pinv operation is a matrix with 10 rows. Here
are the values for a typical ROI. I am not clear what these numbers correspond
to. Since I only had 7 subjects, I wouldn't think the rows correspond to
something related to individual subjects.
579.8134
647.2977
234.4117
186.5248
101.5133
179.2054
170.6050
132.8360
222.0150
0.6998
The final row seems to be as reasonable value for the beta estimate so I
calculated the adjusted values for this ROI using the formula you suggested.
What I do not understand is that the adjusted values still show a
correlation with the global values (r =0.5-0.7), and the slope of the
correlation is negative just as is the correlation between global and
proportionally normalized values. This bothers me because I thought the ANCOVA
was supposed to _remove_ any correlation between the global and ANCOVA adjusted
values.
What I am doing wrong here ?
sg
If all you want to compare is the ROI approach versus the pixel-by-pixel
approach and you want everything else to be identical, by far the
simplest
would be to do as follows:
1. Get your ROI values into matlab organised as a matrix (e.g. Y) with
one
row for each scan and one colum for each region.
2. Load the SPM.mat that you got from your SPM analysis
3. Create a matrix X = [H B G];
4. Solve in a least squares sense by
beta = pinv(X)*Y;
beta will now contain one column for each region with the parameter
estimates you are interested in, and you may subsequently use them to
calculate your adjusted values. Remember to enter your ROI values in the
same order that you entered your files in SPM though.
>In
>the end I want to compare the scatterplots of the correlations with the
>co-variate for SPM and ROI analysis.
>
Why?
>Thanks for you help.
Good luck Jesper
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