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I'm looking at functional connectivity in a brain network, called the default mode network, which has 10 regions of interest. Meaning, if I was to do a comparison between each of the 10 brain regions, I would have a total of 45 comparisons (i.e. region 1 to region 2 , region 1 to region 3, etc). I'm studying 100 patients one group containing healthy individuals and the other group has schezophrenia. So I was thinking of doing an ANOVA test to extract interesting differences between a region pair.

How can I organize my data to perform an ANOVA? So far, I've organized my data such that I have 45 csv files, with each csv file containing an ROI-pair comparison (i.e. ROI 1 to ROI 2) for all 100 subjects. An example as to what one of the csv files might look like (this is the format I used for comparing ROI1 to ROI2 and all other ROI pairs):

|---------------------|------------------|------------------|
|      Subject        | FC value         |   Schizophrenia? |
|---------------------|------------------|------------------|
|  Sub1 (ROI1-ROI2)   |         0.31     |      yes         |
|---------------------|------------------|------------------|
|  Sub2 (ROI1-ROI2)   |         0.04     |       no         |
|---------------------|------------------|------------------|
|  Sub3 (ROI1-ROI2)   |         0.44     |       no         |
|---------------------|------------------|------------------|
  Sub100 (ROI1-ROI2)  |         0.21     |       yes

Should I combine all the csv files into one csv file instead to perform ANOVA? And if I do add them together, should I add another column that would identify which ROI-pair? I'm not sure how to go about this. Also what would the command look like if I was doing it in R?

Any help would be greatly appreciated.

Thanks!

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