help
help > RE: calculating cohen's d from rZ values
Dec 24, 2014 12:12 PM | Patrick McConnell - MUSC
RE: calculating cohen's d from rZ values
Alfonso,
Thank you very much for the thoughtful and detailed reply. I'm sorry that I wasn't clearer in my original post. From c) your understanding/interpretation is spot-on. Just to rephrase again:
1) seed --> voxel bivariate regression with 5-mm spheres and a priori non-directional hypotheses.
2) marsbar --> write functional clusters from SPM.mat in SPM; extract eigenvariates from these clusters to explore directionality of group mean correlation (positive v inverse / strength).
3) enter new rois back into seed--> voxel bivariate correlation analysis; repeat step 2) for any significant target rois.
4) repeat step 3) one more time.
5) calculate cohen's d for each group using group mean eigenvariate for each significant roi.
6) bivariate regression ROI-ROI analysis within-groups using previously determined ROIs.
7) where both directions (e.g., roi1 --> roi2, roi2 --> roi1) were significant, extract single-subject regression coefficients and run paired-sample t-tests on roi1 --> roi2 vs. roi --> roi2 to determine if there is any indication of effective connectivity.
8) we also extracted denoised time series for each roi to explore visually.
Thanks again for the help!!!
-Patrick
Thank you very much for the thoughtful and detailed reply. I'm sorry that I wasn't clearer in my original post. From c) your understanding/interpretation is spot-on. Just to rephrase again:
1) seed --> voxel bivariate regression with 5-mm spheres and a priori non-directional hypotheses.
2) marsbar --> write functional clusters from SPM.mat in SPM; extract eigenvariates from these clusters to explore directionality of group mean correlation (positive v inverse / strength).
3) enter new rois back into seed--> voxel bivariate correlation analysis; repeat step 2) for any significant target rois.
4) repeat step 3) one more time.
5) calculate cohen's d for each group using group mean eigenvariate for each significant roi.
6) bivariate regression ROI-ROI analysis within-groups using previously determined ROIs.
7) where both directions (e.g., roi1 --> roi2, roi2 --> roi1) were significant, extract single-subject regression coefficients and run paired-sample t-tests on roi1 --> roi2 vs. roi --> roi2 to determine if there is any indication of effective connectivity.
8) we also extracted denoised time series for each roi to explore visually.
Thanks again for the help!!!
-Patrick
Threaded View
Title | Author | Date |
---|---|---|
Crystal Goh | Jun 2, 2012 | |
Alfonso Nieto-Castanon | Jul 8, 2012 | |
Patrick McConnell | Dec 20, 2014 | |
Alfonso Nieto-Castanon | Dec 21, 2014 | |
Patrick McConnell | Dec 21, 2014 | |
Alfonso Nieto-Castanon | Dec 24, 2014 | |
Patrick McConnell | Dec 24, 2014 | |
Patrick McConnell | Jan 8, 2015 | |
Alfonso Nieto-Castanon | Dec 27, 2014 | |
Patrick McConnell | Jan 7, 2015 | |
Alfonso Nieto-Castanon | Jan 15, 2015 | |
Patrick McConnell | Jan 22, 2015 | |
Michael King | Dec 16, 2014 | |
Alfonso Nieto-Castanon | Dec 17, 2014 | |
Michael King | Dec 17, 2014 | |
Michael King | Dec 17, 2014 | |