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To view group differences in mricron:

  • Open the *_corrp_fstat1.nii.gz in mricron
  • Set the range to start from 0.95
  • Open *_glm_cope_tstat1.nii.gz
  • Make sure Yoke is set in mricro (Window menu)
  • In the corrp_fstat1 file, move the cursor to a non-zero location >0.05 (a significant voxel)
  • Look at the value in glm_cope_tstat1; this is the size in voxel dimensions of the effect. For example, if the cope is 0.5 and the image resolution is 1mm^3, the the group effect is an increase of 0.5mm outward expansion at that voxel.
    • This assumes that the control group is "1" and the patient group "2" in the design matrix.

Details

The "-glm_output option in randomise creates model estimates. The beta's are *_glm_pe_tstat1.nii.gz", where "pe" = "parameter estimates". We are usually interested in contrast parameter estimates ("cope"), so "_glm_cope_tstat1.nii.gz". The pe files will have one value (volume) per parameter in the model, whereas the cope files will have a single value corresponding to the contrast. For example, if you have group, age and sex, you will get files like below, where the "pe" files have three volumes each:

...

  • Say you have a contrast C = [1 -1 0]', and for a certain voxel, you have beta = [1 4 2]'. The COPE is simply C'*beta = [1 -1 0] * [1 4 2] = 1*1 -1*4 + 0*2 = -3. This is what goes in the numerator of the t statistic.
  •  
    - The *pe* are the parameter estimates, also known as betas (this image has as many volumes as regressors in the design);
    - The *cope* are the contrasts of parameter estimates, one image per contrast. It's the inner product between the contrast vector and the betas;
     
    - Because the *pe* are estimates, so are the *cope*. These estimates have an uncertainty surrounding them, and the variance around these estimates is the *varcope*;
     
  • Open the *_corrp_fstat1.nii.gz in mricron
  • Set the range to start from 0.95
  • Open *_glm_cope_tstat1.nii.gz
  • Make sure Yoke is set in mricro (Window menu)
  • In the corrp_fstat1 file, move the cursor to a non-zero location >0.05 (a significant voxel)
  • Look at the value in glm_cope_tstat1; this is the size in voxel dimensions of the effect. For example, if the cope is 0.5 and the image resolution is 1mm^3, the the group effect is an increase of 0.5mm outward expansion at that voxel.This assumes that the control group is "1" and the patient group "2" in the design matrix
    - The *sigmasqr* is the variance of the residuals.

To view group differences in mricron:

  •  The sigmasquareds volume is the unbiased estimate of the noise standard deviation in the GLM.

To check your variables:

Open Notepad, and drag file the "design.mat" into the application. (This is listed as "MATLAB Data" but is a text file.) You will see columns for each variable. Here is an example with group, age and sex:

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