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Todd,

My question is are the values contained in the output ResMS.img
files scaled and by what value?

Yes, they are scaled by (1/ effective degrees of freedom) = (1/trRV) = (1/SPM.xX.X)

I want to retrieve just the raw
residual sum of squares values and I imagine they are in the ResMS
files either multiplied by a scale factor or not.  Note:  By raw
residual sum of squares I mean ResSS = (Y(actual image values) -
Y(estimated image values)) or i.e. the sum(residuals^2))

The following  generates the actual ResSS.  From your stats directory run this code:
----------------------------------------------------------------------------------------------------------
load SPM.mat
trRV = SPM.xX.trRV;

V = spm_vol('ResMS.img');
ResMS = spm_read_vols(V);

ResSS = ResMS .* trRV;

P.fname = 'ResSS.img';
P.mat = V.mat; P.dt = V.dt; P.dim = V.dim;
P.pinfo = [1 0 0]';

P = spm_create_vol(P);
for i=1:P.dim(3)
    spm_write_plane( P , ResSS( : , : , i ) , i );
end
-----------------------------------------------------------------------------------

Good  luck,
Brian


On 9/20/07, Todd Penney <[log in to unmask]> wrote:
   Hello all,

   I ran a t-test statistical analysis on some fMRI data and I need
the ResMS image files as part of my study.

   When reading spm_spm.m file to find out how the mean squared error
(ResMS) is calculated, there is mention of a scale factor in 2 places.
  One of the comments says the ResMS values written to the ResMS.hdr
files are scaled by the effective degrees of freedom.  At another
comment further down, it mentions that the scale factor ,
1/effective-degrees-of-freedom, is written into the [struct].pinfo(1)
variable.

   My question is are the values contained in the output ResMS.img
files scaled and by what value?  I want to retrieve just the raw
residual sum of squares values and I imagine they are in the ResMS
files either multiplied by a scale factor or not.  Note:  By raw
residual sum of squares I mean ResSS = (Y(actual image values) -
Y(estimated image values)) or i.e. the sum(residuals^2))

Thank you.

Sincerely,

Todd Penney