It's not exactly trivial. I like to add a non-estimable constraint, 
which in this case is a row of 1's and a 0 for the value of the 
corresponding response. The coefficients are not unique, but the t-tests 
  are correct, as are the multiple comparisons.

christoph wrote:
> sorry, maybe an all too trivial question. But we have power data from J
> frequency spectra and to have the same range for the data of all our
> subjects, we just transformed them into % values, pseudo-code:
> 
> power[i,j]=power[i,j]/sum(power[i,1:J])
> 
> of course, now we have perfect collinearity in our x design-matrix,
> since all power-values for each subject sum up to 1.
> 
> How shall we solve this problem: just eliminate one column of x, or
> introduce a restriction which says exactly that our power data sum up to
> 1 for each subject?
> 
> Thanks a lot
> 
> Christoph


-- 
Bob Wheeler --- http://www.bobwheeler.com/
         ECHIP, Inc. ---
                Randomness comes in bunches

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