Hi Eric
One way to check your design matrix and data for posible errors is by
performing a simple univariate analysis using data from a single vertex, eg. at
vertex 1000:
lhstats = lme_fit_FS(X,Zcols,Y(:,lhcortex(1000)),ni);
and check the behavior of the optimization procedure. Make
sure that both your design matrix X and the cortical thickness data
Y are ordered in a way that they contain all the repeated measures for the
first subject (ordered by time), then all the repeated measures for the second
subject and so on. The first element of the vector ni must indicate the number
of repeated measures in the design matrix X for the first subject, the second
element of that vector must indicate the number of repeated measures in the
design matrix for the second subject and so on.
Take a look at the header of lme_mass_vw script for the size of the X, Y etc...
Best
-Jorge
El Lunes 17 de marzo de 2014 18:35, Eric Cunningham <et...@hawaii.edu> escribió:
Hello Freesurfer experts,
>
>The lme_mass_vw script runs for a long time and outputs info into the matlab
>terminal. Most look like this:
>
>Location #####: Algorithm did not converge. Initial and final likelihoods:
>###, ###
>
>Running this script, for almost every line, the initial and final likelihoods
>are "Inf". Is this indicative of a problem?
>
>~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
>
>Getting these results made me wonder if the Y-input was built
properly. Using mris_preproc and mri_surf2surf to smooth, we tested
10mm smoothing and no smoothing in addition to the 30mm smoothing we had
been doing originally. The results:
>
>
>smoothed to 30 ~ almost every likelihood = Inf, Inf
>
>smoothed to 10 ~ some (1 in 5? 10?) likelihood = Inf
>
>not smoothed ~ no instances of likelihood = Inf, Inf
>
>
>Thanks,
>-Eric
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