I am currently trying to run the following 2x2 model on a small portion of my resting state data (just 2 subjects). Each subject's data consists of a z-scored correlation map between a seed region and whole brain. I used the pipeline here to generate the correlation maps per subject: [www.brown.edu]

Here is the code I'm using:

3dLME -prefix Example3 -jobs 24 \
-model "cond*group" \
-bounds -2 2 \
-ranEff '~1' \
-SS_type 3 \
-num_glt 2 \
-gltLabel 1 'pos-neg' -gltCode 1 'cond : 1*pos -1*neg' \
-gltLabel 2 'pat_neg-pos' -gltCode 2 'cond : 1*pos -1*neg group : 1*pat' \
-dataTable @table.txt


'cond' is a within subjects variable with two levels, neg and pos. 'group' is a between subjects variable with two levels, pat and ctr.

My data table is as follows:

Subj cond group InputFile
s10210 pos ctr ctlNeutral_10210_Larea11.z.nii
s10210 neg ctr ctlStrong_10210_Larea11.z.nii
s18526 pos pat ocdNeutral_18526_Larea11.z.nii
s18526 neg pat ocdStrong_18526_Larea11.z.nii

When I try and run the model, I receive a 'Model test failed' error:

~~~~~~~~~~~~~~~~~~~ Model test failed ~~~~~~~~~~~~~~~~~~~
Possible reasons:

0) Make sure that R packages nlme and phia have been installed. See the 3dLME
help documentation for more details.

1) Inappropriate model specification with options -model, or -qVars.

2) In correct specifications in general linear test coding with -gltCode.

3) Mistakes in data table. Check the data structure shown above, and verify
whether there are any inconsistencies.

4) Inconsistent variable names which are case sensitive. For example, factor
named Group in model specification and then listed as group in the table hader
would cause grief for 3dLME.
~~~~~~~~~~~~~~~~~~~

I can't see any issues with the model myself and all my R packages have loaded properly. I was wondering if there were any obvious issues that I've failed to spot? I also suspect a problem with my data files but I want to rule out any issues with the 3dLME code first before inspecting the files further. Just to preface, I'm very new to using AFNI!

Thank you, any help is greatly appreciated.