Dr. Chen,

I appreciate your time indeed.

Unfortunately, removing the line qVars did not help with the problem. I tried adding or removing some options but am still receiving an error. Here is the code I used:
3dMVM -prefix COMPARE -jobs 1 \
-bsVars 'group*relation' \
-SS_type 3 \
-num_glt 1 \
-gltLabel 1 G1_vs_G2 -gltCode 1 'group : 1*G1 -1*G2' \
-dataTable @dataTable_new.txt

in which, group and relation are categorical variables. group is the main factor labeled with names as either 'G1', 'G2', or 'G3' and relation is the covariate coded with numbers (either 1 or 2). I replaced the numbers with names but it did not help either (coded as yes or no). Following is my dataTable:

Subj group relation InputFile
s103 G1 1 stats.s103+tlrc[7]
s107 G1 1 stats.s107+tlrc[7]
...

and here is the error I am receiving:
~~~~~~~~~~~~~~~~~~~ Model test failed! ~~~~~~~~~~~~~~~~~~~
Possible reasons:

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

1) Inappropriate model specification with options -bsVars, -wsVars, or -qVars.
Note that within-subject or repeated-measures variables have to be declared
with -wsVars.

2) Incorrect 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 header
would cause grief for 3dMVM.

5) Not enough number of subjects. This may happen when there are two or more
withi-subject factors. For example, a model with two within-subject factors with
m and n levels respectively requires more than (m-1)*(n-1) subjects to be able to
model the two-way interaction with the multivariate approach.


** Error:
Quitting due to model test failure...
--------------------------------------------------
I checked all the points, but the error remained.

I also needed to add that the three groups are not identical in their size. May I ask if it matters for the 3dMVM or the 3dANOVA functions if the group sizes are not equal?

Thank you so much for your guidance.

Respectfully,
Sanaz



Edited 1 time(s). Last edit at 05/27/2019 04:01PM by Sanaz_khosravani.