Dear All,
I am using the 3dttest++ for comparing two different groups of subjects and would like to control for the effect of gender as a covariate. I referred to the help file of the 3dttest and found the following illustration on the structure of the output:
STRUCTURE OF THE OUTPUT DATASET ~1~

The output dataset is stored in float format; there is no option
to store it in scaled short format 
For each covariate, 2 subbricks are produced:
++ The estimated slope of the beta values vs covariate
++ The tstatistic of this slope
++ If there are 2 sets of subjects, then each pair of subbricks is
produced for the setAsetB, setA, and setB cases, so that youâ€™ll
get 6 subbricks per covariate (plus 6 more for the mean, which
is treated as a special covariate whose values are all 1).
++ Thus the number of subbricks produced is 6*(m+1) for the twosample
case and 2*(m+1) for the onesample case, where m=number of covariates. 
For example, if there is one covariate â€˜IQâ€™, and a two sample analysis
is carried out (â€˜setAâ€™ and â€˜setBâ€™ both used), then the output
dataset will contain the following 12 (6*2) subbricks:
#0 SetASetB_mean = difference of means [covariates removed]
#1 SetASetB_Tstat
#2 SetASetB_IQ = difference of slopes wrt covariate IQ
#3 SetASetB_IQ_Tstat
#4 SetA_mean = mean of SetA [covariates removed]
#5 SetA_Tstat
#6 SetA_IQ = slope of SetA wrt covariate IQ
#7 SetA_IQ_Tstat
#8 SetB_mean = mean of SetB [covariates removed]
#9 SetB_Tstat
#10 SetB_IQ = slope of SetB wrt covariate IQ
#11 SetB_IQ_Tstat
I believe the output I would need to explore is sub brick #1, which states SetASetB_Tstat and demonstrates group mean differences. My understanding was that the term â€˜removedâ€™ in [covariates removed] means that the covariate is controlled for in this comparison. I would be thankful if you could please confirm.
Thank you so much.
Sanaz