Hello AFNI Gurus,

I am interested in examining whole brain activity associated with a quantitative covariate of interest ("DESB") while controlling for both categorical (e.g., sex, data collection site) and quantitative (e.g., age, "PCL5", "CTQ") covariates of no-interest. I also have two within-subjects conditions in my task ("fearful faces", "neutral faces"). I first ran this analysis using 3dMVM, however, I hit a snag once I wanted to correct for multiple comparisons using 3dClustSim. The data were processed originally in SPM12, and I do not have access to the appropriate residual file to estimate smoothness with 3dFWHMx for 3dClustSim. To get around this, I decided to run my group analysis using a paired t-test in 3dttest++ with the -Clustsim option instead.

Per 3dttest++ instructions, I have coded the categorical covariates numerically using, e.g., 1=Male, 2=Female (see below for an excerpt of my covariates file). Is this the correct numerical coding for categorical variables of no interest in 3dttest++? Or do these need to be dummy coded instead?

Furthermore, I do not want the program to center the categorical covariates, so I have set the covariates -center option to "NONE", and I instead mean centered the quantitative covariates before entering them into my covariates file for use with 3dttest++. Is this the correct course of action?

Thanks for your time and help!
Best,
Lauren

Excerpt from Covariate File Used with 3dttest++:

Subj	              Site  Sex	Age	       PCL5	DES 	CTQ
sub-100203	2	2	11.34	30.86	1.64	        -8.95
sub-100311	4	2	-1.66	-24.14	-0.36	-9.95
sub-100325	2	1	5.34	         17.86	1.64	        14.05
sub-100458	3	2	17.34	32.86	2.64	         -7.95
sub-100459	3	2	-8.66	-9.14	-1.36	-1.95
sub-100491	1	2	-5.66	-13.14	-1.36	-6.95
sub-100676	2	2	-9.66	-17.14	0.64	         2.05
sub-100814	1	1	-3.66	-6.14	-0.36	0.05
sub-100926	1	1	0.34	         -1.14	-1.36	20.05
sub-101028	2	2	19.34	-10.14	-1.36	-6.95
sub-101045	2	2	-8.66	-3.14	-1.36	-9.95
sub-101345	1	1	-0.66	-1.14	-1.36	-7.95
sub-101394	4	2	-12.66	-24.14	-1.36	5.05
...