Hello,
I'm having trouble with 3dMVM.
I've found that for my current study - a large analysis of seed based resting state connectivity I am having difficulty running 3dMVM.
My extensive attempts at debugging suggest that the issue was that I didn't have a wsVar *though if you think it may be something else let me know*
As a workaround I put in a dummy wsVariable by copying each subjects dataset twice. This does enable me to get the 3dMVM program to finish running.
I wanted to know if there if:
1. Is there another solution to running 3dMVM without wsVars
2. Is this workaround statistically sound, I am not sure if doubling up on the subjects would artificially inflate df or something else in the statistics of the 3dMVM program.
Below are samples of the scripts.
#./P3.MVM1_BD41R 2>&1 | tee output.P3.MVM1_BD41R
3dMVM_rcc -prefix P3_MVM1_BD41R -jobs 64 \
-bsVars 'P3Lev+Age' \
-wsVars 'wsDummy' \
-qVars 'Age' \
-qVarCenters '38.38' \
-num_glt 6 \
-gltLabel 1 HCvNone -gltCode 1 'P3Lev : 1*HC -1*None' \
-gltLabel 2 HCvMod -gltCode 2 'P3Lev : 1*HC -1*Mod' \
-gltLabel 3 HCvSev -gltCode 3 'P3Lev : 1*HC -1*Sev' \
-gltLabel 4 NonevMod -gltCode 4 'P3Lev : 1*None -1*Mod' \
-gltLabel 5 NonevSev -gltCode 5 'P3Lev : 1*None -1*Sev' \
-gltLabel 6 ModvSev -gltCode 6 'P3Lev : 1*Mod -1*Sev' \
-dataTable @BD41R_DataTable.txt \
Subj wsDummy P3Lev Dx Bio Site Race Age Sex Gaf Hand InputFile \
4 1.00 Mod SADP 3 GP CA 19 1 70 2 /project/skeedy/BSNIP1/fromHartford/rest_2/Hartford/FunImgARCWF/S5366ACM1/BD41R_MNI_RScorr_Z+tlrc \
4 2.00 Mod SADP 3 GP CA 19 1 70 2 /project/skeedy/BSNIP1/fromHartford/rest_2/Hartford/FunImgARCWF/S5366ACM1/BD41R_MNI_RScorr_Z+tlrc \
55 1.00 Mod SZP 999 GP CA 21 1 65 2 /project/skeedy/BSNIP1/fromHartford/rest_2/Hartford/FunImgARCWF/S0092JDO1/BD41R_MNI_RScorr_Z+tlrc \
55 2.00 Mod SZP 999 GP CA 21 1 65 2 /project/skeedy/BSNIP1/fromHartford/rest_2/Hartford/FunImgARCWF/S0092JDO1/BD41R_MNI_RScorr_Z+tlrc \
86 1.00 HC HC 0 GP AA 46 2 80 2 /project/skeedy/BSNIP1/fromHartford/rest_2/Hartford/FunImgARCWF/S1122IJG3/BD41R_MNI_RScorr_Z+tlrc \
86 2.00 HC HC 0 GP AA 46 2 80 2 /project/skeedy/BSNIP1/fromHartford/rest_2/Hartford/FunImgARCWF/S1122IJG3/BD41R_MNI_RScorr_Z+tlrc \
93 1.00 HC HC 0 GP AA 32 2 95 2 /project/skeedy/BSNIP1/fromHartford/rest_2/Hartford/FunImgARCWF/S4090DGW1/BD41R_MNI_RScorr_Z+tlrc \
93 2.00 HC HC 0 GP AA 32 2 95 2 /project/skeedy/BSNIP1/fromHartford/rest_2/Hartford/FunImgARCWF/S4090DGW1/BD41R_MNI_RScorr_Z+tlrc \
94 1.00 HC HC 0 GP AA 49 2 90 2 /project/skeedy/BSNIP1/fromHartford/rest_2/Hartford/FunImgARCWF/S5446BQT8/BD41R_MNI_RScorr_Z+tlrc \
94 2.00 HC HC 0 GP AA 49 2 90 2 /project/skeedy/BSNIP1/fromHartford/rest_2/Hartford/FunImgARCWF/S5446BQT8/BD41R_MNI_RScorr_Z+tlrc \
......
We have a parallel computing adapted version of 3dMVM we use to run faster installed on our university's high performance computing cluster.
Thanks in advance,
Victoria