Hi Gang,
I'm having trouble using 3dLME to examine errors in a cognitive task. The program is hanging at the single voxel model test step, which I assume means I did something dumb. Here's my command:
3dLME -prefix data/group_processed/LME/LME.PASAT_errors \
-model '(Group*Scan):Time' -qVars t -qVarCenters 0 \
-ranEff '~1' -SS_type 3 -num_glf 1 \
-glfLabel 1 Before -glfCode 1 'Time : 1*0_Coef & 1*1_Coef & 1*2_Coef & 1*3_Coef & 1*4_Coef' \
-dataTable @data/group_processed/LME.errors.dataTable.txt
And here's the beginning of the data table:
$ head data/group_processed/LME.errors.dataTable.txt
Subj Group Scan Run Time t InputFile
020VTV xx pre PASAT1 0_Coef -16 data/processed/020VTV_1/epis/REML.errors_mdtwbs+tlrc.HEAD[PASAT1_errors#0_Coef]
020VTV xx pre PASAT1 1_Coef -12 data/processed/020VTV_1/epis/REML.errors_mdtwbs+tlrc.HEAD[PASAT1_errors#1_Coef]
020VTV xx pre PASAT1 2_Coef -8 data/processed/020VTV_1/epis/REML.errors_mdtwbs+tlrc.HEAD[PASAT1_errors#2_Coef]
020VTV xx pre PASAT1 3_Coef -4 data/processed/020VTV_1/epis/REML.errors_mdtwbs+tlrc.HEAD[PASAT1_errors#3_Coef]
020VTV xx pre PASAT1 4_Coef 0 data/processed/020VTV_1/epis/REML.errors_mdtwbs+tlrc.HEAD[PASAT1_errors#4_Coef]
020VTV xx pre PASAT1 5_Coef 4 data/processed/020VTV_1/epis/REML.errors_mdtwbs+tlrc.HEAD[PASAT1_errors#5_Coef]
020VTV xx pre PASAT1 6_Coef 8 data/processed/020VTV_1/epis/REML.errors_mdtwbs+tlrc.HEAD[PASAT1_errors#6_Coef]
020VTV xx pre PASAT1 7_Coef 12 data/processed/020VTV_1/epis/REML.errors_mdtwbs+tlrc.HEAD[PASAT1_errors#7_Coef]
020VTV xx pre PASAT1 8_Coef 16 data/processed/020VTV_1/epis/REML.errors_mdtwbs+tlrc.HEAD[PASAT1_errors#8_Coef]
Here I modelled each error in 3dREMLfit with a 'CSPLIN(-16,16,9)' HRF, and my F-test is to examine the time points before each error. Each subject is in one of two groups (xx/yy) and has data for two scans (pre/post) and three runs (PASAT[1-3]) per scan, but those few runs in which a subject made no errors are omitted, which means there's some missing data. I had a `-corStr 't : AR1'` in my command, but took it out in light of [
afni.nimh.nih.gov] . It seems to me that the model I want is Group*Scan*(0+Time), which is what I think I'm getting here. Any ideas what I've done wrong?
ijs
P.S.: The output is here:
Read 10591 items
Loading required package: nlme
Package nlme loaded successfully!
Loading required package: phia
Loading required package: car
Loading required package: MASS
Loading required package: nnet
Package phia loaded successfully!
++++++++++++++++++++++++++++++++++++++++++++++++++++
***** Summary information of data structure *****
30 subjects : 020VTV 039MX4 129EW1 154BA4 178AEY 241AHN 261UMC 268DFV 296AMW 306VT5 318LYO 362HR9 387RJJ 399YR1 430EEN 440KZC 465FE2 487ZR9 533PLH 552LCJ 554GB6 584VPT 617KGL 662UHF 669YTH 690HKF 733XF9 744GXX 829XGB 977MEG
1512 response values
2 levels for factor Group : xx yy
2 levels for factor Scan : post pre
3 levels for factor Run : PASAT1 PASAT2 PASAT3
9 levels for factor Time : 0_Coef 1_Coef 2_Coef 3_Coef 4_Coef 5_Coef 6_Coef 7_Coef 8_Coef
1512 centered values for numeric variable t : -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16 -16 -12 -8 -4 0 4 8 12 16
0 post hoc tests
Contingency tables of subject distributions among the categorical variables:
Tabulation of subjects against all categorical variables
~~~~~~~~~~~~~~
Subj vs Group:
[redacted]
~~~~~~~~~~~~~~
Subj vs Scan:
post pre
020VTV 27 27
039MX4 27 27
129EW1 27 27
154BA4 27 27
178AEY 27 27
241AHN 27 27
261UMC 27 27
268DFV 27 27
296AMW 18 27
306VT5 27 27
318LYO 27 27
362HR9 27 27
387RJJ 18 27
399YR1 27 27
430EEN 27 27
440KZC 27 27
465FE2 18 18
487ZR9 9 18
533PLH 9 27
552LCJ 27 27
554GB6 18 27
584VPT 27 27
617KGL 27 27
662UHF 27 27
669YTH 27 27
690HKF 27 27
733XF9 27 27
744GXX 27 27
829XGB 27 27
977MEG 18 18
~~~~~~~~~~~~~~
Subj vs Run:
PASAT1 PASAT2 PASAT3
020VTV 18 18 18
039MX4 18 18 18
129EW1 18 18 18
154BA4 18 18 18
178AEY 18 18 18
241AHN 18 18 18
261UMC 18 18 18
268DFV 18 18 18
296AMW 18 9 18
306VT5 18 18 18
318LYO 18 18 18
362HR9 18 18 18
387RJJ 18 18 9
399YR1 18 18 18
430EEN 18 18 18
440KZC 18 18 18
465FE2 9 18 9
487ZR9 9 9 9
533PLH 9 18 9
552LCJ 18 18 18
554GB6 18 18 9
584VPT 18 18 18
617KGL 18 18 18
662UHF 18 18 18
669YTH 18 18 18
690HKF 18 18 18
733XF9 18 18 18
744GXX 18 18 18
829XGB 18 18 18
977MEG 18 18 0
~~~~~~~~~~~~~~
Subj vs Time:
0_Coef 1_Coef 2_Coef 3_Coef 4_Coef 5_Coef 6_Coef 7_Coef 8_Coef
020VTV 6 6 6 6 6 6 6 6 6
039MX4 6 6 6 6 6 6 6 6 6
129EW1 6 6 6 6 6 6 6 6 6
154BA4 6 6 6 6 6 6 6 6 6
178AEY 6 6 6 6 6 6 6 6 6
241AHN 6 6 6 6 6 6 6 6 6
261UMC 6 6 6 6 6 6 6 6 6
268DFV 6 6 6 6 6 6 6 6 6
296AMW 5 5 5 5 5 5 5 5 5
306VT5 6 6 6 6 6 6 6 6 6
318LYO 6 6 6 6 6 6 6 6 6
362HR9 6 6 6 6 6 6 6 6 6
387RJJ 5 5 5 5 5 5 5 5 5
399YR1 6 6 6 6 6 6 6 6 6
430EEN 6 6 6 6 6 6 6 6 6
440KZC 6 6 6 6 6 6 6 6 6
465FE2 4 4 4 4 4 4 4 4 4
487ZR9 3 3 3 3 3 3 3 3 3
533PLH 4 4 4 4 4 4 4 4 4
552LCJ 6 6 6 6 6 6 6 6 6
554GB6 5 5 5 5 5 5 5 5 5
584VPT 6 6 6 6 6 6 6 6 6
617KGL 6 6 6 6 6 6 6 6 6
662UHF 6 6 6 6 6 6 6 6 6
669YTH 6 6 6 6 6 6 6 6 6
690HKF 6 6 6 6 6 6 6 6 6
733XF9 6 6 6 6 6 6 6 6 6
744GXX 6 6 6 6 6 6 6 6 6
829XGB 6 6 6 6 6 6 6 6 6
977MEG 4 4 4 4 4 4 4 4 4
***** End of data structure information *****
++++++++++++++++++++++++++++++++++++++++++++++++++++
Reading input files now...
Reading input files: Done!
If the program hangs here for more than, for example, half an hour,
kill the process because the model specification or the GLT coding
is likely inappropriate.
Edited 3 time(s). Last edit at 07/24/2015 04:16PM by Isaac Schwabacher.
