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Dear AFNI users-
We are very pleased to announce that the new AFNI Message Board framework is up! Please join us at:
Existing user accounts have been migrated, so returning users can login by requesting a password reset. New users can create accounts, as well, through a standard account creation process. Please note that these setup emails might initially go to spam folders (esp. for NIH users!), so please check those locations in the beginning.
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Sincerely, AFNI HQ
We are very pleased to announce that the new AFNI Message Board framework is up! Please join us at:
https://discuss.afni.nimh.nih.gov
Existing user accounts have been migrated, so returning users can login by requesting a password reset. New users can create accounts, as well, through a standard account creation process. Please note that these setup emails might initially go to spam folders (esp. for NIH users!), so please check those locations in the beginning.
The current Message Board discussion threads have been migrated to the new framework. The current Message Board will remain visible, but read-only, for a little while.
Sincerely, AFNI HQ
| October 11, 2014 03:43PM | |
Registered: 10 years ago Posts: 13 |
Hello!
I am having some difficulties getting my 3 x 6 ANOVA to run using 3dMVM. I have also added in 2 covariates and I am not sure if I have done something incorrectly.
Here is what I run (as an executable file):
3dMVM \
-prefix ST_ANOVA_ICUxEmotion \
-jobs 1 \
-wsVars "Emotion" \
-bsVars 'Group' \
-qVars "Age,IQ" \
-mask 'full_mask.KBFST104+tlrc.BRIK' \
-num_glt 18 \
-gltLabel 1 HC_vs_Lo -gltCode 1 'Group : 1*HC -1*Lo' \
-gltLabel 2 HC_vs_Hi -gltCode 2 'Group : 1*HC -1*Hi' \
-gltLabel 3 LoCU_vs_Hi -gltCode 3 'Group : 1*Lo -1*Hi' \
-gltLabel 4 Fear_HC_vs_Lo -gltCode 4 'Group : 1*HC -1*Lo Emotion : 1*Fea' \
-gltLabel 5 Fear_HC_vs_Hi -gltCode 5 'Group : 1*HC -1*Hi Emotion : 1*Fea' \
-gltLabel 6 Fear_Lo_vs_Hi -gltCode 6 'Group : 1*Lo -1*Hi Emotion : 1*Fea' \
-gltLabel 7 Anger_HC_vs_Lo -gltCode 7 'Group : 1*HC -1*Lo Emotion : 1*Ang' \
-gltLabel 8 Anger_HC_vs_Hi -gltCode 8 'Group : 1*HC -1*Hi Emotion : 1*Ang' \
-gltLabel 9 Anger_Lo_vs_Hi -gltCode 9 'Group : 1*Lo -1*Hi Emotion : 1*Ang' \
-gltLabel 10 Disgust_HC_vs_Lo -gltCode 10 'Group : 1*HC -1*Lo Emotion : 1*Dis' \
-gltLabel 11 Disgust_HC_vs_Hi -gltCode 11 'Group : 1*HC -1*Hi Emotion : 1*Dis' \
-gltLabel 12 Disgust_Lo_vs_Hi -gltCode 12 'Group : 1*Lo -1*Hi Emotion : 1*Dis' \
-gltLabel 13 Happiness_HC_vs_Lo -gltCode 13 'Group : 1*HC -1*Lo Emotion : 1*Hap' \
-gltLabel 14 Happiness_HC_vs_Hi -gltCode 14 'Group : 1*HC -1*Hi Emotion : 1*Hap' \
-gltLabel 15 Happiness_Lo_vs_Hi -gltCode 15 'Group : 1*Lo -1*Hi Emotion : 1*Hap' \
-gltLabel 16 Sadness_HC_vs_Lo -gltCode 16 'Group : 1*HC -1*Lo Emotion : 1*Sad' \
-gltLabel 17 Sadness_HC_vs_Hi -gltCode 17 'Group : 1*HC -1*Hi Emotion : 1*Sad' \
-gltLabel 18 Sadness_Lo_vs_Hi -gltCode 18 'Group : 1*Lo -1*Hi Emotion : 1*Sad' \
-dataTable \
Subj Group Emotion Age IQ InputFile \
104 HC Ang -0.77581541 0.366851417 stats.104+tlrc'[Anger#0_Coef]' \
104 HC Dis -0.77581541 0.366851417 stats.104+tlrc'[Disgust#0_Coef]' \
104 HC Fea -0.77581541 0.366851417 stats.104+tlrc'[Fear#0_Coef]' \
104 HC Hap -0.77581541 0.366851417 stats.104+tlrc'[Happiness#0_Coef]' \
104 HC Neu -0.77581541 0.366851417 stats.104+tlrc'[Neutral#0_Coef]' \
104 HC Sad -0.77581541 0.366851417 stats.104+tlrc'[Sadness#0_Coef]' \
110 HC Ang 0.483782317 2.216184591 stats.110+tlrc'[Anger#0_Coef]' \
110 HC Dis 0.483782317 2.216184591 stats.110+tlrc'[Disgust#0_Coef]' \
110 HC Fea 0.483782317 2.216184591 stats.110+tlrc'[Fear#0_Coef]' \
110 HC Hap 0.483782317 2.216184591 stats.110+tlrc'[Happiness#0_Coef]' \
110 HC Neu 0.483782317 2.216184591 stats.110+tlrc'[Neutral#0_Coef]' \
110 HC Sad 0.483782317 2.216184591 stats.110+tlrc'[Sadness#0_Coef]' \
113 HC Ang -1.569909628 -1.000047015 stats.113+tlrc'[Anger#0_Coef]' \
113 HC Dis -1.569909628 -1.000047015 stats.113+tlrc'[Disgust#0_Coef]' \
113 HC Fea -1.569909628 -1.000047015 stats.113+tlrc'[Fear#0_Coef]' \
113 HC Hap -1.569909628 -1.000047015 stats.113+tlrc'[Happiness#0_Coef]' \
113 HC Neu -1.569909628 -1.000047015 stats.113+tlrc'[Neutral#0_Coef]' \
113 HC Sad -1.569909628 -1.000047015 stats.113+tlrc'[Sadness#0_Coef]' \
114 HC Ang 0.256735263 0.849286158 stats.114+tlrc'[Anger#0_Coef]' \
114 HC Dis 0.256735263 0.849286158 stats.114+tlrc'[Disgust#0_Coef]' \
114 HC Fea 0.256735263 0.849286158 stats.114+tlrc'[Fear#0_Coef]' \
114 HC Hap 0.256735263 0.849286158 stats.114+tlrc'[Happiness#0_Coef]' \
114 HC Neu 0.256735263 0.849286158 stats.114+tlrc'[Neutral#0_Coef]' \
114 HC Sad 0.256735263 0.849286158 stats.114+tlrc'[Sadness#0_Coef]' \
117 HC Ang -0.119774927 -0.276394904 stats.117+tlrc'[Anger#0_Coef]' \
117 HC Dis -0.119774927 -0.276394904 stats.117+tlrc'[Disgust#0_Coef]' \
117 HC Fea -0.119774927 -0.276394904 stats.117+tlrc'[Fear#0_Coef]' \
117 HC Hap -0.119774927 -0.276394904 stats.117+tlrc'[Happiness#0_Coef]' \
117 HC Neu -0.119774927 -0.276394904 stats.117+tlrc'[Neutral#0_Coef]' \
117 HC Sad -0.119774927 -0.276394904 stats.117+tlrc'[Sadness#0_Coef]' \
121 HC Ang -0.682258332 -1.160858595 stats.121+tlrc'[Anger#0_Coef]' \
121 HC Dis -0.682258332 -1.160858595 stats.121+tlrc'[Disgust#0_Coef]' \
121 HC Fea -0.682258332 -1.160858595 stats.121+tlrc'[Fear#0_Coef]' \
121 HC Hap -0.682258332 -1.160858595 stats.121+tlrc'[Happiness#0_Coef]' \
121 HC Neu -0.682258332 -1.160858595 stats.121+tlrc'[Neutral#0_Coef]' \
121 HC Sad -0.682258332 -1.160858595 stats.121+tlrc'[Sadness#0_Coef]' \
122 HC Ang -1.025681263 0.849286158 stats.122+tlrc'[Anger#0_Coef]' \
122 HC Dis -1.025681263 0.849286158 stats.122+tlrc'[Disgust#0_Coef]' \
122 HC Fea -1.025681263 0.849286158 stats.122+tlrc'[Fear#0_Coef]' \
122 HC Hap -1.025681263 0.849286158 stats.122+tlrc'[Happiness#0_Coef]' \
122 HC Neu -1.025681263 0.849286158 stats.122+tlrc'[Neutral#0_Coef]' \
122 HC Sad -1.025681263 0.849286158 stats.122+tlrc'[Sadness#0_Coef]' \
123 HC Ang -1.14433902 0.768880368 stats.123+tlrc'[Anger#0_Coef]' \
123 HC Dis -1.14433902 0.768880368 stats.123+tlrc'[Disgust#0_Coef]' \
123 HC Fea -1.14433902 0.768880368 stats.123+tlrc'[Fear#0_Coef]' \
123 HC Hap -1.14433902 0.768880368 stats.123+tlrc'[Happiness#0_Coef]' \
123 HC Neu -1.14433902 0.768880368 stats.123+tlrc'[Neutral#0_Coef]' \
123 HC Sad -1.14433902 0.768880368 stats.123+tlrc'[Sadness#0_Coef]' \
126 HC Ang -0.950379225 2.216184591 stats.126+tlrc'[Anger#0_Coef]' \
126 HC Dis -0.950379225 2.216184591 stats.126+tlrc'[Disgust#0_Coef]' \
126 HC Fea -0.950379225 2.216184591 stats.126+tlrc'[Fear#0_Coef]' \
126 HC Hap -0.950379225 2.216184591 stats.126+tlrc'[Happiness#0_Coef]' \
126 HC Neu -0.950379225 2.216184591 stats.126+tlrc'[Neutral#0_Coef]' \
126 HC Sad -0.950379225 2.216184591 stats.126+tlrc'[Sadness#0_Coef]' \
127 HC Ang -0.489439477 0.849286158 stats.127+tlrc'[Anger#0_Coef]' \
127 HC Dis -0.489439477 0.849286158 stats.127+tlrc'[Disgust#0_Coef]' \
127 HC Fea -0.489439477 0.849286158 stats.127+tlrc'[Fear#0_Coef]' \
127 HC Hap -0.489439477 0.849286158 stats.127+tlrc'[Happiness#0_Coef]' \
127 HC Neu -0.489439477 0.849286158 stats.127+tlrc'[Neutral#0_Coef]' \
127 HC Sad -0.489439477 0.849286158 stats.127+tlrc'[Sadness#0_Coef]' \
130 HC Ang -0.366217961 0.447257208 stats.130+tlrc'[Anger#0_Coef]' \
130 HC Dis -0.366217961 0.447257208 stats.130+tlrc'[Disgust#0_Coef]' \
130 HC Fea -0.366217961 0.447257208 stats.130+tlrc'[Fear#0_Coef]' \
130 HC Hap -0.366217961 0.447257208 stats.130+tlrc'[Happiness#0_Coef]' \
130 HC Neu -0.366217961 0.447257208 stats.130+tlrc'[Neutral#0_Coef]' \
130 HC Sad -0.366217961 0.447257208 stats.130+tlrc'[Sadness#0_Coef]' \
135 HC Ang -1.624674747 -0.356800694 stats.135+tlrc'[Anger#0_Coef]' \
135 HC Dis -1.624674747 -0.356800694 stats.135+tlrc'[Disgust#0_Coef]' \
135 HC Fea -1.624674747 -0.356800694 stats.135+tlrc'[Fear#0_Coef]' \
135 HC Hap -1.624674747 -0.356800694 stats.135+tlrc'[Happiness#0_Coef]' \
135 HC Neu -1.624674747 -0.356800694 stats.135+tlrc'[Neutral#0_Coef]' \
135 HC Sad -1.624674747 -0.356800694 stats.135+tlrc'[Sadness#0_Coef]' \
139 HC Ang -1.167157819 -0.839235435 stats.139+tlrc'[Anger#0_Coef]' \
139 HC Dis -1.167157819 -0.839235435 stats.139+tlrc'[Disgust#0_Coef]' \
139 HC Fea -1.167157819 -0.839235435 stats.139+tlrc'[Fear#0_Coef]' \
139 HC Hap -1.167157819 -0.839235435 stats.139+tlrc'[Happiness#0_Coef]' \
139 HC Neu -1.167157819 -0.839235435 stats.139+tlrc'[Neutral#0_Coef]' \
139 HC Sad -1.167157819 -0.839235435 stats.139+tlrc'[Sadness#0_Coef]' \
140 HC Ang 0.910493865 1.251315109 stats.140+tlrc'[Anger#0_Coef]' \
140 HC Dis 0.910493865 1.251315109 stats.140+tlrc'[Disgust#0_Coef]' \
140 HC Fea 0.910493865 1.251315109 stats.140+tlrc'[Fear#0_Coef]' \
140 HC Hap 0.910493865 1.251315109 stats.140+tlrc'[Happiness#0_Coef]' \
140 HC Neu 0.910493865 1.251315109 stats.140+tlrc'[Neutral#0_Coef]' \
140 HC Sad 0.910493865 1.251315109 stats.140+tlrc'[Sadness#0_Coef]' \
143 HC Ang 1.300695335 1.331720899 stats.143+tlrc'[Anger#0_Coef]' \
143 HC Dis 1.300695335 1.331720899 stats.143+tlrc'[Disgust#0_Coef]' \
143 HC Fea 1.300695335 1.331720899 stats.143+tlrc'[Fear#0_Coef]' \
143 HC Hap 1.300695335 1.331720899 stats.143+tlrc'[Happiness#0_Coef]' \
143 HC Neu 1.300695335 1.331720899 stats.143+tlrc'[Neutral#0_Coef]' \
143 HC Sad 1.300695335 1.331720899 stats.143+tlrc'[Sadness#0_Coef]' \
145 HC Ang 0.087876147 0.768880368 stats.145+tlrc'[Anger#0_Coef]' \
145 HC Dis 0.087876147 0.768880368 stats.145+tlrc'[Disgust#0_Coef]' \
145 HC Fea 0.087876147 0.768880368 stats.145+tlrc'[Fear#0_Coef]' \
145 HC Hap 0.087876147 0.768880368 stats.145+tlrc'[Happiness#0_Coef]' \
145 HC Neu 0.087876147 0.768880368 stats.145+tlrc'[Neutral#0_Coef]' \
145 HC Sad 0.087876147 0.768880368 stats.145+tlrc'[Sadness#0_Coef]' \
146 HC Ang -0.490580417 0.768880368 stats.146+tlrc'[Anger#0_Coef]' \
146 HC Dis -0.490580417 0.768880368 stats.146+tlrc'[Disgust#0_Coef]' \
146 HC Fea -0.490580417 0.768880368 stats.146+tlrc'[Fear#0_Coef]' \
146 HC Hap -0.490580417 0.768880368 stats.146+tlrc'[Happiness#0_Coef]' \
146 HC Neu -0.490580417 0.768880368 stats.146+tlrc'[Neutral#0_Coef]' \
146 HC Sad -0.490580417 0.768880368 stats.146+tlrc'[Sadness#0_Coef]' \
150 HC Ang 1.352037633 0.688474578 stats.150+tlrc'[Anger#0_Coef]' \
150 HC Dis 1.352037633 0.688474578 stats.150+tlrc'[Disgust#0_Coef]' \
150 HC Fea 1.352037633 0.688474578 stats.150+tlrc'[Fear#0_Coef]' \
150 HC Hap 1.352037633 0.688474578 stats.150+tlrc'[Happiness#0_Coef]' \
150 HC Neu 1.352037633 0.688474578 stats.150+tlrc'[Neutral#0_Coef]' \
150 HC Sad 1.352037633 0.688474578 stats.150+tlrc'[Sadness#0_Coef]' \
213 Lo Ang 0.305795681 0.286445627 stats.213+tlrc'[Anger#0_Coef]' \
213 Lo Dis 0.305795681 0.286445627 stats.213+tlrc'[Disgust#0_Coef]' \
213 Lo Fea 0.305795681 0.286445627 stats.213+tlrc'[Fear#0_Coef]' \
213 Lo Hap 0.305795681 0.286445627 stats.213+tlrc'[Happiness#0_Coef]' \
213 Lo Neu 0.305795681 0.286445627 stats.213+tlrc'[Neutral#0_Coef]' \
213 Lo Sad 0.305795681 0.286445627 stats.213+tlrc'[Sadness#0_Coef]' \
218 Lo Ang 1.517473929 -1.643293336 stats.218+tlrc'[Anger#0_Coef]' \
218 Lo Dis 1.517473929 -1.643293336 stats.218+tlrc'[Disgust#0_Coef]' \
218 Lo Fea 1.517473929 -1.643293336 stats.218+tlrc'[Fear#0_Coef]' \
218 Lo Hap 1.517473929 -1.643293336 stats.218+tlrc'[Happiness#0_Coef]' \
218 Lo Neu 1.517473929 -1.643293336 stats.218+tlrc'[Neutral#0_Coef]' \
218 Lo Sad 1.517473929 -1.643293336 stats.218+tlrc'[Sadness#0_Coef]' \
222 Lo Ang 1.259621496 0.447257208 stats.222+tlrc'[Anger#0_Coef]' \
222 Lo Dis 1.259621496 0.447257208 stats.222+tlrc'[Disgust#0_Coef]' \
222 Lo Fea 1.259621496 0.447257208 stats.222+tlrc'[Fear#0_Coef]' \
222 Lo Hap 1.259621496 0.447257208 stats.222+tlrc'[Happiness#0_Coef]' \
222 Lo Neu 1.259621496 0.447257208 stats.222+tlrc'[Neutral#0_Coef]' \
222 Lo Sad 1.259621496 0.447257208 stats.222+tlrc'[Sadness#0_Coef]' \
225 Hi Ang -1.51628545 -1.080452805 stats.225+tlrc'[Anger#0_Coef]' \
225 Hi Dis -1.51628545 -1.080452805 stats.225+tlrc'[Disgust#0_Coef]' \
225 Hi Fea -1.51628545 -1.080452805 stats.225+tlrc'[Fear#0_Coef]' \
225 Hi Hap -1.51628545 -1.080452805 stats.225+tlrc'[Happiness#0_Coef]' \
225 Hi Neu -1.51628545 -1.080452805 stats.225+tlrc'[Neutral#0_Coef]' \
225 Hi Sad -1.51628545 -1.080452805 stats.225+tlrc'[Sadness#0_Coef]' \
227 Lo Ang 0.531701795 -1.321670175 stats.227+tlrc'[Anger#0_Coef]' \
227 Lo Dis 0.531701795 -1.321670175 stats.227+tlrc'[Disgust#0_Coef]' \
227 Lo Fea 0.531701795 -1.321670175 stats.227+tlrc'[Fear#0_Coef]' \
227 Lo Hap 0.531701795 -1.321670175 stats.227+tlrc'[Happiness#0_Coef]' \
227 Lo Neu 0.531701795 -1.321670175 stats.227+tlrc'[Neutral#0_Coef]' \
227 Lo Sad 0.531701795 -1.321670175 stats.227+tlrc'[Sadness#0_Coef]' \
234 Hi Ang 0.101567427 -1.080452805 stats.234+tlrc'[Anger#0_Coef]' \
234 Hi Dis 0.101567427 -1.080452805 stats.234+tlrc'[Disgust#0_Coef]' \
234 Hi Fea 0.101567427 -1.080452805 stats.234+tlrc'[Fear#0_Coef]' \
234 Hi Hap 0.101567427 -1.080452805 stats.234+tlrc'[Happiness#0_Coef]' \
234 Hi Neu 0.101567427 -1.080452805 stats.234+tlrc'[Neutral#0_Coef]' \
234 Hi Sad 0.101567427 -1.080452805 stats.234+tlrc'[Sadness#0_Coef]' \
238 Lo Ang -0.247560204 0.608068788 stats.238+tlrc'[Anger#0_Coef]' \
238 Lo Dis -0.247560204 0.608068788 stats.238+tlrc'[Disgust#0_Coef]' \
238 Lo Fea -0.247560204 0.608068788 stats.238+tlrc'[Fear#0_Coef]' \
238 Lo Hap -0.247560204 0.608068788 stats.238+tlrc'[Happiness#0_Coef]' \
238 Lo Neu -0.247560204 0.608068788 stats.238+tlrc'[Neutral#0_Coef]' \
238 Lo Sad -0.247560204 0.608068788 stats.238+tlrc'[Sadness#0_Coef]' \
241 Hi Ang 0.069621108 -0.195989113 stats.241+tlrc'[Anger#0_Coef]' \
241 Hi Dis 0.069621108 -0.195989113 stats.241+tlrc'[Disgust#0_Coef]' \
241 Hi Fea 0.069621108 -0.195989113 stats.241+tlrc'[Fear#0_Coef]' \
241 Hi Hap 0.069621108 -0.195989113 stats.241+tlrc'[Happiness#0_Coef]' \
241 Hi Neu 0.069621108 -0.195989113 stats.241+tlrc'[Neutral#0_Coef]' \
241 Hi Sad 0.069621108 -0.195989113 stats.241+tlrc'[Sadness#0_Coef]' \
242 Hi Ang 1.718279363 -1.402075965 stats.242+tlrc'[Anger#0_Coef]' \
242 Hi Dis 1.718279363 -1.402075965 stats.242+tlrc'[Disgust#0_Coef]' \
242 Hi Fea 1.718279363 -1.402075965 stats.242+tlrc'[Fear#0_Coef]' \
242 Hi Hap 1.718279363 -1.402075965 stats.242+tlrc'[Happiness#0_Coef]' \
242 Hi Neu 1.718279363 -1.402075965 stats.242+tlrc'[Neutral#0_Coef]' \
242 Hi Sad 1.718279363 -1.402075965 stats.242+tlrc'[Sadness#0_Coef]' \
243 Lo Ang -1.624674747 0.929691948 stats.243+tlrc'[Anger#0_Coef]' \
243 Lo Dis -1.624674747 0.929691948 stats.243+tlrc'[Disgust#0_Coef]' \
243 Lo Fea -1.624674747 0.929691948 stats.243+tlrc'[Fear#0_Coef]' \
243 Lo Hap -1.624674747 0.929691948 stats.243+tlrc'[Happiness#0_Coef]' \
243 Lo Neu -1.624674747 0.929691948 stats.243+tlrc'[Neutral#0_Coef]' \
243 Lo Sad -1.624674747 0.929691948 stats.243+tlrc'[Sadness#0_Coef]' \
248 Lo Ang 1.507205469 1.97496722 stats.248+tlrc'[Anger#0_Coef]' \
248 Lo Dis 1.507205469 1.97496722 stats.248+tlrc'[Disgust#0_Coef]' \
248 Lo Fea 1.507205469 1.97496722 stats.248+tlrc'[Fear#0_Coef]' \
248 Lo Hap 1.507205469 1.97496722 stats.248+tlrc'[Happiness#0_Coef]' \
248 Lo Neu 1.507205469 1.97496722 stats.248+tlrc'[Neutral#0_Coef]' \
248 Lo Sad 1.507205469 1.97496722 stats.248+tlrc'[Sadness#0_Coef]' \
249 Hi Ang -0.500848877 -0.758829644 stats.249+tlrc'[Anger#0_Coef]' \
249 Hi Dis -0.500848877 -0.758829644 stats.249+tlrc'[Disgust#0_Coef]' \
249 Hi Fea -0.500848877 -0.758829644 stats.249+tlrc'[Fear#0_Coef]' \
249 Hi Hap -0.500848877 -0.758829644 stats.249+tlrc'[Happiness#0_Coef]' \
249 Hi Neu -0.500848877 -0.758829644 stats.249+tlrc'[Neutral#0_Coef]' \
249 Hi Sad -0.500848877 -0.758829644 stats.249+tlrc'[Sadness#0_Coef]' \
250 Lo Ang -0.481452897 -0.195989113 stats.250+tlrc'[Anger#0_Coef]' \
250 Lo Dis -0.481452897 -0.195989113 stats.250+tlrc'[Disgust#0_Coef]' \
250 Lo Fea -0.481452897 -0.195989113 stats.250+tlrc'[Fear#0_Coef]' \
250 Lo Hap -0.481452897 -0.195989113 stats.250+tlrc'[Happiness#0_Coef]' \
250 Lo Neu -0.481452897 -0.195989113 stats.250+tlrc'[Neutral#0_Coef]' \
250 Lo Sad -0.481452897 -0.195989113 stats.250+tlrc'[Sadness#0_Coef]' \
251 Hi Ang 0.511164876 0.125634047 stats.251+tlrc'[Anger#0_Coef]' \
251 Hi Dis 0.511164876 0.125634047 stats.251+tlrc'[Disgust#0_Coef]' \
251 Hi Fea 0.511164876 0.125634047 stats.251+tlrc'[Fear#0_Coef]' \
251 Hi Hap 0.511164876 0.125634047 stats.251+tlrc'[Happiness#0_Coef]' \
251 Hi Neu 0.511164876 0.125634047 stats.251+tlrc'[Neutral#0_Coef]' \
251 Hi Sad 0.511164876 0.125634047 stats.251+tlrc'[Sadness#0_Coef]' \
254 Lo Ang 1.129554339 -0.678423854 stats.254+tlrc'[Anger#0_Coef]' \
254 Lo Dis 1.129554339 -0.678423854 stats.254+tlrc'[Disgust#0_Coef]' \
254 Lo Fea 1.129554339 -0.678423854 stats.254+tlrc'[Fear#0_Coef]' \
254 Lo Hap 1.129554339 -0.678423854 stats.254+tlrc'[Happiness#0_Coef]' \
254 Lo Neu 1.129554339 -0.678423854 stats.254+tlrc'[Neutral#0_Coef]' \
254 Lo Sad 1.129554339 -0.678423854 stats.254+tlrc'[Sadness#0_Coef]' \
256 Hi Ang 1.252775856 -0.437206484 stats.256+tlrc'[Anger#0_Coef]' \
256 Hi Dis 1.252775856 -0.437206484 stats.256+tlrc'[Disgust#0_Coef]' \
256 Hi Fea 1.252775856 -0.437206484 stats.256+tlrc'[Fear#0_Coef]' \
256 Hi Hap 1.252775856 -0.437206484 stats.256+tlrc'[Happiness#0_Coef]' \
256 Hi Neu 1.252775856 -0.437206484 stats.256+tlrc'[Neutral#0_Coef]' \
256 Hi Sad 1.252775856 -0.437206484 stats.256+tlrc'[Sadness#0_Coef]' \
257 Lo Ang -1.608701587 -0.035177533 stats.257+tlrc'[Anger#0_Coef]' \
257 Lo Dis -1.608701587 -0.035177533 stats.257+tlrc'[Disgust#0_Coef]' \
257 Lo Fea -1.608701587 -0.035177533 stats.257+tlrc'[Fear#0_Coef]' \
257 Lo Hap -1.608701587 -0.035177533 stats.257+tlrc'[Happiness#0_Coef]' \
257 Lo Neu -1.608701587 -0.035177533 stats.257+tlrc'[Neutral#0_Coef]' \
257 Lo Sad -1.608701587 -0.035177533 stats.257+tlrc'[Sadness#0_Coef]' \
258 Hi Ang 0.832909947 -1.321670175 stats.258+tlrc'[Anger#0_Coef]' \
258 Hi Dis 0.832909947 -1.321670175 stats.258+tlrc'[Disgust#0_Coef]' \
258 Hi Fea 0.832909947 -1.321670175 stats.258+tlrc'[Fear#0_Coef]' \
258 Hi Hap 0.832909947 -1.321670175 stats.258+tlrc'[Happiness#0_Coef]' \
258 Hi Neu 0.832909947 -1.321670175 stats.258+tlrc'[Neutral#0_Coef]' \
258 Hi Sad 0.832909947 -1.321670175 stats.258+tlrc'[Sadness#0_Coef]' \
261 Hi Ang 0.103849307 -1.321670175 stats.261+tlrc'[Anger#0_Coef]' \
261 Hi Dis 0.103849307 -1.321670175 stats.261+tlrc'[Disgust#0_Coef]' \
261 Hi Fea 0.103849307 -1.321670175 stats.261+tlrc'[Fear#0_Coef]' \
261 Hi Hap 0.103849307 -1.321670175 stats.261+tlrc'[Happiness#0_Coef]' \
261 Hi Neu 0.103849307 -1.321670175 stats.261+tlrc'[Neutral#0_Coef]'
261 Hi Sad 0.103849307 -1.321670175 stats.261+tlrc'[Sadness#0_Coef]' \
264 Hi Ang -0.731318751 0.608068788 stats.264+tlrc'[Anger#0_Coef]' \
264 Hi Dis -0.731318751 0.608068788 stats.264+tlrc'[Disgust#0_Coef]' \
264 Hi Fea -0.731318751 0.608068788 stats.264+tlrc'[Fear#0_Coef]' \
264 Hi Hap -0.731318751 0.608068788 stats.264+tlrc'[Happiness#0_Coef]' \
264 Hi Neu -0.731318751 0.608068788 stats.264+tlrc'[Neutral#0_Coef]' \
264 Hi Sad -0.731318751 0.608068788 stats.264+tlrc'[Sadness#0_Coef]' \
270 Lo Ang -0.721050291 1.251315109 stats.270+tlrc'[Anger#0_Coef]' \
270 Lo Dis -0.721050291 1.251315109 stats.270+tlrc'[Disgust#0_Coef]' \
270 Lo Fea -0.721050291 1.251315109 stats.270+tlrc'[Fear#0_Coef]' \
270 Lo Hap -0.721050291 1.251315109 stats.270+tlrc'[Happiness#0_Coef]' \
270 Lo Neu -0.721050291 1.251315109 stats.270+tlrc'[Neutral#0_Coef]' \
270 Lo Sad -0.721050291 1.251315109 stats.270+tlrc'[Sadness#0_Coef]' \
271 Hi Ang -0.919573846 -1.080452805 stats.271+tlrc'[Anger#0_Coef]' \
271 Hi Dis -0.919573846 -1.080452805 stats.271+tlrc'[Disgust#0_Coef]' \
271 Hi Fea -0.919573846 -1.080452805 stats.271+tlrc'[Fear#0_Coef]' \
271 Hi Hap -0.919573846 -1.080452805 stats.271+tlrc'[Happiness#0_Coef]' \
271 Hi Neu -0.919573846 -1.080452805 stats.271+tlrc'[Neutral#0_Coef]' \
271 Hi Sad -0.919573846 -1.080452805 stats.271+tlrc'[Sadness#0_Coef]' \
272 Hi Ang 1.370292673 -0.517612274 stats.272+tlrc'[Anger#0_Coef]' \
272 Hi Dis 1.370292673 -0.517612274 stats.272+tlrc'[Disgust#0_Coef]' \
272 Hi Fea 1.370292673 -0.517612274 stats.272+tlrc'[Fear#0_Coef]' \
272 Hi Hap 1.370292673 -0.517612274 stats.272+tlrc'[Happiness#0_Coef]' \
272 Hi Neu 1.370292673 -0.517612274 stats.272+tlrc'[Neutral#0_Coef]' \
272 Hi Sad 1.370292673 -0.517612274 stats.272+tlrc'[Sadness#0_Coef]' \
274 Lo Ang 1.037138202 -1.160858595 stats.274+tlrc'[Anger#0_Coef]' \
274 Lo Dis 1.037138202 -1.160858595 stats.274+tlrc'[Disgust#0_Coef]' \
274 Lo Fea 1.037138202 -1.160858595 stats.274+tlrc'[Fear#0_Coef]' \
274 Lo Hap 1.037138202 -1.160858595 stats.274+tlrc'[Happiness#0_Coef]' \
274 Lo Neu 1.037138202 -1.160858595 stats.274+tlrc'[Neutral#0_Coef]' \
274 Lo Sad 1.037138202 -1.160858595 stats.274+tlrc'[Sadness#0_Coef]' \
275 Hi Ang -0.529372376 -0.839235435 stats.275+tlrc'[Anger#0_Coef]' \
275 Hi Dis -0.529372376 -0.839235435 stats.275+tlrc'[Disgust#0_Coef]' \
275 Hi Fea -0.529372376 -0.839235435 stats.275+tlrc'[Fear#0_Coef]' \
275 Hi Hap -0.529372376 -0.839235435 stats.275+tlrc'[Happiness#0_Coef]' \
275 Hi Neu -0.529372376 -0.839235435 stats.275+tlrc'[Neutral#0_Coef]' \
275 Hi Sad -0.529372376 -0.839235435 stats.275+tlrc'[Sadness#0_Coef]' \
277 Lo Ang -0.910446326 0.768880368 stats.277+tlrc'[Anger#0_Coef]' \
277 Lo Dis -0.910446326 0.768880368 stats.277+tlrc'[Disgust#0_Coef]' \
277 Lo Fea -0.910446326 0.768880368 stats.277+tlrc'[Fear#0_Coef]' \
277 Lo Hap -0.910446326 0.768880368 stats.277+tlrc'[Happiness#0_Coef]' \
277 Lo Neu -0.910446326 0.768880368 stats.277+tlrc'[Neutral#0_Coef]' \
277 Lo Sad -0.910446326 0.768880368 stats.277+tlrc'[Sadness#0_Coef]' \
278 Lo Ang -0.317157542 -0.276394904 stats.278+tlrc'[Anger#0_Coef]' \
278 Lo Dis -0.317157542 -0.276394904 stats.278+tlrc'[Disgust#0_Coef]' \
278 Lo Fea -0.317157542 -0.276394904 stats.278+tlrc'[Fear#0_Coef]' \
278 Lo Hap -0.317157542 -0.276394904 stats.278+tlrc'[Happiness#0_Coef]' \
278 Lo Neu -0.317157542 -0.276394904 stats.278+tlrc'[Neutral#0_Coef]' \
278 Lo Sad -0.317157542 -0.276394904 stats.278+tlrc'[Sadness#0_Coef]' \
281 Hi Ang 1.355460453 -0.195989113 stats.281+tlrc'[Anger#0_Coef]' \
281 Hi Dis 1.355460453 -0.195989113 stats.281+tlrc'[Disgust#0_Coef]' \
281 Hi Fea 1.355460453 -0.195989113 stats.281+tlrc'[Fear#0_Coef]' \
281 Hi Hap 1.355460453 -0.195989113 stats.281+tlrc'[Happiness#0_Coef]' \
281 Hi Neu 1.355460453 -0.195989113 stats.281+tlrc'[Neutral#0_Coef]' \
281 Hi Sad 1.355460453 -0.195989113 stats.281+tlrc'[Sadness#0_Coef]' \
282 Hi Ang 0.271567482 -0.517612274 stats.282+tlrc'[Anger#0_Coef]' \
282 Hi Dis 0.271567482 -0.517612274 stats.282+tlrc'[Disgust#0_Coef]' \
282 Hi Fea 0.271567482 -0.517612274 stats.282+tlrc'[Fear#0_Coef]' \
282 Hi Hap 0.271567482 -0.517612274 stats.282+tlrc'[Happiness#0_Coef]' \
282 Hi Neu 0.271567482 -0.517612274 stats.282+tlrc'[Neutral#0_Coef]' \
282 Hi Sad 0.271567482 -0.517612274 stats.282+tlrc'[Sadness#0_Coef]' \
284 Lo Ang 1.247071156 -0.678423854 stats.284+tlrc'[Anger#0_Coef]' \
284 Lo Dis 1.247071156 -0.678423854 stats.284+tlrc'[Disgust#0_Coef]' \
284 Lo Fea 1.247071156 -0.678423854 stats.284+tlrc'[Fear#0_Coef]' \
284 Lo Hap 1.247071156 -0.678423854 stats.284+tlrc'[Happiness#0_Coef]' \
284 Lo Neu 1.247071156 -0.678423854 stats.284+tlrc'[Neutral#0_Coef]' \
284 Lo Sad 1.247071156 -0.678423854 stats.284+tlrc'[Sadness#0_Coef]' \
And here is the output I get (error bolded in red):
Loading required package: afex
Loading required package: coin
Loading required package: survival
Loading required package: splines
Loading required package: mvtnorm
Loading required package: modeltools
Loading required package: stats4
Loading required package: car
Loading required package: MASS
Loading required package: nnet
Loading required package: lme4
Loading required package: Matrix
Loading required package: lattice
Attaching package: 'lme4'
The following object is masked from 'package:modeltools':
refit
The following object is masked from 'package:stats':
AIC, BIC
Loading required package: pbkrtest
Loading required package: parallel
Loading required package: reshape2
Loading required package: stringr
Setting contrasts to effects coding: options(contrasts=c('contr.sum', 'contr.poly'))
Loading required package: phia
Warning message:
In if (is.na(lop$wsVars)) ModelForm <- as.formula(paste("Beta ~", :
the condition has length > 1 and only the first element will be used
++++++++++++++++++++++++++++++++++++++++++++++++++++
***** Summary information of data structure *****
48 subjects : 104 110 113 114 117 121 122 123 126 127 130 135 139 140 143 145 146 150 213 218 222 225 227 234 238 241 242 243 248 249 250 251 254 256 257 258 261 264 270 271 272 274 275 277 278 281 282 284
288 response values
3 levels for factor Group : HC Hi Lo
6 levels for factor Emotion : Ang Dis Fea Hap Neu Sad
288 centered values for numeric variable Age : -0.7758154 -0.7758154 -0.7758154 -0.7758154 -0.7758154 -0.7758154 0.4837823 0.4837823 0.4837823 0.4837823 0.4837823 0.4837823 -1.56991 -1.56991 -1.56991 -1.56991 -1.56991 -1.56991 0.2567353 0.2567353 0.2567353 0.2567353 0.2567353 0.2567353 -0.1197749 -0.1197749 -0.1197749 -0.1197749 -0.1197749 -0.1197749 -0.6822583 -0.6822583 -0.6822583 -0.6822583 -0.6822583 -0.6822583 -1.025681 -1.025681 -1.025681 -1.025681 -1.025681 -1.025681 -1.144339 -1.144339 -1.144339 -1.144339 -1.144339 -1.144339 -0.9503792 -0.9503792 -0.9503792 -0.9503792 -0.9503792 -0.9503792 -0.4894395 -0.4894395 -0.4894395 -0.4894395 -0.4894395 -0.4894395 -0.366218 -0.366218 -0.366218 -0.366218 -0.366218 -0.366218 -1.624675 -1.624675 -1.624675 -1.624675 -1.624675 -1.624675 -1.167158 -1.167158 -1.167158 -1.167158 -1.167158 -1.167158 0.9104939 0.9104939 0.9104939 0.9104939 0.9104939 0.9104939 1.300695 1.300695 1.300695 1.300695 1.300695 1.300695 0.08787615 0.08787615 0.08787615 0.08787615 0.08787615 0.08787615 -0.4905804 -0.4905804 -0.4905804 -0.4905804 -0.4905804 -0.4905804 1.352038 1.352038 1.352038 1.352038 1.352038 1.352038 0.3057957 0.3057957 0.3057957 0.3057957 0.3057957 0.3057957 1.517474 1.517474 1.517474 1.517474 1.517474 1.517474 1.259621 1.259621 1.259621 1.259621 1.259621 1.259621 -1.516285 -1.516285 -1.516285 -1.516285 -1.516285 -1.516285 0.5317018 0.5317018 0.5317018 0.5317018 0.5317018 0.5317018 0.1015674 0.1015674 0.1015674 0.1015674 0.1015674 0.1015674 -0.2475602 -0.2475602 -0.2475602 -0.2475602 -0.2475602 -0.2475602 0.06962111 0.06962111 0.06962111 0.06962111 0.06962111 0.06962111 1.718279 1.718279 1.718279 1.718279 1.718279 1.718279 -1.624675 -1.624675 -1.624675 -1.624675 -1.624675 -1.624675 1.507205 1.507205 1.507205 1.507205 1.507205 1.507205 -0.5008489 -0.5008489 -0.5008489 -0.5008489 -0.5008489 -0.5008489 -0.4814529 -0.4814529 -0.4814529 -0.4814529 -0.4814529 -0.4814529 0.5111649 0.5111649 0.5111649 0.5111649 0.5111649 0.5111649 1.129554 1.129554 1.129554 1.129554 1.129554 1.129554 1.252776 1.252776 1.252776 1.252776 1.252776 1.252776 -1.608702 -1.608702 -1.608702 -1.608702 -1.608702 -1.608702 0.8329099 0.8329099 0.8329099 0.8329099 0.8329099 0.8329099 0.1038493 0.1038493 0.1038493 0.1038493 0.1038493 0.1038493 -0.7313188 -0.7313188 -0.7313188 -0.7313188 -0.7313188 -0.7313188 -0.7210503 -0.7210503 -0.7210503 -0.7210503 -0.7210503 -0.7210503 -0.9195738 -0.9195738 -0.9195738 -0.9195738 -0.9195738 -0.9195738 1.370293 1.370293 1.370293 1.370293 1.370293 1.370293 1.037138 1.037138 1.037138 1.037138 1.037138 1.037138 -0.5293724 -0.5293724 -0.5293724 -0.5293724 -0.5293724 -0.5293724 -0.9104463 -0.9104463 -0.9104463 -0.9104463 -0.9104463 -0.9104463 -0.3171575 -0.3171575 -0.3171575 -0.3171575 -0.3171575 -0.3171575 1.35546 1.35546 1.35546 1.35546 1.35546 1.35546 0.2715675 0.2715675 0.2715675 0.2715675 0.2715675 0.2715675 1.247071 1.247071 1.247071 1.247071 1.247071 1.247071
288 centered values for numeric variable IQ : 0.3668514 0.3668514 0.3668514 0.3668514 0.3668514 0.3668514 2.216185 2.216185 2.216185 2.216185 2.216185 2.216185 -1.000047 -1.000047 -1.000047 -1.000047 -1.000047 -1.000047 0.8492862 0.8492862 0.8492862 0.8492862 0.8492862 0.8492862 -0.2763949 -0.2763949 -0.2763949 -0.2763949 -0.2763949 -0.2763949 -1.160859 -1.160859 -1.160859 -1.160859 -1.160859 -1.160859 0.8492862 0.8492862 0.8492862 0.8492862 0.8492862 0.8492862 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 2.216185 2.216185 2.216185 2.216185 2.216185 2.216185 0.8492862 0.8492862 0.8492862 0.8492862 0.8492862 0.8492862 0.4472572 0.4472572 0.4472572 0.4472572 0.4472572 0.4472572 -0.3568007 -0.3568007 -0.3568007 -0.3568007 -0.3568007 -0.3568007 -0.8392354 -0.8392354 -0.8392354 -0.8392354 -0.8392354 -0.8392354 1.251315 1.251315 1.251315 1.251315 1.251315 1.251315 1.331721 1.331721 1.331721 1.331721 1.331721 1.331721 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 0.6884746 0.6884746 0.6884746 0.6884746 0.6884746 0.6884746 0.2864456 0.2864456 0.2864456 0.2864456 0.2864456 0.2864456 -1.643293 -1.643293 -1.643293 -1.643293 -1.643293 -1.643293 0.4472572 0.4472572 0.4472572 0.4472572
0.4472572 0.4472572 -1.080453 -1.080453 -1.080453 -1.080453 -1.080453 -1.080453 -1.32167 -1.32167 -1.32167 -1.32167 -1.32167 -1.32167 -1.080453 -1.080453 -1.080453 -1.080453 -1.080453 -1.080453 0.6080688 0.6080688 0.6080688 0.6080688 0.6080688 0.6080688 -0.1959891 -0.1959891 -0.1959891 -0.1959891 -0.1959891 -0.1959891 -1.402076 -1.402076 -1.402076 -1.402076 -1.402076 -1.402076 0.9296919 0.9296919 0.9296919 0.9296919 0.9296919 0.9296919 1.974967 1.974967 1.974967 1.974967 1.974967 1.974967 -0.7588296 -0.7588296 -0.7588296 -0.7588296 -0.7588296 -0.7588296 -0.1959891 -0.1959891 -0.1959891 -0.1959891 -0.1959891 -0.1959891 0.125634 0.125634 0.125634 0.125634 0.125634 0.125634 -0.6784239 -0.6784239 -0.6784239 -0.6784239 -0.6784239 -0.6784239 -0.4372065 -0.4372065 -0.4372065 -0.4372065 -0.4372065 -0.4372065 -0.03517753 -0.03517753 -0.03517753 -0.03517753 -0.03517753 -0.03517753 -1.32167 -1.32167 -1.32167 -1.32167 -1.32167 -1.32167 -1.32167 -1.32167 -1.32167 -1.32167 -1.32167 -1.32167 0.6080688 0.6080688 0.6080688 0.6080688 0.6080688 0.6080688 1.251315 1.251315 1.251315 1.251315 1.251315 1.251315 -1.080453 -1.080453 -1.080453 -1.080453 -1.080453 -1.080453 -0.5176123 -0.5176123 -0.5176123 -0.5176123 -0.5176123 -0.5176123 -1.160859 -1.160859 -1.160859 -1.160859 -1.160859 -1.160859 -0.8392354 -0.8392354 -0.8392354 -0.8392354 -0.8392354 -0.8392354 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 -0.2763949 -0.2763949 -0.2763949 -0.2763949 -0.2763949 -0.2763949 -0.1959891 -0.1959891 -0.1959891 -0.1959891 -0.1959891 -0.1959891 -0.5176123 -0.5176123 -0.5176123 -0.5176123 -0.5176123 -0.5176123 -0.6784239 -0.6784239 -0.6784239 -0.6784239 -0.6784239 -0.6784239
18 post hoc tests
Tabulation of subjects against all categorical variables
~~~~~~~~~~~~~~
Subj vs Group:
HC Hi Lo
104 6 0 0
110 6 0 0
113 6 0 0
114 6 0 0
117 6 0 0
121 6 0 0
122 6 0 0
123 6 0 0
126 6 0 0
127 6 0 0
130 6 0 0
135 6 0 0
139 6 0 0
140 6 0 0
143 6 0 0
145 6 0 0
146 6 0 0
150 6 0 0
213 0 0 6
218 0 0 6
222 0 0 6
225 0 6 0
227 0 0 6
234 0 6 0
238 0 0 6
241 0 6 0
242 0 6 0
243 0 0 6
248 0 0 6
249 0 6 0
250 0 0 6
251 0 6 0
254 0 0 6
256 0 6 0
257 0 0 6
258 0 6 0
261 0 6 0
264 0 6 0
270 0 0 6
271 0 6 0
272 0 6 0
274 0 0 6
275 0 6 0
277 0 0 6
278 0 0 6
281 0 6 0
282 0 6 0
284 0 0 6
~~~~~~~~~~~~~~
Subj vs Emotion:
Ang Dis Fea Hap Neu Sad
104 1 1 1 1 1 1
110 1 1 1 1 1 1
113 1 1 1 1 1 1
114 1 1 1 1 1 1
117 1 1 1 1 1 1
121 1 1 1 1 1 1
122 1 1 1 1 1 1
123 1 1 1 1 1 1
126 1 1 1 1 1 1
127 1 1 1 1 1 1
130 1 1 1 1 1 1
135 1 1 1 1 1 1
139 1 1 1 1 1 1
140 1 1 1 1 1 1
143 1 1 1 1 1 1
145 1 1 1 1 1 1
146 1 1 1 1 1 1
150 1 1 1 1 1 1
213 1 1 1 1 1 1
218 1 1 1 1 1 1
222 1 1 1 1 1 1
225 1 1 1 1 1 1
227 1 1 1 1 1 1
234 1 1 1 1 1 1
238 1 1 1 1 1 1
241 1 1 1 1 1 1
242 1 1 1 1 1 1
243 1 1 1 1 1 1
248 1 1 1 1 1 1
249 1 1 1 1 1 1
250 1 1 1 1 1 1
251 1 1 1 1 1 1
254 1 1 1 1 1 1
256 1 1 1 1 1 1
257 1 1 1 1 1 1
258 1 1 1 1 1 1
261 1 1 1 1 1 1
264 1 1 1 1 1 1
270 1 1 1 1 1 1
271 1 1 1 1 1 1
272 1 1 1 1 1 1
274 1 1 1 1 1 1
275 1 1 1 1 1 1
277 1 1 1 1 1 1
278 1 1 1 1 1 1
281 1 1 1 1 1 1
282 1 1 1 1 1 1
284 1 1 1 1 1 1
***** End of data structure information *****
++++++++++++++++++++++++++++++++++++++++++++++++++++
Reading input files now...
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.
[1] "Great, test run passed at voxel (18, 32, 25)!"
Error in rep(0, NoBrick) : invalid 'times' argument
Execution halted
Thank you so much for your help!
I am having some difficulties getting my 3 x 6 ANOVA to run using 3dMVM. I have also added in 2 covariates and I am not sure if I have done something incorrectly.
Here is what I run (as an executable file):
3dMVM \
-prefix ST_ANOVA_ICUxEmotion \
-jobs 1 \
-wsVars "Emotion" \
-bsVars 'Group' \
-qVars "Age,IQ" \
-mask 'full_mask.KBFST104+tlrc.BRIK' \
-num_glt 18 \
-gltLabel 1 HC_vs_Lo -gltCode 1 'Group : 1*HC -1*Lo' \
-gltLabel 2 HC_vs_Hi -gltCode 2 'Group : 1*HC -1*Hi' \
-gltLabel 3 LoCU_vs_Hi -gltCode 3 'Group : 1*Lo -1*Hi' \
-gltLabel 4 Fear_HC_vs_Lo -gltCode 4 'Group : 1*HC -1*Lo Emotion : 1*Fea' \
-gltLabel 5 Fear_HC_vs_Hi -gltCode 5 'Group : 1*HC -1*Hi Emotion : 1*Fea' \
-gltLabel 6 Fear_Lo_vs_Hi -gltCode 6 'Group : 1*Lo -1*Hi Emotion : 1*Fea' \
-gltLabel 7 Anger_HC_vs_Lo -gltCode 7 'Group : 1*HC -1*Lo Emotion : 1*Ang' \
-gltLabel 8 Anger_HC_vs_Hi -gltCode 8 'Group : 1*HC -1*Hi Emotion : 1*Ang' \
-gltLabel 9 Anger_Lo_vs_Hi -gltCode 9 'Group : 1*Lo -1*Hi Emotion : 1*Ang' \
-gltLabel 10 Disgust_HC_vs_Lo -gltCode 10 'Group : 1*HC -1*Lo Emotion : 1*Dis' \
-gltLabel 11 Disgust_HC_vs_Hi -gltCode 11 'Group : 1*HC -1*Hi Emotion : 1*Dis' \
-gltLabel 12 Disgust_Lo_vs_Hi -gltCode 12 'Group : 1*Lo -1*Hi Emotion : 1*Dis' \
-gltLabel 13 Happiness_HC_vs_Lo -gltCode 13 'Group : 1*HC -1*Lo Emotion : 1*Hap' \
-gltLabel 14 Happiness_HC_vs_Hi -gltCode 14 'Group : 1*HC -1*Hi Emotion : 1*Hap' \
-gltLabel 15 Happiness_Lo_vs_Hi -gltCode 15 'Group : 1*Lo -1*Hi Emotion : 1*Hap' \
-gltLabel 16 Sadness_HC_vs_Lo -gltCode 16 'Group : 1*HC -1*Lo Emotion : 1*Sad' \
-gltLabel 17 Sadness_HC_vs_Hi -gltCode 17 'Group : 1*HC -1*Hi Emotion : 1*Sad' \
-gltLabel 18 Sadness_Lo_vs_Hi -gltCode 18 'Group : 1*Lo -1*Hi Emotion : 1*Sad' \
-dataTable \
Subj Group Emotion Age IQ InputFile \
104 HC Ang -0.77581541 0.366851417 stats.104+tlrc'[Anger#0_Coef]' \
104 HC Dis -0.77581541 0.366851417 stats.104+tlrc'[Disgust#0_Coef]' \
104 HC Fea -0.77581541 0.366851417 stats.104+tlrc'[Fear#0_Coef]' \
104 HC Hap -0.77581541 0.366851417 stats.104+tlrc'[Happiness#0_Coef]' \
104 HC Neu -0.77581541 0.366851417 stats.104+tlrc'[Neutral#0_Coef]' \
104 HC Sad -0.77581541 0.366851417 stats.104+tlrc'[Sadness#0_Coef]' \
110 HC Ang 0.483782317 2.216184591 stats.110+tlrc'[Anger#0_Coef]' \
110 HC Dis 0.483782317 2.216184591 stats.110+tlrc'[Disgust#0_Coef]' \
110 HC Fea 0.483782317 2.216184591 stats.110+tlrc'[Fear#0_Coef]' \
110 HC Hap 0.483782317 2.216184591 stats.110+tlrc'[Happiness#0_Coef]' \
110 HC Neu 0.483782317 2.216184591 stats.110+tlrc'[Neutral#0_Coef]' \
110 HC Sad 0.483782317 2.216184591 stats.110+tlrc'[Sadness#0_Coef]' \
113 HC Ang -1.569909628 -1.000047015 stats.113+tlrc'[Anger#0_Coef]' \
113 HC Dis -1.569909628 -1.000047015 stats.113+tlrc'[Disgust#0_Coef]' \
113 HC Fea -1.569909628 -1.000047015 stats.113+tlrc'[Fear#0_Coef]' \
113 HC Hap -1.569909628 -1.000047015 stats.113+tlrc'[Happiness#0_Coef]' \
113 HC Neu -1.569909628 -1.000047015 stats.113+tlrc'[Neutral#0_Coef]' \
113 HC Sad -1.569909628 -1.000047015 stats.113+tlrc'[Sadness#0_Coef]' \
114 HC Ang 0.256735263 0.849286158 stats.114+tlrc'[Anger#0_Coef]' \
114 HC Dis 0.256735263 0.849286158 stats.114+tlrc'[Disgust#0_Coef]' \
114 HC Fea 0.256735263 0.849286158 stats.114+tlrc'[Fear#0_Coef]' \
114 HC Hap 0.256735263 0.849286158 stats.114+tlrc'[Happiness#0_Coef]' \
114 HC Neu 0.256735263 0.849286158 stats.114+tlrc'[Neutral#0_Coef]' \
114 HC Sad 0.256735263 0.849286158 stats.114+tlrc'[Sadness#0_Coef]' \
117 HC Ang -0.119774927 -0.276394904 stats.117+tlrc'[Anger#0_Coef]' \
117 HC Dis -0.119774927 -0.276394904 stats.117+tlrc'[Disgust#0_Coef]' \
117 HC Fea -0.119774927 -0.276394904 stats.117+tlrc'[Fear#0_Coef]' \
117 HC Hap -0.119774927 -0.276394904 stats.117+tlrc'[Happiness#0_Coef]' \
117 HC Neu -0.119774927 -0.276394904 stats.117+tlrc'[Neutral#0_Coef]' \
117 HC Sad -0.119774927 -0.276394904 stats.117+tlrc'[Sadness#0_Coef]' \
121 HC Ang -0.682258332 -1.160858595 stats.121+tlrc'[Anger#0_Coef]' \
121 HC Dis -0.682258332 -1.160858595 stats.121+tlrc'[Disgust#0_Coef]' \
121 HC Fea -0.682258332 -1.160858595 stats.121+tlrc'[Fear#0_Coef]' \
121 HC Hap -0.682258332 -1.160858595 stats.121+tlrc'[Happiness#0_Coef]' \
121 HC Neu -0.682258332 -1.160858595 stats.121+tlrc'[Neutral#0_Coef]' \
121 HC Sad -0.682258332 -1.160858595 stats.121+tlrc'[Sadness#0_Coef]' \
122 HC Ang -1.025681263 0.849286158 stats.122+tlrc'[Anger#0_Coef]' \
122 HC Dis -1.025681263 0.849286158 stats.122+tlrc'[Disgust#0_Coef]' \
122 HC Fea -1.025681263 0.849286158 stats.122+tlrc'[Fear#0_Coef]' \
122 HC Hap -1.025681263 0.849286158 stats.122+tlrc'[Happiness#0_Coef]' \
122 HC Neu -1.025681263 0.849286158 stats.122+tlrc'[Neutral#0_Coef]' \
122 HC Sad -1.025681263 0.849286158 stats.122+tlrc'[Sadness#0_Coef]' \
123 HC Ang -1.14433902 0.768880368 stats.123+tlrc'[Anger#0_Coef]' \
123 HC Dis -1.14433902 0.768880368 stats.123+tlrc'[Disgust#0_Coef]' \
123 HC Fea -1.14433902 0.768880368 stats.123+tlrc'[Fear#0_Coef]' \
123 HC Hap -1.14433902 0.768880368 stats.123+tlrc'[Happiness#0_Coef]' \
123 HC Neu -1.14433902 0.768880368 stats.123+tlrc'[Neutral#0_Coef]' \
123 HC Sad -1.14433902 0.768880368 stats.123+tlrc'[Sadness#0_Coef]' \
126 HC Ang -0.950379225 2.216184591 stats.126+tlrc'[Anger#0_Coef]' \
126 HC Dis -0.950379225 2.216184591 stats.126+tlrc'[Disgust#0_Coef]' \
126 HC Fea -0.950379225 2.216184591 stats.126+tlrc'[Fear#0_Coef]' \
126 HC Hap -0.950379225 2.216184591 stats.126+tlrc'[Happiness#0_Coef]' \
126 HC Neu -0.950379225 2.216184591 stats.126+tlrc'[Neutral#0_Coef]' \
126 HC Sad -0.950379225 2.216184591 stats.126+tlrc'[Sadness#0_Coef]' \
127 HC Ang -0.489439477 0.849286158 stats.127+tlrc'[Anger#0_Coef]' \
127 HC Dis -0.489439477 0.849286158 stats.127+tlrc'[Disgust#0_Coef]' \
127 HC Fea -0.489439477 0.849286158 stats.127+tlrc'[Fear#0_Coef]' \
127 HC Hap -0.489439477 0.849286158 stats.127+tlrc'[Happiness#0_Coef]' \
127 HC Neu -0.489439477 0.849286158 stats.127+tlrc'[Neutral#0_Coef]' \
127 HC Sad -0.489439477 0.849286158 stats.127+tlrc'[Sadness#0_Coef]' \
130 HC Ang -0.366217961 0.447257208 stats.130+tlrc'[Anger#0_Coef]' \
130 HC Dis -0.366217961 0.447257208 stats.130+tlrc'[Disgust#0_Coef]' \
130 HC Fea -0.366217961 0.447257208 stats.130+tlrc'[Fear#0_Coef]' \
130 HC Hap -0.366217961 0.447257208 stats.130+tlrc'[Happiness#0_Coef]' \
130 HC Neu -0.366217961 0.447257208 stats.130+tlrc'[Neutral#0_Coef]' \
130 HC Sad -0.366217961 0.447257208 stats.130+tlrc'[Sadness#0_Coef]' \
135 HC Ang -1.624674747 -0.356800694 stats.135+tlrc'[Anger#0_Coef]' \
135 HC Dis -1.624674747 -0.356800694 stats.135+tlrc'[Disgust#0_Coef]' \
135 HC Fea -1.624674747 -0.356800694 stats.135+tlrc'[Fear#0_Coef]' \
135 HC Hap -1.624674747 -0.356800694 stats.135+tlrc'[Happiness#0_Coef]' \
135 HC Neu -1.624674747 -0.356800694 stats.135+tlrc'[Neutral#0_Coef]' \
135 HC Sad -1.624674747 -0.356800694 stats.135+tlrc'[Sadness#0_Coef]' \
139 HC Ang -1.167157819 -0.839235435 stats.139+tlrc'[Anger#0_Coef]' \
139 HC Dis -1.167157819 -0.839235435 stats.139+tlrc'[Disgust#0_Coef]' \
139 HC Fea -1.167157819 -0.839235435 stats.139+tlrc'[Fear#0_Coef]' \
139 HC Hap -1.167157819 -0.839235435 stats.139+tlrc'[Happiness#0_Coef]' \
139 HC Neu -1.167157819 -0.839235435 stats.139+tlrc'[Neutral#0_Coef]' \
139 HC Sad -1.167157819 -0.839235435 stats.139+tlrc'[Sadness#0_Coef]' \
140 HC Ang 0.910493865 1.251315109 stats.140+tlrc'[Anger#0_Coef]' \
140 HC Dis 0.910493865 1.251315109 stats.140+tlrc'[Disgust#0_Coef]' \
140 HC Fea 0.910493865 1.251315109 stats.140+tlrc'[Fear#0_Coef]' \
140 HC Hap 0.910493865 1.251315109 stats.140+tlrc'[Happiness#0_Coef]' \
140 HC Neu 0.910493865 1.251315109 stats.140+tlrc'[Neutral#0_Coef]' \
140 HC Sad 0.910493865 1.251315109 stats.140+tlrc'[Sadness#0_Coef]' \
143 HC Ang 1.300695335 1.331720899 stats.143+tlrc'[Anger#0_Coef]' \
143 HC Dis 1.300695335 1.331720899 stats.143+tlrc'[Disgust#0_Coef]' \
143 HC Fea 1.300695335 1.331720899 stats.143+tlrc'[Fear#0_Coef]' \
143 HC Hap 1.300695335 1.331720899 stats.143+tlrc'[Happiness#0_Coef]' \
143 HC Neu 1.300695335 1.331720899 stats.143+tlrc'[Neutral#0_Coef]' \
143 HC Sad 1.300695335 1.331720899 stats.143+tlrc'[Sadness#0_Coef]' \
145 HC Ang 0.087876147 0.768880368 stats.145+tlrc'[Anger#0_Coef]' \
145 HC Dis 0.087876147 0.768880368 stats.145+tlrc'[Disgust#0_Coef]' \
145 HC Fea 0.087876147 0.768880368 stats.145+tlrc'[Fear#0_Coef]' \
145 HC Hap 0.087876147 0.768880368 stats.145+tlrc'[Happiness#0_Coef]' \
145 HC Neu 0.087876147 0.768880368 stats.145+tlrc'[Neutral#0_Coef]' \
145 HC Sad 0.087876147 0.768880368 stats.145+tlrc'[Sadness#0_Coef]' \
146 HC Ang -0.490580417 0.768880368 stats.146+tlrc'[Anger#0_Coef]' \
146 HC Dis -0.490580417 0.768880368 stats.146+tlrc'[Disgust#0_Coef]' \
146 HC Fea -0.490580417 0.768880368 stats.146+tlrc'[Fear#0_Coef]' \
146 HC Hap -0.490580417 0.768880368 stats.146+tlrc'[Happiness#0_Coef]' \
146 HC Neu -0.490580417 0.768880368 stats.146+tlrc'[Neutral#0_Coef]' \
146 HC Sad -0.490580417 0.768880368 stats.146+tlrc'[Sadness#0_Coef]' \
150 HC Ang 1.352037633 0.688474578 stats.150+tlrc'[Anger#0_Coef]' \
150 HC Dis 1.352037633 0.688474578 stats.150+tlrc'[Disgust#0_Coef]' \
150 HC Fea 1.352037633 0.688474578 stats.150+tlrc'[Fear#0_Coef]' \
150 HC Hap 1.352037633 0.688474578 stats.150+tlrc'[Happiness#0_Coef]' \
150 HC Neu 1.352037633 0.688474578 stats.150+tlrc'[Neutral#0_Coef]' \
150 HC Sad 1.352037633 0.688474578 stats.150+tlrc'[Sadness#0_Coef]' \
213 Lo Ang 0.305795681 0.286445627 stats.213+tlrc'[Anger#0_Coef]' \
213 Lo Dis 0.305795681 0.286445627 stats.213+tlrc'[Disgust#0_Coef]' \
213 Lo Fea 0.305795681 0.286445627 stats.213+tlrc'[Fear#0_Coef]' \
213 Lo Hap 0.305795681 0.286445627 stats.213+tlrc'[Happiness#0_Coef]' \
213 Lo Neu 0.305795681 0.286445627 stats.213+tlrc'[Neutral#0_Coef]' \
213 Lo Sad 0.305795681 0.286445627 stats.213+tlrc'[Sadness#0_Coef]' \
218 Lo Ang 1.517473929 -1.643293336 stats.218+tlrc'[Anger#0_Coef]' \
218 Lo Dis 1.517473929 -1.643293336 stats.218+tlrc'[Disgust#0_Coef]' \
218 Lo Fea 1.517473929 -1.643293336 stats.218+tlrc'[Fear#0_Coef]' \
218 Lo Hap 1.517473929 -1.643293336 stats.218+tlrc'[Happiness#0_Coef]' \
218 Lo Neu 1.517473929 -1.643293336 stats.218+tlrc'[Neutral#0_Coef]' \
218 Lo Sad 1.517473929 -1.643293336 stats.218+tlrc'[Sadness#0_Coef]' \
222 Lo Ang 1.259621496 0.447257208 stats.222+tlrc'[Anger#0_Coef]' \
222 Lo Dis 1.259621496 0.447257208 stats.222+tlrc'[Disgust#0_Coef]' \
222 Lo Fea 1.259621496 0.447257208 stats.222+tlrc'[Fear#0_Coef]' \
222 Lo Hap 1.259621496 0.447257208 stats.222+tlrc'[Happiness#0_Coef]' \
222 Lo Neu 1.259621496 0.447257208 stats.222+tlrc'[Neutral#0_Coef]' \
222 Lo Sad 1.259621496 0.447257208 stats.222+tlrc'[Sadness#0_Coef]' \
225 Hi Ang -1.51628545 -1.080452805 stats.225+tlrc'[Anger#0_Coef]' \
225 Hi Dis -1.51628545 -1.080452805 stats.225+tlrc'[Disgust#0_Coef]' \
225 Hi Fea -1.51628545 -1.080452805 stats.225+tlrc'[Fear#0_Coef]' \
225 Hi Hap -1.51628545 -1.080452805 stats.225+tlrc'[Happiness#0_Coef]' \
225 Hi Neu -1.51628545 -1.080452805 stats.225+tlrc'[Neutral#0_Coef]' \
225 Hi Sad -1.51628545 -1.080452805 stats.225+tlrc'[Sadness#0_Coef]' \
227 Lo Ang 0.531701795 -1.321670175 stats.227+tlrc'[Anger#0_Coef]' \
227 Lo Dis 0.531701795 -1.321670175 stats.227+tlrc'[Disgust#0_Coef]' \
227 Lo Fea 0.531701795 -1.321670175 stats.227+tlrc'[Fear#0_Coef]' \
227 Lo Hap 0.531701795 -1.321670175 stats.227+tlrc'[Happiness#0_Coef]' \
227 Lo Neu 0.531701795 -1.321670175 stats.227+tlrc'[Neutral#0_Coef]' \
227 Lo Sad 0.531701795 -1.321670175 stats.227+tlrc'[Sadness#0_Coef]' \
234 Hi Ang 0.101567427 -1.080452805 stats.234+tlrc'[Anger#0_Coef]' \
234 Hi Dis 0.101567427 -1.080452805 stats.234+tlrc'[Disgust#0_Coef]' \
234 Hi Fea 0.101567427 -1.080452805 stats.234+tlrc'[Fear#0_Coef]' \
234 Hi Hap 0.101567427 -1.080452805 stats.234+tlrc'[Happiness#0_Coef]' \
234 Hi Neu 0.101567427 -1.080452805 stats.234+tlrc'[Neutral#0_Coef]' \
234 Hi Sad 0.101567427 -1.080452805 stats.234+tlrc'[Sadness#0_Coef]' \
238 Lo Ang -0.247560204 0.608068788 stats.238+tlrc'[Anger#0_Coef]' \
238 Lo Dis -0.247560204 0.608068788 stats.238+tlrc'[Disgust#0_Coef]' \
238 Lo Fea -0.247560204 0.608068788 stats.238+tlrc'[Fear#0_Coef]' \
238 Lo Hap -0.247560204 0.608068788 stats.238+tlrc'[Happiness#0_Coef]' \
238 Lo Neu -0.247560204 0.608068788 stats.238+tlrc'[Neutral#0_Coef]' \
238 Lo Sad -0.247560204 0.608068788 stats.238+tlrc'[Sadness#0_Coef]' \
241 Hi Ang 0.069621108 -0.195989113 stats.241+tlrc'[Anger#0_Coef]' \
241 Hi Dis 0.069621108 -0.195989113 stats.241+tlrc'[Disgust#0_Coef]' \
241 Hi Fea 0.069621108 -0.195989113 stats.241+tlrc'[Fear#0_Coef]' \
241 Hi Hap 0.069621108 -0.195989113 stats.241+tlrc'[Happiness#0_Coef]' \
241 Hi Neu 0.069621108 -0.195989113 stats.241+tlrc'[Neutral#0_Coef]' \
241 Hi Sad 0.069621108 -0.195989113 stats.241+tlrc'[Sadness#0_Coef]' \
242 Hi Ang 1.718279363 -1.402075965 stats.242+tlrc'[Anger#0_Coef]' \
242 Hi Dis 1.718279363 -1.402075965 stats.242+tlrc'[Disgust#0_Coef]' \
242 Hi Fea 1.718279363 -1.402075965 stats.242+tlrc'[Fear#0_Coef]' \
242 Hi Hap 1.718279363 -1.402075965 stats.242+tlrc'[Happiness#0_Coef]' \
242 Hi Neu 1.718279363 -1.402075965 stats.242+tlrc'[Neutral#0_Coef]' \
242 Hi Sad 1.718279363 -1.402075965 stats.242+tlrc'[Sadness#0_Coef]' \
243 Lo Ang -1.624674747 0.929691948 stats.243+tlrc'[Anger#0_Coef]' \
243 Lo Dis -1.624674747 0.929691948 stats.243+tlrc'[Disgust#0_Coef]' \
243 Lo Fea -1.624674747 0.929691948 stats.243+tlrc'[Fear#0_Coef]' \
243 Lo Hap -1.624674747 0.929691948 stats.243+tlrc'[Happiness#0_Coef]' \
243 Lo Neu -1.624674747 0.929691948 stats.243+tlrc'[Neutral#0_Coef]' \
243 Lo Sad -1.624674747 0.929691948 stats.243+tlrc'[Sadness#0_Coef]' \
248 Lo Ang 1.507205469 1.97496722 stats.248+tlrc'[Anger#0_Coef]' \
248 Lo Dis 1.507205469 1.97496722 stats.248+tlrc'[Disgust#0_Coef]' \
248 Lo Fea 1.507205469 1.97496722 stats.248+tlrc'[Fear#0_Coef]' \
248 Lo Hap 1.507205469 1.97496722 stats.248+tlrc'[Happiness#0_Coef]' \
248 Lo Neu 1.507205469 1.97496722 stats.248+tlrc'[Neutral#0_Coef]' \
248 Lo Sad 1.507205469 1.97496722 stats.248+tlrc'[Sadness#0_Coef]' \
249 Hi Ang -0.500848877 -0.758829644 stats.249+tlrc'[Anger#0_Coef]' \
249 Hi Dis -0.500848877 -0.758829644 stats.249+tlrc'[Disgust#0_Coef]' \
249 Hi Fea -0.500848877 -0.758829644 stats.249+tlrc'[Fear#0_Coef]' \
249 Hi Hap -0.500848877 -0.758829644 stats.249+tlrc'[Happiness#0_Coef]' \
249 Hi Neu -0.500848877 -0.758829644 stats.249+tlrc'[Neutral#0_Coef]' \
249 Hi Sad -0.500848877 -0.758829644 stats.249+tlrc'[Sadness#0_Coef]' \
250 Lo Ang -0.481452897 -0.195989113 stats.250+tlrc'[Anger#0_Coef]' \
250 Lo Dis -0.481452897 -0.195989113 stats.250+tlrc'[Disgust#0_Coef]' \
250 Lo Fea -0.481452897 -0.195989113 stats.250+tlrc'[Fear#0_Coef]' \
250 Lo Hap -0.481452897 -0.195989113 stats.250+tlrc'[Happiness#0_Coef]' \
250 Lo Neu -0.481452897 -0.195989113 stats.250+tlrc'[Neutral#0_Coef]' \
250 Lo Sad -0.481452897 -0.195989113 stats.250+tlrc'[Sadness#0_Coef]' \
251 Hi Ang 0.511164876 0.125634047 stats.251+tlrc'[Anger#0_Coef]' \
251 Hi Dis 0.511164876 0.125634047 stats.251+tlrc'[Disgust#0_Coef]' \
251 Hi Fea 0.511164876 0.125634047 stats.251+tlrc'[Fear#0_Coef]' \
251 Hi Hap 0.511164876 0.125634047 stats.251+tlrc'[Happiness#0_Coef]' \
251 Hi Neu 0.511164876 0.125634047 stats.251+tlrc'[Neutral#0_Coef]' \
251 Hi Sad 0.511164876 0.125634047 stats.251+tlrc'[Sadness#0_Coef]' \
254 Lo Ang 1.129554339 -0.678423854 stats.254+tlrc'[Anger#0_Coef]' \
254 Lo Dis 1.129554339 -0.678423854 stats.254+tlrc'[Disgust#0_Coef]' \
254 Lo Fea 1.129554339 -0.678423854 stats.254+tlrc'[Fear#0_Coef]' \
254 Lo Hap 1.129554339 -0.678423854 stats.254+tlrc'[Happiness#0_Coef]' \
254 Lo Neu 1.129554339 -0.678423854 stats.254+tlrc'[Neutral#0_Coef]' \
254 Lo Sad 1.129554339 -0.678423854 stats.254+tlrc'[Sadness#0_Coef]' \
256 Hi Ang 1.252775856 -0.437206484 stats.256+tlrc'[Anger#0_Coef]' \
256 Hi Dis 1.252775856 -0.437206484 stats.256+tlrc'[Disgust#0_Coef]' \
256 Hi Fea 1.252775856 -0.437206484 stats.256+tlrc'[Fear#0_Coef]' \
256 Hi Hap 1.252775856 -0.437206484 stats.256+tlrc'[Happiness#0_Coef]' \
256 Hi Neu 1.252775856 -0.437206484 stats.256+tlrc'[Neutral#0_Coef]' \
256 Hi Sad 1.252775856 -0.437206484 stats.256+tlrc'[Sadness#0_Coef]' \
257 Lo Ang -1.608701587 -0.035177533 stats.257+tlrc'[Anger#0_Coef]' \
257 Lo Dis -1.608701587 -0.035177533 stats.257+tlrc'[Disgust#0_Coef]' \
257 Lo Fea -1.608701587 -0.035177533 stats.257+tlrc'[Fear#0_Coef]' \
257 Lo Hap -1.608701587 -0.035177533 stats.257+tlrc'[Happiness#0_Coef]' \
257 Lo Neu -1.608701587 -0.035177533 stats.257+tlrc'[Neutral#0_Coef]' \
257 Lo Sad -1.608701587 -0.035177533 stats.257+tlrc'[Sadness#0_Coef]' \
258 Hi Ang 0.832909947 -1.321670175 stats.258+tlrc'[Anger#0_Coef]' \
258 Hi Dis 0.832909947 -1.321670175 stats.258+tlrc'[Disgust#0_Coef]' \
258 Hi Fea 0.832909947 -1.321670175 stats.258+tlrc'[Fear#0_Coef]' \
258 Hi Hap 0.832909947 -1.321670175 stats.258+tlrc'[Happiness#0_Coef]' \
258 Hi Neu 0.832909947 -1.321670175 stats.258+tlrc'[Neutral#0_Coef]' \
258 Hi Sad 0.832909947 -1.321670175 stats.258+tlrc'[Sadness#0_Coef]' \
261 Hi Ang 0.103849307 -1.321670175 stats.261+tlrc'[Anger#0_Coef]' \
261 Hi Dis 0.103849307 -1.321670175 stats.261+tlrc'[Disgust#0_Coef]' \
261 Hi Fea 0.103849307 -1.321670175 stats.261+tlrc'[Fear#0_Coef]' \
261 Hi Hap 0.103849307 -1.321670175 stats.261+tlrc'[Happiness#0_Coef]' \
261 Hi Neu 0.103849307 -1.321670175 stats.261+tlrc'[Neutral#0_Coef]'
261 Hi Sad 0.103849307 -1.321670175 stats.261+tlrc'[Sadness#0_Coef]' \
264 Hi Ang -0.731318751 0.608068788 stats.264+tlrc'[Anger#0_Coef]' \
264 Hi Dis -0.731318751 0.608068788 stats.264+tlrc'[Disgust#0_Coef]' \
264 Hi Fea -0.731318751 0.608068788 stats.264+tlrc'[Fear#0_Coef]' \
264 Hi Hap -0.731318751 0.608068788 stats.264+tlrc'[Happiness#0_Coef]' \
264 Hi Neu -0.731318751 0.608068788 stats.264+tlrc'[Neutral#0_Coef]' \
264 Hi Sad -0.731318751 0.608068788 stats.264+tlrc'[Sadness#0_Coef]' \
270 Lo Ang -0.721050291 1.251315109 stats.270+tlrc'[Anger#0_Coef]' \
270 Lo Dis -0.721050291 1.251315109 stats.270+tlrc'[Disgust#0_Coef]' \
270 Lo Fea -0.721050291 1.251315109 stats.270+tlrc'[Fear#0_Coef]' \
270 Lo Hap -0.721050291 1.251315109 stats.270+tlrc'[Happiness#0_Coef]' \
270 Lo Neu -0.721050291 1.251315109 stats.270+tlrc'[Neutral#0_Coef]' \
270 Lo Sad -0.721050291 1.251315109 stats.270+tlrc'[Sadness#0_Coef]' \
271 Hi Ang -0.919573846 -1.080452805 stats.271+tlrc'[Anger#0_Coef]' \
271 Hi Dis -0.919573846 -1.080452805 stats.271+tlrc'[Disgust#0_Coef]' \
271 Hi Fea -0.919573846 -1.080452805 stats.271+tlrc'[Fear#0_Coef]' \
271 Hi Hap -0.919573846 -1.080452805 stats.271+tlrc'[Happiness#0_Coef]' \
271 Hi Neu -0.919573846 -1.080452805 stats.271+tlrc'[Neutral#0_Coef]' \
271 Hi Sad -0.919573846 -1.080452805 stats.271+tlrc'[Sadness#0_Coef]' \
272 Hi Ang 1.370292673 -0.517612274 stats.272+tlrc'[Anger#0_Coef]' \
272 Hi Dis 1.370292673 -0.517612274 stats.272+tlrc'[Disgust#0_Coef]' \
272 Hi Fea 1.370292673 -0.517612274 stats.272+tlrc'[Fear#0_Coef]' \
272 Hi Hap 1.370292673 -0.517612274 stats.272+tlrc'[Happiness#0_Coef]' \
272 Hi Neu 1.370292673 -0.517612274 stats.272+tlrc'[Neutral#0_Coef]' \
272 Hi Sad 1.370292673 -0.517612274 stats.272+tlrc'[Sadness#0_Coef]' \
274 Lo Ang 1.037138202 -1.160858595 stats.274+tlrc'[Anger#0_Coef]' \
274 Lo Dis 1.037138202 -1.160858595 stats.274+tlrc'[Disgust#0_Coef]' \
274 Lo Fea 1.037138202 -1.160858595 stats.274+tlrc'[Fear#0_Coef]' \
274 Lo Hap 1.037138202 -1.160858595 stats.274+tlrc'[Happiness#0_Coef]' \
274 Lo Neu 1.037138202 -1.160858595 stats.274+tlrc'[Neutral#0_Coef]' \
274 Lo Sad 1.037138202 -1.160858595 stats.274+tlrc'[Sadness#0_Coef]' \
275 Hi Ang -0.529372376 -0.839235435 stats.275+tlrc'[Anger#0_Coef]' \
275 Hi Dis -0.529372376 -0.839235435 stats.275+tlrc'[Disgust#0_Coef]' \
275 Hi Fea -0.529372376 -0.839235435 stats.275+tlrc'[Fear#0_Coef]' \
275 Hi Hap -0.529372376 -0.839235435 stats.275+tlrc'[Happiness#0_Coef]' \
275 Hi Neu -0.529372376 -0.839235435 stats.275+tlrc'[Neutral#0_Coef]' \
275 Hi Sad -0.529372376 -0.839235435 stats.275+tlrc'[Sadness#0_Coef]' \
277 Lo Ang -0.910446326 0.768880368 stats.277+tlrc'[Anger#0_Coef]' \
277 Lo Dis -0.910446326 0.768880368 stats.277+tlrc'[Disgust#0_Coef]' \
277 Lo Fea -0.910446326 0.768880368 stats.277+tlrc'[Fear#0_Coef]' \
277 Lo Hap -0.910446326 0.768880368 stats.277+tlrc'[Happiness#0_Coef]' \
277 Lo Neu -0.910446326 0.768880368 stats.277+tlrc'[Neutral#0_Coef]' \
277 Lo Sad -0.910446326 0.768880368 stats.277+tlrc'[Sadness#0_Coef]' \
278 Lo Ang -0.317157542 -0.276394904 stats.278+tlrc'[Anger#0_Coef]' \
278 Lo Dis -0.317157542 -0.276394904 stats.278+tlrc'[Disgust#0_Coef]' \
278 Lo Fea -0.317157542 -0.276394904 stats.278+tlrc'[Fear#0_Coef]' \
278 Lo Hap -0.317157542 -0.276394904 stats.278+tlrc'[Happiness#0_Coef]' \
278 Lo Neu -0.317157542 -0.276394904 stats.278+tlrc'[Neutral#0_Coef]' \
278 Lo Sad -0.317157542 -0.276394904 stats.278+tlrc'[Sadness#0_Coef]' \
281 Hi Ang 1.355460453 -0.195989113 stats.281+tlrc'[Anger#0_Coef]' \
281 Hi Dis 1.355460453 -0.195989113 stats.281+tlrc'[Disgust#0_Coef]' \
281 Hi Fea 1.355460453 -0.195989113 stats.281+tlrc'[Fear#0_Coef]' \
281 Hi Hap 1.355460453 -0.195989113 stats.281+tlrc'[Happiness#0_Coef]' \
281 Hi Neu 1.355460453 -0.195989113 stats.281+tlrc'[Neutral#0_Coef]' \
281 Hi Sad 1.355460453 -0.195989113 stats.281+tlrc'[Sadness#0_Coef]' \
282 Hi Ang 0.271567482 -0.517612274 stats.282+tlrc'[Anger#0_Coef]' \
282 Hi Dis 0.271567482 -0.517612274 stats.282+tlrc'[Disgust#0_Coef]' \
282 Hi Fea 0.271567482 -0.517612274 stats.282+tlrc'[Fear#0_Coef]' \
282 Hi Hap 0.271567482 -0.517612274 stats.282+tlrc'[Happiness#0_Coef]' \
282 Hi Neu 0.271567482 -0.517612274 stats.282+tlrc'[Neutral#0_Coef]' \
282 Hi Sad 0.271567482 -0.517612274 stats.282+tlrc'[Sadness#0_Coef]' \
284 Lo Ang 1.247071156 -0.678423854 stats.284+tlrc'[Anger#0_Coef]' \
284 Lo Dis 1.247071156 -0.678423854 stats.284+tlrc'[Disgust#0_Coef]' \
284 Lo Fea 1.247071156 -0.678423854 stats.284+tlrc'[Fear#0_Coef]' \
284 Lo Hap 1.247071156 -0.678423854 stats.284+tlrc'[Happiness#0_Coef]' \
284 Lo Neu 1.247071156 -0.678423854 stats.284+tlrc'[Neutral#0_Coef]' \
284 Lo Sad 1.247071156 -0.678423854 stats.284+tlrc'[Sadness#0_Coef]' \
And here is the output I get (error bolded in red):
Loading required package: afex
Loading required package: coin
Loading required package: survival
Loading required package: splines
Loading required package: mvtnorm
Loading required package: modeltools
Loading required package: stats4
Loading required package: car
Loading required package: MASS
Loading required package: nnet
Loading required package: lme4
Loading required package: Matrix
Loading required package: lattice
Attaching package: 'lme4'
The following object is masked from 'package:modeltools':
refit
The following object is masked from 'package:stats':
AIC, BIC
Loading required package: pbkrtest
Loading required package: parallel
Loading required package: reshape2
Loading required package: stringr
Setting contrasts to effects coding: options(contrasts=c('contr.sum', 'contr.poly'))
Loading required package: phia
Warning message:
In if (is.na(lop$wsVars)) ModelForm <- as.formula(paste("Beta ~", :
the condition has length > 1 and only the first element will be used
++++++++++++++++++++++++++++++++++++++++++++++++++++
***** Summary information of data structure *****
48 subjects : 104 110 113 114 117 121 122 123 126 127 130 135 139 140 143 145 146 150 213 218 222 225 227 234 238 241 242 243 248 249 250 251 254 256 257 258 261 264 270 271 272 274 275 277 278 281 282 284
288 response values
3 levels for factor Group : HC Hi Lo
6 levels for factor Emotion : Ang Dis Fea Hap Neu Sad
288 centered values for numeric variable Age : -0.7758154 -0.7758154 -0.7758154 -0.7758154 -0.7758154 -0.7758154 0.4837823 0.4837823 0.4837823 0.4837823 0.4837823 0.4837823 -1.56991 -1.56991 -1.56991 -1.56991 -1.56991 -1.56991 0.2567353 0.2567353 0.2567353 0.2567353 0.2567353 0.2567353 -0.1197749 -0.1197749 -0.1197749 -0.1197749 -0.1197749 -0.1197749 -0.6822583 -0.6822583 -0.6822583 -0.6822583 -0.6822583 -0.6822583 -1.025681 -1.025681 -1.025681 -1.025681 -1.025681 -1.025681 -1.144339 -1.144339 -1.144339 -1.144339 -1.144339 -1.144339 -0.9503792 -0.9503792 -0.9503792 -0.9503792 -0.9503792 -0.9503792 -0.4894395 -0.4894395 -0.4894395 -0.4894395 -0.4894395 -0.4894395 -0.366218 -0.366218 -0.366218 -0.366218 -0.366218 -0.366218 -1.624675 -1.624675 -1.624675 -1.624675 -1.624675 -1.624675 -1.167158 -1.167158 -1.167158 -1.167158 -1.167158 -1.167158 0.9104939 0.9104939 0.9104939 0.9104939 0.9104939 0.9104939 1.300695 1.300695 1.300695 1.300695 1.300695 1.300695 0.08787615 0.08787615 0.08787615 0.08787615 0.08787615 0.08787615 -0.4905804 -0.4905804 -0.4905804 -0.4905804 -0.4905804 -0.4905804 1.352038 1.352038 1.352038 1.352038 1.352038 1.352038 0.3057957 0.3057957 0.3057957 0.3057957 0.3057957 0.3057957 1.517474 1.517474 1.517474 1.517474 1.517474 1.517474 1.259621 1.259621 1.259621 1.259621 1.259621 1.259621 -1.516285 -1.516285 -1.516285 -1.516285 -1.516285 -1.516285 0.5317018 0.5317018 0.5317018 0.5317018 0.5317018 0.5317018 0.1015674 0.1015674 0.1015674 0.1015674 0.1015674 0.1015674 -0.2475602 -0.2475602 -0.2475602 -0.2475602 -0.2475602 -0.2475602 0.06962111 0.06962111 0.06962111 0.06962111 0.06962111 0.06962111 1.718279 1.718279 1.718279 1.718279 1.718279 1.718279 -1.624675 -1.624675 -1.624675 -1.624675 -1.624675 -1.624675 1.507205 1.507205 1.507205 1.507205 1.507205 1.507205 -0.5008489 -0.5008489 -0.5008489 -0.5008489 -0.5008489 -0.5008489 -0.4814529 -0.4814529 -0.4814529 -0.4814529 -0.4814529 -0.4814529 0.5111649 0.5111649 0.5111649 0.5111649 0.5111649 0.5111649 1.129554 1.129554 1.129554 1.129554 1.129554 1.129554 1.252776 1.252776 1.252776 1.252776 1.252776 1.252776 -1.608702 -1.608702 -1.608702 -1.608702 -1.608702 -1.608702 0.8329099 0.8329099 0.8329099 0.8329099 0.8329099 0.8329099 0.1038493 0.1038493 0.1038493 0.1038493 0.1038493 0.1038493 -0.7313188 -0.7313188 -0.7313188 -0.7313188 -0.7313188 -0.7313188 -0.7210503 -0.7210503 -0.7210503 -0.7210503 -0.7210503 -0.7210503 -0.9195738 -0.9195738 -0.9195738 -0.9195738 -0.9195738 -0.9195738 1.370293 1.370293 1.370293 1.370293 1.370293 1.370293 1.037138 1.037138 1.037138 1.037138 1.037138 1.037138 -0.5293724 -0.5293724 -0.5293724 -0.5293724 -0.5293724 -0.5293724 -0.9104463 -0.9104463 -0.9104463 -0.9104463 -0.9104463 -0.9104463 -0.3171575 -0.3171575 -0.3171575 -0.3171575 -0.3171575 -0.3171575 1.35546 1.35546 1.35546 1.35546 1.35546 1.35546 0.2715675 0.2715675 0.2715675 0.2715675 0.2715675 0.2715675 1.247071 1.247071 1.247071 1.247071 1.247071 1.247071
288 centered values for numeric variable IQ : 0.3668514 0.3668514 0.3668514 0.3668514 0.3668514 0.3668514 2.216185 2.216185 2.216185 2.216185 2.216185 2.216185 -1.000047 -1.000047 -1.000047 -1.000047 -1.000047 -1.000047 0.8492862 0.8492862 0.8492862 0.8492862 0.8492862 0.8492862 -0.2763949 -0.2763949 -0.2763949 -0.2763949 -0.2763949 -0.2763949 -1.160859 -1.160859 -1.160859 -1.160859 -1.160859 -1.160859 0.8492862 0.8492862 0.8492862 0.8492862 0.8492862 0.8492862 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 2.216185 2.216185 2.216185 2.216185 2.216185 2.216185 0.8492862 0.8492862 0.8492862 0.8492862 0.8492862 0.8492862 0.4472572 0.4472572 0.4472572 0.4472572 0.4472572 0.4472572 -0.3568007 -0.3568007 -0.3568007 -0.3568007 -0.3568007 -0.3568007 -0.8392354 -0.8392354 -0.8392354 -0.8392354 -0.8392354 -0.8392354 1.251315 1.251315 1.251315 1.251315 1.251315 1.251315 1.331721 1.331721 1.331721 1.331721 1.331721 1.331721 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 0.6884746 0.6884746 0.6884746 0.6884746 0.6884746 0.6884746 0.2864456 0.2864456 0.2864456 0.2864456 0.2864456 0.2864456 -1.643293 -1.643293 -1.643293 -1.643293 -1.643293 -1.643293 0.4472572 0.4472572 0.4472572 0.4472572
0.4472572 0.4472572 -1.080453 -1.080453 -1.080453 -1.080453 -1.080453 -1.080453 -1.32167 -1.32167 -1.32167 -1.32167 -1.32167 -1.32167 -1.080453 -1.080453 -1.080453 -1.080453 -1.080453 -1.080453 0.6080688 0.6080688 0.6080688 0.6080688 0.6080688 0.6080688 -0.1959891 -0.1959891 -0.1959891 -0.1959891 -0.1959891 -0.1959891 -1.402076 -1.402076 -1.402076 -1.402076 -1.402076 -1.402076 0.9296919 0.9296919 0.9296919 0.9296919 0.9296919 0.9296919 1.974967 1.974967 1.974967 1.974967 1.974967 1.974967 -0.7588296 -0.7588296 -0.7588296 -0.7588296 -0.7588296 -0.7588296 -0.1959891 -0.1959891 -0.1959891 -0.1959891 -0.1959891 -0.1959891 0.125634 0.125634 0.125634 0.125634 0.125634 0.125634 -0.6784239 -0.6784239 -0.6784239 -0.6784239 -0.6784239 -0.6784239 -0.4372065 -0.4372065 -0.4372065 -0.4372065 -0.4372065 -0.4372065 -0.03517753 -0.03517753 -0.03517753 -0.03517753 -0.03517753 -0.03517753 -1.32167 -1.32167 -1.32167 -1.32167 -1.32167 -1.32167 -1.32167 -1.32167 -1.32167 -1.32167 -1.32167 -1.32167 0.6080688 0.6080688 0.6080688 0.6080688 0.6080688 0.6080688 1.251315 1.251315 1.251315 1.251315 1.251315 1.251315 -1.080453 -1.080453 -1.080453 -1.080453 -1.080453 -1.080453 -0.5176123 -0.5176123 -0.5176123 -0.5176123 -0.5176123 -0.5176123 -1.160859 -1.160859 -1.160859 -1.160859 -1.160859 -1.160859 -0.8392354 -0.8392354 -0.8392354 -0.8392354 -0.8392354 -0.8392354 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 0.7688804 -0.2763949 -0.2763949 -0.2763949 -0.2763949 -0.2763949 -0.2763949 -0.1959891 -0.1959891 -0.1959891 -0.1959891 -0.1959891 -0.1959891 -0.5176123 -0.5176123 -0.5176123 -0.5176123 -0.5176123 -0.5176123 -0.6784239 -0.6784239 -0.6784239 -0.6784239 -0.6784239 -0.6784239
18 post hoc tests
Tabulation of subjects against all categorical variables
~~~~~~~~~~~~~~
Subj vs Group:
HC Hi Lo
104 6 0 0
110 6 0 0
113 6 0 0
114 6 0 0
117 6 0 0
121 6 0 0
122 6 0 0
123 6 0 0
126 6 0 0
127 6 0 0
130 6 0 0
135 6 0 0
139 6 0 0
140 6 0 0
143 6 0 0
145 6 0 0
146 6 0 0
150 6 0 0
213 0 0 6
218 0 0 6
222 0 0 6
225 0 6 0
227 0 0 6
234 0 6 0
238 0 0 6
241 0 6 0
242 0 6 0
243 0 0 6
248 0 0 6
249 0 6 0
250 0 0 6
251 0 6 0
254 0 0 6
256 0 6 0
257 0 0 6
258 0 6 0
261 0 6 0
264 0 6 0
270 0 0 6
271 0 6 0
272 0 6 0
274 0 0 6
275 0 6 0
277 0 0 6
278 0 0 6
281 0 6 0
282 0 6 0
284 0 0 6
~~~~~~~~~~~~~~
Subj vs Emotion:
Ang Dis Fea Hap Neu Sad
104 1 1 1 1 1 1
110 1 1 1 1 1 1
113 1 1 1 1 1 1
114 1 1 1 1 1 1
117 1 1 1 1 1 1
121 1 1 1 1 1 1
122 1 1 1 1 1 1
123 1 1 1 1 1 1
126 1 1 1 1 1 1
127 1 1 1 1 1 1
130 1 1 1 1 1 1
135 1 1 1 1 1 1
139 1 1 1 1 1 1
140 1 1 1 1 1 1
143 1 1 1 1 1 1
145 1 1 1 1 1 1
146 1 1 1 1 1 1
150 1 1 1 1 1 1
213 1 1 1 1 1 1
218 1 1 1 1 1 1
222 1 1 1 1 1 1
225 1 1 1 1 1 1
227 1 1 1 1 1 1
234 1 1 1 1 1 1
238 1 1 1 1 1 1
241 1 1 1 1 1 1
242 1 1 1 1 1 1
243 1 1 1 1 1 1
248 1 1 1 1 1 1
249 1 1 1 1 1 1
250 1 1 1 1 1 1
251 1 1 1 1 1 1
254 1 1 1 1 1 1
256 1 1 1 1 1 1
257 1 1 1 1 1 1
258 1 1 1 1 1 1
261 1 1 1 1 1 1
264 1 1 1 1 1 1
270 1 1 1 1 1 1
271 1 1 1 1 1 1
272 1 1 1 1 1 1
274 1 1 1 1 1 1
275 1 1 1 1 1 1
277 1 1 1 1 1 1
278 1 1 1 1 1 1
281 1 1 1 1 1 1
282 1 1 1 1 1 1
284 1 1 1 1 1 1
***** End of data structure information *****
++++++++++++++++++++++++++++++++++++++++++++++++++++
Reading input files now...
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.
[1] "Great, test run passed at voxel (18, 32, 25)!"
Error in rep(0, NoBrick) : invalid 'times' argument
Execution halted
Thank you so much for your help!
| Subject | Author | Posted |
|---|---|---|
|
emc62 | October 11, 2014 03:43PM |
|
gang | October 12, 2014 04:38PM |
|
emc62 | October 12, 2014 06:57PM |
|
gang | October 12, 2014 07:51PM |
