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For example, if my Class CaseFemaleNonWhite has no subject, should I cancel the contrast between CaseFemaleNonWhite vs ControlFemaleNonWhite? However, that will leave my ControlFemaleNonWhite subjects unrecognized? Or it is better to cancel the race discrete as covariates?

Best, 
Zeng


On Thu, Nov 11, 2021 at 4:07 PM Zeng, Qi <qi.zeng@icahn.mssm.edu> wrote:
got you, thanks

Best, 
Zeng



On Thu, Nov 11, 2021 at 4:06 PM Douglas N. Greve <dgreve@mgh.harvard.edu> wrote:
For DODS you would add 16 zeros (8 classes times 2 continuous variables)

On 11/11/2021 4:00 PM, Zeng, Qi wrote:

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So for the DODS case, is "1 -1 1 -1 1 -1 1 -1 0 0 0 0" for the following FSGD:

GroupDescriptorFile 1
Title MyStudy
Class CaseMaleWhite
Class ControlMaleWhite
Class CaseMaleNonWhite
Class ControlMaleNonWhite
Class CaseFemaleWhite
Class ControlFemaleWhite
Class CaseFemaleNonWhite
Class ControlFemaleNonWhite
Variables age_bl eTIV
Input Sub001_base ControlFemaleWhite 85 1350519.71
Input Sub002_base ControlFemaleWhite 81.3 1558515.86

Best, 
Qi

On Thu, Nov 11, 2021 at 3:28 PM Douglas N. Greve <dgreve@mgh.harvard.edu> wrote:
For the DOSS case, yes.

On 11/11/2021 3:23 PM, Zeng, Qi wrote:

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Hi  Douglas, 

If to set up the FSGD as below, is my design matrix for case and control comparison as "1 -1 1 -1 1 -1 1 -1 0 0"  ?

GroupDescriptorFile 1
Title MyStudy
Class CaseMaleWhite
Class ControlMaleWhite
Class CaseMaleNonWhite
Class ControlMaleNonWhite
Class CaseFemaleWhite
Class ControlFemaleWhite
Class CaseFemaleNonWhite
Class ControlFemaleNonWhite
Variables    Age eTIV
Input Sub001_base  Control   Female  White   85     1350519.71
Input Sub002_base  Control   Female  White   81.3   1558515.86

Best, 
Qi

On Thu, Nov 11, 2021 at 3:06 PM Douglas N. Greve <dgreve@mgh.harvard.edu> wrote:
I would advice setting up the FSGD files with 8 classes based on your 3 discrete, 2-level variables, eg, MaleControlWhite then use two continuous variables Age and eTIV.
You should definitely normalize the eTIV (and probably age too)

On 11/10/2021 7:07 PM, Zeng, Qi wrote:

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Hi Douglas, 

Just to be clear, should I recode discrete variables as numeric as sample1) or change discrete variables into strings 2) or even change the comparison groups into strings too 3)?
1) 
Variables Age Gender Race eTIV
Input Sub001_base Control 85 1 1 1350519.71
Input Sub002_base Control 81.3   0 1 1558515.86
Input Sub003_base Control 81.3   0 0 1558515.86

or 2)
Variables Age Gender Race eTIV
Input Sub001_base Control 85 "Female" "White" 1350519.71
Input Sub002_base Control 81.3  "Male" "White" 1558515.86
Input Sub003_base Control 72.7  "Male" "White" 1187649.47

or 3)
Variables  Age Gender Race eTIV
Input Sub001_base "Control" 85 "Female" "White" 1350519.71
Input Sub002_base "Control" 81.3  "Male" "White" 1558515.86
Input Sub003_base "Control" 72.7  "Male" "White" 1187649.47


Best, 
Zeng



On Wed, Nov 10, 2021 at 6:38 PM Douglas N. Greve <dgreve@mgh.harvard.edu> wrote:
Did you read the error message? It says:
Variable 2 has character string Female
Variables should be continuous numbers
You have listed Gender and Race as strings, they have to be numbers (eg, 1, 2)
You probably want to have these be discrete variables instead of continuous

On 11/10/2021 6:20 PM, Zeng, Qi wrote:

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Hi Douglas, 

Here is the command line: 
mri_glmfit \
  --y rh.thickness-rate.MyStudy.10.mgh \
  --fsgd FSGD/MyStudy.fsgd dods\
  --C Contrasts/Case-Control_age_gender_race_etiv.mtx\
  --surf fsaverage rh \
  --cortex \
  --glmdir rh.thickness-rate.MyStudy.10.mgh_age_gender_race_etiv.glmdir \
  --eres-save

Also error message in terminal:
gdfRead(): reading FSGD/MyStudy.fsgd
WARNING: variable 1 is "Gender" which is often a discrete factor
  The proper way to handle discrete factors is to create classes.
ERROR: gdfReadV1: Format Error: Input line 1, subjid = sub001_base
 Variable 2 has character string Female
 Variables should be continuous numbers
FSGDF Format Error: file = FSGD/MyStudy.fsgd, tag=Input

Also attached FSGD file below. 
Thank you so much for the help!

Best, 
Zeng




On Wed, Nov 10, 2021 at 5:41 PM Douglas N. Greve <dgreve@mgh.harvard.edu> wrote:
please send your command line and full terminal output as well as the fsgd file

On 11/10/2021 5:12 PM, Zeng, Qi wrote:

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Hi Freesurfer experts, 

Here, I want to design a simple group comparison (two levels: Case vs. Control) and also count for 4 covariates (two continuous and two categoricals). However, the GLM model cannot recognize my discrete variables. What do you suggest to change?
>> FSDG file:
GroupDescriptorFile 1
Title MyStudy
Class Control
Class Case
Variables age gender race  eTIV
Input sub001_base Control 85 Female White 1350519
Contrast:
>> Design matrix for Case-Control and regress out the effect of age, gender, race, and eTIV. 
-1 1 0 0 0 0 0 0 0 0 

Best, 
Zeng




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