For the DOSS case, yes.
On 11/11/2021 3:23 PM, Zeng, Qi wrote:
External Email - Use Caution
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 AgeeTIV
InputSub001_base Control Female White 85 1350519.71
InputSub002_base Control Female White 81.3 1558515.86
Best,
Qi
On Thu, Nov 11, 2021 at 3:06 PM Douglas N. Greve
<dgr...@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:
External Email - Use Caution
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 AgeGenderRaceeTIV
InputSub001_baseControl85111350519.71
InputSub002_baseControl81.3 011558515.86
InputSub003_baseControl81.3 001558515.86
or 2)
Variables AgeGenderRaceeTIV
InputSub001_baseControl85"Female""White"1350519.71
InputSub002_baseControl81.3 "Male""White"1558515.86
InputSub003_baseControl72.7 "Male""White"1187649.47
or 3)
Variables AgeGenderRaceeTIV
InputSub001_base"Control"85"Female""White"1350519.71
InputSub002_base"Control"81.3 "Male""White"1558515.86
InputSub003_base"Control"72.7 "Male""White"1187649.47
Best,
Zeng
On Wed, Nov 10, 2021 at 6:38 PM Douglas N. Greve
<dgr...@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.
See *MailScanner has detected a possible fraud attempt
from "secure-web.cisco.com" claiming to be*
https://surfer.nmr.mgh.harvard.edu/fswiki/FsgdExamples
<https://secure-web.cisco.com/1NHVxBIRnha6EjEdEho81-VE9d-vjJ6ivzt10z28vhX9c94pCwosQpkLG4Hfu3nLYp7KMDne5wAk9mK45YIQJEZBe6UlteF2wwLohmZJzp070UjHvv6fqugRAkgBk0uNO3Fsgo5BzblW95J5iO5sXWwZLK-LGAZJJTBaU7mLTkO5L70JRSscCW3pdc-G5KchZMbVyeY65gGH4w5MMIYBSVHvX03spMjZ85XkHbkgYYmWXTFnzqUGhqGgHygP5sLeR7OWPKIzEb7X3pHi7POf0UyEHJAZpQLU9bgT2BnOcClt0kW4mll1ODQDC2Y0U7-0f/https%3A%2F%2Fsurfer.nmr.mgh.harvard.edu%2Ffswiki%2FFsgdExamples>
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
<dgr...@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:
External Email - Use Caution
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 agegenderrace eTIV
Inputsub001_baseControl85FemaleWhite1350519
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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