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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
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
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
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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 https://secure-web.cisco.com/1NHVxBIRnha6EjEdEho81-VE9d-vjJ6ivzt10z28vhX9c94... 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:
External Email - Use CautionHi 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
Freesurfer mailing listFreesurfer@nmr.mgh.harvard.eduhttps://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://secure-web.cisco.com/12U-W_RSiRIJWjQDCBYfqvGXFwFXZQgpm04lVl3v5K0t8IY... The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Mass General Brigham Compliance HelpLine at http://secure-web.cisco.com/1YGeBpazeZXSLfsCEO4_vE11nUNbtdYgN2Tpx1anls1heh4x... . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail. Please note that this e-mail is not secure (encrypted). If you do not wish to continue communication over unencrypted e-mail, please notify the sender of this message immediately. Continuing to send or respond to e-mail after receiving this message means you understand and accept this risk and wish to continue to communicate over unencrypted e-mail.
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 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: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 _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://secure-web.cisco.com/12U-W_RSiRIJWjQDCBYfqvGXFwFXZQgpm04lVl3v5K0t8IYtpEx5cD1xcltIygwIKmo05cI6l-2nfk9uxFgBdWGoedjfSO3t3_Hbh1NQQDj4gxzchE8QF5shV5fOP8ukCqp6pHmkq140ase4PWm8-1key4YN4H_tSk9Wh09gbrQK4nERYcXWQYw8fkpCXcQ3U5MXxTyPgoKWJY68te_B_XbFVhWWhzaz65RTcy1JyJlfZLY6Nyv0LACWWHmWU4NzLmBeHSMh8lssnATJq77P16Tl72f8QkK6_lB_cDhEWqJocd9RxUL3qeDAwtK9UbRCY/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer>_______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://secure-web.cisco.com/12U-W_RSiRIJWjQDCBYfqvGXFwFXZQgpm04lVl3v5K0t8IYtpEx5cD1xcltIygwIKmo05cI6l-2nfk9uxFgBdWGoedjfSO3t3_Hbh1NQQDj4gxzchE8QF5shV5fOP8ukCqp6pHmkq140ase4PWm8-1key4YN4H_tSk9Wh09gbrQK4nERYcXWQYw8fkpCXcQ3U5MXxTyPgoKWJY68te_B_XbFVhWWhzaz65RTcy1JyJlfZLY6Nyv0LACWWHmWU4NzLmBeHSMh8lssnATJq77P16Tl72f8QkK6_lB_cDhEWqJocd9RxUL3qeDAwtK9UbRCY/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer> The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Mass General Brigham Compliance HelpLine at *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* http://www.massgeneralbrigham.org/complianceline <http://secure-web.cisco.com/1YGeBpazeZXSLfsCEO4_vE11nUNbtdYgN2Tpx1anls1heh4xx3r9SAPXdptyAb3NQFEWW_wDyFNgmJO__d_VUJ4ZoDc6uOlHryomgspKnDLXlJUxYcwmHguKWwgYZamww28y60Aeq0gJLeaCWbwoahgMRrH8-z5ta2ABmTVYMWcGgKuwlAOzE5hf9artWSY3R9z36qyZBlqSphIF6fAWzYMk0dO_RcNVOZUxOpurwkn6dbDtArOd-sJXNda8_EWB9OYHZ2g5P_tcrpodvlf-MKZGF3VZ3bJH8C4OO5j6Di85pQ4alax7KCxKTYsi_o7YJ/http%3A%2F%2Fwww.massgeneralbrigham.org%2Fcomplianceline> . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail. Please note that this e-mail is not secure (encrypted). If you do not wish to continue communication over unencrypted e-mail, please notify the sender of this message immediately. Continuing to send or respond to e-mail after receiving this message means you understand and accept this risk and wish to continue to communicate over unencrypted e-mail.--
Ph.D. candidate Icahn School of Medicine at Mount Sinai
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
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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:
External Email - Use CautionHi 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://secure-web.cisco.com/1wooLw3zkqSmNDmxJNAdL3vHs5YqXnNqVwhC-ElE-BfUuDb... 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 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:
External Email - Use CautionHi 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
Freesurfer mailing listFreesurfer@nmr.mgh.harvard.edu*MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://secure-web.cisco.com/1riDKYS-FGseRCaBPDFbfM10KeLQ0kNrmsbKoEpOzznltcG... https://secure-web.cisco.com/12U-W_RSiRIJWjQDCBYfqvGXFwFXZQgpm04lVl3v5K0t8IYtpEx5cD1xcltIygwIKmo05cI6l-2nfk9uxFgBdWGoedjfSO3t3_Hbh1NQQDj4gxzchE8QF5shV5fOP8ukCqp6pHmkq140ase4PWm8-1key4YN4H_tSk9Wh09gbrQK4nERYcXWQYw8fkpCXcQ3U5MXxTyPgoKWJY68te_B_XbFVhWWhzaz65RTcy1JyJlfZLY6Nyv0LACWWHmWU4NzLmBeHSMh8lssnATJq77P16Tl72f8QkK6_lB_cDhEWqJocd9RxUL3qeDAwtK9UbRCY/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer
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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)?
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 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:External Email - Use Caution 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 <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: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 _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://secure-web.cisco.com/12U-W_RSiRIJWjQDCBYfqvGXFwFXZQgpm04lVl3v5K0t8IYtpEx5cD1xcltIygwIKmo05cI6l-2nfk9uxFgBdWGoedjfSO3t3_Hbh1NQQDj4gxzchE8QF5shV5fOP8ukCqp6pHmkq140ase4PWm8-1key4YN4H_tSk9Wh09gbrQK4nERYcXWQYw8fkpCXcQ3U5MXxTyPgoKWJY68te_B_XbFVhWWhzaz65RTcy1JyJlfZLY6Nyv0LACWWHmWU4NzLmBeHSMh8lssnATJq77P16Tl72f8QkK6_lB_cDhEWqJocd9RxUL3qeDAwtK9UbRCY/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer>_______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://secure-web.cisco.com/12U-W_RSiRIJWjQDCBYfqvGXFwFXZQgpm04lVl3v5K0t8IYtpEx5cD1xcltIygwIKmo05cI6l-2nfk9uxFgBdWGoedjfSO3t3_Hbh1NQQDj4gxzchE8QF5shV5fOP8ukCqp6pHmkq140ase4PWm8-1key4YN4H_tSk9Wh09gbrQK4nERYcXWQYw8fkpCXcQ3U5MXxTyPgoKWJY68te_B_XbFVhWWhzaz65RTcy1JyJlfZLY6Nyv0LACWWHmWU4NzLmBeHSMh8lssnATJq77P16Tl72f8QkK6_lB_cDhEWqJocd9RxUL3qeDAwtK9UbRCY/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer> The information in this e-mail is intended only for the person to whom it is addressed. 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Continuing to send or respond to e-mail after receiving this message means you understand and accept this risk and wish to continue to communicate over unencrypted e-mail. -- Ph.D. candidate Icahn School of Medicine at Mount Sinai _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://secure-web.cisco.com/1riDKYS-FGseRCaBPDFbfM10KeLQ0kNrmsbKoEpOzznltcGj9v-5n_mtcH4iuPpyQdPnJpDqv2oznuvHcCG0AoePAHtplLU3aqtaLbpH7r9l72LUZMShuoVRoexJpk22Z0KJ4UF-qkQIfw_bIfhHlkLc9H1-DLhctPeXE_toredYS7-4qs-W0QxiUq1kBtbAmLnJmze-ioLsfDBZDMhUGZSIqNcc_nJSQEFuPObCRfGVv7Y_ezTrjPIZOHsEOd76lP4BnUE2VlZRnW0o0mGf6V2ypN9V9CJ1uEZL6XvCbunFWu-JldhQmq1KCGRlJsi29A0RAnLJ_ZCLu878-nqCy4A/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer>_______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://secure-web.cisco.com/1riDKYS-FGseRCaBPDFbfM10KeLQ0kNrmsbKoEpOzznltcGj9v-5n_mtcH4iuPpyQdPnJpDqv2oznuvHcCG0AoePAHtplLU3aqtaLbpH7r9l72LUZMShuoVRoexJpk22Z0KJ4UF-qkQIfw_bIfhHlkLc9H1-DLhctPeXE_toredYS7-4qs-W0QxiUq1kBtbAmLnJmze-ioLsfDBZDMhUGZSIqNcc_nJSQEFuPObCRfGVv7Y_ezTrjPIZOHsEOd76lP4BnUE2VlZRnW0o0mGf6V2ypN9V9CJ1uEZL6XvCbunFWu-JldhQmq1KCGRlJsi29A0RAnLJ_ZCLu878-nqCy4A/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer> The information in this e-mail is intended only for the person to whom it is addressed. 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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:
External Email - Use CautionHi 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)?
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:
External Email - Use CautionHi 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://secure-web.cisco.com/1NEzix1p8cerzV2CscGJeOM5AxEOJi5zLORLiOeZ2wx-E6_... 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 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:
External Email - Use CautionHi 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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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 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: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 <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:External Email - Use Caution 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 <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: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 _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://secure-web.cisco.com/12U-W_RSiRIJWjQDCBYfqvGXFwFXZQgpm04lVl3v5K0t8IYtpEx5cD1xcltIygwIKmo05cI6l-2nfk9uxFgBdWGoedjfSO3t3_Hbh1NQQDj4gxzchE8QF5shV5fOP8ukCqp6pHmkq140ase4PWm8-1key4YN4H_tSk9Wh09gbrQK4nERYcXWQYw8fkpCXcQ3U5MXxTyPgoKWJY68te_B_XbFVhWWhzaz65RTcy1JyJlfZLY6Nyv0LACWWHmWU4NzLmBeHSMh8lssnATJq77P16Tl72f8QkK6_lB_cDhEWqJocd9RxUL3qeDAwtK9UbRCY/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer>_______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://secure-web.cisco.com/12U-W_RSiRIJWjQDCBYfqvGXFwFXZQgpm04lVl3v5K0t8IYtpEx5cD1xcltIygwIKmo05cI6l-2nfk9uxFgBdWGoedjfSO3t3_Hbh1NQQDj4gxzchE8QF5shV5fOP8ukCqp6pHmkq140ase4PWm8-1key4YN4H_tSk9Wh09gbrQK4nERYcXWQYw8fkpCXcQ3U5MXxTyPgoKWJY68te_B_XbFVhWWhzaz65RTcy1JyJlfZLY6Nyv0LACWWHmWU4NzLmBeHSMh8lssnATJq77P16Tl72f8QkK6_lB_cDhEWqJocd9RxUL3qeDAwtK9UbRCY/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer> The information in this e-mail is intended only for the person to whom it is addressed. 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External Email - Use Caution
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:
External Email - Use CautionHi 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:
External Email - Use CautionHi 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)?
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:
External Email - Use CautionHi 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://secure-web.cisco.com/1YCu4DNGxoLi5zalwi9XfWKMLYA4OOBRYPZEzRdP4RJSWFg... 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 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:
External Email - Use CautionHi 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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Ph.D. candidate Icahn School of Medicine at Mount Sinai
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Ph.D. candidate Icahn School of Medicine at Mount Sinai
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For DODS you would add 16 zeros (8 classes times 2 continuous variables)
On 11/11/2021 4:00 PM, Zeng, Qi wrote:
External Email - Use Caution
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_bleTIV InputSub001_baseControlFemaleWhite851350519.71 InputSub002_baseControlFemaleWhite81.31558515.86
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: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 <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: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 <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:External Email - Use Caution 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 <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: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 _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://secure-web.cisco.com/12U-W_RSiRIJWjQDCBYfqvGXFwFXZQgpm04lVl3v5K0t8IYtpEx5cD1xcltIygwIKmo05cI6l-2nfk9uxFgBdWGoedjfSO3t3_Hbh1NQQDj4gxzchE8QF5shV5fOP8ukCqp6pHmkq140ase4PWm8-1key4YN4H_tSk9Wh09gbrQK4nERYcXWQYw8fkpCXcQ3U5MXxTyPgoKWJY68te_B_XbFVhWWhzaz65RTcy1JyJlfZLY6Nyv0LACWWHmWU4NzLmBeHSMh8lssnATJq77P16Tl72f8QkK6_lB_cDhEWqJocd9RxUL3qeDAwtK9UbRCY/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer>_______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer <https://secure-web.cisco.com/12U-W_RSiRIJWjQDCBYfqvGXFwFXZQgpm04lVl3v5K0t8IYtpEx5cD1xcltIygwIKmo05cI6l-2nfk9uxFgBdWGoedjfSO3t3_Hbh1NQQDj4gxzchE8QF5shV5fOP8ukCqp6pHmkq140ase4PWm8-1key4YN4H_tSk9Wh09gbrQK4nERYcXWQYw8fkpCXcQ3U5MXxTyPgoKWJY68te_B_XbFVhWWhzaz65RTcy1JyJlfZLY6Nyv0LACWWHmWU4NzLmBeHSMh8lssnATJq77P16Tl72f8QkK6_lB_cDhEWqJocd9RxUL3qeDAwtK9UbRCY/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer> The information in this e-mail is intended only for the person to whom it is addressed. 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External Email - Use Caution
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:
External Email - Use CautionSo 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:
External Email - Use CautionHi 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:
External Email - Use CautionHi 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)?
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:
External Email - Use CautionHi 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://secure-web.cisco.com/1yZjSb88ByC6LpqTpxoDlPxIRkwZ4AgKf-ntdFS_UoHQnXx... 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 < 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:
External Email - Use CautionHi 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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Ph.D. candidate Icahn School of Medicine at Mount Sinai
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Ph.D. candidate Icahn School of Medicine at Mount Sinai
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External Email - Use Caution
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:
External Email - Use CautionSo 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:
External Email - Use CautionHi 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:
External Email - Use CautionHi 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)?
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:
External Email - Use CautionHi 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://secure-web.cisco.com/1c_MdQ5rEp7srI_kPpk4efkiqV9_OF913y30NhIzAsUQpPJ... 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 < 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:
External Email - Use CautionHi 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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Ph.D. candidate Icahn School of Medicine at Mount Sinai
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Ph.D. candidate Icahn School of Medicine at Mount Sinai
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Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://secure-web.cisco.com/1WD9qkCTOBwTuKeut2tReo9orTPCzvJFaGvuPulpBQUZqjw... https://secure-web.cisco.com/1DlZ2fTOF2AmzPXQrBuHInam5F1ZSU5iCJjKeJJqWAASMhfJ8i189eI_CZ7gpxiK9dX7CRMmSB4f-Zx7Im7ODFwlJoj2233ZFP1qJxD4VXSfJyrulgaWnSgifBjf0Psmnc33uWViiYCmCpRBUhWJG1LRYZ77cEqTBKU3aWhcMeYq8V7--0ZjTZ9IsonGh7ZLsjBqXj0ovIWso1L853fVjTdphN6Onhv4NagUX45XhqU4957lqTWsgHcMB1xQhazgsAxjOHe2VujiJJR5xYdOY2TAxbvci75FfG7B1hl6vIr7BxmiWamDP_FnLSlCA1GGAtJrOgACL8pGZTMpTHAWItg/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Mass General Brigham Compliance HelpLine at *MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* http://secure-web.cisco.com/1Euk_1CCZjqIe90CE5bS2SjRd8Yd5ma7OwyINqVI3VyRLM62... http://secure-web.cisco.com/1-qjxHtsxsujfAJD78Q5f8o2Z_2grSqK7CGIEyXX1kcG0lM5l06jwYSp5S8eKA8HSSBV06Tlzy5tnybuvY6VDKAV3MTzcS2NCox67GmGepW59h5IXq1UvLq-HCBKg0-MAURQid2sgka7FhgPioBdIK32828K9UZNZEcDMT3aOXcC7jsTpE6Fhj___vPFdgCSrwXLUR14qQS15Q8Yx6k3pZg5xffs3FBipoVjwUnRuo-3zDgZ4bRU1kE7bC-nP3nbyEnJTU6nZaerOL8Dl0H9pFCuYutUjAmYqZiZUgGbdtuOmaK0AmfpKTKAtbndoWIk_p95FKHp1bXBqdeDH2Stc-Q/http%3A%2F%2Fwww.massgeneralbrigham.org%2Fcomplianceline . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail. Please note that this e-mail is not secure (encrypted). If you do not wish to continue communication over unencrypted e-mail, please notify the sender of this message immediately. Continuing to send or respond to e-mail after receiving this message means you understand and accept this risk and wish to continue to communicate over unencrypted e-mail.
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Ph.D. candidate Icahn School of Medicine at Mount Sinai
Freesurfer mailing listFreesurfer@nmr.mgh.harvard.edu*MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be* https://secure-web.cisco.com/1WD9qkCTOBwTuKeut2tReo9orTPCzvJFaGvuPulpBQUZqjw... https://secure-web.cisco.com/1riQwbV7SivOWmdRI3o8g5unLSLoMUwk1_Fe2aJGWmlht2oA0tkB_pfg7aJpN2VZ4rdRk9wchQhy7dHG840cTDmQyLjxhOeNa8jDlUwt4bjgokARlChK0GQhA8Y58s0frdc4RK3WP8MTsDM2NIQ6KZQixcFPOmCBh2FkGCVF4QxgS7b4SEPFHSHMIqTCPorlGC6izGZs4cwDb5HHQq1FgLwsN0_Mgj9u_oPnftJrsLBP8Tb-iLVQiAsO08g7FpP4n4jRj_j4hyu73-rC21XlibZmnyhNuZXD4RX0RSD5rOWZflVfrl3_fNpXgcdTPfTyQ/https%3A%2F%2Fmail.nmr.mgh.harvard.edu%2Fmailman%2Flistinfo%2Ffreesurfer
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Ph.D. candidate Icahn School of Medicine at Mount Sinai
Freesurfer mailing listFreesurfer@nmr.mgh.harvard.eduhttps://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://secure-web.cisco.com/1WD9qkCTOBwTuKeut2tReo9orTPCzvJFaGvuPulpBQUZqjw... The information in this e-mail is intended only for the person to whom it is addressed. If you believe this e-mail was sent to you in error and the e-mail contains patient information, please contact the Mass General Brigham Compliance HelpLine at http://secure-web.cisco.com/1Euk_1CCZjqIe90CE5bS2SjRd8Yd5ma7OwyINqVI3VyRLM62... . If the e-mail was sent to you in error but does not contain patient information, please contact the sender and properly dispose of the e-mail. Please note that this e-mail is not secure (encrypted). If you do not wish to continue communication over unencrypted e-mail, please notify the sender of this message immediately. Continuing to send or respond to e-mail after receiving this message means you understand and accept this risk and wish to continue to communicate over unencrypted e-mail.
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Ph.D. candidate Icahn School of Medicine at Mount Sinai
freesurfer@nmr.mgh.harvard.edu
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Douglas N. Greve -
Zeng, Qi