Dear all, I want to design a group t-test analysis and correlation analysis for pial thickness. I have read the PPT of freesurfer.groupanalysis, and I wrote a specific design matrix and contrast for my data. However it is the first time that I design matrix in fsgdf by freesurfer. I didnot confirm whether I wrote is correct. I need someone to help me review it. I have two groups, four groups were classified as sex.(Is this necessary or correct?) Here is my design matrix in fsgdf for 2 group t-test: GroupDescriptorFile 1 Title lh_ttest Class con_male Class con_female Class pat_male Class pat_female Variables Age edu Input subjid1 con_male 19 10 Input subjid2 con_male 20 20 Input subjid3 con_male 20 20 Input subjid4 con_male 19 10 Input subjid5 con_female 20 20 Input subjid6 con_female 20 20 Input subjid7 con_female 19 10 Input subjid8 pat_male 20 20 Input subjid9 pat_male 20 20 Input subjid10 pat_male 19 10 Input subjid11 pat_female 20 20 Input subjid12 pat_female 20 20 DefaultVariable Age In this section, I just want to compare the patient group(class 3 and 4) and control group(class 1 and 2) in thickness controling the age and education by ANCOVA. Does this fsgdf implement ANCOVA? Here is my contrast for this: 0.5 0.5 -0.5 -0.5 0 0 0 0 0 0 0 0 Here is my design matrix in fsgdf for partial regression: GroupDescriptorFile 1 Title lh_regression Class con_male Class con_female Class pat_male Class pat_female Variables Age edu score1 score2 Input subjid1 con_male 19 10 20 30 Input subjid2 con_male 20 20 20 30 Input subjid3 con_male 20 20 20 30 Input subjid4 con_male 19 10 20 30 Input subjid5 con_female 20 20 20 30 Input subjid6 con_female 20 20 20 30 Input subjid7 con_female 19 10 20 30 Input subjid8 pat_male 20 20 20 30 Input subjid9 pat_male 20 20 20 30 Input subjid10 pat_male 19 10 20 30 Input subjid11 pat_female 20 20 20 30 Input subjid12 pat_female 20 20 20 30 DefaultVariable score1 In this section, I want to implement partial regression analysis(i.e. score1 and score2) by controling the age,edu and sex. Here is my contrast for score1: 0 0 0 0 0 0 0 0 0 0 0 0 0.25 0.25 0.25 0.25 0 0 0 0 Here is my contrast for score2: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.25 0.25 0.25 0.25
Any reply will be highly appreciated. Thanks. All the best.
2013-12-17
Rujing Zha
That looks correct. The contrasts for the 2nd example will test whether the score is equal to 0 or not (and not an interaction between diagnosis and score). It is not wrong, but I just wanted to make sure you know what you are testing.
doug
On 12/17/2013 01:50 AM, Rujing Zha wrote:
Dear all, I want to design a group t-test analysis and correlation analysis for pial thickness. I have read the PPT of freesurfer.groupanalysis, and I wrote a specific design matrix and contrast for my data. However it is the first time that I design matrix in fsgdf by freesurfer. I didnot confirm whether I wrote is correct. I need someone to help me review it. I have two groups, four groups were classified as sex.(Is this necessary or correct?) Here is my design matrix in fsgdf for 2 group t-test: GroupDescriptorFile 1 Title lh_ttest Class con_male Class con_female Class pat_male Class pat_female Variables Age edu Input subjid1 con_male 19 10 Input subjid2 con_male 20 20 Input subjid3 con_male 20 20 Input subjid4 con_male 19 10 Input subjid5 con_female 20 20 Input subjid6 con_female 20 20 Input subjid7 con_female 19 10 Input subjid8 pat_male 20 20 Input subjid9 pat_male 20 20 Input subjid10 pat_male 19 10 Input subjid11 pat_female 20 20 Input subjid12 pat_female 20 20 DefaultVariable Age In this section, I just want to compare the patient group(class 3 and 4) and control group(class 1 and 2) in thickness controling the age and education by ANCOVA. Does this fsgdf implement ANCOVA? Here is my contrast for this: 0.5 0.5 -0.5 -0.5 0 0 0 0 0 0 0 0 Here is my design matrix in fsgdf for partial regression: GroupDescriptorFile 1 Title lh_regression Class con_male Class con_female Class pat_male Class pat_female Variables Age edu score1 score2 Input subjid1 con_male 19 10 20 30 Input subjid2 con_male 20 20 20 30 Input subjid3 con_male 20 20 20 30 Input subjid4 con_male 19 10 20 30 Input subjid5 con_female 20 20 20 30 Input subjid6 con_female 20 20 20 30 Input subjid7 con_female 19 10 20 30 Input subjid8 pat_male 20 20 20 30 Input subjid9 pat_male 20 20 20 30 Input subjid10 pat_male 19 10 20 30 Input subjid11 pat_female 20 20 20 30 Input subjid12 pat_female 20 20 20 30 DefaultVariable score1 In this section, I want to implement partial regression analysis(i.e. score1 and score2) by controling the age,edu and sex. Here is my contrast for score1: 0 0 0 0 0 0 0 0 0 0 0 0 0.25 0.25 0.25 0.25 0 0 0 0 Here is my contrast for score2: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.25 0.25 0.25 0.25 Any reply will be highly appreciated. Thanks. All the best. 2013-12-17
/Rujing Zha/
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Dear Doug, Thanks for your precious help. Considering the 2nd example, I just want to know whether some brain surface thickness correlate the score without subjects coming from control or patient group. I think my aim is the same as want you told me "test whether the score is equal to 0 or not". Am I right? Thanks. All the best.
2013-12-18
Rujing Zha
发件人：Douglas N Greve greve@nmr.mgh.harvard.edu 发送时间：2013-12-18 00:31 主题：Re: [Freesurfer] design matrix and contrast in fsgdf 收件人："freesurfer"freesurfer@nmr.mgh.harvard.edu 抄送：
That looks correct. The contrasts for the 2nd example will test whether the score is equal to 0 or not (and not an interaction between diagnosis and score). It is not wrong, but I just wanted to make sure you know what you are testing.
doug
On 12/17/2013 01:50 AM, Rujing Zha wrote:
Dear all, I want to design a group t-test analysis and correlation analysis for pial thickness. I have read the PPT of freesurfer.groupanalysis, and I wrote a specific design matrix and contrast for my data. However it is the first time that I design matrix in fsgdf by freesurfer. I didnot confirm whether I wrote is correct. I need someone to help me review it. I have two groups, four groups were classified as sex.(Is this necessary or correct?) Here is my design matrix in fsgdf for 2 group t-test: GroupDescriptorFile 1 Title lh_ttest Class con_male Class con_female Class pat_male Class pat_female Variables Age edu Input subjid1 con_male 19 10 Input subjid2 con_male 20 20 Input subjid3 con_male 20 20 Input subjid4 con_male 19 10 Input subjid5 con_female 20 20 Input subjid6 con_female 20 20 Input subjid7 con_female 19 10 Input subjid8 pat_male 20 20 Input subjid9 pat_male 20 20 Input subjid10 pat_male 19 10 Input subjid11 pat_female 20 20 Input subjid12 pat_female 20 20 DefaultVariable Age In this section, I just want to compare the patient group(class 3 and 4) and control group(class 1 and 2) in thickness controling the age and education by ANCOVA. Does this fsgdf implement ANCOVA? Here is my contrast for this: 0.5 0.5 -0.5 -0.5 0 0 0 0 0 0 0 0 Here is my design matrix in fsgdf for partial regression: GroupDescriptorFile 1 Title lh_regression Class con_male Class con_female Class pat_male Class pat_female Variables Age edu score1 score2 Input subjid1 con_male 19 10 20 30 Input subjid2 con_male 20 20 20 30 Input subjid3 con_male 20 20 20 30 Input subjid4 con_male 19 10 20 30 Input subjid5 con_female 20 20 20 30 Input subjid6 con_female 20 20 20 30 Input subjid7 con_female 19 10 20 30 Input subjid8 pat_male 20 20 20 30 Input subjid9 pat_male 20 20 20 30 Input subjid10 pat_male 19 10 20 30 Input subjid11 pat_female 20 20 20 30 Input subjid12 pat_female 20 20 20 30 DefaultVariable score1 In this section, I want to implement partial regression analysis(i.e. score1 and score2) by controling the age,edu and sex. Here is my contrast for score1: 0 0 0 0 0 0 0 0 0 0 0 0 0.25 0.25 0.25 0.25 0 0 0 0 Here is my contrast for score2: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.25 0.25 0.25 0.25 Any reply will be highly appreciated. Thanks. All the best. 2013-12-17
/Rujing Zha/
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
-- Douglas N. Greve, Ph.D. MGH-NMR Center greve@nmr.mgh.harvard.edu Phone Number: 617-724-2358 Fax: 617-726-7422
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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 Partners Compliance HelpLine at http://www.partners.org/complianceline . 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.
yes On 12/17/2013 10:06 PM, Rujing Zha wrote:
Dear Doug, Thanks for your precious help. Considering the 2nd example, I just want to know whether some brain surface thickness correlate the score without subjects coming from control or patient group. I think my aim is the same as want you told me "test whether the score is equal to 0 or not". Am I right? Thanks. All the best. 2013-12-18
/Rujing Zha/
*发件人：*Douglas N Greve greve@nmr.mgh.harvard.edu *发送时间：*2013-12-18 00:31 *主题：*Re: [Freesurfer] design matrix and contrast in fsgdf *收件人：*"freesurfer"freesurfer@nmr.mgh.harvard.edu *抄送：* That looks correct. The contrasts for the 2nd example will test whether the score is equal to 0 or not (and not an interaction between diagnosis and score). It is not wrong, but I just wanted to make sure you know what you are testing. doug On 12/17/2013 01:50 AM, Rujing Zha wrote:
Dear all, I want to design a group t-test analysis and correlation analysis for pial thickness. I have read the PPT of freesurfer.groupanalysis, and I wrote a specific design matrix and contrast for my data. However it is the first time that I design matrix in fsgdf by freesurfer. I didnot confirm whether I wrote is correct. I need someone to help me review it.
I have two groups, four groups were classified as sex.(Is this necessary or correct?) Here is my design matrix in fsgdf for 2 group t-test: GroupDescriptorFile 1 Title lh_ttest Class con_male Class con_female Class pat_male Class pat_female Variables Age edu Input subjid1 con_male 19 10 Input subjid2 con_male 20 20 Input subjid3 con_male 20 20 Input subjid4 con_male 19 10 Input subjid5 con_female 20 20 Input subjid6 con_female 20 20 Input subjid7 con_female 19 10 Input subjid8 pat_male 20 20 Input subjid9 pat_male 20 20 Input subjid10 pat_male 19 10 Input subjid11 pat_female 20 20 Input subjid12 pat_female 20 20 DefaultVariable Age In this section, I just want to compare the patient group(class 3 and 4) and control group(class 1 and 2) in thickness controling the age and education by ANCOVA. Does this fsgdf implement ANCOVA? Here is my contrast for this: 0.5 0.5 -0.5 -0.5 0 0 0 0 0 0 0 0 Here is my design matrix in fsgdf for partial regression: GroupDescriptorFile 1 Title lh_regression Class con_male Class con_female Class pat_male Class pat_female Variables Age edu score1 score2 Input subjid1 con_male 19 10 20 30 Input subjid2 con_male 20 20 20 30 Input subjid3 con_male 20 20 20 30 Input subjid4 con_male 19 10 20 30 Input subjid5 con_female 20 20 20 30 Input subjid6 con_female 20 20 20 30 Input subjid7 con_female 19 10 20 30 Input subjid8 pat_male 20 20 20 30 Input subjid9 pat_male 20 20 20 30 Input subjid10 pat_male 19 10 20 30 Input subjid11 pat_female 20 20 20 30 Input subjid12 pat_female 20 20 20 30 DefaultVariable score1 In this section, I want to implement partial regression analysis(i.e. score1 and score2) by controling the age,edu and sex. Here is my contrast for score1: 0 0 0 0 0 0 0 0 0 0 0 0 0.25 0.25 0.25 0.25 0 0 0 0 Here is my contrast for score2: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.25 0.25 0.25 0.25 Any reply will be highly appreciated. Thanks. All the best. 2013-12-17
/Rujing Zha/
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
-- Douglas N. Greve, Ph.D. MGH-NMR Center greve@nmr.mgh.harvard.edu Phone Number: 617-724-2358 Fax: 617-726-7422 Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting FileDrop: https://gate.nmr.mgh.harvard.edu/filedrop2 www.nmr.mgh.harvard.edu/facility/filedrop/index.html Outgoing: ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/ _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer 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 Partners Compliance HelpLine at
http://www.partners.org/complianceline . If the e-mail was sent to you in error
but does not contain patient information, please contact the sender and properly
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Hi Doug, OK, I see. Thanks Doug. All the best.
2013-12-19
Rujing Zha
发件人：Douglas N Greve greve@nmr.mgh.harvard.edu 发送时间：2013-12-19 04:38 主题：Re: [Freesurfer] design matrix and contrast in fsgdf 收件人："Rujing Zha"charujing123@163.com 抄送："freesurfer"freesurfer@nmr.mgh.harvard.edu
yes On 12/17/2013 10:06 PM, Rujing Zha wrote:
Dear Doug, Thanks for your precious help. Considering the 2nd example, I just want to know whether some brain surface thickness correlate the score without subjects coming from control or patient group. I think my aim is the same as want you told me "test whether the score is equal to 0 or not". Am I right? Thanks. All the best. 2013-12-18
/Rujing Zha/
*发件人：*Douglas N Greve greve@nmr.mgh.harvard.edu *发送时间：*2013-12-18 00:31 *主题：*Re: [Freesurfer] design matrix and contrast in fsgdf *收件人：*"freesurfer"freesurfer@nmr.mgh.harvard.edu *抄送：* That looks correct. The contrasts for the 2nd example will test whether the score is equal to 0 or not (and not an interaction between diagnosis and score). It is not wrong, but I just wanted to make sure you know what you are testing. doug On 12/17/2013 01:50 AM, Rujing Zha wrote:
Dear all, I want to design a group t-test analysis and correlation analysis for pial thickness. I have read the PPT of freesurfer.groupanalysis, and I wrote a specific design matrix and contrast for my data. However it is the first time that I design matrix in fsgdf by freesurfer. I didnot confirm whether I wrote is correct. I need someone to help me review it.
I have two groups, four groups were classified as sex.(Is this necessary or correct?) Here is my design matrix in fsgdf for 2 group t-test: GroupDescriptorFile 1 Title lh_ttest Class con_male Class con_female Class pat_male Class pat_female Variables Age edu Input subjid1 con_male 19 10 Input subjid2 con_male 20 20 Input subjid3 con_male 20 20 Input subjid4 con_male 19 10 Input subjid5 con_female 20 20 Input subjid6 con_female 20 20 Input subjid7 con_female 19 10 Input subjid8 pat_male 20 20 Input subjid9 pat_male 20 20 Input subjid10 pat_male 19 10 Input subjid11 pat_female 20 20 Input subjid12 pat_female 20 20 DefaultVariable Age In this section, I just want to compare the patient group(class 3 and 4) and control group(class 1 and 2) in thickness controling the age and education by ANCOVA. Does this fsgdf implement ANCOVA? Here is my contrast for this: 0.5 0.5 -0.5 -0.5 0 0 0 0 0 0 0 0 Here is my design matrix in fsgdf for partial regression: GroupDescriptorFile 1 Title lh_regression Class con_male Class con_female Class pat_male Class pat_female Variables Age edu score1 score2 Input subjid1 con_male 19 10 20 30 Input subjid2 con_male 20 20 20 30 Input subjid3 con_male 20 20 20 30 Input subjid4 con_male 19 10 20 30 Input subjid5 con_female 20 20 20 30 Input subjid6 con_female 20 20 20 30 Input subjid7 con_female 19 10 20 30 Input subjid8 pat_male 20 20 20 30 Input subjid9 pat_male 20 20 20 30 Input subjid10 pat_male 19 10 20 30 Input subjid11 pat_female 20 20 20 30 Input subjid12 pat_female 20 20 20 30 DefaultVariable score1 In this section, I want to implement partial regression analysis(i.e. score1 and score2) by controling the age,edu and sex. Here is my contrast for score1: 0 0 0 0 0 0 0 0 0 0 0 0 0.25 0.25 0.25 0.25 0 0 0 0 Here is my contrast for score2: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0.25 0.25 0.25 0.25 Any reply will be highly appreciated. Thanks. All the best. 2013-12-17
/Rujing Zha/
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
-- Douglas N. Greve, Ph.D. MGH-NMR Center greve@nmr.mgh.harvard.edu Phone Number: 617-724-2358 Fax: 617-726-7422 Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting FileDrop: https://gate.nmr.mgh.harvard.edu/filedrop2 www.nmr.mgh.harvard.edu/facility/filedrop/index.html Outgoing: ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/ _______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer 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 Partners Compliance HelpLine at
http://www.partners.org/complianceline . 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.
-- Douglas N. Greve, Ph.D. MGH-NMR Center greve@nmr.mgh.harvard.edu Phone Number: 617-724-2358 Fax: 617-726-7422
Bugs: surfer.nmr.mgh.harvard.edu/fswiki/BugReporting FileDrop: https://gate.nmr.mgh.harvard.edu/filedrop2 www.nmr.mgh.harvard.edu/facility/filedrop/index.html Outgoing: ftp://surfer.nmr.mgh.harvard.edu/transfer/outgoing/flat/greve/
_______________________________________________ Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
freesurfer@nmr.mgh.harvard.edu
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Rujing Zha