Dear FreeSurfer experts,
We have run a vertex-wise analysis regressing a continuous variable onto cortical thickness on the surface, and would like to verify that our contrast that uses Age and Sex as covariates was defined correctly, especially since there is probably more than one way to control for a binary variable like Sex.
On the website (https://surfer.nmr.mgh.harvard.edu/fswiki/DodsDoss) it suggests to make two regressors, one for Males, and one for Females, where for the former a 1 is indicative of the Male category, and a 1 on the latter is indicative of the Female category. However, using that FSGD file and running a DOSS contrast as [0 1 0 0 0], we get the error: matrix is ill-condition or badly scaled, condno=2.01889e+07. We believe this may be due to the fact that Male and Female categories are autocorrelated and Freesurfer likes variables to be de-meaned. Running a FSGD file with only Age and our variable of interest via a DOSS contrast of [0 1 0] works without any errors.
We thus created an FSGD file where we have Sex as our third variable (in addition to our continuous variable of interest and one demeaned continuous covariate), coding 1s for Males and 0s for Females, and we used a DOSS contrast of [0 1 0 0]. This provided us with a map that makes sense with our expectations.
We would like to verify if this is doing what we believe it is doing; that is, looking at the relationship of our continuous variable or interest after accounting for age and sex. Any thoughts would be greatly appreciated.
Thank you so much.
Best,
Fred
can you send the fsgd file for the analysis that is failing?
On 08/29/2017 02:29 PM, Uquillas, Federico D'Oleire wrote:
Dear FreeSurfer experts,
We have run a vertex-wise analysis regressing a continuous variable onto cortical thickness on the surface, and would like to verify that our contrast that uses Age and Sex as covariates was defined correctly, especially since there is probably more than one way to control for a binary variable like Sex.
On the website (https://surfer.nmr.mgh.harvard.edu/fswiki/DodsDoss) it suggests to make two regressors, one for Males, and one for Females, where for the former a 1 is indicative of the Male category, and a 1 on the latter is indicative of the Female category. However, using that FSGD file and running a DOSS contrast as [0 1 0 0 0], we get the error: matrix is ill-condition or badly scaled, condno=2.01889e+07. We believe this may be due to the fact that Male and Female categories are autocorrelated and Freesurfer likes variables to be de-meaned. Running a FSGD file with only Age and our variable of interest via a DOSS contrast of [0 1 0] works without any errors.
We thus created an FSGD file where we have Sex as our third variable (in addition to our continuous variable of interest and one demeaned continuous covariate), coding 1s for Males and 0s for Females, and we used a DOSS contrast of [0 1 0 0]. This provided us with a map that makes sense with our expectations.
We would like to verify if this is doing what we believe it is doing; that is, looking at the relationship of our continuous variable or interest after accounting for age and sex. Any thoughts would be greatly appreciated.
Thank you so much.
Best,
Fred
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Dear FS Team,
We are running recon-all for a large dataset and 5 of the cases keep getting stuck at the exact same spot. It is the point at which the following has just been displayed on the screen:
#@# WM Segmentation Wed Aug 30 17:34:40 EDT 2017
mri_segment brain.mgz wm.seg.mgz
doing initial intensity segmentation... using local statistics to label ambiguous voxels... computing class statistics for intensity windows... WM (107.0): 105.5 +- 6.4 [91.0 --> 125.0] GM (78.0) : 81.0 +- 6.1 [56.0 --> 94.0] setting bottom of white matter range to 87.1 setting top of gray matter range to 93.2 doing initial intensity segmentation... using local statistics to label ambiguous voxels...
For these 5 cases it will sit at this step apparently still running for over a week without any change before I cancel the job. There does not seem to be anything special about these 5 cases either in terms of their header information or visually. We have not found any artifacts in the images except for some minor ringing which is present in many images in the dataset, not just these. The rest of the cases of the dataset all ran to completion and produced all of the files we were expecting, but a subset of them seem to have a related issue where most of the wmparc.mgz labelmap is unsegmented white matter. Only the very edges and the very center are getting designated as something other than this label. The rest of the files in the "mri" directory such as aparc+aseg.mgz and so on are equally as affected by this. Do you know what could be going on here? I would be happy to give you any more information that could be helpful.
Best, Elisabetta and Nate
Elisabetta C. del Re, Ph.D. Assistant Professor of Psychiatry, Department of Psychiatry Harvard Medical School phone 617 9675569 mail elisabetta_delre@hms.harvard.edu
really? I've never seen that. If you upload one of the subjects to our ftp site (the entire subject dir tarred and gzipped) I will take a look
cheers Bruce On Tue, 5 Sep 2017, Del Re, Elisabetta wrote:
Dear FS Team,
We are running recon-all for a large dataset and 5 of the cases keep getting stuck at the exact same spot. It is the point at which the following has just been displayed on the screen:
#@# WM Segmentation Wed Aug 30 17:34:40 EDT 2017
mri_segment brain.mgz wm.seg.mgz
doing initial intensity segmentation... using local statistics to label ambiguous voxels... computing class statistics for intensity windows... WM (107.0): 105.5 +- 6.4 [91.0 --> 125.0] GM (78.0) : 81.0 +- 6.1 [56.0 --> 94.0] setting bottom of white matter range to 87.1 setting top of gray matter range to 93.2 doing initial intensity segmentation... using local statistics to label ambiguous voxels...
For these 5 cases it will sit at this step apparently still running for over a week without any change before I cancel the job. There does not seem to be anything special about these 5 cases either in terms of their header information or visually. We have not found any artifacts in the images except for some minor ringing which is present in many images in the dataset, not just these. The rest of the cases of the dataset all ran to completion and produced all of the files we were expecting, but a subset of them seem to have a related issue where most of the wmparc.mgz labelmap is unsegmented white matter. Only the very edges and the very center are getting designated as something other than this label. The rest of the files in the "mri" directory such as aparc+aseg.mgz and so on are equally as affected by this. Do you know what could be going on here? I would be happy to give you any more information that could be helpful.
Best, Elisabetta and Nate
Elisabetta C. del Re, Ph.D. Assistant Professor of Psychiatry, Department of Psychiatry Harvard Medical School phone 617 9675569 mail elisabetta_delre@hms.harvard.edu
Dear Doug,
Sending the FSGD described in our original email as failing due to it being "ill-conditioned or badly scaled" with DOSS [0 1 0 0 0]. It is titled "FAILS_N47_edited_BL_CT_PiB_centAge_fsgd.txt".
The other one is the one that runs and gives expected results with a DOSS contrast [0 1 0 0].
Thanks so much.
Best regards,
Fred
________________________________________ From: freesurfer-bounces@nmr.mgh.harvard.edu [freesurfer-bounces@nmr.mgh.harvard.edu] on behalf of Douglas N Greve [greve@nmr.mgh.harvard.edu] Sent: Tuesday, September 05, 2017 12:01 PM To: freesurfer@nmr.mgh.harvard.edu Subject: Re: [Freesurfer] controlling for Sex in a model using two continuous variables onto CTh
can you send the fsgd file for the analysis that is failing?
On 08/29/2017 02:29 PM, Uquillas, Federico D'Oleire wrote:
Dear FreeSurfer experts,
We have run a vertex-wise analysis regressing a continuous variable onto cortical thickness on the surface, and would like to verify that our contrast that uses Age and Sex as covariates was defined correctly, especially since there is probably more than one way to control for a binary variable like Sex.
On the website (https://surfer.nmr.mgh.harvard.edu/fswiki/DodsDoss) it suggests to make two regressors, one for Males, and one for Females, where for the former a 1 is indicative of the Male category, and a 1 on the latter is indicative of the Female category. However, using that FSGD file and running a DOSS contrast as [0 1 0 0 0], we get the error: matrix is ill-condition or badly scaled, condno=2.01889e+07. We believe this may be due to the fact that Male and Female categories are autocorrelated and Freesurfer likes variables to be de-meaned. Running a FSGD file with only Age and our variable of interest via a DOSS contrast of [0 1 0] works without any errors.
We thus created an FSGD file where we have Sex as our third variable (in addition to our continuous variable of interest and one demeaned continuous covariate), coding 1s for Males and 0s for Females, and we used a DOSS contrast of [0 1 0 0]. This provided us with a map that makes sense with our expectations.
We would like to verify if this is doing what we believe it is doing; that is, looking at the relationship of our continuous variable or interest after accounting for age and sex. Any thoughts would be greatly appreciated.
Thank you so much.
Best,
Fred
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
in the one that fails you are including the binary gender as a continuous variable, which will fail in FSGD. All catagorical variables need to be coded as classes. see https://surfer.nmr.mgh.harvard.edu/fswiki/FsgdExamples
On 09/05/2017 03:07 PM, Uquillas, Federico D'Oleire wrote:
Dear Doug,
Sending the FSGD described in our original email as failing due to it being "ill-conditioned or badly scaled" with DOSS [0 1 0 0 0]. It is titled "FAILS_N47_edited_BL_CT_PiB_centAge_fsgd.txt".
The other one is the one that runs and gives expected results with a DOSS contrast [0 1 0 0].
Thanks so much.
Best regards,
Fred
From: freesurfer-bounces@nmr.mgh.harvard.edu [freesurfer-bounces@nmr.mgh.harvard.edu] on behalf of Douglas N Greve [greve@nmr.mgh.harvard.edu] Sent: Tuesday, September 05, 2017 12:01 PM To: freesurfer@nmr.mgh.harvard.edu Subject: Re: [Freesurfer] controlling for Sex in a model using two continuous variables onto CTh
can you send the fsgd file for the analysis that is failing?
On 08/29/2017 02:29 PM, Uquillas, Federico D'Oleire wrote:
Dear FreeSurfer experts,
We have run a vertex-wise analysis regressing a continuous variable onto cortical thickness on the surface, and would like to verify that our contrast that uses Age and Sex as covariates was defined correctly, especially since there is probably more than one way to control for a binary variable like Sex.
On the website (https://surfer.nmr.mgh.harvard.edu/fswiki/DodsDoss) it suggests to make two regressors, one for Males, and one for Females, where for the former a 1 is indicative of the Male category, and a 1 on the latter is indicative of the Female category. However, using that FSGD file and running a DOSS contrast as [0 1 0 0 0], we get the error: matrix is ill-condition or badly scaled, condno=2.01889e+07. We believe this may be due to the fact that Male and Female categories are autocorrelated and Freesurfer likes variables to be de-meaned. Running a FSGD file with only Age and our variable of interest via a DOSS contrast of [0 1 0] works without any errors.
We thus created an FSGD file where we have Sex as our third variable (in addition to our continuous variable of interest and one demeaned continuous covariate), coding 1s for Males and 0s for Females, and we used a DOSS contrast of [0 1 0 0]. This provided us with a map that makes sense with our expectations.
We would like to verify if this is doing what we believe it is doing; that is, looking at the relationship of our continuous variable or interest after accounting for age and sex. Any thoughts would be greatly appreciated.
Thank you so much.
Best,
Fred
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
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Thank you Doug. Is the one that doesn't fail okay?
Best,
Fred
On Sep 5, 2017, at 16:57, Douglas N Greve greve@nmr.mgh.harvard.edu wrote:
in the one that fails you are including the binary gender as a continuous variable, which will fail in FSGD. All catagorical variables need to be coded as classes. see https://surfer.nmr.mgh.harvard.edu/fswiki/FsgdExamples
On 09/05/2017 03:07 PM, Uquillas, Federico D'Oleire wrote: Dear Doug,
Sending the FSGD described in our original email as failing due to it being "ill-conditioned or badly scaled" with DOSS [0 1 0 0 0]. It is titled "FAILS_N47_edited_BL_CT_PiB_centAge_fsgd.txt".
The other one is the one that runs and gives expected results with a DOSS contrast [0 1 0 0].
Thanks so much.
Best regards,
Fred
From: freesurfer-bounces@nmr.mgh.harvard.edu [freesurfer-bounces@nmr.mgh.harvard.edu] on behalf of Douglas N Greve [greve@nmr.mgh.harvard.edu] Sent: Tuesday, September 05, 2017 12:01 PM To: freesurfer@nmr.mgh.harvard.edu Subject: Re: [Freesurfer] controlling for Sex in a model using two continuous variables onto CTh
can you send the fsgd file for the analysis that is failing?
On 08/29/2017 02:29 PM, Uquillas, Federico D'Oleire wrote: Dear FreeSurfer experts,
We have run a vertex-wise analysis regressing a continuous variable onto cortical thickness on the surface, and would like to verify that our contrast that uses Age and Sex as covariates was defined correctly, especially since there is probably more than one way to control for a binary variable like Sex.
On the website (https://surfer.nmr.mgh.harvard.edu/fswiki/DodsDoss) it suggests to make two regressors, one for Males, and one for Females, where for the former a 1 is indicative of the Male category, and a 1 on the latter is indicative of the Female category. However, using that FSGD file and running a DOSS contrast as [0 1 0 0 0], we get the error: matrix is ill-condition or badly scaled, condno=2.01889e+07. We believe this may be due to the fact that Male and Female categories are autocorrelated and Freesurfer likes variables to be de-meaned. Running a FSGD file with only Age and our variable of interest via a DOSS contrast of [0 1 0] works without any errors.
We thus created an FSGD file where we have Sex as our third variable (in addition to our continuous variable of interest and one demeaned continuous covariate), coding 1s for Males and 0s for Females, and we used a DOSS contrast of [0 1 0 0]. This provided us with a map that makes sense with our expectations.
We would like to verify if this is doing what we believe it is doing; that is, looking at the relationship of our continuous variable or interest after accounting for age and sex. Any thoughts would be greatly appreciated.
Thank you so much.
Best,
Fred
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
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
For DOSS, It will work, but harder to set up the contrast matrices to look at a sex effect. I would just do it coding males and females as separate classes and not include sex as a variable
On 09/05/2017 06:00 PM, Uquillas, Federico D'Oleire wrote:
Thank you Doug. Is the one that doesn't fail okay?
Best,
Fred
On Sep 5, 2017, at 16:57, Douglas N Greve greve@nmr.mgh.harvard.edu wrote:
in the one that fails you are including the binary gender as a continuous variable, which will fail in FSGD. All catagorical variables need to be coded as classes. see https://surfer.nmr.mgh.harvard.edu/fswiki/FsgdExamples
On 09/05/2017 03:07 PM, Uquillas, Federico D'Oleire wrote: Dear Doug,
Sending the FSGD described in our original email as failing due to it being "ill-conditioned or badly scaled" with DOSS [0 1 0 0 0]. It is titled "FAILS_N47_edited_BL_CT_PiB_centAge_fsgd.txt".
The other one is the one that runs and gives expected results with a DOSS contrast [0 1 0 0].
Thanks so much.
Best regards,
Fred
From: freesurfer-bounces@nmr.mgh.harvard.edu [freesurfer-bounces@nmr.mgh.harvard.edu] on behalf of Douglas N Greve [greve@nmr.mgh.harvard.edu] Sent: Tuesday, September 05, 2017 12:01 PM To: freesurfer@nmr.mgh.harvard.edu Subject: Re: [Freesurfer] controlling for Sex in a model using two continuous variables onto CTh
can you send the fsgd file for the analysis that is failing?
On 08/29/2017 02:29 PM, Uquillas, Federico D'Oleire wrote: Dear FreeSurfer experts,
We have run a vertex-wise analysis regressing a continuous variable onto cortical thickness on the surface, and would like to verify that our contrast that uses Age and Sex as covariates was defined correctly, especially since there is probably more than one way to control for a binary variable like Sex.
On the website (https://surfer.nmr.mgh.harvard.edu/fswiki/DodsDoss) it suggests to make two regressors, one for Males, and one for Females, where for the former a 1 is indicative of the Male category, and a 1 on the latter is indicative of the Female category. However, using that FSGD file and running a DOSS contrast as [0 1 0 0 0], we get the error: matrix is ill-condition or badly scaled, condno=2.01889e+07. We believe this may be due to the fact that Male and Female categories are autocorrelated and Freesurfer likes variables to be de-meaned. Running a FSGD file with only Age and our variable of interest via a DOSS contrast of [0 1 0] works without any errors.
We thus created an FSGD file where we have Sex as our third variable (in addition to our continuous variable of interest and one demeaned continuous covariate), coding 1s for Males and 0s for Females, and we used a DOSS contrast of [0 1 0 0]. This provided us with a map that makes sense with our expectations.
We would like to verify if this is doing what we believe it is doing; that is, looking at the relationship of our continuous variable or interest after accounting for age and sex. Any thoughts would be greatly appreciated.
Thank you so much.
Best,
Fred
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
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
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Thank you so much Doug. We're mainly interested in controlling for Sex so it is great to know that it does work for DOSS.
Best,
Fred
On Sep 5, 2017, at 18:07, Douglas N Greve greve@nmr.mgh.harvard.edu wrote:
For DOSS, It will work, but harder to set up the contrast matrices to look at a sex effect. I would just do it coding males and females as separate classes and not include sex as a variable
On 09/05/2017 06:00 PM, Uquillas, Federico D'Oleire wrote: Thank you Doug. Is the one that doesn't fail okay?
Best,
Fred
On Sep 5, 2017, at 16:57, Douglas N Greve greve@nmr.mgh.harvard.edu wrote:
in the one that fails you are including the binary gender as a continuous variable, which will fail in FSGD. All catagorical variables need to be coded as classes. see https://surfer.nmr.mgh.harvard.edu/fswiki/FsgdExamples
On 09/05/2017 03:07 PM, Uquillas, Federico D'Oleire wrote: Dear Doug,
Sending the FSGD described in our original email as failing due to it being "ill-conditioned or badly scaled" with DOSS [0 1 0 0 0]. It is titled "FAILS_N47_edited_BL_CT_PiB_centAge_fsgd.txt".
The other one is the one that runs and gives expected results with a DOSS contrast [0 1 0 0].
Thanks so much.
Best regards,
Fred
From: freesurfer-bounces@nmr.mgh.harvard.edu [freesurfer-bounces@nmr.mgh.harvard.edu] on behalf of Douglas N Greve [greve@nmr.mgh.harvard.edu] Sent: Tuesday, September 05, 2017 12:01 PM To: freesurfer@nmr.mgh.harvard.edu Subject: Re: [Freesurfer] controlling for Sex in a model using two continuous variables onto CTh
can you send the fsgd file for the analysis that is failing?
On 08/29/2017 02:29 PM, Uquillas, Federico D'Oleire wrote: Dear FreeSurfer experts,
We have run a vertex-wise analysis regressing a continuous variable onto cortical thickness on the surface, and would like to verify that our contrast that uses Age and Sex as covariates was defined correctly, especially since there is probably more than one way to control for a binary variable like Sex.
On the website (https://surfer.nmr.mgh.harvard.edu/fswiki/DodsDoss) it suggests to make two regressors, one for Males, and one for Females, where for the former a 1 is indicative of the Male category, and a 1 on the latter is indicative of the Female category. However, using that FSGD file and running a DOSS contrast as [0 1 0 0 0], we get the error: matrix is ill-condition or badly scaled, condno=2.01889e+07. We believe this may be due to the fact that Male and Female categories are autocorrelated and Freesurfer likes variables to be de-meaned. Running a FSGD file with only Age and our variable of interest via a DOSS contrast of [0 1 0] works without any errors.
We thus created an FSGD file where we have Sex as our third variable (in addition to our continuous variable of interest and one demeaned continuous covariate), coding 1s for Males and 0s for Females, and we used a DOSS contrast of [0 1 0 0]. This provided us with a map that makes sense with our expectations.
We would like to verify if this is doing what we believe it is doing; that is, looking at the relationship of our continuous variable or interest after accounting for age and sex. Any thoughts would be greatly appreciated.
Thank you so much.
Best,
Fred
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
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
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
freesurfer@nmr.mgh.harvard.edu
-
Bruce Fischl -
Del Re, Elisabetta -
Douglas N Greve -
Uquillas, Federico D'Oleire