Hi Mailing List,
If you are comparing two matlab based linear mixed effects models (vertex-wise) with the same number of random effects (e.g. model with random effect for time vs. model with random effect for age at baseline), which segmentation should you use to estimate the parameters for both models? Kind regards, Bronwyn Overs Research Assistant
Neuroscience Research Australia Margarete Ainsworth Building Barker Street Randwick Sydney NSW 2031 Australia M 0411 308 769 T +61 2 9399 1883 F +61 2 9399 1265
neura.edu.au http://neura.edu.au/ https://twitter.com/neuraustralia https://www.facebook.com/NeuroscienceResearchAustralia http://www.neura.edu.au/help-research/subscribe
Hi Bronwyn,
is this for a mass univariate approach? What do you mean with segmentation? ROI or vertex-wise vs region-wise?
Best, Martin
On 03/29/2017 01:23 AM, Bronwyn Overs wrote:
Hi Mailing List,
If you are comparing two matlab based linear mixed effects models (vertex-wise) with the same number of random effects (e.g. model with random effect for time vs. model with random effect for age at baseline), which segmentation should you use to estimate the parameters for both models?
Kind regards,
Bronwyn Overs Research Assistant
Neuroscience Research Australia
Neuroscience Research Australia Margarete Ainsworth Building Barker Street Randwick Sydney NSW 2031 Australia *M* 0411 308 769 *T* +61 2 9399 1883 *F* +61 2 9399 1265
neura.edu.au http://neura.edu.au
Follow @neuraustralia on twitter https://twitter.com/neuraustraliaFollow NeuRA on facebook https://www.facebook.com/NeuroscienceResearchAustraliaSubscribe to the NeuRA Magazine http://www.neura.edu.au/help-research/subscribe
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Hi Martin,
Yes this is for a mass univariate approach. Re segmentation I was referring to the lhRgs output from the lme_mass_fit_Rgw command: lhstats_1RF = lme_mass_fit_Rgw(X,[1],Y,ni,lhTh0_1RF,lhRgs,lhsphere); So if both models have the same number of random effect, does it matter which lhRgs do I use? Kind regards, Bronwyn Overs Research Assistant
Neuroscience Research Australia Margarete Ainsworth Building Barker Street Randwick Sydney NSW 2031 Australia M 0411 308 769 T +61 2 9399 1883 F +61 2 9399 1265
neura.edu.au http://neura.edu.au/ https://twitter.com/neuraustralia https://www.facebook.com/NeuroscienceResearchAustralia http://www.neura.edu.au/help-research/subscribe
On 30 Mar 2017, at 12:18 am, Martin Reuter mreuter@nmr.mgh.harvard.edu wrote:
Hi Bronwyn, is this for a mass univariate approach? What do you mean with segmentation? ROI or vertex-wise vs region-wise?
Best, Martin On 03/29/2017 01:23 AM, Bronwyn Overs wrote:
Hi Mailing List,
If you are comparing two matlab based linear mixed effects models (vertex-wise) with the same number of random effects (e.g. model with random effect for time vs. model with random effect for age at baseline), which segmentation should you use to estimate the parameters for both models? Kind regards, Bronwyn Overs Research Assistant
Neuroscience Research Australia Margarete Ainsworth Building Barker Street Randwick Sydney NSW 2031 Australia M 0411 308 769 T +61 2 9399 1883 F +61 2 9399 1265
neura.edu.au http://neura.edu.au/ https://twitter.com/neuraustralia https://www.facebook.com/NeuroscienceResearchAustralia http://www.neura.edu.au/help-research/subscribe
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu mailto:Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
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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.
Hi Bronwyn,
ok, now I understand. I am not sure which one to take, I guess it won't matter much. Why don't you try either way and see if you get the same result.
Best, Martin
On 03/30/2017 12:59 AM, Bronwyn Overs wrote:
Hi Martin,
Yes this is for a mass univariate approach. Re segmentation I was referring to the lhRgs output from the lme_mass_fit_Rgw command: lhstats_1RF = lme_mass_fit_Rgw(X,[1],Y,ni,lhTh0_1RF,lhRgs,lhsphere); So if both models have the same number of random effect, does it matter which lhRgs do I use?
Kind regards,
Bronwyn Overs Research Assistant
Neuroscience Research Australia
Neuroscience Research Australia Margarete Ainsworth Building Barker Street Randwick Sydney NSW 2031 Australia *M* 0411 308 769 *T* +61 2 9399 1883 *F* +61 2 9399 1265
neura.edu.au http://neura.edu.au
Follow @neuraustralia on twitter https://twitter.com/neuraustraliaFollow NeuRA on facebook https://www.facebook.com/NeuroscienceResearchAustraliaSubscribe to the NeuRA Magazine http://www.neura.edu.au/help-research/subscribe
On 30 Mar 2017, at 12:18 am, Martin Reuter <mreuter@nmr.mgh.harvard.edu mailto:mreuter@nmr.mgh.harvard.edu> wrote:
Hi Bronwyn,
is this for a mass univariate approach? What do you mean with segmentation? ROI or vertex-wise vs region-wise?
Best, Martin
On 03/29/2017 01:23 AM, Bronwyn Overs wrote:
Hi Mailing List,
If you are comparing two matlab based linear mixed effects models (vertex-wise) with the same number of random effects (e.g. model with random effect for time vs. model with random effect for age at baseline), which segmentation should you use to estimate the parameters for both models?
Kind regards,
Bronwyn Overs Research Assistant
Neuroscience Research Australia
Neuroscience Research Australia Margarete Ainsworth Building Barker Street Randwick Sydney NSW 2031 Australia *M* 0411 308 769 *T* +61 2 9399 1883 *F* +61 2 9399 1265
neura.edu.au http://neura.edu.au/
Follow @neuraustralia on twitter https://twitter.com/neuraustraliaFollow NeuRA on facebook https://www.facebook.com/NeuroscienceResearchAustraliaSubscribe to the NeuRA Magazine http://www.neura.edu.au/help-research/subscribe
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 mailto: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.
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Great thanks Martin. Kind regards, Bronwyn Overs Research Assistant
Neuroscience Research Australia Margarete Ainsworth Building Barker Street Randwick Sydney NSW 2031 Australia M 0411 308 769 T +61 2 9399 1883 F +61 2 9399 1265
neura.edu.au http://neura.edu.au/ https://twitter.com/neuraustralia https://www.facebook.com/NeuroscienceResearchAustralia http://www.neura.edu.au/help-research/subscribe
On 4 Apr 2017, at 11:47 pm, Martin Reuter mreuter@nmr.mgh.harvard.edu wrote:
Hi Bronwyn, ok, now I understand. I am not sure which one to take, I guess it won't matter much. Why don't you try either way and see if you get the same result. Best, Martin
On 03/30/2017 12:59 AM, Bronwyn Overs wrote:
Hi Martin,
Yes this is for a mass univariate approach. Re segmentation I was referring to the lhRgs output from the lme_mass_fit_Rgw command: lhstats_1RF = lme_mass_fit_Rgw(X,[1],Y,ni,lhTh0_1RF,lhRgs,lhsphere); So if both models have the same number of random effect, does it matter which lhRgs do I use? Kind regards, Bronwyn Overs Research Assistant
Neuroscience Research Australia Margarete Ainsworth Building Barker Street Randwick Sydney NSW 2031 Australia M 0411 308 769 T +61 2 9399 1883 F +61 2 9399 1265
neura.edu.au http://neura.edu.au/ https://twitter.com/neuraustralia https://www.facebook.com/NeuroscienceResearchAustralia http://www.neura.edu.au/help-research/subscribe
On 30 Mar 2017, at 12:18 am, Martin Reuter <mreuter@nmr.mgh.harvard.edu mailto:mreuter@nmr.mgh.harvard.edu> wrote:
Hi Bronwyn, is this for a mass univariate approach? What do you mean with segmentation? ROI or vertex-wise vs region-wise?
Best, Martin On 03/29/2017 01:23 AM, Bronwyn Overs wrote:
Hi Mailing List,
If you are comparing two matlab based linear mixed effects models (vertex-wise) with the same number of random effects (e.g. model with random effect for time vs. model with random effect for age at baseline), which segmentation should you use to estimate the parameters for both models? Kind regards, Bronwyn Overs Research Assistant
Neuroscience Research Australia Margarete Ainsworth Building Barker Street Randwick Sydney NSW 2031 Australia M 0411 308 769 T +61 2 9399 1883 F +61 2 9399 1265
neura.edu.au http://neura.edu.au/ https://twitter.com/neuraustralia https://www.facebook.com/NeuroscienceResearchAustralia http://www.neura.edu.au/help-research/subscribe
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu mailto:Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu mailto:Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer 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 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.
Freesurfer mailing list Freesurfer@nmr.mgh.harvard.edu mailto:Freesurfer@nmr.mgh.harvard.edu https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer 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
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.
freesurfer@nmr.mgh.harvard.edu
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Bronwyn Overs -
Martin Reuter