That looks right for DOSS
On 05/08/2018 11:56 AM, C.P.E. Rollins wrote: > External Email - Use Caution > Ah, I think I understand now, thanks. I've attached my contrast and > FSGD file to confirm. In the FSGD file, the format for the classes are > <group>_<sex>_<centre>. > Please let me know. > > Thanks again, > Colleen > > On 2018-05-04 09:49, C.P.E. Rollins wrote: >> Hi, >> >> Sorry for coming back to this, but I'm still confused about the issue >> of having unbalanced classes. I thought that I could not remove the >> class as you suggested since this would mean that the contrast >> positive and negative values would no longer add up to 0. For >> instance if I remove only class "patient_centre2_female", then my >> contrast would have 11 (-1) and 12 (1) as opposed to 12 and 12. Could >> you please clarify? >> >> Thanks again, >> Colleen >> >> >> On 2018-04-30 14:43, C.P.E. Rollins wrote: >>> I thought that I could not remove the class since this would mean that >>> the contrast positive and negative values would no longer add up to 0. >>> For instance if I remove only class "patient_centre2_female", then my >>> contrast would have 11 (-1) and 12 (1) as opposed to 12 and 12. Could >>> you please clarify? >>> >>> Thanks again, >>> Colleen >>> >>> -------- Original Message -------- >>> Subject: Re: [Freesurfer] FSGD design for multi-centre study >>> Date: 2018-04-20 11:19 >>> From: "C.P.E. Rollins" <cp...@cam.ac.uk> >>> To: Freesurfer <freesurfer@nmr.mgh.harvard.edu> >>> >>> Thanks a lot for the explanation. The issue is that I don't think >>> Freesurfer will run a design for which there are no subjects for a >>> given class. So if I keep the classes (24 classes since 6 centres x 2 >>> gender x 2 groups (patient vs. control), and have the contrast with 12 >>> (-1) and 12 (1), >>> -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 -1 1 1 1 1 1 1 1 1 1 1 1 1 0 >>> I get the error: >>> -------------------------------- >>> ERROR: matrix is ill-conditioned or badly scaled, condno = 1e+08 >>> -------------------------------- >>> Possible problem with experimental design: >>> Check for duplicate entries and/or lack of range of >>> continuous variables within a class. >>> >>> I'm assuming this is because there are no participants in, for >>> example, patient_centre2_female >>> Is there any way to get around this issue, or should I remove those >>> centres from my analysis (since I can't only remove >>> "patient_centre2_female", as this would make the contrast unbalanced >>> (positives and negatives would not add to the same number). I hope >>> this was clear but please let me know if it was not. >>> >>> Thanks again, >>> Colleen > > > _______________________________________________ > 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 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.
