You cannot have empty classes. You should adjust the weights so that all the positives add up to 1 and all the negatives add up to -1
On 05/04/2018 04:49 AM, C.P.E. Rollins wrote: > External Email - Use Caution > > 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.
