It will be constrained by the group with the smaller number of subjects. There is not anything wrong with unequal group sizes, but it is less efficient than if you had split your acquisitions evenly.



On 10/13/16 10:17 AM, Bruce Fischl wrote:
Hi Eelco

it depends on how you setup your GLM. Are you trying to regress out the effects of obesity in some way? If you give us more details I expect someone else can answer your question (Doug!)

cheers
Bruce


On Thu, 13 Oct 2016, Eelco van Duinkerken wrote:

Thanks for the quick reply!
So if I understand correctly, the power of say the controls vs. diabetes
(indeed it is type 2 diabetes) comparison is constrained by the sample size
of the obese group?

2016-10-13 11:02 GMT-03:00 Bruce Fischl <fis...@nmr.mgh.harvard.edu>:
      Hi Eelco

      it isn't really a question of whether our implementation is
      senstitive to
      this. It's that in general your power will be constrained by the
      size of
      the smaller group (I assume this is Type 2 diabetes by the way).

      cheers
      Bruce


      On Thu, 13 Oct 2016, Eelco van Duinkerken wrote:

      > Hi all,
      > I am using FS with data from 2 different studies that were
      acquired on the
      > same MRI-machine with the same T1 and FLAIR sequences.
      Unfortunately, the
      > group sizes are not very balanced, with 31 controls, 16 obese
      and 32
      > diabetes patients.
      >
      > Is the GLM for thickness used in FS very sensitive to this
      unequal group
      > size?
      >
      >
      > Thanks for the help,
      >
      > Eelco
      >
      >
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--
Eelco van Duinkerken, PhD
Pontifícia Universidade Católica | Department of Psychology |
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Brasil |
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