On Wed, Mar 7, 2012 at 1:34 PM, Bruce Fischl <fischl@nmr.mgh.harvard.edu> wrote:

Hi Allie

perhaps David Salat (ccd) can comment. He definitely saw some areas that thickened with age. They weren't common, but they were definitely in the data.

cheers
Bruce

On Wed, 7 Mar 2012, Allie Rosen wrote:

Hi Bruce and Doug,
Given the fact that all my surfaces for my 16 patients and controls are fine, I'm still left with some basic questions:

Since there is this interaction effect for age, how can I actually compare the thickness of the two populations?

And should I be worried about the fact that some areas are thickening with age, despite the fact that this isn't caused by defects in the surface
topology of the subjects?

Thank you for the help,
Allie

On Wed, Mar 7, 2012 at 10:02 AM, Bruce Fischl <fischl@nmr.mgh.harvard.edu> wrote:
Hi Allie

the real question is whether the surfaces are accurate in that place for that subject. The only way to tell is to visually inspect
them.

cheers
Bruce
On Wed, 7 Mar 2012, Allie Rosen wrote:

Hi Bruce,
I'm not sure if this qualifies as an outlier, but I do have one individual (and the age-matched control) who is much older
than the rest (see
attached). Do you think elimination of this subject could make the comparison possible?

Thanks,
Allie

On Tue, Mar 6, 2012 at 5:10 PM, Bruce Fischl <fischl@nmr.mgh.harvard.edu> wrote:
   do you have a big outlier in the thickness measures? I didn't see one. It seems unlikely that all your subject have a
defect in that
   spot
   On Tue, 6 Mar 2012, Douglas N Greve wrote:

   It means that any comparison depends on age. Eg, if you compare them at
   an age where the lines cross, you will see no effect. If you compare
   them at age=0 (what you were doing before), then you see a big effect.
   Some statisticians will say that you cannot do the comparison in the
   presence of an interaction.
   dogu

   Allie Rosen wrote:
   So if my findings show that each group ages differently, does that
   mean I can't compare them at all because I can't regress out age? Or
   is there some way of comparing the groups despite this difference in
   aging patterns?

   Thanks again,
   Allie

   On Tue, Mar 6, 2012 at 4:44 PM, Douglas N Greve
   <greve@nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu>> wrote:

      It might, don't know

      Allie Rosen wrote:

      Hi Doug,

      Yes, I think there actually may be a topologic defect in this
      area, although not directly where the cluster is (attached).
      Could this be the cause of the thickness result? If I go back
      and try to repair the defect, will that make the results more
      typical and, more importantly, correct?

      Thanks again,
      Allie

      On Tue, Mar 6, 2012 at 3:57 PM, Douglas N Greve
      <greve@nmr.mgh.harvard.edu <mailto:greve@nmr.mgh.harvard.edu>
      <mailto:greve@nmr.mgh.harvard.edu
      <mailto:greve@nmr.mgh.harvard.edu>>> wrote:

      Hi Allie, yes, it means that each group is affected
      differently by
      age. The controls are increasing their thickness with age
      in this
      area (which seems strange, usually you expect general decreases
      with age). You might check the quality of the surfaces in
      this area.
      doug

      Allie Rosen wrote:

      Hi Doug,

      Thanks for the response. I've actually already run an
      interaction contrast and the same area is still significant
      (attached). I'm not sure how to interpret this either,
      unfortunately. Does it say that both groups are affected
      significantly differently by age? Can you tell me what it
      means? I'm having problems trying to do this myself.

      Thanks very much,
      Allie

      On Tue, Mar 6, 2012 at 3:47 PM, Douglas N Greve
      <greve@nmr.mgh.harvard.edu
      <mailto:greve@nmr.mgh.harvard.edu>
      <mailto:greve@nmr.mgh.harvard.edu
      <mailto:greve@nmr.mgh.harvard.edu>>
      <mailto:greve@nmr.mgh.harvard.edu
      <mailto:greve@nmr.mgh.harvard.edu>

      <mailto:greve@nmr.mgh.harvard.edu
      <mailto:greve@nmr.mgh.harvard.edu>>>> wrote:

      Allie, to be more precise, you have selected
      control<patient
      regressing out the effects of age. This second part
      is the key.
      If you were to trace the regression lines back to
      age=0 (the
      meaning of "regressing out age"), then
      control<patient by a
      wide
      margin. But you have a problem here in that the
      regression
      lines
      are crossed. This means that you have an interaction
      between age
      and patient (no interaction means that the lines
      would be
      parallel). An interaction means that you cannot
      assess whether
      there is a difference in the thickness because this
      difference
      changes depending upon the age. One thing you can
      try is to
      actually compute an interaction contrast (something
      like [0 0 1
      -1]). If it is significant in this area, then
      there's not
      much you
      can do (though it may be interesting in itself). If
      it is not
      significant, then you can switch to a DOSS model which
      forces the
      lines to be parallel and makes the distance between the
      lines be
      independent of age. Does this make sense?
      doug

      Allie Rosen wrote:

      Hi All,

      I'm having trouble reconciling the cluster
      colours with the
      graph that can be made when you load the group
      descriptor file
      and click on a point. I've attached an example.
      In this study, I'm comparing thickness in a
      patient and
      control group, with age regressed out. The contrast
      I've used
      means that blue means control<patient. Therefore,
      patients are
      thicker than controls. But in the graph,
      patients don't
      seem
      to be thicker. I've seen the same results with
      red clusters
      (i.e. they should mean that controls are thicker but
      the graph
      shows otherwhise). Please let me know how I can
      interpret my
      findings given the graph. Which group is
      actually thicker?

      Thank you,
      Allison

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