They are not identical, for sure. In general, I discourage people from
modeling categorical variables (eg, Group1/2 below) as continuous
variables because you make assumptions that might not be reasonable (eg,
females will have twice the thickness as males). I would use the first
method.
On 5/2/2024 8:20 PM, Lydia Chung wrote:
External Email - Use Caution
Hi FS support team,
I am going to be using mri_glmfit to test 1) main effects (which
regions show differences in cortical thickness between group 1 and
group 2) and 2) interaction effects (does the relationship between IV
and DV depend on moderator). Depending on the model, the IV is
sometimes a binary categorical variable and sometimes a continuous
variable. The moderator is always continuous. So, interaction effects
are either continuous x continuous OR categorical x continuous.
One thing I'm trying to understand is whether the two examples below
are basically two different approaches that answer the SAME question:
Do people in Group 1 differ from Group 2 on cortical thickness?
Version 1 is the one provided by FS and Version 2 is an analog of
another setup I have been provided by colleagues. Are these models
answering the same or different questions? The freesurfer link below
also shows an example of how to do an interaction (Group x Age) using
Version 1 setup; for Version 2 setup of an interaction, I know I would
multiply the IV and Moderator before this step so that I would have an
additional "interaction variable" column to add as one of the
'Variables' listed in the fsgd code. So, I'm also curious if the two
different methods of testing an interaction (in addition to the first
question about the main effect) will get you the identical answer OR
if there is something conceptually different? Do the nuances of this
setup have to do with the difference between using DODS or DOSS?
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_Main effect of Group on cortical thickness Version 1 (copied from FS
example. link here
<https://secure-web.cisco.com/1cgzre8FgLw0c17s9QNhmU_14vQ714XlLV20U4K14P96Afbs-6Heo84PLySiwVhDEZMhxP0C6FgIow7J7CguJV6osIK9fC2z1hN85kjx1hYSlGn-ewBZLibOXP73prq6qzehGuWIRDsDCEiRBlSxahnAXEQvrZFCHQKMOQR2X4kI3qYW5Lz5tLkGPv3ihsbW73z7AgR__zjM9Q0tck9Z_lN10U8oIYt6XTvyXshAZinK2vbV5cFWo8PxMMpXWi37uJxfQNvoOksCQwKocaxlN5ontLF542jDxjQ-MXsnM1VfM2onrGG6H9M-rle6KQe7JYj9siXKlYK3v1WBNbA874g/https%3A%2F%2Fsurfer.nmr.mgh.harvard.edu%2Ffswiki%2FFsgdf2G2V>)_
GroupDescriptorFile 1
Title OSGM
Class Group1
Class Group2
Variables Age Weight
Input subject1 Group1 30 100
Input subject2 Group2 40 120
Contrasts: 1 -1 0 0 0 0 (to test main effect of group; this feels like
an anova approach?)
_Main effect of Group on cortical thickness Version 2_
GroupDescriptorFile 1
Title OSGM
Class Subjects
Variables Group Age Weight
Input subject1 Subjects 0.5 30 100
Input subject2 Subjects -.5 40 120
contrasts: 0 1 0 0 (to test main effect of group; this feels like a
linear regression approach?)
Thank you in advance for your help!
Lydia
--
Lydia Wu-Chung, M.A.
Doctoral candidate
BMED Lab
Department of Psychological Sciences
Rice University
6500 Main St - MS201
Houston, TX 77030
Lab Phone: 713-348-8126
Email: lydia...@rice.edu <mailto:l...@rice.edu>
_
_
_
_
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