Hi Sasha--
There is an excellent statistical source on interactions of the sort you
are interested in. It may help you in setting up your tests. The name of
the book is "Interaction Effects in Factorial Analysis of Variance" by
James Jaccard. It should be available at your library, but if not it
only costs about $17. It may appear a bit dense at first, but it should
make sense if you work through the examples.
Anthony
Doug Greve wrote:
Still valid.
Sasha Wolosin wrote:
Is running a t-test contrast still valid if I don't have equal numbers
in the four groups (Male Treatment, Male Control, Female Treatment,
Female Control) or should I be running an F test instead?
Sasha
Doug Greve <[EMAIL PROTECTED]> 4/14/2006 3:18 pm >>>
Yes, you just need to come up with the the contrast matrix taht tests
what you want to test. If the contrast matrix has one row, then it's a
t-test. If there are more than one, then it's an F test. You example is
actually a t-test, I think, just:
(MaleTreatment-MaleControl) - (FemaleTreatment-FemaleControl)
for a contrast of: +1 -1 -1 +1
doug
Sasha Wolosin wrote:
Dear FreeSurfers,
I am interested in examining interaction effects between two sets
of
classes where each covers all the data, let's say Male/Female and
Treatment/Control. I know mri_glmfit can be used to run t-test
comparisons between groups (e.g. All Treatment vs. All Control , or
Male
& Control vs. Male & Treatment), but can mri_glmfit be used to
examine
interaction effects between these two sets of classes (for surface
data)?
my FSGD file looks like this:
GroupDescriptorFile 1
Class MaleTreatment
Class MaleControl
Class FemaleTreatment
Class FemaleControl
Input subjid1a MaleTreatment
Input subjid1b FemaleTreatment
Input subjid2a FemaleControl
Input subjid2b MaleControl
etc...
Thanks,
Sasha
Sasha Wolosin
Research Assistant
Developmental Cognitive Neurology
Kennedy Krieger Institute
707 N. Broadway
Baltimore, MD 21205
ph: (443) 923-9270
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