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
[EMAIL PROTECTED]


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