oops sorry! (I also miscalculated the # of regressors - there's actually
 12 (not 10 as previously noted). Here is the list of column labels:
Grp1male  Grp1female Grp2male Grp2female Grp1maleVar1 Grp1femaleVar1
Grp1maleVar2 Grp1femaleVar2 Grp2maleVar1 Grp2femaleVar1 Grp2maleVar2
Grp2femaleVar2

And what I think is actually an F test looking for group x var 1
interaction OR group x variable 2 interaction whilst accounting for gender.
.5 .5 -.5 -.5 0 0 0 0 0 0
0 0 0 0 0 0 .5 .5 -.5 -.5

But what I actually WANT to test is a  multiple regression style model -
i.e. if I put var 1 AND 2 into the model together do they explain more
variance than either variable alone, AND does this vary by group (is this
even a sensible contrast to make?). Which I *think* would look something
like this...

0 0 0 0 .125 .125 .125 .125 .125 .125 .125 .125

Laura.



On Thu, Mar 21, 2013 at 5:51 PM, MCLAREN, Donald
<mclaren.don...@gmail.com>wrote:

> Please include the list of the column labels.
>
> Best Regards, Donald McLaren
> =================
> D.G. McLaren, Ph.D.
> Research Fellow, Department of Neurology, Massachusetts General Hospital
> and
> Harvard Medical School
> Postdoctoral Research Fellow, GRECC, Bedford VA
> Website: http://www.martinos.org/~mclaren
> Office: (773) 406-2464
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> On Thu, Mar 21, 2013 at 6:43 PM, Laura M. Tully <
> tully.la...@googlemail.com> wrote:
>
>> hi Experts,
>>
>> I'm struggling to conceptualize the appropriate contrasts for my cortical
>> thickness analysis. I have four classes [two groups; two levels
>> (patients,controls; male,female) and two behavioral variables. I want to
>> see if together the two variables account significant proportion of the
>> variance in y (thickness) and if this differs by group whilst regressing
>> out gender. - i.e. if I enter both behavioral variables into the model does
>> it account for more variance than either variable on their own (after
>> controlling for gender)? What I have is this:
>>
>> .5 .5 -.5 -.5 0 0 0 0
>> 0 0 0 0 .5 .5 -.5 -.5
>>
>> Does this look right?
>>
>> Thanks!
>>
>> Laura.
>>
>>
>>
>>
>> --
>> --
>> Laura M. Tully, MA
>> Social Neuroscience & Psychopathology, Harvard University
>> Center for the Assessment and Prevention of Prodromal States, UCLA Semel
>> Institute of Neuroscience
>> ltu...@mednet.ucla.edu
>> ltu...@fas.harvard.edu
>> 310-267-0170
>> --
>> My musings as a young clinical scientist:
>> http://theclinicalbrain.blogspot.com/
>> Follow me on Twitter: @tully_laura
>>
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>


-- 
--
Laura M. Tully, MA
Social Neuroscience & Psychopathology, Harvard University
Center for the Assessment and Prevention of Prodromal States, UCLA Semel
Institute of Neuroscience
ltu...@mednet.ucla.edu
ltu...@fas.harvard.edu
310-267-0170
--
My musings as a young clinical scientist:
http://theclinicalbrain.blogspot.com/
Follow me on Twitter: @tully_laura
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