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 Grp2femaleVar2And 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 00 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.donald@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
=====================
This e-mail contains CONFIDENTIAL INFORMATION which may contain PROTECTED
HEALTHCARE INFORMATION and may also be LEGALLY PRIVILEGED and which is
intended only for the use of the individual or entity named above. If the
reader of the e-mail is not the intended recipient or the employee or agent
responsible for delivering it to the intended recipient, you are hereby
notified that you are in possession of confidential and privileged
information. Any unauthorized use, disclosure, copying or the taking of any
action in reliance on the contents of this information is strictly
prohibited and may be unlawful. If you have received this e-mail
unintentionally, please immediately notify the sender via telephone at (773)
406-2464 or email.On Thu, Mar 21, 2013 at 6:43 PM, Laura M. Tully <tully.laura@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 00 0 0 0 .5 .5 -.5 -.5Does 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
ltully@mednet.ucla.edu
ltully@fas.harvard.edu
310-267-0170
--My musings as a young clinical scientist: http://theclinicalbrain.blogspot.com/Follow me on Twitter: @tully_laura
Freesurfer mailing list
Freesurfer@nmr.mgh.harvard.edu
https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer
The information in this e-mail is intended only for the person to whom it is
addressed. If you believe this e-mail was sent to you in error and the e-mail
contains patient information, please contact the Partners Compliance HelpLine at
http://www.partners.org/complianceline . If the e-mail was sent to you in error
but does not contain patient information, please contact the sender and properly
dispose of the e-mail.
--
--
Laura M. Tully, MA
Social Neuroscience & Psychopathology, Harvard University
Center for the Assessment and Prevention of Prodromal States, UCLA Semel Institute of Neuroscience
ltully@mednet.ucla.edu
ltully@fas.harvard.edu
310-267-0170
--My musings as a young clinical scientist: http://theclinicalbrain.blogspot.com/Follow me on Twitter: @tully_laura