Thanks for your suggestion Donald. How would you go about to set up the
design martrix (in FEAT) in this case?
MCLAREN, Donald wrote:
> I'd agree on the age part since its likely everyone is a different
> age; however, I'd add gender as a covariate and make it interact with
> the repeated measure (essentially coding it as the covariate and also
> as the covariate*each measure). This would allow you to investigate
> any gender*measure interactions.
>
> Best Regards, Donald McLaren
> =================
> D.G. McLaren, Ph.D.
> Postdoctoral Research Fellow, GRECC, Bedford VA
> Research Fellow, Department of Neurology, Massachusetts General
> Hospital and Harvard Medical School
> 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, May 12, 2011 at 1:44 PM, Alexander Olsen
> <[log in to unmask] <mailto:[log in to unmask]>> wrote:
>
> Hi Michael,
> Thank you so much for helping me. So that means that I should set
> up the design matrices without any covariates for age and gender?
>
> cheers,
> Alexander
>
>
>
> Michael Harms wrote:
>
> Hi Alexander,
> Given that you are modeling the mean of each subject using a
> repeated
> measures design, that mean already incorporates that subject's
> age and
> gender as part of its estimate. That is, if you added EVs for age
> and/or gender, those EVs can be represented as a linear
> combination of
> the columns modeling each subject's overall mean, and thus you
> would get
> a degenerate design matrix. (This wouldn't strictly be true
> for age IF
> the value you used for age differed across the repeated scans of a
> subject, but unless your scans were spaced far apart
> temporally, you
> still might get a poorly conditioned design matrix).
>
> cheers,
> -MH
>
> On Thu, 2011-05-12 at 01:12 +0100, Alexander Olsen wrote:
>
>
> Dear FLS experts, I'm struggling a bit with setting up my
> analysis. What I would like to do is a repeated measures
> design with four timepoints, as in this example:
> http://www.fmrib.ox.ac.uk/fsl/feat5/detail.html#ANOVA1factor4levelsRepeatedMeasures
>
> However, I would also like to add age and gender as
> covariates in order to "remove" these effects. I hope
> anyone can help me, or direct me to an example which
> describes this.
> Thank you so much in advance.
> Alexander
>
>
>
|