No, what I'm saying is true for the specific 2nd level design that was
originally proposed as a template -- the "ANOVA: 1-factor 4-levels
(Repeated Measures)" example on the FEAT website.
cheers,
-MH
On Fri, 2011-05-13 at 05:04 +0900, Hyo Jong Lee wrote:
> If your hypothesis denpends on gender and age, those should be
> covariated.
> I guess what Michael explained is true in the first level analysis.
> You may include the gender and age, which is demeaned seperately for
> gender in
> the higher level analysis.
>
> Hyo Jong
> --- Original Message ---
> From : "Alexander Olsen"<[log in to unmask]>
> To : [log in to unmask]
> Date : 2011/05/13 금요일 오전 4:20:38
> Subject : Re: [FSL] help! repeated measures with covariate in
> FEAT
>
> Thanks again! so then I will go along with setting up the
> analysis
> without covariates :)
>
> cheers,
> Alex
>
> Michael Harms wrote:
> > Yes, I understand that you were inquiring about controlling
> for gender
> > across subjects (gender presumably isn't changing within a
> subject
> > unless you're conducting a study involving sex change
> operations!). But
> > in a repeated measures design, in which you have an EV with
> a column of
> > 1's at your 4 timepoints for each subject (to model the mean
> of that
> > specific subject), and you have such an EV for each subject,
> then your
> > gender EV can always be expressed as linear combination of
> the subject
> > specific mean EVs, and thus you would have a rank deficient
> design
> > matrix. The same reasoning applies to age if you were to use
> the same
> > age value at all 4 timepoints for a given subject.
> >
> > cheers,
> > -MH
> >
> > On Thu, 2011-05-12 at 20:14 +0200, Alexander Olsen wrote:
> >
> >> Ok. I see. However, I don't thing this was what I wanted to
> do. What I
> >> want to do is to control for age and gender differences
> between
> >> subjects, not within subjects (e.g. control for the fact
> that I have
> >> more younger than older participants, look at gender*time
> effects etc.).
> >> Sorry if I'm not being very clear.
> >>
> >> Alexander
> >>
> >> Michael Harms wrote:
> >>
> >>> You can't covary for gender in your repeated measure
> model, for the
> >>> reason that I explained. Try including a gender covariate
> and you'll
> >>> find that your design matrix will be rank deficient. As
> for age, it
> >>> would only be an option to consider if you want to use a
> different value
> >>> for age for each repeated visit of a subject, and even
> then I think
> >>> you'll get a poorly conditioned design matrix unless your
> age at the
> >>> repeated visits for a subject differed in an appreciable
> manner (where
> >>> "appreciable" would be relative to the variation in ages
> across
> >>> subjects).
> >>>
> >>> cheers,
> >>> -MH
> >>>
> >>> On Thu, 2011-05-12 at 19:44 +0200, Alexander Olsen 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
> >>>>>>
> >>>>>>
> >>>>>>
>
>
>
> -----
> Professor
> Dept. of Computer Science and Engineering
> Chonbuk National University, Korea
> ----
> Visiting scholar
> Dept. of Human Behavior and Psychology
> UC Irvine, CA
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