Hi Cornelius,
thank you for your reply.
However, you did not completely answer to my doubts.
Let me make an example:
I am studying a brain area whose connectivity (resting state) seems to
show a positive correlation with a cognitive variable in the patient group
and a negative correlation with the same variable in the control group.
This cognitive variable also differ between groups.
If I want to test the differences between groups in SLOPES, I will demean
within groups. Is it right?
If I want to test the differences between groups in connectivity removing
the effects of the cognitive variable (suppose this has some sense), I
will demean across groups or (according to type of variable) I can not
demean at all. Right?
For the second question: in a design with two groups and a covariate of
interest demeaned across groups. Do I need to use the -D option? And what
if the demeaning is within groups?
Thanks!
Angela
> Hi Angela,
>
> let's see if I got it right.
>
> 1) Besides testing for slopes, I am also interested in average group
> differences. Thus, if ages weren't matched, I would be introducing a
> confound, i.e., any effect introduced by progressing age (e.g. task
> speed) would also influence the group mean. As long as I demean ACROSS
> groups, this will not influence the *group means* and their contrasts
> - in the GLM, any *shared* variability simply disappears (and will
> lower "sensitivity" of either contrast, and rightly so. Teaches me to
> match groups the next time, as Jesper put it two days ago).
> If, on the other hand, I demeaned only within groups, I would not
> correct for the fact that there was a significant contribution of the
> factor "age" to either group. All variability due to the difference of
> age means would be soaked up by the group means and their contrasts.
> Therefore, if these group contrasts showed something significant, it
> might have been just due to the age difference (group a is slower than
> b, but also happens to be the older one!), but not due to treatment or
> diagnosis, or whatever I was actually interested in.
>
> 2) As far as I got it, if you are only interested in correlations with
> a (demeaned) covariate and did not model any group mean, you also
> should demean the data before "randomise"ing. As an example: running
> randomise on VBM data of a depressed patient cohort, looking for GM
> changes correlating with a suicidal ideation score ranging from -5 to
> +5, mean 0. In this case, randomise -D will do the demeaning of the
> DATA (not the covariates) for you, saving you the effort of running
> fslmaths on the data.
>
> If anything of this is wrong, I am sure one of the other contributors
> will point it out rather quickly and I'll have lost posting rights for
> 4 weeks or so :-)
>
> Cheers,
> Cornelius
>
> On Thu, Mar 31, 2011 at 11:36 PM, Angela Favaro <[log in to unmask]>
> wrote:
>> Dear FSL Masters,
>> this discussion has been very helpful for me.
>> But I still have two doubts:
>> 1. Demeaning within groups is more an exception than a rule, but it is
>> the
>> correct thing when I want to test differences between slopes (and not
>> differences between groups). Is it correct?
>> In the example below the two groups have a similar age. What happens if
>> the covariate differs in the two groups?
>>
>> 2. What continues to be unclear to me is the use of the -D option in
>> randomise. When is it necessary/advisable to use it? Only in one group
>> covariate analysis?
>>
>> Thank you
>>
>> Angela
>>
>>
>>
>>> Yeah, that's what I thought. And basically that's why I asked in the
>>> first place :-)
>>> But thanks for all the contributions to this topic. I believe I have
>>> an idea on how to go about it, now.
>>> Best regards,
>>> Cornelius
>>>
>>> On Thu, Mar 31, 2011 at 5:06 PM, Michael Harms <[log in to unmask]>
>>> wrote:
>>>> Just wanted to chime in that demeaning the performance EV separately
>>>> within group is a rather unique case that is specific to this
>>>> particular
>>>> post.
>>>>
>>>> Recent posts by Jesper (just yesterday), Jeannette, Tom, and myself
>>>> have
>>>> all advised that, in general, one should demean across all subjects
>>>> (NOT
>>>> within group separately).
>>>>
>>>> Given the recent posts on this, I thought it was worth making explicit
>>>> that demeaning within groups is not a "typical" situation.
>>>>
>>>> And as a matter of good reporting practice, any time that demeaning is
>>>> performed separately within group, rather than across all subjects,
>>>> that
>>>> should be noted (and justified) very explicitly in any presentation of
>>>> the ensuing results.
>>>>
>>>> cheers,
>>>> -MH
>>>>
>>>> On Thu, 2011-03-31 at 08:42 +0100, Stephen Smith wrote:
>>>>> Hi
>>>>>
>>>>> On 30 Mar 2011, at 11:30, Cornelius Werner wrote:
>>>>>
>>>>> > Hi,
>>>>> >
>>>>> > sorry to revive such a well-worn topic. But there is something I
>>>>> did
>>>>> > not quite get so far.
>>>>> > As an example, I am examining a patient cohort and a control cohort
>>>>> > in
>>>>> > a Dual Regression setup (resting state data). Patients and controls
>>>>> > are matched for age and gender. They obviously differ in diagnosis,
>>>>> > but also in one performance score. I am interested in basic group
>>>>> > differences and the differential correlation of connectivity
>>>>> > strength
>>>>> > of several RSNs with performance. For the final randomise-step, my
>>>>> > design matrix has a column for group mean "patient" and one for
>>>>> > "controls" (consisting of 1, padded with zeroes where applicable),
>>>>> > and
>>>>> > two separate columns for age (as a confounder) - one for each
>>>>> group,
>>>>> > respectively, because an age*group interaction on connectivities
>>>>> > could
>>>>> > not be excluded a priori. As I was modelling the group mean
>>>>> > separately, only the slopes associated with age were tested. Is
>>>>> that
>>>>> > correct so far?
>>>>>
>>>>>
>>>>> I think so - sounds fine.
>>>>>
>>>>> > As the age means did not differ (tested beforehand),
>>>>> > does it matter if I demeaned within group or across groups?
>>>>> > Shouldn't
>>>>> > the intercept be modelled by the group mean regressor, in any case?
>>>>> > Following Tom's last post, I'd probably demean across groups.
>>>>> >
>>>>> > The next thing is even more unclear to me:
>>>>> > Due to an expected group*performance interaction (i.e. steeper
>>>>> slope
>>>>> > of increases in connectivity along with better performance in
>>>>> > contrast
>>>>> > to the other group), also the performance scores are split. BUT:
>>>>> > should I demean?
>>>>>
>>>>>
>>>>> Yes - if you want to compare the *slopes* between the two groups,
>>>>> demean the performance scores within group before padding with zeros,
>>>>> for each group's performance EV.
>>>>>
>>>>> > And if so, within groups, or across groups? In this
>>>>> > case, mean differences in performance are believed to be *due to*
>>>>> > diagnosis - therefore, variability associated with the mean should
>>>>> > go
>>>>> > to the group regressor, shouldn't it? In this case, I'd be inclined
>>>>> > to
>>>>> > demean in order not to affect the group mean regressor negatively,
>>>>> > and
>>>>> > to demean within groups, because of the (clearly) attributable mean
>>>>> > variability...?!
>>>>> >
>>>>> > Example:
>>>>> >
>>>>> > EV1: Patient mean
>>>>> > EV2: Control mean
>>>>> > EV3: Patient age (demeaned across groups - EV of no interest)
>>>>> >
>>>>>
>>>>>
>>>>> I presume you mean demeaned within group, then padded with zeros.
>>>>>
>>>>>
>>>>> Cheers.
>>>>>
>>>>> > EV4: Control age ( " )
>>>>> > EV5: Patient performance score (demeaned within patients)
>>>>> > EV6: Control performance score (demeaned within controls)
>>>>> >
>>>>> > Patients>controls: 1 -1 0 0 0 0
>>>>> > Controls>patients: -1 1 0 0 0 0
>>>>> > Slope(performance score) patients > Slope(performance score)
>>>>> > controls:
>>>>> > 0 0 0 0 1 -1
>>>>> > Slope(performance score) controls > Slope(performance score)
>>>>> > patients:
>>>>> > 0 0 0 0 -1 1
>>>>> >
>>>>> > Please don't hit me - I'm having a hard time getting my head around
>>>>> > this :-)
>>>>> > Cheers,
>>>>> > Cornelius
>>>>> >
>>>>> >
>>>>>
>>>>> ---------------------------------------------------------------------------
>>>>> Stephen M. Smith, Professor of Biomedical Engineering
>>>>> Associate Director, Oxford University FMRIB Centre
>>>>>
>>>>> FMRIB, JR Hospital, Headington, Oxford OX3 9DU, UK
>>>>> +44 (0) 1865 222726 (fax 222717)
>>>>> [log in to unmask] http://www.fmrib.ox.ac.uk/~steve
>>>>> ---------------------------------------------------------------------------
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>
>>>
>>>
>>>
>>> --
>>> Dr. med. Cornelius J. Werner
>>> Department of Neurology
>>> RWTH Aachen University
>>> Pauwelsstr. 30
>>> 52074 Aachen
>>> Germany
>>>
>>>
>>
>
>
>
> --
> Dr. med. Cornelius J. Werner
> Department of Neurology
> RWTH Aachen University
> Pauwelsstr. 30
> 52074 Aachen
> Germany
>
>
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