Sure, I understand that. Perhaps I need to reword me question.
I do plan to select VOI based upon a group level contrast and using a
cutoff distance from the group peak in selecting individual VOIs. My
concern lies in the event activation from one subject in one or two of
three sessions is absent or does not meet my selection criteria. Knowing
that parameter semesters across sessions will be averaged, is it advised
to remove the subject from further analysis or only the sessions of that
subject that do not meet selection criteria, thereby creating average
parameter estimates based on, let's say, 2 sessions rather than 3. Does
that make more sense?
Many thanks,
Drew
On 5/29/13 4:29 AM, "Zeidman, Peter" <[log in to unmask]> wrote:
>It may be that you don't have effects at the level of an individual
>session due to a lack of power - there could be an effect, but not
>significant unless you look at it at a group level. How you choose the
>location of your ROI depends on your question, but it would be unusual to
>do it on a session-by-session basis. Consider choosing the location based
>on activations in the group level second-level contrast. Or anatomically
>if that is more relevant to your question...
>
>P.
>
>> -----Original Message-----
>> From: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]]
>> On Behalf Of Sevel,Landrew S
>> Sent: 28 May 2013 18:22
>> To: [log in to unmask]
>> Subject: Re: [SPM] DCM-related questions
>>
>> Thanks for your reply.
>>
>> I see that it would be preferable to include all sessions and all
>> subjects. If activation is not show in one session though, it would not
>> be possible to make an an eigenvariate from the contrast showing your
>> effects of interest (even if you used an incredibly generous p-value
>> the resulting time series would negatively impact resulting model fit
>> and interpretation). If you were to throw out one session of three that
>> were going to be averaged, the affected subject's parameters would be
>> based upon a different amount information than others. To completely
>> remove this subject would at the same time lose two sessions of
>> potentially relevant information. Is there a preferable course of
>> action?
>>
>> Best,
>>
>> Drew
>> ________________________________________
>> From: Zeidman, Peter [[log in to unmask]]
>> Sent: Tuesday, May 28, 2013 6:24 AM
>> To: Sevel,Landrew S; [log in to unmask]
>> Subject: RE: DCM-related questions
>>
>> Hi Drew,
>>
>> > If we were to concatenate all three sessions, would the scale of each
>> time series be in the same metric? If this is not the case, are there
>> any sets I can take to correct this issue?
>>
>> It's best not to concatenate, but if you need to, you'll need to add an
>> extra regressor for all but one session in your GLM. I.e. given three
>> sessions, you'll have a column marking every scan from session 1 and a
>> column for every scan from session 2. These will model the mean for
>> each session. (You shouldn't have a regressor for the last session, or
>> your model will be over-specified).
>>
>> > In the event that we were not to concatenate sessions but to average
>> parameters across models after model selection for parameter comparison
>> between groups, are there any guidelines in the event that one or two
>> of three sessions does not show significant activation in our VOIs?I'm
>> aware that it is standard to remove single subjects from analysis if
>> they do not obtain significant activation in VOIs, but what about
>> single sessions?
>>
>> In general I would include all sessions and subjects, not just those
>> showing the effects at the individual level.
>>
>> > Lastly on parameter interpretation. For the connection A-->B,
>> increases in activity of B correspond to 10% of the activity in A per
>> unit time when the parameter is 0.10. Can these values exceed 1.00 and
>> if so how could this be interpreted?
>>
>> Someone else may know better than me - but I believe they can go over
>> 1, which would mean a value of 1.1 would mean region B increases by
>> 1.1 times the activity in unit A in the context of your modulation.
>>
>> Best,
>> Peter.
>>
>
>
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