Dear Peter,
thank you for your suggestion, I'll experiment with this solution.
One problem is that I will need to define families within BMS; but maybe I could
bypass it by arbitrarily assigning models to e.g. 2 families and then calculate
BMA over 'All Families'?
If your colleagues at the FIL have other suggestions, please let me know.
Best!
Marco
On 08/28/2014 09:06 AM, Zeidman, Peter wrote:
> Dear Marco, This is a good question. One possibility would be to create all
> the models you want for a subject (as actual DCM files), and then use
> spm_dcm_search (or the 'search' item from the DCM menu) to estimate them all
> at once using the post-hoc scheme. Then repeat this for each subject. You
> could now do BMS / BMA on the models in the normal way.
>
> I'll speak to my colleagues at the FIL to see if anyone has any other ideas.
>
> Best, Peter.
>
--------------------------------------------------------------------------
IL MIO 5XMILLE VA AL SAN RAFFAELE DI MILANO
PERCHE' QUI LA RICERCA DIVENTA CURA.
CF 07636600962
SE NON QUI, DOVE?
Info: [log in to unmask] - http://www.5xmille.org/
Disclaimer added by CodeTwo Exchange Rules 2007
http://www.codetwo.com
> -----Original Message----- From: SPM (Statistical Parametric Mapping)
> [mailto:[log in to unmask]] On Behalf Of marco tettamanti Sent: 27 August
> 2014 17:09 To: [log in to unmask] Subject: [SPM] DCM network discovery and
> comparison between groups
>
> Dear all, I have a question regarding the correct manner to perform a
> between-group comparison within the framework of DCM network discovery.
>
> In the framework of BMS, the suggested approach in the presence of more than
> one experimental group (or family), when the winning models for the different
> groups differ with respect to parameters/connections, is to use Bayesian
> Model Averaging (Penny et al. 2010). This provides weighted summary coupling
> parameters e.g. over the entire model space of each group, and it then allows
> to perform between-group comparisons, thus avoiding conservative assumptions
> about any particular model.
>
> In one experiment, I have now used DCM network discovery, instead of BMS, to
> identify a group-specific optimum model for two different experimental
> groups. The resulting optimum models have different parameter/connection
> configurations between the two groups, and it is therefore difficult to
> perform between-group comparisons on the coupling parameters. The problem is
> that in this case BMA does not seem to be a viable solution since, strictly
> speaking, I only have one model per group (i.e. the winning model), instead
> of a model space constituted by several models whose parameters can be
> averaged. Are there any recommended approaches to overcome this problem in
> this case?
>
> I could e.g. manually specify and estimate a set (or even the full set?) of
> alternative models to the optimum model, then perform BMS to actually verify
> that the optimum model is indeed the winning model, and, contextually, also
> calculate BMA. But this does not seem a very efficient solution. Also, I
> would need to specify families to calculate BMA, and I do not think that
> there is any particular rationale to do so here.
>
> Another solution that I have explored is, given that for each subject I have
> both the fully connected model entered in the DCM network discovery and the
> output optimum model, I can in principle perform BMS entering the two models
> for each subject and arbitrarily assigning the fully connected model to
> family 1 and the optimum model to family 2, and in such a way calculate BMA.
> But I am not sure that this is a sensible solution. In addition, in one of my
> two experimental groups, the optimum model has the same number of
> connections/parameters as the fully connected model (though e.g. DCM.F
> differs between the two models). Therefore, BMS/BMA seems to make even less
> sense to me.
>
> Any help would be warmly appreciated!
>
> Thank you and best wishes, Marco
>
> -- Marco Tettamanti, Ph.D. Nuclear Medicine Department & Division of
> Neuroscience San Raffaele Scientific Institute Via Olgettina 58 I-20132
> Milano, Italy Phone ++39-02-26434888 Fax ++39-02-26434892 Email:
> [log in to unmask] Skype: mtettamanti
> http://scholar.google.it/citations?user=x4qQl4AAAAAJ
> -------------------------------------------------------------------------- IL
> MIO 5XMILLE VA AL SAN RAFFAELE DI MILANO PERCHE' QUI LA RICERCA DIVENTA
> CURA. CF 07636600962 SE NON QUI, DOVE? Info: [log in to unmask] -
> http://www.5xmille.org/
>
>
> Disclaimer added by CodeTwo Exchange Rules 2007 http://www.codetwo.com .
>
--
Marco Tettamanti, Ph.D.
Nuclear Medicine Department & Division of Neuroscience
San Raffaele Scientific Institute
Via Olgettina 58
I-20132 Milano, Italy
Phone ++39-02-26434888
Fax ++39-02-26434892
Email: [log in to unmask]
Skype: mtettamanti
http://scholar.google.it/citations?user=x4qQl4AAAAAJ
|