Dear Arkan
Sorry I still don't understand. Let's say you have estimated a group-level model of the subjects' parameters (a PEB model). This gives you:
- Parameters representing the group average connection strengths (expected values and covariance)
- Parameters representing the variability in the connection strengths across subjects
- The free energy of the group level model, which you can use to compare group level models with different covariates.
Now you introduce an additional (left-out) subject who was not included in the analysis above. What would you like to do with that subject's data and why? You say you would like "to predict the connectivity and hemodynamic parameters" - predict this from what? The left-out subject's behavioural scores? And for what purpose?
Hopefully with some more detail we can give you some advice.
Best
Peter
-----Original Message-----
From: Arkan Al-Zubaidi [mailto:[log in to unmask]]
Sent: 20 June 2018 11:13
To: Zeidman, Peter <[log in to unmask]>; [log in to unmask]
Subject: Re: [SPM] Accuracy of DCM model
Dear Peter,
I would like to to know the accuracy of spectral DCM model to predict the connectivity and hemodynamic parameters for a subject from DCM parameters of group of subjects.
Can I do something similar to the following lines?
If this code is correct, how can I setup the hemodynamic parameter in field cell array?
Mean_effect=ones(20,1); % one group of 20 subjects
CP_4_5 = [GCM(1,1).Ep.A(4,5); GCM(2,1).Ep.A(4,5); ........; GCM(20,1).Ep.A(4,5)]; % connectivity parameters from connection 5 to 4 field = {'A(4,5)'}; M.X = [Mean_effect,CP_4_5]; [qE,qC,Q]=spm_dcm_loo(GCM,M,field);
Best regards,
Arkan
________________________________________
From: Zeidman, Peter <[log in to unmask]>
Sent: 20 June 2018 11:13
To: Arkan Al-Zubaidi; [log in to unmask]
Subject: RE: [SPM] Accuracy of DCM model
Dear Arkan
The Leave-One-Out (LOO) function is intended to check whether your effect sizes (DCM parameters) are large enough to predict subject-level covariates (e.g. group membership or behavioural scores). However, you say you want to predict unseen subjects' effective connectivity parameters, in order to validate DCM. I don't understand that. Please could you clarify the validation you are trying to perform?
All the best
Peter
-----Original Message-----
From: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]] On Behalf Of Arkan
Sent: 19 June 2018 16:55
To: [log in to unmask]
Subject: [SPM] Accuracy of DCM model
Dear SPM list,
I know that the spm_dcm_loo function is for distinguishing (classify) between two groups if the subject is unseen.
Here, I would like to validate the spectral DCM model to predict the unseen subject parameters (effective connectivity and hemodynamic) for one group.
How can I use the spm_dcm_loo function in this case?
I would like to plot the expected parameter and the real parameter (not the classification).
Regards,
Arkan
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