Dear Stefan,
The computation of the exceedance probability is based on a sampling approach - which can potentially produce small differences each time you run it.
To see if the differences are due to this 'sampling variability' perhaps you could just run
the algorithm twice with exactly the same configuration (eg. both with no families) to see what the variability is.
To reduce this variability you can increase the number of samples used - there's an option in the GUI for this.
Best,
Will.
> -----Original Message-----
> From: SPM (Statistical Parametric Mapping) [mailto:[log in to unmask]]
> On Behalf Of Stefan Frässle
> Sent: 13 June 2013 14:17
> To: [log in to unmask]
> Subject: [SPM] DCM: BMS
>
> Dear DCM experts,
>
> I have a question regarding BMS RFX for DCM. I compared 16 DCM models
> for fMRI data and found one model to be the best with an exceedance
> probability of around 0.6.
>
> In a subsequent analysis step I intended to compared the 16 models
> according to a specific property, thus creating 4 different families
> (each including 4 models) in order to compare those families.
>
> When running the batch (including the definition of the families) SPM
> still shows me information about the comparison of the individual
> models and I noticed that the exceedance probability for my winning
> model is now around 0.7!
>
> I'm confused why there are differences in the exceedance probabilities
> when defining families as compared to when I just compare the
> individual models?
>
> I would be very grateful, if anyone could give his opinion on why this
> occurs.
>
> Thanks a lot in advance
> Stefan
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