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Dear Yin,

The params(1).model(1).Ep.D field corresponds to the non-linear DCM parameters D. The BMA function only works with DCMs estimated with the newest version of DCM (version 4010): ftp://ftp.fil.ion.ucl.ac.uk/spm/spm8_updates.

If estimated with the newest version, DCM.Ep always contains a field D. If the DCM is linear the dimensions of this field are [nregions x nregions x 0]; if the DCM is nonlinear the dimensions are [nregions x nregions x nregions].

More information about non-linear DCMs:
http://dx.doi.org/10.1016/j.neuroimage.2008.04.262

I hope this helps.
Maria

On Thu, Aug 12, 2010 at 3:23 PM, Yin Wang <[log in to unmask]> wrote:
Dear Experts,
 
I just finished my BMS and found the best model. But I have to get all the parameters for the optimal model when I start to write. I have two questions for getting these parameters.
 
1) I know I can use the new BMA function to get these parameters, however when I used the function, there is an error following like this:
 
Running 'BMS: DCM'
Loading model space
Computing FFX model/family posteriors ...
FFX Bayesian model averaging ...
 
6 models in Occams window
Model 15, p(m|Y)=0.13
Model 16, p(m|Y)=0.14
Model 17, p(m|Y)=0.01
Model 18, p(m|Y)=0.07
Model 19, p(m|Y)=0.07

Failed  'BMS: DCM'
Attempt to reference field of non-structure array.
In file "C:\Program Files\MATLAB71\toolbox\spm8\spm_dcm_bma.m" (v3966), function "spm_dcm_bma" at line 255.
In file "C:\Program Files\MATLAB71\toolbox\spm8\config\spm_run_bms_dcm.m" (v3955), function "spm_run_bms_dcm" at line 341.
The following modules did not run:
Failed: BMS: DCM


The syntax at line 255 is:  dimd = size(params(1).model(1).Ep.D,3);
 
I checked and found no data called params(1).model(1).Ep.D, what is D here representing for? I don't know why the BMA fails,  but the BMS ffx works very well.
 
Thanks
 
2) as I failed in BMA, then I have to use the classical t-test approach. I loaded the best model's DCM file in every participant's folder. However, I was frustrated about the parameters called A, pA, vA. What are the differences between them? Which one should I use for the intrinsic connection of the best model? 
 
Thank you very much
 
Yin
--
Yin Wang
Antonia Hamilton's Social Cognition Lab
School of Psychology
University of Nottingham,
University Park, Nottingham, UK
NG7 2RD
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