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Dear Shary,

SPM8 should be installed in a separate folder. 

There is no single publication, to my knowledge, that can be used as a reference for SPM8.  Instead, for the different analyses steps you should refer to the specific papers.  Articles describing the innovations in SPM8 are listed in the release notes which you can find on the web:
http://www.fil.ion.ucl.ac..uk/spm/software/spm8/SPM8_Release_Notes.pdf

Best wishes,
Klaas



Von: Shary <[log in to unmask]>
An: Klaas Enno Stephan <[log in to unmask]>
Gesendet: Mittwoch, den 8. Juli 2009, 15:28:09 Uhr
Betreff: SPM8 reference(s)?

Hi Klaas,

I have lost touch with SPM in the past few months.  Hopefully, you can help me with the following questions:

1. Should I unzip SPM8 into SPM5's folder?
2. Is there any publications that I can use in my next paper as reference for SPM8?  Currently, I use SPM5.

Thanks a lot,
Shary


From: Klaas Enno Stephan <[log in to unmask]>
To: [log in to unmask]
Sent: Wednesday, July 8, 2009 10:06:55 AM
Subject: Re: BMS DCM SPM8

Dear colleague,

The subject-specific log model evidences are the input to the random effects BMS procedure, not its output.  In other words, if you use the random effects BMS method, there is no need to look at any differences in log model evidence.  The results that you are interested in are the expected posterior model probabilities (exp_r) and the exceedance probability of all models (xp).  Both of them will give an identical ranking of models and tell you which model is the best. 

Best wishes,
Klaas



Von: Maz <[log in to unmask]>
An: [log in to unmask]
Gesendet: Mittwoch, den 8. Juli 2009, 06:11:23 Uhr
Betreff: [SPM] BMS DCM SPM8

Dear SPMers,

Really needs help regarding BMS in SPM8. After comparing 6 subject/ 4 models
each, and got all the BMS.DCM.rfx value (F, SF, alpha, exp_r and xp). How
should I conclude the result? In Stephan (2009) paper, I should calculate
log model evidence differences, this is the F value right? For example, the
values for subject 1, model 1 is -505.75 and model 2 is -510.76. There for
log model evidence differences (only the magnitude?) = 510.76 - 505.76 = 5.
Favour model 2. Is this the correct way? Is this method can only consider 2
models (Best and 2nd Best Models)?

Other than that I also need to consider the exceedance probability value.

Thank you in advanced.