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Hello William, after playing around a bit with bayesian analysis at the 2nd level another question arose and I hope you can help me with that once again. Is it possible to run a bayesian analysis at the 2nd level for any kind of data? That is, for example running a two-sample t-test where the inputs are preprocessed (smoothed, nuisance regressed, standardized etc.) functional connectivity maps of some seed region instead of contrast maps from a 1st level analysis. Thanks in advance David 2017-02-14 11:46 GMT+01:00 David Hofmann <[log in to unmask]>: > Thanks for the support Willliam! > > greetings > > David > > > 2017-02-07 20:50 GMT+01:00 Penny, William <[log in to unmask]>: > >> Dear David, >> >> >> Here are my answers to your follow-ups. >> >> >> 1. This is hard to quantify - there is potentially an advantage (assuming >> you used some form of spatial prior at the first level) - in that the >> regression coefficients and therefore contrasts are implicitly smoothed by >> a data-defined amount - and this is tuned to each regression coefficient. >> So the advantage, if any, would be that an optimal smoothing would have >> been applied. Whether this justifies the extra amount of time to fit the >> model is up to the user. >> >> >> 2. That's correct - given the connection with FDR there is no need for a >> multiple comparisons correction. >> >> >> 3. The main article to read is: >> >> >> http://www.fil.ion.ucl.ac.uk/spm/doc/papers/karl_posterior.pdf >> >> >> More recently we have added a new functionality for the equivalent of >> F-contrasts which does not require an effect size threshold. It computes >> log-evidence maps and you just threshold the log-odds ratio: >> >> >> http://www.fil.ion.ucl.ac.uk/~wpenny/publications/penny13.pdf >> >> >> Best, >> >> >> Will. >> >> >> ------------------------------ >> *From:* David Hofmann <[log in to unmask]> >> *Sent:* 06 February 2017 11:27 >> *To:* Penny, William >> *Cc:* [log in to unmask] >> *Subject:* Re: [SPM] How to run a (1st + 2nd level) Bayesian analysis in >> SPM >> >> Hi William, >> >> thanks for the helpful reply! I have a few follow-up questions and hope >> you can also help me with those: >> >> 1. Is there any advantage in running a first level Bayesian analysis >> beforehand, i.e. what more can be done? >> >> 2. Is it necessary to correct for multiple comparisons (either 1st or 2nd >> level respectively)? I read that this is never necessary and that a PPM >> thresholded at 95 % confidence is related to an FDR of 5 % in classical >> analysis. >> >> 3. Can you recommend an article which can be cited and that explains the >> method used for running a 2nd level Bayesian analysis on top or a normal >> GLM? >> >> Thanks again! >> >> David >> >> 2017-02-03 14:57 GMT+01:00 Penny, William <[log in to unmask]>: >> >>> Dear David, >>> >>> >>> For one-dimensional contrasts (e.g. t-tests) SPM asks you for two >>> parameters for Bayesian inference at the second level (i) Effect Size >>> Threshold (Default 0.1) and (ii) Log Odds Threshold (Default 10). >>> >>> >>> Other reasonable choices would be 0 and 3. >>> >>> >>> The effect size threshold, T, tells SPM that you are only interested in >>> voxels with contrast values C^beta > T. ie. that your experimental effect >>> is bigger than T. >>> >>> >>> The Log Odds Threshold, L, tells SPM that you are only interested in >>> voxels where SPM is sure (with posterior probability 1/(1+exp(-L)) ) >>> >>> that this is the case. >>> >>> >>> Note that L=3 gives you p=0.95. >>> >>> L=10 is much, much more stringent giving p=0.99995. >>> >>> I would advise you use the most recent version of SPM when doing this. >>> >>> >>> Also, you don't have to do a first level Bayesian analysis if you want >>> to a second-level one. >>> >>> >>> All the best, >>> >>> >>> Will. >>> >>> >>> ------------------------------ >>> *From:* SPM (Statistical Parametric Mapping) <[log in to unmask]> on >>> behalf of David Hofmann <[log in to unmask]> >>> *Sent:* 31 January 2017 10:52 >>> *To:* [log in to unmask] >>> *Subject:* [SPM] How to run a (1st + 2nd level) Bayesian analysis in SPM >>> >>> Hi all, >>> >>> I have an fMRI event-related design in which subjects viewed fearful and >>> neutral faces. I want to run a 1st level and a second level Bayesian >>> analysis in SPM. For this, I did the following steps: >>> >>> 1. 1st level Bayesian analysis with standard settings as described in >>> the manual >>> 2. Contrast fear faces > neutral faces >>> 3. For the 2nd level analysis, I smoothed the con-files and ran a >>> one-sample t-test (estimated the model first with the classical and then >>> with the 2nd level Bayesian option) >>> 4. I specified a t-contrast (i.e. [1]) for the one-sample t-test of the >>> subjects >>> 5. I chose apply masking - none >>> >>> Now SPM is asking me for the *Effect size threshold for PPM at the 2nd >>> level* and suggests 0.99. Whereas the meaning of the effect size >>> threshold was clearly explained in the manual for the 1st level analysis, I >>> not sure what value to choose for the 2nd level analysis and what this >>> value means.When I select the suggested value (0.99) and choose as Log Odds >>> Threshold 10, which should correspond to 95 % certainty, then there is no >>> effect. There are also no effects for a value as low as 0.2. This is >>> very strange since in the classical analysis there are very strong effects >>> (fusiform gyrus) which survive an FWE correction at 0.01. >>> >>> The questions are as follows: >>> >>> 1. Are the analysis steps I did correct or is there a *better* way to >>> test for group effect by means of Bayesian analysis (e.g. Bayesian model >>> comparison, Rosa, M.J. et al., 2010) >>> >>> 2. What does the effect size threshold at the 2nd level mean and what >>> are reasonable values? >>> >>> >>> Here is an overview of posts with topic Bayesian analysis, which did not >>> help me answering my questions: >>> 1.https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=spm;888fe64.1503 >>> 2.https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=SPM;41144d5.1403 >>> 3.https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=SPM;5f9a54e5.1405 >>> 4.https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=ind1603&L=s >>> pm&F=&S=&P=639757 >>> 5.https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=spm;2e6e6dca.1405 >>> 6.https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=spm;a5ab6e97.1603 >>> 7.https://www.jiscmail.ac.uk/cgi-bin/webadmin?A2=SPM;377114fa.0909 >>> >>> >>> greetings >>> >>> David >>> >>> >