Hi all,
I’ve successfully run 3dMVM on a dataset to do second level analyses. Do you have any suggestions as to what I should use to do cluster correction? I’ve used -clustsim in for t-tests, but that is not part of 3dMVM. I’m also not certain how to come up with a smoothing factor if that is required. I used a smoothing kernel of 4mm on my data, but I know it’s the smoothness of the residuals that matters. I did output an errts datasets for each case. My guess is I use 3dClustSim, but I’m not sure how to use it or how to apply it to the dataset I’ve obtained.
I also was curious how to apply ETAC or ACF options to this analysis.
Thanks!
Matt
Hi all,
I just wanted to check in on whether you could offer any advice on how best to do a group-level threshold on data analyzed using 3dMVM, as I do not see a ClustSim option for that program. In the past, I had seen that we could average the <3dFWHM errts*> output values across subjects to use as the smoothing parameter in 3dClustSim. Is that what one would do in the case of ACF (i.e., average each of the values in the output of 3dFWHMx)?
Thanks,
Matt
I had seen that we could average the <3dFWHM errts*> output values across subjects to use as the smoothing parameter
in 3dClustSim. Is that what one would do in the case of ACF (i.e., average each of the values in the output of 3dFWHMx)?
Some extent of arbitrariness is involved here. In addition to the averaging approach, another conventional method is to obtain the population-level residuals from, for example, 3dMVM using the option -resid, and then estimate the spatial smoothness on the population-level residuals.
Do I use 0.71478 5.91395 9.13712 in the 3dClustsim?
Yes, I believe that’s correct. The first three numbers are the (a,b,c)-parameters from the ACF expression, and the last number (13.7085) is the effective FWHM.
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