Hi Pedro
Sorry, right now the only multiple comparisons corrections implemented in lme
are the original Benjamini and Hochberg (1995) FDR procedure (lme_mass_FDR) and
a more recent and powerful two-stage FDR procedure (lme_mass_FDR2):
Benjamini, Y., Krieger, A.M., Yekutieli, D. (2006). Adaptive linear step-up
procedures that control the false discovery rate. Biometrika, 93, 491-507.
In my experience, this procedure is as powerful to detect effects in neuroimage
data as alternative corrections with strong control of the family-wise error
rate (FWE). However it would be great if we could use an implementation of any
multiple comparisons correction with strong control of the FWE (MC, RFT,
ect...) for lme (FDR procedures only provide weak control). The residual errors
at each location required to compute an estimate of the image FWHM can be
obtained from the lme output. But an actual FWHM estimate is not currently
saved.
Best
-Jorge
El Martes 25 de marzo de 2014 8:15, Pedro Rosa <pedrogomesr...@gmail.com>
escribió:
Dear Doug,
>Thank you very much!
>I will try what you suggested, although I am not sure if Jorge's stream
>outputs the FMHM, or if I would need to run the statistics from the beggining
>using in the terminal, and not in MatLab.
>Do you think Jorge could comment on this issue?
>Regards,
>Pedro Rosa.
>
>On Mar 24, 2014, at 12:44 PM, Douglas Greve <gr...@nmr.mgh.harvard.edu> wrote:
>
>
>In theory, it should be possible. I have not used Jorge's stream, so I
>don't know that much about it. Does it save an estimate of the FWHM? If
>so, then you can run mri_surfcluster passing it the p-value (ie,
>-log10(p)) map, the FWHM, the mask, and a voxel-wise threshold. This is
>what mri_glmfit-sim does, so you might check that script for
>mri_surfcluster command line options
>
>doug
>
>
>> On 3/22/14 11:03 PM, Pedro Rosa wrote:
>> Dear list,
>> I ran the recon-all and the Freesurfer 5.1 longitudinal pipeline in a
>> structural MRI dataset and I would like to use Monte Carlo as the method for
>> correction for multiple comparisons. However, the longitudinal LME tutorial
>> includes only FDR correction (lme_mass_FDR2).
>> Is it possible to use Monte Carlo correction for longitudinal data? Can I
>> input the outputs from MatLab (fstats = lme_mass_F(?h,CM): stats.F / pval /
>> sgn / df) into mri_glmfit and then run Monte Carlo?
>> If not, do you have any other suggestions of how I use Monte Carlo in
>> longitudinal analyses?
>> Thanks in advance,
>
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