We were running an analysis (95 subjects) examining a group effect (two groups, controlling for the effects of a covariate and two cofactors, DODS model) on cortical thickness with mri_glmfit. We then corrected our results for multiple comparisons using two methods, FDR and Monte Carlo simulation with 4000 repeats. The threshold was set at p=0.05 respectively. Although examining the same population we got results in very different regions.
command for the simulation:
mri_glmfit-sim --glmdir xxxx.glmdir --sim mc-z 4000 1.301 mc-z abs.1.301 --sim-sign abs
the fdr results were obtained setting the fdr-threshold at p=0.05 with the tksurfer script command (sclv_set current_threshold_using_fdr 0.05 0)
With the fdr method we found a spot in the left supramarginal gyrus and with the clusterwise correction we got a cluster in the right middle temporal lobe (see pictures of corrected and uncorrected results attached). No other clusters/findings survived one of the correction methods.
We are well aware of the fact that FDR and Monte Carlo simulation are very different statistical methods and that FDR is more conservative. Does that explain the discrepant results? Would you expect a highly robust FDR finding to not show up at all when using Monte Carlo? What additional information could be used to decide which method to use for the final models?