Hello,

I've been following the FreeSurfer longitudinal LME analysis tutorial (MailScanner has detected a possible fraud attempt from "secure-web.cisco.com" claiming to be https://surfer.nmr.mgh.harvard.edu/fswiki/LinearMixedEffectsModels), which has been excellent; however I have a few lingering questions pertaining to my specific analysis. For reference, I am interested in assessing rates of longitudinal atrophy in each of my two groups (0=controls, 1=clinical). Regarding what I've currently done:

1). My Qdec file contains 4 columns: fsid, fsid_base, time(years), group

2). I followed the steps to create the appropriate M matrix, and since my preliminary analysis is simply to create a group x time linear model, my design matrix is X = [ones(length(M),1) M M(:,1).*M(:,2)]; and my contrast is CM = [0 0 0 1]

3). I've followed the pipeline for the lme_mass_fit_EMinit, lme_mass_RgGrow, and lme_mass_fit_Rgw functions.

4). I'm skipping the model comparison steps, as I prefer my model with the two random effects (intercept, time).

5). Get stats (F_lhstats = lme_mass_F(lhstats, CM), applied multiple comparison correction ([detvtx,sided_pval,pth] = lme_mass_FDR2(F_lhstats.pval,F_lhstats.sgn,lhcortex,0.05,0); and saved the sided p-values.

My questions are:

a). Since I'm interested in both hemispheres and the tutorial only assesses the left, do I need to do step #3 with the right hemisphere data?

b). Would I need to do the last step in the tutorial to get a single threshold for both hemispheres and then perform the analysis this way?

P = [ F_lhstats.pval(lhcortex) F_rhstats.pval(rhcortex) ];
G = [ F_lhstats.sgn(lhcortex) F_rhstats.sgn(rhcortex) ];
[detvtx,sided_pval,pth] = lme_mass_FDR2(P,G,[],0.05,0);

pcor = -log10(pth)

Thank you for the clarification.

Dan