External Email - Use Caution Hello,
I've been following the FreeSurfer longitudinal LME analysis tutorial ( https://secure-web.cisco.com/1UXjrD54pEj2u6JH6Y-Z-dHoSgY6qcbXqPg43uVU2GGyBvmGYSpOkab0ovGwllJVYA7PInB9Oa-cCSrq2yGN2zfn8EBAUtT_yeaabIRnE4HnyhF8G3FJoSd6nbCQUf195Ng-xfgCokq08rSxUZyhLIudt89kSPoVeftxH2HVDuF_OGK79dGemsmZ9orDudMA-Cp7oYpc2RXdD8YCqfNyYt6_scLBGlRJRuEPFUB2VJ1FxbOhV03qDT2ew4MzWMCKM0Xw_IVRTpq4P4ugt6Je82KwqRE7bJ9N2IKyLNPi8qFlU0jq_4SXO3FEcOVXsCNepnt7A5dSfDApyBtv-yOTbHA/https%3A%2F%2Fsurfer.nmr.mgh.harvard.edu%2Ffswiki%2FLinearMixedEffectsModels), 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
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