Dear FS-Group
I am attempting to use the lme matlab tools for my longitudinal analysis.
My dataset consists of 2 time-points and 2 groups (patients and controls). I will not use covariates since the groups are well matched for age, gender and education.
I am trying to adapt the wiki instructions of the mass-univariate model to our data.
Our design matrix X contains 4 columns:
1. intercept
2. time
3. group
4. interaction group*time
Our Cmd history:
[Y,mri] = fs_read_Y('lh.thickness_sm15.mgh');
lhsphere = fs_read_surf('/subjects/average_LTHV_long_all_49/surf/lh.sphere');
lhcortex = fs_read_label('/subjects/average_LTHV_long_all_49/label/lh.cortex.label');
Qdec = fReadQdec('qdec.long.table_4columns.txt');
Qdec = rmQdecCol(Qdec,1);
sID = Qdec(2:end,1);
Qdec = rmQdecCol(Qdec,1);
M = Qdec2num(Qdec);
[M,Y,ni] = sortData(M,1,Y,sID);
X = [ones(length(M),1) M M(:,1).*M(:,2)];
lhstats = lme_mass_fit_vw(X, [4], Y, ni, lhcortex)
I am mainly interested in comparing longitudinal changes between groups (group*time interaction) but also interested in the main effect of group and time.
I have two questions:
1. I am not sure about my „interpretation“ of random and fixed effect. Since I am interested in the group*time interaction (4. column), does it make sense to use a single random effect for this interaction or should I take a second random effect for time (2. column)?
2. If a model with two random effects make sense (2. and 4. column), should I compare the model including two random effects with a model with a single random effect to test which one is significantly better?
Thank you for your help!
Patrizia