Thanks a lot Jorge, that's a big help.
On 12 December 2013 23:54, jorge luis <jbernal0...@yahoo.es> wrote: > Hi Sean > > An important issue in the LME model concerns the centering of the times > of measurement. It changes the interpretation of both the mean response and > the variance of the random effects. If tij represents time since baseline > then the subject-specific intercept coefficient ß1+b1i represents the > subject-specific mean response at baseline and Var(b1i) is the > between-subject variation in the mean response at baseline. On the other > hand, if tij is an individual's age at the jth measurement occasion, then > ß1+b1i might not have a useful interpretation since it represents the > subject-specific mean response at age zero. Another choice is to center > the times of measurement for all subjects at some common fixed age within > the age range of the study participants (i.e. tij-a, for some fixed value > a). In this case ß1+b1i represents the subject-specific mean response at > the common age a and Var(b1i ) is the between-subject variation in the > mean response at that age. > > You should use real-valued time measurements so the first and second scan > times on the same subject are always different. > > In your setting you only have two measurement occasions so you can only > use a single random effect. If tij represents time since baseline then > you can only use a random effect for the intercept term and add > age-at-baseline as an additional time-independent covariate (its value > doesn't change through measurement occasions). Otherwise if tij doesn't > represent > time since baseline you can test whether a single random effect for the > time variable works better (i.e see if it produces higher optimal > likelihood values). You can specify a random effect for the slope by > indicating the column of the time variable: > > [stats, st] = lme_mass_fit_vw(X,3,Y,ni,Mask,[],12); > > BTW it is best to order your design matrix in the following way (just for > organizational purposes): > X = [Intercept Age(at scan) Group Group*Age Gender] so the > time-variying covariates appear first. > > You don't need to re-do the design matrix to test the effect of age within > a group (group-specific slope different from zero) just use the appropriate > contrast. > > Hope this helps > > -Jorge > > > El Jueves 12 de diciembre de 2013 14:29, Seán Froudist Walsh < > froud...@tcd.ie> escribió: > > Dear Jorge and FreeSurfers, > > Would you mind having a look at my set-up and advising on whether it is > correct or needs changing? > > I have participants with one or two scans, who are divided into two > groups. I'm interested in the longitudinal effects of aging, and the > difference in the effect of age on the two groups. Not all people were > scanned at exactly the same age, and the interscan interval in not exactly > the same for each person. Rather, the age at scan looks like a bimodal > distribution around the mean 1st and 2nd timepoint. > > I believe I read on the list that you should have more timepoints than > random effects. I guess I should then only name one random effect > (intercept). > > At the moment I have my model set up as follows: > > X = Intercept Group Age(at scan) Group*Age Gender > [stats, st] = lme_mass_fit_vw(X,1,Y,ni,Mask,[],12); > > CM.C = [0 0 0 1 0] > > I guess I should then run > * lme_mass_F(stats,CM); * > and > > *lme_mass_FDR2.* > Here I am trying to look find the areas that develop differently between > the two groups over the timespan we are studying. If you would be able to > advise me as to whether I have set up the model wrong it would be greatly > appreciated. Age in this case refers to the the age at scan time, > regardless of whether it is the first or second scan, so many participants > will have two distinct values in the age column. > > Also, is it possible within this set-up to test the effect of age within a > group, or would that require re-doing the design matrix? > > Finally, is it possible to include the by-subject random slopes for the > effect of age? In R (lmer) it would be something like (1+age|subject). > > Best wishes y gracias, > > Seán > > > > _______________________________________________ > Freesurfer mailing list > Freesurfer@nmr.mgh.harvard.edu > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/freesurfer > > > The information in this e-mail is intended only for the person to whom it > is > addressed. If you believe this e-mail was sent to you in error and the > e-mail > contains patient information, please contact the Partners Compliance > HelpLine at > http://www.partners.org/complianceline . If the e-mail was sent to you in > error > but does not contain patient information, please contact the sender and > properly > dispose of the e-mail. > > >
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