Hi, I think (hope) i am finally getting to grips with how to analyse things but wanted to check one last thing.
Say I have 1 factor with 3 levels (3 groups of subjects) and 2 covariates (age and icv). My design matrix would include: Regressor 1 - ones for subject in Gp 1, 0 otherwise, codes intercept/mean for gp 1 Regressor 2 - ones for subject in Gp 2, 0 otherwise, codes intercept/mean for gp 2 Regressor 3 - ones for subject in Gp 3, 0 otherwise, codes intercept/mean for gp 3 Regressor 4 - age for subjects in Gp 1, 0 otherwise, codes age slope for gp 1 Regressor 5- age for subjects in Gp 2, 0 otherwise, codes age slope for gp 2 Regressor 6 - age for subjects in Gp 3, 0 otherwise, codes age slope for gp 3 Regressor 7 - icv for subjects in Gp 1, 0 otherwise, codes icv slope for gp 1 Regressor 8 - icv for subjects in Gp 2, 0 otherwise, codes icv slope for gp 2 Regressor 9 - icv for subjects in Gp 3, 0 otherwise, codes icv slope for gp 3 In terms of contrast would the following be correct: 1.5 0.5 -1.5 0 0 0 0 0 0 - to look for linear change in dependent variable across groups after correcting for age and icv 0 0 0 1.5 0.5 -1.5 0 0 0 - to look for linear change in age slope against dependent variable across groups while correcting for icv ie whether age-dependent measure correlations get stronger/weaker across gps Thanks Mahinda _______________________________________________ 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.
