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