Charlotte,
There is no difference, from a statistical perspective, of nuisance factors and covariates.
The key questions are: (1) Do any of these covariates have a differential effect on thickness between groups? (2) Do you want to compare the actual group means or the covariate-adjusted group means (e.g. test the means for subjects as if the subjects all had the same covariate values)? (3) Do you have enough subjects to add 5 covariates? (4) Do you have a valid reason for why all the covariates would have an effect on thickness? One can always add more covariates to reduce the error, but its not always a good thing to add covariates just to reduce the error of the model.
On 2/23/12, Charlotte Bernard chakeba@live.fr wrote:
Dear Freesurfur users,
I have a question about the design for a surface based analysis! I want to compare controls and patients. I have 5 covariates. One is a continous variable. The others are categorial variables (4 with 2 levels and 1 with 5 levels). I want to ajust my result with all of thoses variables. I am interested in the difference in thickness between patients and controls. Is it possible to construct such design? Can I put some of my variables in the "nuisance factors" ? I don't really understand the difference between "nuisance factor" and covariabes. I really hope somebody can help me. Thanks for all! All the best, Charlotte