Hi Freesurfers,

For obtaining my undergraduate degree I’m performing a study using Freesurfer. I’m stuck with the centering (de-meaning) issue. I have two discrete variables, gender, and patient-control, and a continuous variable which is age. The age population range goes from 20 to 55 years and is paired between patients and controls. Patient’s disease affects cortical thickness over time and every patient has been presenting the disease for 6 years (no more, no less). I’ve runned QDEC and mri_glmfit using DODS obtaining the same results, the problem is that when I demean the age (I used the grandmean) the results are very differente. If I don’t demean some clusters survive the monte-carlo multiple comparisons correction (p<0.05), but, when I demean no cluster survive. I have this questions:

1. Since most of my subjects are in the range of 20-35 years and only a few have more than 35 years, it is correct to use the mean? Wouldn’t be better to use the median or some other value?
2. This is maybe a silly question, but why should I care about the intercept? I know that demeaning doesn’t change the slope, just the intercept, but I don’t understand why I should care, I read in some publications that demeaning is not always necessary.

1. Most of my subjects are women (around 80%, N=18), Does it have an advantage to remove the males to get rid of the gender variable?, or should I continue as I’ve been doing, controlling for the effect of gender.
2. Since I don’t know if this disease is more aggressive when is developed at some stage of life, I mean, if young patients are less affected than older patients after six years of presenting it, it is correct to control the effect of age? (Entering the variable as a nuisance factor), or should I search for an interaction between age and the condition variable? I only care about differences in cortical thickness.

Any suggestion is very welcome, thanks in advance for your answer.

Rodrigo