Dear Freesurfer’s experts,

I would like to test if neuropsychological score across time (continuous time-varying covariate) has an effect on metabolism maps. However, I don’t manage to understand how to define design matrix and contrast associated to assess it with LME models.

I picked up from one former mailing list discussion including Jorge:

we recommended to order the columns of the design matrix in the following way:

Column 1: the intercept term (which is a column of ones)

Colum 2: the time covariate if it varies across subjects (eg. time from 
baseline)

Column 3-q: any time-varying covariates (eg. training: 0 before training, 1 
after training)

Column q+1-r: the group covariates of interest (eg. a binary variable 
indicating whether or not the subject is a patient), for n groups you will have 
n-1 binary covariates

Column r+1-s: interactions between group covariates with the time-varying 
covariates (only the interesting interactions)

Column s+1-p: any other nuisance time-invariant covariates (eg. 
age-at-baseline, gender, etc...)

1) If I apply these advices, I would define in Column 3 my neuropsychological scores as my time-varying covariate but should I have to normalize these scores ?

2) If I want to correlate my metabolic maps (inputs) with my neuropsychological time-varying covariate should I have to define a column of interaction between neuropsychological time-varying covariate and (group or time) ?

3) How should I define contrast matrix to assess this effect ?

Thank you for your advices !!

Best regards,

Matthieu