I would like to test is a given variable is associated with both the dependent and the independent variables (and therefore a potential confounder) in a repeated-measures design.
My model has a continuous dependent variable and two independent variables: a within-subject factor with 6 levels and a between-subject factor with 2 levels. I also have a continuous independent variable that is statistically associated with my between-subject factor (tested using a 2 sample t-test).
How should I test the association between this continuous variable and the dependent variable?
(1) adding this variable to my original model and check the effect of this extra variable? or (2) fitting a new model with only my within-subject factor and this extra variable (i.e. without the between-subject factor)?