Suppose I conducted an experience sampling study and set up a multi-level regression, in which episodic well-being (LVL-1) is predicted by episodic flow (LVL-1) and episodic loneliness (LVL-1) (measurement occasions nested in participants; both LVL-1 predictors flow and loneliness with random slope).
I am interested in whether flow and loneliness are associated with well-being and for which predictor the association is higher. Based on the recommendations of Enders and Togfighi (2007; https://psycnet.apa.org/doiLanding?doi=10.1037%2F1082-989X.12.2.121), I group-mean centered the two LVL-1 predictors. Both are significant, positive predictors of well-being. But now I'm faced with the problem that I can't compare the height of the association of the predictors with well-being. I suppose that to do that I'd have to scale them using z-values instead (using scale() function)? But then I fear that the model will not be calculated correctly anymore. Or is the group-mean centering in case of LVL-1 predictors only done to make the intercept more meaningful (which in this case would be secondary)?
Thank you in advance for any advice.
Kindest Regards, Dominik