I'm re-analyzing some old datasets (e.g. from pilots for my dissertation I ran in 2015) and find myself wanting to re-run some multilevel models. However, the first time I did this, I used grand mean centering. That means I combine the within-cluster effects and between-cluster effects into a single parameter estimate (Curran and Bauer have for a great summary). Instead, I want to cluster mean center. That means calculating the mean of the variable within each cluster, then subtracting the mean of each cluster from the individuals scores in each cluster. Then you include both the cluster means and the cluster mean centered scores in the regression. The coefficient on…