I'm running a model where slopes and intercepts are imputed but the variables they are predicting are not (i.e., the outcome variables are all in one dataset). I want to combine results across the 10 imputed sets of intercepts and slopes, with the same outcome values used for each imputation. Did I read correctly in an earlier threat (from Bengt I think) that we would need to run a separate model with each set of intercepts and slopes and then manually average the point estimates and standard errors across the 10 imputations?
If I understand you correctly, in the run where you do the imputations, you can add the outcome variables on the "Auxiliary" list so that they get transferred to the imputed data sets (with the same values for all sets). No manual averaging etc is needed.