Hi,   I'm using SAS On Demand for Academics and new to multilevel modeling as well. I have a dataset with 8300 children who are nested in Mothers nested in household nested in clusters. But I have predictor variables only for child level, mother level and household level. I used PROC GLIMMIX to fit the empty model of the multilevel logistic regression model first with the following code.   PROC GLIMMIX data=FINAL.DATABASE NOCLPRINT; class Cluster_number Household_number Mother_Number; model Living_Status=/dist=binomial link=logit; random int/subject=Mother_Number*Household_number*Cluster_number; COVTEST/ WALD; RUN;   So is it ok to use Cluster_number in the Subject=Mother_Number*Household_number*Cluster_number even though there are no predictors to be added in the full model for cluster level?   Also below code does not give the covariance parameter values of Cluster_number,Household_number*Cluster_number,Mother_Number*Household_number*Cluster_number and residual covariance parameter together. Is there any modification needs to be done to the code to get those values? I need to calculate the ICC for each level.   PROC GLIMMIX data=FINAL.DATABASE NOCLPRINT; class Cluster_number Household_number Mother_Number; model Living_Status=/dist=binomial link=logit; random int/subject=Cluster_number; random int/subject=Household_number*Cluster_number; random int/subject=Mother_Number*Household_number*Cluster_number; COVTEST/ WALD; RUN; ... View more