Hello, I would like to compute intraclass correlation using Proc Glimmix for a generalized linear mixed modelling (Poisson) with 1 fixed effect (intervention) and 1 random effect (cluster). I model proportions with the Poisson model, defining log(n) in the offset term : proc glimmix data=test method=quad; class CLUSTER INTERVENTION; model NEVENTS = INTERVENTION / link=log dist=poisson s offset=logn ; random intercept / subject=CLUSTER G solution I understand that the residual variance is the 'Estimate' listed in the "Covariance Parameter Estimates" table (or in the G matrix with only 1 row) but I have maybe some misunderstanding.  I can't find the common variance in order to estimate the ICC for this model: does it correspond to the 'Estimate' per cluster in the "Solution for random effects" ? The ICC could then be calculated with ( common variance / common variance + residual variance ) but I'm not sure this is appropriate here. I thought maybe others with more knowledge in GLMM and GLIMMIX may be able to enlighten me.  Regards, Jude ... View more