Hi, I was wondering if anyone can help me on this. I am not sure whether I am correctly specifying the random intercept in my model. I need some advices. I am interested in understanding if there are differences in looking behaviours between 5 groups of children, between 2 conditions (condition 1 and 2). Looking behaviours were collected at 2 time points (time 1 and time 2 - repeated measure). I want to model a random intercept for each subject and fit random intercept for time. The model fits the beta distribution as the outcome variable is proportion data using the logit link function (values vary between 0 and 1).    Example of my data ID   Group   Time   Condition  Looking 1         0            1              1                 0.87 1         0            2             2                0.22 2         1             1              1                0.97 2         1             2             2              0.30        This is my code proc glimmix data=mydata plots=residualpanel; class group condition time; model Looking= group condition time group*condition group*condition*time /dist=beta link=logit ddfm=satterthwaite solution; random intercept / subject=ID type=un; random intercept time / subject=ID type=un;  run; I believe that the first random intercept specify the subject variation. In the second random intercept I am not sure whether the random intercept applies variability across subjects at each level of time point. When I add the intercept of time the residuals plots show more deviations than the subject variation model only.  Also, the empirical = classical accounts for robust standard error? Thank you for your time and help      ... View more