Dear All, I am fitting a model for a binary response variable measured repeatedly at multiple visits. I am using the binomial GLMM using the glmer() function in lme4 package. How can I evaluate the model assumptions (e.g., residual diagnostics, adequacy of random effects distribution) for a binomial GLMM? Are there any standard checks that are commonly done? Are there any pedagogical examples or data sets where model assumptions have been examined for binomial GLMMs? Any suggestions/guidance is appreciated. Thank you, Ravi [[alternative HTML version deleted]]