# How to assess GEE quality and fit, e.g. by residuals(?)

In contrast for generalized linear models (for GLM, there is e.g. AIC and null vs. residual deviance), I could not find such criteria implemented in R to judge my generalized equation (GEE) models.
Is it appropriate to look at

• residuals vs predicted values scatterplot?
• normal distribution of residuals (e.g. QQ plot)?

I am also happy to learn a better way to assess GEE models (available in an R package, or easily possible to calculate on my own if you show me how).
So far, I am using geepack::geeglm (or gee::gee)

library(geepack)