# R^2 for mixed effect models (both generalized linear and additive)

I have seen from several discussion threads that there are a few ways of calculating R^2 for LMMs and GLMMs - albeit with a caveat for GLMM being that the existing methods work for only gaussian distribution (for example here).

1. Is there a method for GLMM that is less sensitive to the distribution family?
2. Are there methods that can be used with Generalized additive models (for instance gamm4 class of models, lme4)

There is probably no simple answer for these questions, but suggestions on workarounds and the associated caveats would be great.