It looks like AIC may be feasible, although you will need to transform the results of the logged model to be comparable to the original scale, https://stats.stackexchange.com/a/343176/1036.

]]>The library has examples for different link functions. So normal is one, but you could have 0/1 data, or Poisson count data, and then just use the particular link function that works the best for your data. (So it may make sense to log-transform, or may not if it is say counts of something.)

]]>Thanks so much for sharing this code. I am wondering whether there’s any restriction for the dependent variables: should the repeated measurements be conformed to normal distribution and do I need to log-transform these data before running GBTM?

Thanks in advance and looking forward to hearing from you soon! ]]>