Hi everyone,

i just have a quick technical question.

My task is to run in *brms* a mixed effects, random intercept, random slope model on a very large data set, 400k observations that would take me days to run on a good EC2 instance.

My strategy would involve drawing random sub-samples from the complete dataset, run the models independently and then average the posteriors using the *pp_average.brmsfit* function.

Question: is this a legitmate use of the pp_average function, and is my approach valid, from a theoretical standpoint?

Thanks!

G.