Hello @dmphillippo.
Any way of using different likelihoods / links on different elements of a dataset contributing to a shared model? Motivation: if I use cloglog--binomial on dichotomous data, I end up on log-hazard scale so, in principle, there's no reason why I couldn't combine with explicitly reported rate data (log--Poisson model), with both estimating log(HR)s. But combine_network() complains of a type mismatch. Is there any way around that?
Hello @dmphillippo.
Any way of using different likelihoods / links on different elements of a dataset contributing to a shared model? Motivation: if I use cloglog--binomial on dichotomous data, I end up on log-hazard scale so, in principle, there's no reason why I couldn't combine with explicitly reported rate data (log--Poisson model), with both estimating log(HR)s. But combine_network() complains of a type mismatch. Is there any way around that?