I am considering using a Generalised Additive model for prediction and a Generalised Mixed effects model for inference to explain the relationship between variables, so I can play to the strengths of the two model types.
Does this make sense to do? Or is it recommended to build only one model and have a compromise between explanatory power and predictive power?