I have become a great believer in simulating data in order to pre-specify models and ensure your model can actually model what you’re setting out to. McElreath takes this to its natural conclusion using Stan and R in his book. Harrell talks about its importance in his course. However, apart from the Bayesian approach in McElreath I can’t find a good guide on how best to actually do it. My qestion is: Is there a good book, site or references on the methodology, and pitfalls and pearls? Perhaps McElreath is it, but what if Stan is not an option? Open to any suggestions at all. Kind regards.