It depends on the inference you want to make. Average treatment effects are integrated over the entire sample. But that means it can “miss” or be biased for a s

It depends on the inference you want to make. Average treatment effects are integrated over the entire sample. But that means it can “miss” or be biased for a subsample. You can then explicitly model that subsample, but sub samples by definition have less power. It’s not just black or minority, it’s also any subsample, like a history of hear disease, or height. For further reading google: “Gelman there is never enough data”