Dealing with confounders

One topic that isn't touched upon is confounding variables. I've use models selection on them in the past, because I don't really care about them, but some might be important and dropping minor confounders should give more power elsewhere. Of course, regularisation does the same thing.

I guess my main point is that confounders are slightly different, so might have to be dealt with, even if you end up with 2 lines saying "treat them like everything else in the model, but interpret them differently".