I've been using Cox for survival analysis with the goal of identifying the effect of 5 different levels of a treatment on survival. My dataset is not small and has 130 covariates after dummy encoding.
About 15 of these - including one level of my treatment - violate the PH assumption.
I think in my situation the best extended Cox option would be adding time interactions to those that violate the PH assumption meaningfully. Another option, of course, could be an AFT, if the assumptions there are also satisfied.
My question is: If I were to try each of these approaches, how could I compare which these are preferred given my objective. That is, how would I know which is better? It's not like I'm making a prediction about survival in which case I could use CI or something more precise. Thus, comparing which is best and knowing how to know this is not obvious to me.