Specifically, for the estimators and metalearners we should make a separate risk ratio function; we should find a way to make estimate_causal_effect! for g-computation smaller; estimate_causal_effect! for double machine learning should definitely be broken up into smaller functions; and crossfitting_sets should also be smaller. These smaller functions will then need to be testes.
dscolby
commented
8 months ago
Specifically, for the estimators and metalearners we should make a separate risk ratio function; we should find a way to make estimate_causal_effect! for g-computation smaller; estimate_causal_effect! for double machine learning should definitely be broken up into smaller functions; and crossfitting_sets should also be smaller. These smaller functions will then need to be testes.