Ramiro Lugo

Comparison of meta-learners for estimating multi-valued treatment heterogeneous effects

Conditional Average Treatment Effects (CATE) estimation is one of the main challenges in causal inference with observational data. In addition to Machine Learning based-models, nonparametric estimators called meta-learners have been developed to estimate the CATE with the main advantage of not restr…