Causal Inference, Machine Learning, Azure, Microsoft, Data Science.
individual level. CATE (as mentioned, also known as heterogeneous treatment effect) is where the treatment effect varies across different subgroups. When the goal is to understand program-level treatment effects, we focus on ATE/ATT. When the goal is to estimate the individual level treatment