Beginner question: getting CATE estimations & confidence intervalls

Hi,

based on the attached graph, I would like to estimate the CATE for the variable 'komplex' (discret) on 'dlz_implementierung' (continuous) based on the treatment 'spm' (binary). From the data generation process I know, that 'komplex' does not affect the assignment of 'spm' (in terms if it is 1 or 0). But 'komplex' is used to determine the effect of the treatment (if 'komplex' > 5 then -10 else 0). Therefore, I would like the retrieve the treatment effect for the different levels 'komplex' together with its confidence intervals. By using the econml estimation methods (e.g. T-Learner, CausalForestDML) with X=['komplex', 'team'], I get the effect and confidence interval on this exact level. Since I have to control for 'team', is there any way in this setup to get the treatment effect and confidence intervals on the 'komplex'-level from the estimator? Any help is appreciated!

Thank you very much!

Start with the EconML documentation and the T-Learner and CausalForestDML interfaces named in the issue. Determine whether either estimator supports treatment effects and confidence intervals aggregated over komplex while controlling for team; done means providing a documented usage path or clarifying that this is unsupported.