Causal and statistical inference on an arbitrary treatment effect curve requires care in both estimation and inference. This package, implements the Method of Direct Estimation and Inference as introduced in "Estimation and Inference on Nonlinear and Heterogeneous Effects" by Ratkovic and Tingley (2023) <doi:10.1086/723811>. The method takes an outcome, variable of theoretical interest (treatment), and set of variables and then returns a partial derivative (marginal effect) of the treatment variable at each point along with uncertainty intervals. The approach offers two advances. First, a splitsample approach is used as a guard against overfitting. Second, the method uses a datadriven interval derived from conformal inference, rather than relying on a normality assumption on the error terms.
Package details 


Author  Marc Ratkovic [aut, cre], Dustin Tingley [ctb], Nithin Kavi [aut] 
Maintainer  Marc Ratkovic <ratkovic@princeton.edu> 
License  GPL (>= 2) 
Version  1.0 
Package repository  View on CRAN 
Installation 
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