MDEI: Implementing the Method of Direct Estimation and Inference

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 split-sample approach is used as a guard against over-fitting. Second, the method uses a data-driven interval derived from conformal inference, rather than relying on a normality assumption on the error terms.

Version: 1.0
Depends: R (≥ 3.6.0)
Imports: grDevices, MASS, ranger, Rcpp (≥ 1.0.6), splines2
LinkingTo: Rcpp, RcppArmadillo
Published: 2023-05-04
Author: Marc Ratkovic [aut, cre], Dustin Tingley [ctb], Nithin Kavi [aut]
Maintainer: Marc Ratkovic <ratkovic at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Materials: NEWS
CRAN checks: MDEI results


Reference manual: MDEI.pdf


Package source: MDEI_1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): MDEI_1.0.tgz, r-oldrel (arm64): MDEI_1.0.tgz, r-release (x86_64): MDEI_1.0.tgz, r-oldrel (x86_64): MDEI_1.0.tgz


Please use the canonical form to link to this page.