Package: MDEI 1.0

Marc Ratkovic

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.

Authors:Marc Ratkovic [aut, cre], Dustin Tingley [ctb], Nithin Kavi [aut]

MDEI_1.0.tar.gz
MDEI_1.0.tar.gz(r-4.5-noble)MDEI_1.0.tar.gz(r-4.4-noble)
MDEI_1.0.tgz(r-4.4-emscripten)MDEI_1.0.tgz(r-4.3-emscripten)
MDEI.pdf |MDEI.html
MDEI/json (API)
NEWS

# Install 'MDEI' in R:
install.packages('MDEI', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascppopenmp

1.00 score 638 downloads 2 exports 8 dependencies

Last updated 2 years agofrom:c27b5b61a6. Checks:2 OK. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKFeb 15 2025
R-4.5-linux-x86_64OKFeb 15 2025

Exports:coverPlotMDEI

Dependencies:latticeMASSMatrixrangerRcppRcppArmadilloRcppEigensplines2