med_bench is a Python package designed to wrap the most common estimators for causal mediation analysis in a single framework. We additionally allow for some flexibility in the choice of nuisance parameters models.
The simulations and performances evaluations realized here are presented in the following article
Judith Abécassis, Julie Josse and Bertrand Thirion (2022). Causal mediation analysis with one or multiple mediators: a comparative study. pdf
med_bench can be installed by executing
python setup.py install
Or the package can be directly installed from the GitHub repository using
pip install git+git://github.com/judithabk6/med_bench.git
Installation time is a few minutes on a standard personal computer.
Some estimators rely on their R implementation which requires the installation of the corresponding R packages. This can be done using rpy2
import rpy2
import rpy2.robjects.packages as rpackages
utils = rpackages.importr('utils')
utils.chooseCRANmirror(ind=33)
utils.install_packages('grf')
utils.install_packages('causalweight')
utils.install_packages('mediation')
utils.install_packages('devtools')
devtools = rpackages.importr('devtools')
devtools.install_github('ohines/plmed')
plmed = rpackages.importr('plmed')The src folder contains the main module with the implementation of the different estimators, the script folder contains the function used to simulate data and run the experiments, and the results folder contains all available results and code to reproduce the figures.