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causalOT: Optimal transport methods for causal inference

This R package implements the methods described in Optimal transport methods for causal inference.

Installation

This package can be installed in a few ways.

1. devtools

Using the remotes package in R, one can install the package with

remotes::install_github("ericdunipace/causalOT")

2. download and install

After downloading the git package using git clone or by downloading the .zip file from the button above (Code -> Download Zip) and unzipping, you can install the package with

devtools::install("path/to/causalOT")

3. CRAN

A stable version of this package is available on CRAN, but usually this GitHub will have the latest version.

Usage

The functions in the package are built to construct weights to make distributions more same and estimate causal effects. The primary method we recommend is by using optimal transport weights which balance distributions by design. For more information about using this package, see the vignette "Using causalOT".

Reproducing the paper

In the folder inst/Reproduce you can find code and an RMarkdown file to reproduce the figures present in the paper.

Package author

Eric Dunipace

License

This package is licensed under GPL 3.0.

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Version

Install

install.packages('causalOT')

Monthly Downloads

298

Version

1.0.3

License

GPL (== 3.0)

Maintainer

Eric Dunipace

Last Published

February 15th, 2026

Functions in causalOT (1.0.3)

cot_solve,gridSearch-method

cot_solve for gridSearch
coef.causalEffect

Extract treatment effect estimate
cotOptions

Options available for the COT method
cot_solve,likelihoodMethods-method

cot_solve method for likelihoodMethods
dataHolder-class

dataHolder-class
causalEffect-class

causalEffect class
cot_solve,ateClass-method

cot_solve method for ateClass objects
estimate_effect

Estimate treatment effects
dataHolder,dataHolder-method

dataHolder-methods
causalWeights-class

causalWeights class
mean_balance

Standardized absolute mean difference calculations
gridSearch-class

gridSearch S4 class
estimate_model

Function to estimate outcome models
plot.causalWeights

plot.causalWeights
pph

An external control trial of treatments for post-partum hemorrhage
supported_methods

Supported Methods
vcov.causalEffect

Get the variance of a causalEffect
summary.causalWeights

Summary diagnostics for causalWeights
df2dataHolder,ANY,ANY,data.frame-method

df2dataHolder-methods
data_separate.dataHolder

Title
print.dataHolder

print.dataHolder
df2dataHolder

df2dataHolder
entBWOptions

Options for the Entropy Balancing Weights
predict.bp

Predict method for barycentric projection models
scmOptions

Options for the SCM Method
sbwOptions

Options for the SBW method
oop_loss_select

Internal function to select appropriate loss function
ot_distance

Optimal Transport Distance
dataHolder

dataHolder
PSIS.causalWeights

PSIS casualWeights class
OTProblem

OTProblem
LaLonde

LaLonde data example
Measure

Measure
Hainmueller

Hainmueller data example
DataSim

R6 Data Generating Parent Class
barycentric_projection

Barycentric Projection outcome estimation
CRASH3

CRASH3 data example
PSIS

Pareto-Smoothed Importance Sampling
ESS

Effective Sample Size
causalOT

An R package to perform causal inference using optimal transport distances.
calc_weight

Estimate causal weights