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cates icon cates

Machine Learning Estimation of Heterogeneous Causal Effects

causal-1 icon causal-1

Causal Inference using R. Examples are from the book Causal Inference (Chapman & Hall/CRC, 2012) by Miguel Hernán and Jamie Robins. Complete contributor/reviewer list is updated in http://www.hsph.harvard.edu/faculty/miguel-hernan/causal-inference-book/

causalforest icon causalforest

Causal trees and forests for estimating heterogeneous treatment effects

causalmediation icon causalmediation

Implementation of Causal Mediation Analysis as published by Valeri and VanderWeele (2013, doi: 10.1037/a0031034)

causalmgm icon causalmgm

causalMGM is an R package that allow users to learn undirected and directed (causal) graphs over mixed data types (i.e., continuous and discrete variables).

causalsandwich icon causalsandwich

Simple implementation for estimating causal effects with M-estimation and sandwich variance estimators

causaltrail icon causaltrail

CausalTrail - a tool for performing causal reasoning using the do-calculus

causaltree icon causaltree

Working repository for Causal Tree and extensions

causalxtreme icon causalxtreme

An R package for causal discovery in heavy-tailed models

causamed icon causamed

Implementation of Tyler Vanderweele's methods for mediation

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