R Implementations
Below we link to R packages that performs various forms of causal estimation.
Simulation
simcausal: Simulating Longitudinal Data with Causal Inference Applications
Adaptive treatment strategy estimation
DTRreg: DTR Estimation and Inference via G-Estimation, Dynamic WOLS, and Q-Learning
DynTxRegime: Methods for Estimating Optimal Dynamic Treatment Regimes
iqLearn: Interactive Q-Learning
qLearn: Estimation and Inference for Q-Learning
stremr: Streamlined Estimation of Survival for Static, Dynamic and Stochastic Treatment and Monitoring Regimes
Other
twang: Toolkit for Weighting and Analysis of Nonequivalent Groups
Evalue: Sensitivity Analyses for Unmeasured Confounding or Selection Bias in Observational Studies and Meta-Analyses
MatchIt: Nonparametric Preprocessing for Parametric Causal Inference
cem: Coarsened Exact Matching
optmatch: Functions for Optimal Matching
PSAgraphics: Propensity Score Analysis Graphics
RCAL: Regularized calibrated estimation for causal inference
Synth: Synthetic Control Group Method for Comparative Case Studies
cobalt: Covariate Balance Tables and Plots
ebal: Entropy Reweighting to Create Balanced Samples