Causal Inference with Spatio-Temporal Data.

geocausal

The goal of the package geocausal is to implement causal inference analytic methods based on spatio-temporal data. Users provide the raw data of locations and timings of treatment and outcome events, specify counterfactual scenarios, and the package estimates causal effects over specified spatial and temporal windows.

Please refer to the following preprint for the user guide.

Mukaigawara M, Zhou L, Papadogeorgou G, Lyall J, and Imai K (2024). Geocausal: An R Package for Spatio-temporal Causal Inference. OSF Preprints. December 16. https://doi.org/10.31219/osf.io/5kc6f.

For methodological details, please refer to the following article.

Papadogeorgou G, Imai K, Lyall J, and Li F (2022). Causal inference with spatio-temporal data: Estimating the effects of airstrikes on insurgent violence in Iraq. J R Stat Soc Series B.https://doi.org/10.1111/rssb.12548.

Citation

Please cite this package as follows:

Mukaigawara M, Zhou L, Papadogeorgou G, Lyall J, and Imai K (2024). Geocausal: An R Package for Spatio-temporal Causal Inference. OSF Preprints. December 16. https://doi.org/10.31219/osf.io/5kc6f.

Installation

You can install the package geocausal from GitHub with:

# install.packages("devtools")
devtools::install_github("mmukaigawara/geocausal")

and CRAN with:

install.packages("geocausal")