latenetwork: Inference on LATEs under Network Interference of Unknown Form

Estimating causal parameters in the presence of treatment spillover is of great interest in statistics. This package provides tools for instrumental variables estimation of average causal effects under network interference of unknown form. The target parameters are the local average direct effect, the local average indirect effect, the local average overall effect, and the local average spillover effect. The methods are developed by Hoshino and Yanagi (2023) <doi:10.48550/arXiv.2108.07455>.

Version: 1.0.1
Imports: igraph, methods, statip, stats
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2023-08-08
Author: Tadao Hoshino ORCID iD [aut, cph], Takahide Yanagi ORCID iD [aut, cre, cph]
Maintainer: Takahide Yanagi <yanagi at econ.kyoto-u.ac.jp>
License: MIT + file LICENSE
URL: https://tkhdyanagi.github.io/latenetwork/
NeedsCompilation: no
Materials: README NEWS
CRAN checks: latenetwork results

Documentation:

Reference manual: latenetwork.pdf
Vignettes: Getting Started with the latenetwork Package
Review of Causal Inference with Noncompliance and Unknown Interference

Downloads:

Package source: latenetwork_1.0.1.tar.gz
Windows binaries: r-prerel: latenetwork_1.0.1.zip, r-release: latenetwork_1.0.1.zip, r-oldrel: latenetwork_1.0.1.zip
macOS binaries: r-prerel (arm64): latenetwork_1.0.1.tgz, r-release (arm64): latenetwork_1.0.1.tgz, r-oldrel (arm64): latenetwork_1.0.1.tgz, r-prerel (x86_64): latenetwork_1.0.1.tgz, r-release (x86_64): latenetwork_1.0.1.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=latenetwork to link to this page.