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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 |
DOI: | 10.32614/CRAN.package.latenetwork |
Author: | Tadao Hoshino [aut, cph], Takahide Yanagi [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 |
Reference manual: | latenetwork.pdf |
Vignettes: |
Getting Started with the latenetwork Package Review of Causal Inference with Noncompliance and Unknown Interference |
Package source: | latenetwork_1.0.1.tar.gz |
Windows binaries: | r-devel: latenetwork_1.0.1.zip, r-release: latenetwork_1.0.1.zip, r-oldrel: latenetwork_1.0.1.zip |
macOS binaries: | r-release (arm64): latenetwork_1.0.1.tgz, r-oldrel (arm64): latenetwork_1.0.1.tgz, r-release (x86_64): latenetwork_1.0.1.tgz, r-oldrel (x86_64): latenetwork_1.0.1.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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