The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

CausalGAM: Estimation of Causal Effects with Generalized Additive Models

Implements various estimators for average treatment effects - an inverse probability weighted (IPW) estimator, an augmented inverse probability weighted (AIPW) estimator, and a standard regression estimator - that make use of generalized additive models for the treatment assignment model and/or outcome model. See: Glynn, Adam N. and Kevin M. Quinn. 2010. "An Introduction to the Augmented Inverse Propensity Weighted Estimator." Political Analysis. 18: 36-56.

Version: 0.1-4
Depends: R (≥ 2.9.0), gam (≥ 1.0.1)
Published: 2017-10-19
DOI: 10.32614/CRAN.package.CausalGAM
Author: Adam Glynn, Kevin Quinn
Maintainer: Kevin Quinn <kmq at umich.edu>
License: GPL-2
NeedsCompilation: no
Materials: README
In views: CausalInference
CRAN checks: CausalGAM results

Documentation:

Reference manual: CausalGAM.pdf

Downloads:

Package source: CausalGAM_0.1-4.tar.gz
Windows binaries: r-devel: CausalGAM_0.1-4.zip, r-release: CausalGAM_0.1-4.zip, r-oldrel: CausalGAM_0.1-4.zip
macOS binaries: r-release (arm64): CausalGAM_0.1-4.tgz, r-oldrel (arm64): CausalGAM_0.1-4.tgz, r-release (x86_64): CausalGAM_0.1-4.tgz, r-oldrel (x86_64): CausalGAM_0.1-4.tgz
Old sources: CausalGAM archive

Linking:

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

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.