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
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

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