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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 |
| Reference manual: | CausalGAM.pdf |
| 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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