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CausalGAM (version 0.1-4)

Estimation of Causal Effects with Generalized Additive Models

Description

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.

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Version

Install

install.packages('CausalGAM')

Monthly Downloads

234

Version

0.1-4

License

GPL-2

Maintainer

Last Published

October 19th, 2017

Functions in CausalGAM (0.1-4)

balance.IPW

Check Post-Weighting Balance for (A)IPW Estimators Using Generalized Additive Models
estimate.ATE

Estimate Population Average Treatment Effects (ATE) Using Generalized Additive Models