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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.

Versions across snapshots

VersionRepositoryFileSize
0.1-4 rolling linux/jammy R-4.5 CausalGAM_0.1-4.tar.gz 48.3 KiB
0.1-4 rolling linux/noble R-4.5 CausalGAM_0.1-4.tar.gz 48.3 KiB
0.1-4 rolling source/ R- CausalGAM_0.1-4.tar.gz 15.4 KiB
0.1-4 latest linux/jammy R-4.5 CausalGAM_0.1-4.tar.gz 48.3 KiB
0.1-4 latest linux/noble R-4.5 CausalGAM_0.1-4.tar.gz 48.3 KiB
0.1-4 latest source/ R- CausalGAM_0.1-4.tar.gz 15.4 KiB
0.1-4 2026-04-26 source/ R- CausalGAM_0.1-4.tar.gz 15.4 KiB
0.1-4 2026-04-23 source/ R- CausalGAM_0.1-4.tar.gz 15.4 KiB
0.1-4 2026-04-09 windows/windows R-4.5 CausalGAM_0.1-4.zip 50.9 KiB
0.1-4 2025-04-20 source/ R- CausalGAM_0.1-4.tar.gz 15.4 KiB

Dependencies (latest)

Depends