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ATbounds  

Bounding Treatment Effects by Limited Information Pooling
View on CRAN: Click here


Download and install ATbounds package within the R console
Install from CRAN:
install.packages("ATbounds")

Install from Github:
library("remotes")
install_github("cran/ATbounds")

Install by package version:
library("remotes")
install_version("ATbounds", "0.1.0")



Attach the package and use:
library("ATbounds")
Maintained by
Sokbae Lee
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-11-24
Latest Update: 2021-11-24
Description:
Estimation and inference methods for bounding average treatment effects (on the treated) that are valid under an unconfoundedness assumption. The bounds are designed to be robust in challenging situations, for example, when the conditioning variables take on a large number of different values in the observed sample, or when the overlap condition is violated. This robustness is achieved by only using limited "pooling" of information across observations. For more details, see the paper by Lee and Weidner (2021), "Bounding Treatment Effects by Pooling Limited Information across Observations," .
How to cite:
Sokbae Lee (2021). ATbounds: Bounding Treatment Effects by Limited Information Pooling. R package version 0.1.0, https://cran.r-project.org/web/packages/ATbounds. Accessed 06 Nov. 2024.
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Complete documentation for ATbounds
Functions, R codes and Examples using the ATbounds R package
Some associated functions: EFM . RHC . atebounds . attbounds . simulation_dgp . summary.ATbounds . 
Some associated R codes: atebounds.R . attbounds.R . data_EFM.R . data_RHC.R . simulation_dgp.R . summary.ATbounds.R .  Full ATbounds package functions and examples
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