Package: ATbounds 0.1.0

Sokbae Lee

ATbounds: Bounding Treatment Effects by Limited Information Pooling

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," <arxiv:2111.05243>.

Authors:Sokbae Lee [aut, cre], Martin Weidner [aut]

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ATbounds.pdf |ATbounds.html
ATbounds/json (API)
NEWS

# Install 'ATbounds' in R:
install.packages('ATbounds', repos = c('https://atbounds.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/atbounds/atbounds-r/issues

Datasets:

On CRAN:

causal-inferencelack-of-overlaplimited-overlappartial-identificationtreatment-effectsunconfoundedness-assumption

4.18 score 3 stars 6 scripts 245 downloads 3 exports 4 dependencies

Last updated 3 years agofrom:b54d4f8f45. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 12 2024
R-4.5-winNOTENov 12 2024
R-4.5-linuxNOTENov 12 2024
R-4.4-winNOTENov 12 2024
R-4.4-macNOTENov 12 2024
R-4.3-winOKNov 12 2024
R-4.3-macOKNov 12 2024

Exports:ateboundsattboundssimulation_dgp

Dependencies:latticeMatrixmgcvnlme

ATbounds: An R Vignette

Rendered fromATbounds_vignette.Rmdusingknitr::rmarkdownon Nov 12 2024.

Last update: 2021-11-16
Started: 2021-08-28