Package: lmw 0.0.2

lmw: Linear Model Weights

Computes the implied weights of linear regression models for estimating average causal effects and provides diagnostics based on these weights. These diagnostics rely on the analyses in Chattopadhyay and Zubizarreta (2023) <doi:10.1093/biomet/asac058> where several regression estimators are represented as weighting estimators, in connection to inverse probability weighting. 'lmw' provides tools to diagnose representativeness, balance, extrapolation, and influence for these models, clarifying the target population of inference. Tools are also available to simplify estimating treatment effects for specific target populations of interest.

Authors:Ambarish Chattopadhyay [aut], Noah Greifer [aut, cre], Jose Zubizarreta [aut]

lmw_0.0.2.tar.gz
lmw_0.0.2.zip(r-4.7)lmw_0.0.2.zip(r-4.6)lmw_0.0.2.zip(r-4.5)
lmw_0.0.2.tgz(r-4.6-any)lmw_0.0.2.tgz(r-4.5-any)
lmw_0.0.2.tar.gz(r-4.7-any)lmw_0.0.2.tar.gz(r-4.6-any)
lmw_0.0.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
lmw/json (API)

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

Bug tracker:https://github.com/ngreifer/lmw/issues

Datasets:
  • lalonde - Data from National Supported Work Demonstration and PSID, as analyzed by Dehejia and Wahba (1999).

On CRAN:

Conda:

4.12 score 11 stars 24 scripts 230 downloads 3 exports 8 dependencies

Last updated from:e86a8f967f. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK140
source / vignettesOK196
linux-release-x86_64OK140
macos-release-arm64OK105
macos-oldrel-arm64OK106
windows-develOK87
windows-releaseOK88
windows-oldrelOK100
wasm-releaseOK118

Exports:lmwlmw_estlmw_iv

Dependencies:backportschkclilatticelifecyclerlangsandwichzoo