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-any)lmw_0.0.2.zip(r-4.6-any)lmw_0.0.2.zip(r-4.5-any)
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:

4.17 score 11 stars 27 scripts 246 downloads 3 exports 8 dependencies

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

TargetResultTimeFilesSyslog
linux-develOK127
source / vignettesOK207
linux-releaseOK170
macos-releaseOK100
macos-oldrelOK103
windows-develOK70
windows-releaseOK88
windows-oldrelOK73
wasm-releaseOK120

Exports:lmwlmw_estlmw_iv

Dependencies:backportschkclilatticelifecyclerlangsandwichzoo