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-4.5)lmw_0.0.2.zip(r-4.4)lmw_0.0.2.zip(r-4.3)
lmw_0.0.2.tgz(r-4.5-any)lmw_0.0.2.tgz(r-4.4-any)lmw_0.0.2.tgz(r-4.3-any)
lmw_0.0.2.tar.gz(r-4.5-noble)lmw_0.0.2.tar.gz(r-4.4-noble)
lmw_0.0.2.tgz(r-4.4-emscripten)lmw_0.0.2.tgz(r-4.3-emscripten)
lmw.pdf |lmw.html
lmw/json (API)
NEWS

# 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:

4.02 score 11 stars 19 scripts 169 downloads 3 exports 9 dependencies

Last updated 1 years agofrom:e86a8f967f. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKApr 03 2025
R-4.5-winOKApr 03 2025
R-4.5-macOKApr 03 2025
R-4.5-linuxOKApr 03 2025
R-4.4-winOKApr 03 2025
R-4.4-macOKApr 03 2025
R-4.4-linuxOKApr 03 2025
R-4.3-winOKApr 03 2025
R-4.3-macOKApr 03 2025

Exports:lmwlmw_estlmw_iv

Dependencies:backportschkcligluelatticelifecyclerlangsandwichzoo