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lmw
View on CRAN: Click
here
Download and install lmw package within the R console
Install from CRAN:
install.packages("lmw")
Install from Github:
library("remotes")
install_github("cran/lmw")
Install by package version:
library("remotes")
install_version("lmw", "0.0.2")
Attach the package and use:
library("lmw")
Maintained by
Noah Greifer
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-03-14
Latest Update: 2024-02-08
Description:
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)
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.
How to cite:
Noah Greifer (2023). lmw: Linear Model Weights. R package version 0.0.2, https://cran.r-project.org/web/packages/lmw
Previous versions and publish date:
0.0.1 (2023-03-14 19:40)
Other packages that cited lmw R package
View lmw citation profile
Other R packages that lmw depends,
imports, suggests or enhances
Functions, R codes and Examples using
the lmw R package
Some associated functions: influence.lmw . lalonde . lmw-package . lmw . lmw_est . lmw_iv . plot.lmw . plot.lmw_est . plot.summary.lmw . summary.lmw . summary.lmw_est .
Some associated R codes: aux_functions.R . get_X.R . get_w.R . influence.lmw.R . input_processing.R . lalonde.R . lmw-package.R . lmw.R . lmw_est.R . lmw_est_aipw.R . lmw_est_iv.R . lmw_iv.R . plot.lmw.R . plot.lmw_est.R . plot.summary.lmw.R . summary.lmw.R . summary.lmw_est.R . zzz.R . Full lmw package functions and examples
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