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sbw  

Stable Balancing Weights for Causal Inference and Missing Data
View on CRAN: Click here


Download and install sbw package within the R console
Install from CRAN:
install.packages("sbw")

Install from Github:
library("remotes")
install_github("cran/sbw")

Install by package version:
library("remotes")
install_version("sbw", "1.1.9")



Attach the package and use:
library("sbw")
Maintained by
Jose R. Zubizarreta
[Scholar Profile | Author Map]
First Published: 2019-12-30
Latest Update: 2021-09-22
Description:
Implements the Stable Balancing Weights by Zubizarreta (2015) . These are the weights of minimum variance that approximately balance the empirical distribution of the observed covariates. For an overview, see Chattopadhyay, Hase and Zubizarreta (2020) . To solve the optimization problem in 'sbw', the default solver is 'quadprog', which is readily available through CRAN. The solver 'osqp' is also posted on CRAN. To enhance the performance of 'sbw', users are encouraged to install other solvers such as 'gurobi' and 'Rmosek', which require special installation. For the installation of gurobi and pogs, please follow the instructions at and .
How to cite:
Jose R. Zubizarreta (2019). sbw: Stable Balancing Weights for Causal Inference and Missing Data. R package version 1.1.9, https://cran.r-project.org/web/packages/sbw. Accessed 29 Mar. 2025.
Previous versions and publish date:
1.0 (2019-12-30 16:20), 1.1.1 (2020-06-23 17:30), 1.1.3 (2021-06-18 10:10), 1.1.5 (2021-09-22 10:30), 1.1.8 (2024-07-09 23:30)
Other packages that cited sbw R package
View sbw citation profile
Other R packages that sbw depends, imports, suggests or enhances
Complete documentation for sbw
Functions, R codes and Examples using the sbw R package
Some associated functions: estimate . lalonde . sbw . summarize . visualize . 
Some associated R codes: data.R . duatab.R . estimate.R . propar.R . sbw.R . sbwauxfix.R . sbwauxtun.R . sbwcaufix.R . sbwcautun.R . sbwfix.R . sbwpri.R . sbwtun.R . summarize.R . visualize.R .  Full sbw package functions and examples
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