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clubSandwich  

Cluster-Robust (Sandwich) Variance Estimators with Small-Sample Corrections
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Download and install clubSandwich package within the R console
Install from CRAN:
install.packages("clubSandwich")

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

Install by package version:
library("remotes")
install_version("clubSandwich", "0.5.11")



Attach the package and use:
library("clubSandwich")
Maintained by
James Pustejovsky
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-07-23
Latest Update: 2023-07-20
Description:
Provides several cluster-robust variance estimators (i.e., sandwich estimators) for ordinary and weighted least squares linear regression models, including the bias-reduced linearization estimator introduced by Bell and McCaffrey (2002) and developed further by Pustejovsky and Tipton (2017) . The package includes functions for estimating the variance- covariance matrix and for testing single- and multiple- contrast hypotheses based on Wald test statistics. Tests of single regression coefficients use Satterthwaite or saddle-point corrections. Tests of multiple- contrast hypotheses use an approximation to Hotelling's T-squared distribution. Methods are provided for a variety of fitted models, including lm() and mlm objects, glm(), geeglm() (from package 'geepack'), ivreg() (from package 'AER'), ivreg() (from package 'ivreg' when estimated by ordinary least squares), plm() (from package 'plm'), gls() and lme() (from 'nlme'), lmer() (from `lme4`), robu() (from 'robumeta'), and rma.uni() and rma.mv() (from 'metafor').
How to cite:
James Pustejovsky (2016). clubSandwich: Cluster-Robust (Sandwich) Variance Estimators with Small-Sample Corrections. R package version 0.5.11, https://cran.r-project.org/web/packages/clubSandwich. Accessed 22 Dec. 2024.
Previous versions and publish date:
0.2.1 (2016-07-23 21:07), 0.2.2 (2016-12-01 19:44), 0.2.3 (2017-08-10 21:07), 0.3.0 (2017-11-13 11:23), 0.3.1 (2018-04-04 16:50), 0.3.2 (2018-05-22 00:54), 0.3.3 (2019-01-24 15:10), 0.3.4 (2019-05-11 17:10), 0.3.5 (2019-05-14 23:40), 0.4.0 (2019-12-18 16:30), 0.4.1 (2020-01-28 10:40), 0.4.2 (2020-07-23 06:57), 0.5.0 (2020-09-01 10:40), 0.5.1 (2020-10-12 13:20), 0.5.2 (2020-11-14 14:40), 0.5.3 (2021-01-24 01:20), 0.5.4 (2022-01-09 02:32), 0.5.5 (2022-01-18 17:02), 0.5.6 (2022-04-23 10:10), 0.5.7 (2022-06-15 11:20), 0.5.8 (2022-08-15 09:50), 0.5.9 (2023-07-12 20:30), 0.5.10 (2023-07-20 04:50)
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