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) <http://www.statcan.gc.ca/pub/12-001-x/2002002/article/9058-eng.pdf> and developed further by Pustejovsky and Tipton (2016) <doi:10.1080/07350015.2016.1247004>. 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(), plm() (from package 'plm'), gls() and lme() (from 'nlme'), robu() (from 'robumeta'), and rma.uni() and rma.mv() (from 'metafor').
|Depends:||R (≥ 3.0.0)|
|Suggests:||Formula, knitr, car, metafor, robumeta, nlme, mlmRev, AER, plm, testthat, rmarkdown|
|Author:||James Pustejovsky [aut, cre]|
|Maintainer:||James Pustejovsky <jepusto at gmail.com>|
|CRAN checks:||clubSandwich results|
Cluster-robust variance estimation with clubSandwich
Meta-analysis with cluster-robust variance estimation
Cluster-robust standard errors and hypothesis tests in panel data models
|Windows binaries:||r-devel: clubSandwich_0.2.2.zip, r-release: clubSandwich_0.2.2.zip, r-oldrel: clubSandwich_0.2.2.zip|
|OS X El Capitan binaries:||r-release: clubSandwich_0.2.2.tgz|
|OS X Mavericks binaries:||r-oldrel: clubSandwich_0.2.2.tgz|
|Old sources:||clubSandwich archive|
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