clubSandwich (version 0.2.2)
Cluster-Robust (Sandwich) Variance Estimators with Small-Sample
Corrections
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 (2016) .
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').