Cluster-Robust (Sandwich) Variance Estimators with Small-Sample Corrections

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(), ivreg (from package 'AER'), plm() (from package 'plm'), gls() and lme() (from 'nlme'), robu() (from 'robumeta'), and rma.uni() and (from 'metafor').


clubSandwich 0.2.2

  • Added bread() methods for all supported model classes.
  • vcovCR() is now calculated using bread(), and carries attributes for bread, est_mat, and adjustment matrices.
  • vcovCR() gains a 'form' argument to obtain just the meat of the sandwich, or to use a user-specified bread matrix.
  • Refactored internal functions for degrees of freedom calculation to improve speed and memory usage.
  • Bug fixes:
    • updated nobs.plm method to handle first-differenced models

clubSandwich 0.2.1

  • First version released on CRAN.

Reference manual

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0.3.0 by James Pustejovsky, 12 days ago

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Browse source code at

Authors: James Pustejovsky [aut, cre]

Documentation:   PDF Manual  

Task views: Econometrics, Meta-Analysis

GPL-3 license

Imports stats, sandwich

Suggests Formula, knitr, car, geepack, metafor, robumeta, nlme, mlmRev, AER, plm, testthat, rmarkdown

Suggested by plm, robumeta.

See at CRAN