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) < http://www.statcan.gc.ca/pub/12-001-x/2002002/article/9058-eng.pdf> 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 rma.mv() (from 'metafor').

News

clubSandwich 0.3.2

Added conf_int() to provide easy cluster-robust confidence intervals.
Added examples to documentaiton for conf_int() and coef_test().

clubSandwich 0.3.1

Added "coefs" option to coef_test() to allow testing of subsets of coefficients.
Updated tests to use carData instead of car package.

clubSandwich 0.3.0

Added methods for ivreg objects.
Added methods for mlm objects.
Updated residuals_CS.plm to account for changes in plm 1.6-6.

clubSandwich 0.2.3

Updated methods for plm objects to account for changes in plm 1.6-6.
Added methods for glm objects.
Added documentation of "type" options in vcovCR().
Added examples for all vcovCR() methods.
Provide facility to cluster at higher level than highest random effects for lme and gls objects.
Added impute_covariance_matrix() utility function for multivariate meta-analysis.

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