Cluster-Robust (Sandwich) Variance Estimators with Small-Sample
Corrections
c(
  person(c("James","E."), "Pustejovsky", email = "jepusto@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-0591-9465")),
  person("Hazim", "Izani", email = "hazimizani@gmail.com", role = "ctb"),
  person("Samuel", "Pekofsky", email = "sampekofsky@gmail.com", role = "ctb"),
  person("Jingru", "Zhang", email = "jz26372022@hotmail.com", role = "ctb")
  )
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) 
    <https://www150.statcan.gc.ca/n1/pub/12-001-x/2002002/article/9058-eng.pdf> and 
    developed further by Pustejovsky and Tipton (2017) 
    <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() and mlm
    objects; glm(); geeglm() (from package 'geepack'); lm_robust(), lm_lin(), and 
    iv_robust() (from package 'estimatr'); 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'); rma.uni() and rma.mv() (from 'metafor'); and mmrm() (from 'mmrm').
Formula, knitr, testthat, rmarkdown, covr, AER, carData,
estimatr, fixest, geepack, ivreg, Matrix, lme4, metafor,
metadat, mlmRev, mmrm, nlme, plm (>= 1.6-4), robumeta, zoo
James E. Pustejovsky [aut, cre] (ORCID:
    <https://orcid.org/0000-0003-0591-9465>),
  Hazim Izani [ctb],
  Samuel Pekofsky [ctb],
  Jingru Zhang [ctb]