Central Limit Theorem Experiments (Theoretical and Simulation)
Central limit theorem experiments presented by data frames or plots. Functions include generating theoretical sample space, corresponding probability, and simulated results as well.

Cluster-Robust (Sandwich) Variance Estimators with Small-Sample
Corrections
person("James", "Pustejovsky", email = "jepusto@gmail.com", role = c("aut", "cre"))
Provides several cluster-robust variance estimators
(i.e., sandwich estimators) for ordinary and weighted least squares linear
regression models. Several adjustments are incorporated to improve small-
sample performance. 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').
Formula, knitr, car, metafor, robumeta, nlme, mlmRev, AER,
plm, testthat, rmarkdown

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').