The package provides a function to compute Cluster Estimated Standard Errors (CESE).
For details, see Jackson, John (2020) Corrected Standard Errors with Clustered Data. Political Analysis, Volume 28, Issue 3July 2020 , pp. 318-339.
From CRAN
install.packages("ceser")
To install the development version (it requires the package "devtools"):
devtools::install_github("DiogoFerrari/ceser")
# If you don't want to update the dependencies, use: (you may need to install some dependencies manually)
devtools::install_github("DiogoFerrari/ceser", dependencies=F)
Check the complete documentation here and vignette here.
Here is a simple example (for more information, see =help(ceser)= and =help(vocvCESE)=).
library(ceser)
data(dcese)
mod = lm(enep ~ enpc + fapres + enpcfapres + proximity + eneg + logmag + logmag_eneg , data=dcese)
## --------------------------------------
## Getting the variance covariance matrix
## --------------------------------------
## Original variance-covariance matrix (no clustered std. errors)
vcov(mod)
## Variance-covariance matrix using CRSE (sandwish package)
## sandwich::vcovCL(mod, cluster = ~ country)
## sandwich::vcovCL(mod, cluster = ~ country, type="HC3")
## Variance-covariance matrix using CESE
ceser::vcovCESE(mod, cluster = ~ country)
ceser::vcovCESE(mod, cluster = ~ country, type="HC3") # HC3 correction
## ---------
## Summaries
## ---------
## no robust SE
summary(mod)
## summary table using CRSE (sandwich package)
## lmtest::coeftest(mod, vcov = sandwich::vcovCL, cluster = ~ country)
## summary using CESE
lmtest::coeftest(mod, vcov = ceser::vcovCESE, cluster = ~ country, type='HC3')