A function and vignettes for computing an intraclass correlation
described in Aguinis & Culpepper (2015)
A function and vignettes for computing an intraclass correlation described in Aguinis & Culpepper (in press). iccbeta quantifies the share of variance in a dependent variable that is attributed to group heterogeneity in slopes.
You can install iccbeta
from CRAN using:
install.packages("iccbeta")
Or, you can be on the cutting-edge development version on GitHub using:
if(!requireNamespace("devtools")) install.packages("devtools")devtools::install_github("tmsalab/iccbeta")
To use the iccbeta
package, load it into R using:
library("iccbeta")
From there, calling the icc_beta()
function with either a lmer()
model object or the desired individual components will compute the
intraclass correlation:
# Automatically calculate icc from modelresults_model = icc_beta(<lmer-model>)# Calculate icc from individual terms.results_component = icc_beta(X, l2id, T, vy)
Steven Andrew Culpepper and Herman Aguinis
iccbeta
packageTo ensure future development of the package, please cite iccbeta
package if used during an analysis or simulation studies. Citation
information for the package may be acquired by using in R:
citation("iccbeta")
GPL (>= 2)
lmer
model objects.DESCRIPTION
CITATION
information for the R package.simICCdata2
to relevant helpdocssrc/init.c
.lme4
and RLRsim
to documentation.\src/init.c
to comply with R 3.4 requirements