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A function and vignettes for computing an intraclass correlation described in Aguinis & Culpepper (2015) <doi:10.1177/1094428114563618>. This package quantifies the share of variance in a dependent variable that is attributed to group heterogeneity in slopes.

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tmsalab/iccbeta

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iccbeta: Intraclass Correlation

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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.

Installation

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")

Usage

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 model
results_model = icc_beta(<lmer-model>)

# Calculate icc from individual terms.
results_component = icc_beta(X, l2id, T, vy)

Authors

Steven Andrew Culpepper and Herman Aguinis

Citing the iccbeta package

To 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")

License

GPL (>= 2)

About

A function and vignettes for computing an intraclass correlation described in Aguinis & Culpepper (2015) <doi:10.1177/1094428114563618>. This package quantifies the share of variance in a dependent variable that is attributed to group heterogeneity in slopes.

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