Package: iccbeta 1.2.0

Steven Andrew Culpepper

iccbeta: Multilevel Model Intraclass Correlation for Slope Heterogeneity

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.

Authors:Steven Andrew Culpepper [aut, cph, cre], Herman Aguinis [aut, cph]

iccbeta_1.2.0.tar.gz
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iccbeta.pdf |iccbeta.html✨
iccbeta/json (API)
NEWS

# Install 'iccbeta' in R:
install.packages('iccbeta', repos = 'https://cloud.r-project.org')

Bug tracker:https://github.com/tmsalab/iccbeta/issues2 issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • Hofmann - A multilevel dataset from Hofmann, Griffin, and Gavin (2000).
  • simICCdata - Simulated data example from Aguinis and Culpepper (2015).

On CRAN:

Conda:r-iccbeta-1.2.0(2025-03-25)

openblascpp

1.70 score 185 downloads 1 exports 14 dependencies

Last updated 6 years agofrom:6e3451ba3e. Checks:1 OK, 2 NOTE. Indexed: no.

TargetResultLatest binary
Doc / VignettesOKMar 21 2025
R-4.5-linux-x86_64NOTEMar 21 2025
R-4.4-linux-x86_64NOTEMar 21 2025

Exports:icc_beta

Dependencies:bootlatticelme4MASSMatrixminqanlmenloptrrbibutilsRcppRcppArmadilloRcppEigenRdpackreformulas

Citation

To cite the package 'iccbeta' in publications use:

Culpepper, S. A. and Agunis, H. (2015). iccbeta: Multilevel Model Intraclass Correlation for Slope Heterogeneity. URL https://cran.r-project.org/package=iccbeta.

Agunis, H. & Culpepper, S. A. (2015). An expanded decision making procedure for examining cross-level interaction effects with multilevel modeling. Organizational Research Methods.

Corresponding BibTeX entries: 

  @Manual{,
    title = {{iccbeta: Multilevel Model Intraclass Correlation for
      Slope Heterogeneity}},
    author = {Steven Andrew Culpepper and Herman Agunis},
    year = {2015},
  }

  @Article{,
    title = {An expanded decision making procedure for examining
      cross-level interaction effects with multilevel modeling},
    author = {Herman Aguinis and Steven Andrew Culpepper},
    journal = {Organization Research Methods},
    year = {2015},
    url = {http://www.hermanaguinis.com/pubs.html},
    pdf = {http://www.hermanaguinis.com/ORM2015.pdf},
    doi = {10.1177/1094428114563618},
  }

Readme and manuals

iccbeta R packageiccbeta

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 packageiccbeta

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)