Title: Multilevel Model Intraclass Correlation for Slope Heterogeneity
person("Herman", "Aguinis", role = c("aut", "cph"), email =
Description: A function and vignettes for computing an intraclass correlation
This package quantifies the share of variance in a dependent variable that
is attributed to group heterogeneity in slopes.
Author: Steven Andrew Culpepper [aut, cph, cre],

Title: Multilevel model intraclass correlation for slope heterogeneity
"sculpepp@illinois.edu"),person("Herman", "Aguinis", role = c("aut", "cph"), email =
Description: 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.

LinkingTo: Rcpp (>= 0.12.12), RcppArmadillo (>= 0.7.800)

LinkingTo: Rcpp (>= 1.0.0), RcppArmadillo (>= 0.9.200)
Herman Aguinis [aut, cph] (<https://orcid.org/0000-0002-3485-9484>)

Title: Computation of the Double-Entry Intraclass Correlation
Author: Christian Blötner, Michael Paul Grosz
Description: The function computes the profile similarity measure double-entry intraclass correlation. It is a more precise index of the agreement of two empirically observed profiles than the often used intraclass correlation or profile correlation. In the case of score data with different scale formats, it is recommended to z-standardize the scores before entering into the function. For details, see Furr (2010) <doi:10.1080/00223890903379134> or McCrae (2008) <doi:10.1080/00223890701845104>.
Packaged: 2020-12-02 11:42:30 UTC; Christian Blötner

Description: The function computes the profile similarity measure double-entry intraclass correlation. It is a more precise index of the agreement of two
empirically observed profiles than the often used intraclass correlation or profile correlation. Profiles comprising correlations are transformed         according to the Fisher z transformation before the index is calculated. In the case of score data with different scale formats (e.g., if the profile        contains different IQ or a variety of personality tests), it is recommended to z-standardize the scores before entering into the function. For details,     see Furr (2010) <doi:10.1080/00223890903379134> or McCrae (2008) <doi:10.1080/00223890701845104>.
Packaged: 2021-01-21 19:20:08 UTC; Christian Blötner