Unidimensional and Multidimensional Reliability Coefficients

Calculates and compares various reliability coefficients for unidimensional and multidimensional scales. Supported unidimensional estimators include coefficient alpha, congeneric reliability, the Gilmer-Feldt coefficient, Feldt's classical congeneric reliability, Hancock's H, Heise-Bohrnstedt's omega, Kaiser-Caffrey's alpha, and Ten Berge and Zegers' mu series. Multidimensional estimators include stratified alpha, maximal reliability, correlated factors reliability, second-order factor reliability, and bifactor reliability. See Cho (2021) , Cho (2024) , Cho (2025) .

reliacoef

The goal of reliacoef is to calculate and compare various unidimensional and multidimensional reliability coefficients.

• Provides the following unidimensional reliability coefficients
  • coefficient alpha
  • Unidimensional confirmatory factor analysis reliability, commonly referred to as composite reliability
  • Gilmer-Feldt reliability coefficient
  • Feldt's classical congeneric reliability coefficient
  • Hancock's H
  • Heise-Borhnstedt's Omega
  • Kaiser-Caffrey's alpha
  • Ten Berge and Zegers's mu series (mu2, mu3, mu4)
• Provides the following multidimensional reliability coefficients, omega hierarchical, and subdimensional reliability
  • Stratified alpha
  • Maximal reliability
  • Multidimensional parallel reliability
  • Correlated factors reliability
  • Second-order factor reliability
  • Bifactor reliability
• Collects and compare reliability coefficients provided by other packages
  • Two versions of GLB (greatest lower bounds) offered by the package psych
  • Guttman's lamdas offered by the package Lambda4
• Test essential tau-equivalence and explore unidimensionality

Installation

You can download and install it from Github using the devtools package:

install.packages("devtools")
devtools::install_github("eunscho/reliacoef")

Example

The most typical use would be the unirel and multirel function comparing several reliability coefficients:

library(unirel)
unirel(Graham1)
## compare various unidimensional reliability coefficients
multirel(Osburn_moderate, until = 4)
## compare various multidimensional reliability coefficients

You can also get each coefficient separately.

alpha(Graham1)
## obtain coefficient alpha
joreskog(Graham1)
## obtain composite (congeneric) reliability (unidimensional CFA reliability)
gilmer(Graham1)
## obtain the Gilmer-Feldt coefficient
feldt(Graham1)
## obtain Feldt's classical congeneric reliability
hancock(Graham1)
## obtain Hancock's H (maximal reliability)
heise(Graham1)
## obtain Heise-Borhnstedt's Omega
kaisercaffrey(Graham1)
## obtain Kaiser-Caffrey's alpha
mu2(Graham1)
## obtain Ten Berge and Zegers' mu2
mu3(Graham1)
## obtain Ten Berge and Zegers' mu3
mu4(Graham1)
## obtain Ten Berge and Zegers' mu4
stratified_alpha(Osburn_moderate, 4)
## obtain stratified alpha
multi_parallel(Osburn_moderate, 4)
## obtain multidimensional parallel reliability
second_order(Osburn_moderate, 4)
## obtain second-order factor reliability
bifactor(Osburn_moderate, 4)
## obtain bifactor reliability
maximal_reliability(Osburn_moderate, 4)
## obtain maximal reliability
correlated_factors(Osburn_moderate, 4)
## obtain correlated factors reliability

You can test essential tau-equivalence and explore unidimensionality.

test.tauequivalence(Graham1)
## test the assumption of essential tau-equivalence 

Troubleshooting

Sometimes an error message appears.

Error in standardizedsolution(fit) :

The solution is to activate the lavaan package.

library(lavaan)