alpha: Robust Cronbach's alpha and McDonald's omega

In coefficientalpha: Robust Coefficient Alpha and Omega with Missing and Non-Normal Data

Robust Cronbach's alpha and McDonald's omega

Description

Calculate alpha or omega for a given data set.

Usage

alpha(y, varphi = 0.1, se = FALSE, test = TRUE, 
complete =FALSE, auxiliary = NULL, drop, silent = TRUE)
omega(y, varphi = 0.1, se = FALSE, test = TRUE, 
complete =FALSE, auxiliary = NULL, drop, silent = TRUE)

Arguments

y	Data
varphi	Downweight rate
se	Whether to estimate standard error. It might take significant more time if se is requested with many items.
test	Whether to test the assumption of alpha (tau equivalent test) or omega (homogeneous test).
complete	Calculate alpha/omega only based on complete data (listwise deletion)
auxiliary	Provide a matrix or data frame of auxiliary variables for missing data analysis.
drop	The row number of cases to be dropped from the analysis.
silent	Whether to print information of the analysis.

Author(s)

Zhiyong Zhang and Ke-Hai Yuan

References

Zhang, Z. & Yuan, K.-H. (2014). Robust Coefficients Alpha and Omega and their Confidence Intervals: Methods and Software.

Examples

data(example)

alpha(example, varphi=.01)
omega(example, varphi=.01)

coefficientalpha documentation built on Aug. 27, 2023, 9:06 a.m.