cronbach: Robust Cronbach's alpha

In alpha: Robust Cronbach's alpha with missing and non-normal data

Description

Calculate alpha for a given data set.

Usage

cronbach(y, varphi = 0.1, se = FALSE, complete = FALSE)

Arguments

y	Data
varphi	Downweight rate
se	Whether to estimate standard error. It will take significant more time if se is requested.
complete	Calculate alpha only based on complete data (lisewise deletion)

Author(s)

Zhiyong Zhang and Ke-Hai Yuan

References

Zhang, Z. & Yuan, K.-H. (2013). Robust Cronbach's alpha.

Examples

data(holzinger)
spatial<-holzinger[, c('visual', 'cubes', 'paper', 'lozenge', 'paperrev','flagssub')]
verbal<-holzinger[, c('general', 'paragrap', 'sentence', 'wordc', 'wordm')]
speed<-holzinger[, c('add', 'code', 'counting', 'straight')]
memory<-holzinger[, c('wordr', 'numberr', 'figurer', 'object', 'numberf', 'figurew')]

alpha.spatial<-cronbach(spatial, varphi=.01)

alpha documentation built on May 2, 2019, 6:11 p.m.