stratified.cronbach.alpha {sirt} | R Documentation |
Stratified Cronbach's Alpha
Description
This function computes the stratified Cronbach's Alpha for composite scales (Cronbach, Schoenemann & McKie, 1965; He, 2010; Meyer, 2010).
Usage
stratified.cronbach.alpha(data, itemstrata=NULL)
Arguments
data |
An |
itemstrata |
A matrix with two columns defining the item stratification.
The first column contains the item names, the second column
the item stratification label (these can be integers).
The default |
References
Cronbach, L. J., Schoenemann, P., & McKie, D. (1965). Alpha coefficient for stratified-parallel tests. Educational and Psychological Measurement, 25, 291-312. doi:10.1177/001316446502500201
He, Q. (2010). Estimating the reliability of composite scores. Ofqual/10/4703. Coventry: The Office of Qualifications and Examinations Regulation.
Meyer, P. (2010). Reliability. Cambridge: Oxford University Press.
Examples
#############################################################################
# EXAMPLE 1: data.read
#############################################################################
data(data.read, package="sirt")
dat <- data.read
I <- ncol(dat)
# apply function without defining item strata
sirt::stratified.cronbach.alpha( data.read )
# define item strata
itemstrata <- cbind( colnames(dat), substring( colnames(dat), 1,1 ) )
sirt::stratified.cronbach.alpha( dat, itemstrata=itemstrata )
## scale I alpha mean.tot var.tot alpha.stratified
## 1 total 12 0.677 8.680 5.668 0.703
## 2 A 4 0.545 2.616 1.381 NA
## 3 B 4 0.381 2.811 1.059 NA
## 4 C 4 0.640 3.253 1.107 NA
## Not run:
#**************************
# reliability analysis in psych package
library(psych)
# Cronbach's alpha and item discriminations
psych::alpha(dat)
# McDonald's omega
psych::omega(dat, nfactors=1) # 1 factor
## Alpha: 0.69
## Omega Total 0.69
##=> Note that alpha in this function is the standardized Cronbach's
## alpha, i.e. alpha computed for standardized variables.
psych::omega(dat, nfactors=2) # 2 factors
## Omega Total 0.72
psych::omega(dat, nfactors=3) # 3 factors
## Omega Total 0.74
## End(Not run)