stratified.cronbach.alpha.Rd
This function computes the stratified Cronbach's Alpha for composite scales (Cronbach, Schoenemann & McKie, 1965; He, 2010; Meyer, 2010).
stratified.cronbach.alpha(data, itemstrata=NULL)
data | An \(N \times I\) data frame |
---|---|
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 |
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.
############################################################################# # 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 if (FALSE) { #************************** # 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 }