mcron {CMO} | R Documentation |
Calculate Cronbach's Alpha
mcron(dataf, ifItemDel = TRUE, nBootRep = 0)
dataf |
n*p data frame, n subjects p items |
ifItemDel |
TRUE if Cronbach's alpha should be computed only from complete data sets (No NA allowed). FALSE otherwise. |
nBootRep |
number of bootstrap replicates to estimate Cronbach's Alpha. If zero (default) no bootstrapping will be performed. |
Cronbach's alpha has an important use as a measure of the reliability of a psychometric instrument. It indicates the extent to which a set of test items can be treated as measuring a single latent variable. Alpha can take values between minus infinity and 1 (although only positive values make sense). As a rule of thumb, a proposed psychometric instrument should only be used if an alpha value of 0.70 or higher is obtained on a substantial sample. However the standard of reliability required varies between fields of psychology: cognitive tests (tests of intelligence or achievement) tend to be more reliable than tests of attitudes or personality. There is also variation within fields: it is easier to construct a reliable test of a specific attitude than of a general one, for example.
AllAlpha |
Cronbach's alpha |
IfItemDel |
|
Nalpha |
number of subjects |
Boot.StatDist |
(only if bootstrapping is used) Distance statistic for Cronbach's Alpha |
Boot.95PercConf |
(only if bootstrapping is used) 95% confidence interval for bootstrapping distance statistic |
Boot.nBootRep |
(only if bootstrapping is used) number of bootstrap replicates used |
Christian Montel
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297-333.
Allen, M.J., & Yen, W. M. (2002). Introduction to Measurement Theory. Long Grove, IL: Waveland Press.
function cronbach in package psy
#create some arbitrary results data <- matrix(ceiling(runif(400)*100),nrow=20) #works #create some missing values does not work a BUG! #data[round(runif(400)*0.7) == 1] <- NA mcron(data,ifItemDel = TRUE,nBootRep=100)