Cronbach's Coefficient Alpha
Cronbach's alpha is a measure of internal consistency and often used for validating psychometric tests. It determines the internal consistency or average correlation of items in a survey instrument to gauge its reliability. This reduces to Kuder-Richardson formula 20 (KR-20) when the columns of the data matrix are dichotomous.
CronbachAlpha(x, conf.level = NA, cond = FALSE, na.rm = FALSE)
x |
k x m matrix or dataframe with item responses, k subjects (in rows) m items (in columns). |
conf.level |
confidence level of the interval. If set to |
cond |
logical. If set to |
na.rm |
logical, indicating whether |
Either a numeric value or
a named vector of 3 columns if confidence levels are required (estimate, lower and upper ci) or
a list containing the following components, if the argument cond
is set to TRUE
:
unconditional |
Cronbach's Alpha, either the single value only or with confidence intervals |
condCronbachAlpha |
The alpha that would be realized if the item were excluded |
Andri Signorell <andri@signorell.net>, based on code of Harold C. Doran
Cohen, J. (1960), A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20, 37-46.
set.seed(1234) tmp <- data.frame( item1=sample(c(0,1), 20, replace=TRUE), item2=sample(c(0,1), 20, replace=TRUE), item3=sample(c(0,1), 20, replace=TRUE), item4=sample(c(0,1), 20, replace=TRUE), item5=sample(c(0,1), 20, replace=TRUE) ) CronbachAlpha(tmp[,1:4], cond=FALSE, conf.level=0.95) CronbachAlpha(tmp[,1:4], cond=TRUE, conf.level=0.95) CronbachAlpha(tmp[,1:4], cond=FALSE) CronbachAlpha(tmp[,1:2], cond=TRUE, conf.level=0.95) ## Not run: # Calculate bootstrap confidence intervals for CronbachAlpha library(boot) cronbach.boot <- function(data,x) {CronbachAlpha(data[x,])[[3]]} res <- boot(datafile, cronbach.boot, 1000) quantile(res$t, c(0.025,0.975)) # two-sided bootstrapped confidence interval of Cronbach's alpha boot.ci(res, type="bca") # adjusted bootstrap percentile (BCa) confidence interval (better) ## End(Not run)
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