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)
if (FALSE) {
# 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)
}
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