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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