CronbachAlpha(x, conf.level = NA, cond = FALSE, na.rm = FALSE)
NA
(which is the default) no confidence interval will be calculated.TRUE
, alpha is additionally calculated for the dataset with each item left out. NA
values should be stripped before the computation proceeds. If set to TRUE
only the complete cases of the ratings will be used. Defaults to FALSE
.
cond
is set to TRUE
:CohenKappa
, KappaM
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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