# CronbachAlpha

0th

Percentile

##### 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.

Keywords
multivar
##### Usage
CronbachAlpha(x, conf.level = NA, cond = FALSE, na.rm = FALSE)
##### Arguments
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 NA (which is the default) no confidence interval will be calculated.
cond
logical. If set to TRUE, alpha is additionally calculated for the dataset with each item left out.
na.rm
logical, indicating whether 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.
##### Value

Either a numeric value or a named vector of 3 columns if confidence levels are required (estimate, lower and upper ci) ora list containing the following components, if the argument cond is set to TRUE:

##### References

Cohen, J. (1960), A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20, 37-46.

##### See Also

CohenKappa, KappaM

##### Aliases
• CronbachAlpha
##### Examples
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,])[]}
# 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)

Documentation reproduced from package DescTools, version 0.99.19, License: GPL (>= 2)

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