cronbach.alpha {ltm} | R Documentation |
Cronbach's alpha
Description
Computes Cronbach's alpha for a given data-set.
Usage
cronbach.alpha(data, standardized = FALSE, CI = FALSE,
probs = c(0.025, 0.975), B = 1000, na.rm = FALSE)
Arguments
data |
a |
standardized |
logical; if |
CI |
logical; if |
probs |
a numeric vector of length two indicating which quantiles to use for the Bootstrap CI. |
B |
the number of Bootstrap samples to use. |
na.rm |
logical; what to do with |
Details
The Cronbach's alpha computed by cronbach.alpha()
is defined as follows
where is the number of items
is the variance of the observed total test scores, and
is the variance
of the
th item.
The standardized Cronbach's alpha computed by cronbach.alpha()
is defined as follows
where is the
number of items, and
is the average of all (Pearson) correlation coefficients between the
items. In this case if
na.rm = TRUE
, then the complete observations (i.e., rows) are used.
The Bootstrap confidence interval is calculated by simply taking B
samples with replacement from data
,
calculating for each or
, and computing the quantiles according to
probs
.
Value
cronbach.alpha()
returns an object of class cronbachAlpha
with components
alpha |
the value of Cronbach's alpha. |
n |
the number of sample units. |
p |
the number of items. |
standardized |
a copy of the |
name |
the name of argument |
ci |
the confidence interval for alpha; returned if |
probs |
a copy of the |
B |
a copy of the |
Author(s)
Dimitris Rizopoulos d.rizopoulos@erasmusmc.nl
References
Cronbach, L. J. (1951) Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297–334.
Examples
# Cronbach's alpha for the LSAT data-set
# with a Bootstrap 95% CI
cronbach.alpha(LSAT, CI = TRUE, B = 500)