| confint.krippendorffsalpha {krippendorffsalpha} | R Documentation |
Compute a confidence interval for Krippendorff's Alpha.
Description
Compute a confidence interval for Krippendorff's Alpha.
Usage
## S3 method for class 'krippendorffsalpha'
confint(object, parm = "alpha", level = 0.95, ...)
Arguments
object |
an object of class |
parm |
always ignored since there is only one parameter. |
level |
the desired confidence level for the interval. The default is 0.95. |
... |
additional arguments. These are passed to |
Details
This function computes a confidence interval for alpha, assuming that krippendorffs.alpha was called with confint = TRUE.
For method = "analytical", a jackknife-based interval is computed. For smaller samples the jackknife interval offers a very substantial improvement over the bootstrap interval, the latter of which offers quite poor coverage. For larger samples method = "customary" can safely be used, in which case a bootstrap interval is provided. For sufficiently large datasets the two intervals will be nearly equal, but the bootstrap approach is preferred owing to its much faster execution speed.
Value
A vector with entries giving lower and upper confidence limits. These will be labelled as (1 - level) / 2 and 1 - (1 - level) / 2.
References
Nissi, M. J., Mortazavi, S., Hughes, J., Morgan, P., and Ellermann, J. (2015). T2* relaxation time of acetabular and femoral cartilage with and without intra-articular Gd-DTPA2 in patients with femoroacetabular impingement. American Journal of Roentgenology, 204(6), W695.
See Also
Examples
# Fit a subset of the cartilage data, using the customary methodology.
# Compute bootstrap confidence intervals using a bootstrap sample size
# of 1,000. Report the estimate of alpha, and produce a 99% interval.
data(cartilage)
cartilage = as.matrix(cartilage[1:100, ])
fit.cart = krippendorffs.alpha(cartilage, level = "ratio", method = "customary", confint = TRUE,
control = list(bootit = 1000, parallel = FALSE))
fit.cart$alpha.hat
confint(fit.cart, level = 0.99)