Kappa
Cohen's Kappa and Weighted Kappa
Computes two agreement rates: Cohen's kappa and weighted kappa, and confidence bands.
- Keywords
- category
Usage
Kappa(x, weights = c("Equal-Spacing", "Fleiss-Cohen"))
# S3 method for Kappa
print(x, digits=max(getOption("digits") - 3, 3),
CI=FALSE, level=0.95, ...)
# S3 method for Kappa
confint(object, parm, level = 0.95, ...)
# S3 method for Kappa
summary(object, ...)
# S3 method for summary.Kappa
print(x, ...)Arguments
- x
For
Kappa: a confusion matrix. For the print methods: object of class"Kappa"or"summary.Kappa"- weights
either one of the character strings given in the default value, or a user-specified matrix with same dimensions as
x.- digits
minimal number of significant digits.
- CI
logical; shall confidence limits be added to the output?
- level
confidence level between 0 and 1 used for the confidence interval.
- object
object of class
"Kappa".- parm
Currently, ignored.
- …
Further arguments passed to the default print method.
Details
Cohen's kappa is the diagonal sum of the (possibly weighted) relative frequencies, corrected for expected values and standardized by its maximum value. The equal-spacing weights are defined by \(1 - |i - j| / (r - 1)\), \(r\) number of columns/rows, and the Fleiss-Cohen weights by \(1 - |i - j|^2 / (r - 1)^2\). The latter one attaches greater importance to near disagreements.
Value
An object of class "Kappa" with three components:
numeric vector of length 2 with the kappa statistic
(value component), along with Approximate Standard Error
(ASE component)
idem for the weighted kappa.
numeric matrix with weights used.
Note
The summary method also prints the weights.
There is a confint method for computing approximate confidence
intervals.
References
Cohen, J. (1960), A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20, 37--46.
Everitt, B.S. (1968), Moments of statistics kappa and weighted kappa. The British Journal of Mathematical and Statistical Psychology, 21, 97--103.
Fleiss, J.L., Cohen, J., and Everitt, B.S. (1969), Large sample standard errors of kappa and weighted kappa. Psychological Bulletin, 72, 332--327.
See Also
Examples
# NOT RUN {
data("SexualFun")
K <- Kappa(SexualFun)
K
confint(K)
summary(K)
print(K, CI = TRUE)
# }