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vcd (version 1.4-13)

Kappa: Cohen's Kappa and Weighted Kappa

Description

Computes two agreement rates: Cohen's kappa and weighted kappa, and confidence bands.

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, ...)

Value

An object of class "Kappa" with three components:

Unweighted

numeric vector of length 2 with the kappa statistic (value component), along with Approximate Standard Error (ASE component)

Weighted

idem for the weighted kappa.

Weights

numeric matrix with weights used.

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.

Author

David Meyer David.Meyer@R-project.org

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.

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

agreementplot, confint

Examples

Run this code
data("SexualFun")
K <- Kappa(SexualFun)
K
confint(K)
summary(K)
print(K, CI = TRUE)

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