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

```
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, ...)
```

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.

- 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.

David Meyer David.Meyer@R-project.org

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.

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.

`agreementplot`

,
`confint`

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

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