weighted Kappa for 2 raters

Description

Computes a weighted Kappa for agreement in the case of 2 raters. The diagnosis (the object of the rating) may have k possible ordered values.

Usage

1
wkappa(r,weights="squared")

Arguments

r

n*2 matrix or dataframe, n subjects and 2 raters

weights

weights="squared" to obtain squared weights. If not, absolute weights are computed (see details)

Details

The diagnoses are ordered as follow: numbers < letters, letters and numbers ordered naturally. For weigths="squared", weights are related to squared differences between rows and columns indices (in this situation wkappa is close to an icc). For weights!="squared", weights are related to absolute values of differences between rows and columns indices. The function deals with the case where the two raters have not exactly the same scope of rating (some software associate an error with this situation). Missing value are omitted.

Value

A list with :

$table

the 2*k table of raw data (first rater in rows, second rater in columns)

$weights

"squared" or "absolute"

$kappa

Weighted Kappa

Author(s)

Bruno Falissard

References

Cohen, J. Weighted kappa: nominal scale agreement with provision for scaled disagreement or partial credit. Psychological Bulletin 70 (1968): 213-220.

Examples

1
2
3
4
5
6
7
8
9
data(expsy)
wkappa(expsy[,c(11,13)])        # weighted kappa (squared weights)

#to obtain a 95%confidence interval:
#library(boot)
#wkappa.boot <- function(data,x) {wkappa(data[x,])[[3]]}
#res <- boot(expsy[,c(11,13)],wkappa.boot,1000)
#quantile(res$t,c(0.025,0.975))  # two-sided bootstrapped confidence interval of weighted kappa
#boot.ci(res,type="bca")         # adjusted bootstrap percentile (BCa) confidence interval (better)