lkappa {psy}

Light's kappa for n raters

Description

Computes Light's Kappa for agreement in the case of n raters. The diagnosis (the object of the rating) may have k possible values (ordered or not).

Usage

lkappa(r, type="Cohen", weights="squared")

Arguments

r

m*n matrix, m subjects and n raters

type

type="Cohen" for a categorical diagnosis. If not, the diagnosis is supposed to be ordered

weights

weights="squared" for a weighted kappa with squared weights. If not, weigths are computed with absolute values.

Details

Light's Kappa is equal to the mean of the n(n-1)/2 kappas obtained from each pair of raters. Missing values are omitted locally when considering each pair of raters. If type="Cohen" the diagnosis is considered as a categorical variable. If not, the diagnosis is considered as an ordered variable and weigthed kappa's are computed. In this last situation, the type of weights that is used (squared or absolute values) is given by the variable weigths.

Value

kappa (mean of the n(n-1)/2 kappas obtained from each pair of raters)

Author(s)

Bruno Falissard

References

Conger, A.J. (1980), Integration and generalisation of Kappas for multiple raters, Psychological Bulletin, 88, 322-328.

Examples

data(expsy)
lkappa(expsy[,c(11,13,15)])       # Light's kappa for non binary diagnosis
lkappa(expsy[,c(12,14,16)])       # Light's kappa for binary diagnosis
lkappa(expsy[,c(11,13,15)], type="weighted")      # Light's kappa for non binary ordered diagnosis

#to obtain a 95%confidence interval:
#library(boot)
#lkappa.boot <- function(data,x) {lkappa(data[x,], type="weighted")}
#res <- boot(expsy[,c(11,13,15)],lkappa.boot,1000)
#quantile(res$t,c(0.025,0.975))    # Bootstrapped confidence interval of Light's kappa
#boot.ci(res,type="bca")           # adjusted bootstrap percentile (BCa) confidence interval