# Interpretation of R output from Cohen's Kappa

I have the following result from carrying out Cohen's kappa in R

library(irr)
n = 100
o = c(rep(0,n), rep(1,n))
p = c(rbinom(n,1,0.5), rbinom(n,1,0.51))
k = kappa2(
data.frame(p,o), "unweighted"
)
k


Which outputs

 Cohen's Kappa for 2 Raters (Weights: unweighted)

Subjects = 200
Raters = 2
Kappa = -0.08

z = -1.13
p-value = 0.258


My interpretation of this

the test is displaying that there seems to be disagreement between the two vectors as kappa is negative. However, given the p value of 0.258 we can't say that this disagreement is significant, and may just be down to chance.

If someone could highlight if there is anything I'm missing from this interpretation that would be appreciated.

• Please use seeded-random data (set.seed()) so we get a reproducible example. Also, try other package implementations such as DescTools::CohenKappa(), it gives you lower and upper confidence intervals which might be more meaningful to decide whether you can conclude there was no agreement/disagreement. – smci Apr 23 '19 at 8:45

• report the percentage agreement, note if any one category was more prevalent (a case when % agreement may be high but $$\kappa$$ may be low)