Hi,
It doesn't seem happy with non-numeric data in the data frame version.
Maybe a recode would work?
> x1 <- c(1, 2, 3, 1)
> y1 <- c(1, 3, 3, 1)
> cohen.kappa(data.frame(x = x1, y = y1))
Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha)
Cohen Kappa and Weighted Kappa correlation coefficients and confidence
boundaries
lower estimate upper
unweighted kappa 0.098 0.60 1.1
weighted kappa 0.601 0.86 1.1
The unweighted kappa is .60.
I also tried to create the p x p table version, thinking that it would
be unhappy with less than a p x p table. The example dataset produces a
3 x 2 table, so this pads it out to a 3 x 3:
> x <- factor(x)
> y <- factor(y, levels = c("blue", "red", "yellow"))
> table(x,y)
y
x blue red yellow
blue 1 0 0
red 0 2 0
yellow 1 0 0
> cohen.kappa(table(x,y))
Call: cohen.kappa1(x = x, w = w, n.obs = n.obs, alpha = alpha)
Cohen Kappa and Weighted Kappa correlation coefficients and confidence
boundaries
lower estimate upper
unweighted kappa 0.098 0.6 1.10
weighted kappa -0.693 0.0 0.69
Number of subjects = 4>
The unweighted kappa is the same as above and as found by Jim with other
packages.
Scot
On 5/25/2010 7:31 AM, Jim Lemon wrote:
On 05/25/2010 06:01 PM, Jason Priem wrote:
Hi,
I've got two vectors with ratings from two coders, like this:
x<-c("red", "yellow", "blue", "red") #coder number 1
y<-c("red", "blue", "blue", "red") #coder number 2
I want to find Cohen's Kappa using the wkappa function in the psych
package. The only example in the docs is using a matrix, which I'm
afraid I don't understand--I don't know how to get there from what I've
got. Could anyone point me in the right direction? Thanks!
Hi Jason,
You're not alone. I tried to work out how to run this and it took a
while. Both kappa2 in the "irr" package:
kappa2(cbind(x,y))
and classAgreement in the "e1071" package:
classAgreement(table(x,y))
produce a kappa of 0.6. I was unable to work out how to use the wkappa
function in the "psych" package:
wkappa(table(x,y))
The above led to a kappa of -0.8. Although wkappa is presented as a
test of the reliability of ratings of nominal level data, the example
uses numeric data.
Jim
--
Scot McNary
smcnary at charm dot net
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