I was working with R and SPSS trying to determine Cohen's Kappa for a dataset. I decided to test the two and see if they would end up getting the same numbers. However, they did not. I was wondering if there might be something I am doing wrong, but I cannot think what it would be.
R code:
library(irr)
var1<-c(94,25,1,6,3,7,2,9,14,13,12)
var2<-c(90,23,1,7,3,7,2,8,13,12,12)
vars.test<-cbind(var1,var2)
kappa2(vars.test)
This results in a Cohen's Kappa of 0.416 and a p-value of 4.49e-08. However when I test this within SPSS I get a a Cohen's Kappa of 0.926 with a p-value of 0.000. What is the issue?
How I entered it in SPSS: Column 1 is rater 1 and Column 2 is rater 2. Column 3 is the frequency. The numbers in column 1 and 2 refer to categories, with 12 being None observed. This is not scaled data or anything funky, simply the number of observed events for a category.
irr
package is quite clear. You have to enter two-column caseweise data, or a two-column aggregared data plus a weight column (same as you did in SPSS). But I can't understand at all how your 11 pairs in R correspond to your SPSS data. $\endgroup$