### Chapter: Levels of agreement: Kappa, Krippendorff and the ICC

cohen_1960data <- read.delim("http://www.robin-beaumont.co.uk/virtualclassroom/book2data/cohen_1960.dat", header=TRUE)
cohen_1960data

install.packages("irr", dependencies=TRUE)
library(irr)

kappa2(cohen_1960data)

# how to do it if you need to select columns 
# does not work for the example dataset as only has the required columns:
# kappa2(cohen_1960data[,2:3]) 
#kappa2(cohen_1960data[,c(1,4)]) 

## Krippendorff - the do it all statistic:
## kripp.alpha(x, method=c("nominal","ordinal","interval","ratio"))

cohen_1960data_trans   <- t(cohen_1960data)
cohen_1960data_trans

kripp.alpha(cohen_1960data_trans, "nominal")

## Ordinal level of measurement variables 
# kripp.alpha(dataframe, "ordinal") 
# or for weighted Kappa: kappa2(cohen_1960data, "squared").
kripp.alpha(cohen_1960data_trans, "ordinal")
 kappa2(cohen_1960data, "squared")
 
# Interval/ ratio data level of measurement variables 

data(anxiety)
icc(anxiety, model="twoway", type="agreeement")
# or Krippendorff equivalent:
# first transpose data row/columns
anxiety_trans <- t(anxiety)
kripp.alpha(anxiety_trans, "interval")
kripp.alpha(anxiety_trans, "ratio")