Main File for S2 main CAM study

Notes

compute reliability coefficients

### compute inter-rater coefficients


# addRatingColum(filesRater = files_rater)
cohensKappas <- computeCohensKappa(files = files_rater,
                                   numberRaters = length(files_rater))
cohensKappas

           [,1]       [,2] [,3]       [,4]
[1,] 1.00000000 0.02912621    0 0.00000000
[2,] 0.02912621 1.00000000    0 0.00990099
[3,] 0.00000000 0.00000000    1 0.00000000
[4,] 0.00000000 0.00990099    0 1.00000000

cohensKappasMaximized <- computeCohensKappaMaximized(files = files_rater,
                                                     numberRaters = length(files_rater))
cohensKappasMaximized

          [,1]      [,2]      [,3]      [,4]
[1,] 1.0000000 0.2829132 0.4595216 0.4923259
[2,] 0.2829132 1.0000000 0.2181392 0.2834395
[3,] 0.4595216 0.2181392 1.0000000 0.5106036
[4,] 0.4923259 0.2834395 0.5106036 1.0000000

see raw data

setwd("data")
tmp_namesRater <- files <- list.files(pattern = "xlsx")
setwd("..")
ovallRaterList <- getOverallRaterList(files = files_rater,
                                        orderAlphabetically = TRUE,
                                        raterNames = tmp_namesRater)

DT::datatable(ovallRaterList[,c("Words", str_subset(string = colnames(ovallRaterList), pattern = "Superordinate"))], options = list(pageLength = 5))

compute percantage of overlap

ovallRaterList$overlapNum <- NA
for(i in 1:nrow(ovallRaterList)){
ovallRaterList$overlapNum[i] <- max(table(unlist(ovallRaterList[i,c(str_subset(string = colnames(ovallRaterList), pattern = "Superordinate"))])))
}

## number raters
length(str_subset(string = colnames(ovallRaterList), pattern = "Superordinate"))

[1] 4

table(ovallRaterList$overlapNum)

 1  2  3 
17 57 26 

barplot(table(ovallRaterList$overlapNum) / nrow(ovallRaterList) * 100)

DT::datatable(ovallRaterList[ovallRaterList$overlapNum >= 3,c("Words", str_subset(string = colnames(ovallRaterList), pattern = "Superordinate"))], options = list(pageLength = 5))