kappaCohen: Calculates Cohen's kappa for all pairs of columns in a given...
In KappaGUI: An R-Shiny Application for Calculating Cohen's and Fleiss' Kappa

Description Usage Arguments Details Value Author(s) References See Also Examples

This function is based on the function 'kappa2' from the package 'irr', and simply adds the possibility of calculating several kappas at once.

1	kappaCohen(data, weight="unweighted")

data

dataframe with 2 x p columns, p being the number of traits coded by the two raters. The first two columns represent the scores attributed by the two raters for the first trait; the next two columns represent the scores attributed by the two raters for the second trait; etc. The dataframe must contains a header, and each column must be labeled as follows: ‘VariableName_X’, where X is a unique character (letter or number) associated with each rater (cf. below for an example).

weight

character string specifying the weighting scheme ("unweighted", "equal" or "squared"). See the function ‘kappa2’ from the package ‘irr’.

For each trait, only complete cases are used for the calculation.

A dataframe with p rows (one per trait) and three columns, giving respectively the kappa value for each trait, the number of individuals used to calculate this value, and the associated p-value.

Frédéric Santos, frederic.santos@u-bordeaux.fr

Cohen, J. (1960) A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20, 37–46.

Cohen, J. (1968) Weighted kappa: Nominal scale agreement with provision for scaled disagreement or partial credit. Psychological Bulletin, 70, 213–220.

irr::kappa2

# Here we create and display an artifical dataset,
# describing two traits coded by two raters:
scores <- data.frame(
	Trait1_A = c(1,0,2,1,1,1,0,2,1,1),
	Trait1_B = c(1,2,0,1,2,1,0,1,2,1),
	Trait2_A = c(1,4,5,2,3,5,1,2,3,4),
	Trait2_B = c(2,5,2,2,4,5,1,3,1,4)
	)
scores

# Retrieve Cohen's kappa for Trait1 and Trait2,
# to evaluate inter-rater agreement between raters A and B:
kappaCohen(scores, weight="unweighted")
kappaCohen(scores, weight="squared")

Loading required package: shiny
Loading required package: irr
Loading required package: lpSolve
   Trait1_A Trait1_B Trait2_A Trait2_B
1         1        1        1        2
2         0        2        4        5
3         2        0        5        2
4         1        1        2        2
5         1        2        3        4
6         1        1        5        5
7         0        0        1        1
8         2        1        2        3
9         1        2        3        1
10        1        1        4        4
           Kappa Subjects   p-value
Trait1 0.1666667       10 0.4609948
Trait2 0.2500000       10 0.1093146
            Kappa Subjects    p-value
Trait1 -0.2222222       10 0.47505052
Trait2  0.5853659       10 0.06344434