KappaGUI (version 2.0.2)

kappaFleiss: Calculates Fleiss' kappa between \(k\) raters for all \(k\)-uplets of columns in a given dataframe

Description

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

Usage

kappaFleiss(data, nb_raters=3)

Arguments

data

dataframe with \(k \times p\) columns, \(k\) being the number of raters, and \(p\) the number of traits. The first \(k\) columns represent the scores attributed by the \(k\) raters for the first trait; the next \(k\) columns represent the scores attributed by the \(k\) 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).

nb_raters

integer for the number of raters.

Value

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

Details

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

References

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.

See Also

irr::kappam.fleiss

Examples

# NOT RUN {
# Here we create and display an artifical dataset,
# describing two traits coded by three 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),
	Trait1_C = c(2,2,2,1,1,1,0,1,2,1),
	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),
	Trait2_C = c(2,4,3,2,4,5,2,2,3,4)
	)
scores

# Retrieve Fleiss' kappa for Trait1 and Trait2,
# to evaluate inter-rater agreement between raters A, B and C:
kappaFleiss(scores, nb_raters=3)
# }