kappaFleiss {KappaGUI}

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.

Details

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

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.

Author(s)

Frédéric Santos, [e-mail]

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

# 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)