KappaGUI (version 2.0.2)

kappaCohen: Calculates Cohen's kappa for all pairs of columns in a given dataframe

Description

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

Usage

kappaCohen(data, weight="unweighted")

Arguments

data

dataframe with \(2 \times p\) 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’.

Value

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.

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::kappa2

Examples

# NOT RUN {
# 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")
# }