kendall.u: Kendall's Coefficient of Agreement

In eba: Elimination-by-Aspects Models

Description

Kendall's u coefficient of agreement between judges.

Usage

kendall.u(M, correct = TRUE)

Arguments

M	a square matrix or a data frame consisting of absolute choice frequencies; row stimuli are chosen over column stimuli
correct	logical, if TRUE (default) a continuity correction is applied when computing the test statistic (by subtracting one from the sum of agreeing pairs)

Details

Kendall's u (Kendall and Babington Smith, 1940) takes on values between min.u (minimum agreement) and 1 (maximum agreement). The minimum min.u equals -1/(m - 1), if m is even, and -1/m, if m is odd, where m is the number of subjects (judges).

The null hypothesis in the chi-square test is that the agreement between judges is by chance.

It is assumed that there is an equal number of observations per pair and that each subject judges each pair only once.

Value

u	Kendall's u coefficient of agreement
min.u	the minimum value for u
chi2	the chi-square statistic for a test that the agreement is by chance
df	the degrees of freedom
p.value	the p-value of the test

References

Kendall, M.G., & Babington Smith, B. (1940). On the method of paired comparisons. Biometrika, 31, 324–345. doi: 10.1093/biomet/31.3-4.324

See Also

schoolsubjects, eba, strans, circular.

Examples

data(schoolsubjects)
lapply(schoolsubjects, kendall.u)  # better-than-chance agreement

Example output

$boys

Kendall's u coefficient of agreement

u = 0.1866, minimum u = -0.04762
chi2 = 412.22, df = 90.75, p-value = 1.721e-42
alternative hypothesis: between-judges agreement is not by chance
continuity correction has been applied


$girls

Kendall's u coefficient of agreement

u = 0.08218, minimum u = -0.04
chi2 = 180.12, df = 62.38, p-value = 2.307e-13
alternative hypothesis: between-judges agreement is not by chance
continuity correction has been applied

eba documentation built on Jan. 13, 2021, 10:12 a.m.