Kendall's Coefficient of Concordance W
Computes Kendall's coefficient of concordance, a popular measure of association. It is an index of interrater reliability of ordinal data. The coefficient could be corrected for ties within raters.
KendallW(x, correct = FALSE, test = FALSE, na.rm = FALSE)
x |
k x m matrix or dataframe, k subjects (in rows) m raters (in columns). |
correct |
a logical indicating whether the coefficient should be corrected for ties within raters. |
test |
a logical indicating whether the test statistic and p-value should be reported. |
na.rm |
logical, indicating whether |
The test for Kendall's W is completely equivalent to friedman.test. The only advantage of this test over Friedman's is that Kendall's W has an interpretation as the coefficient of concordance. The test itself is only valid for large samples.
Kendall's W should be corrected for ties, if raters did not use a true ranking order for the subjects.
Either a single value if test is set to FALSE or else
a list with class “htest” containing the following components:
statistic |
the value of the chi-square statistic. |
p.value |
the p-value for the test. |
method |
the character string “Kendall's coefficient of concordance W”. |
data.name |
a character string giving the name(s) of the data. |
estimate |
the coefficient of concordance. |
parameter |
the degrees of freedom df, the number of subjects examined and the number of raters. |
This function was previously published as kendall() in the irr package and has been
integrated here without logical changes, but with some adaptations in the result structure.
Matthias Gamer <m.gamer@uke.uni-hamburg.de>
Kendall, M.G. (1948) Rank correlation methods. London: Griffin.
anxiety <- data.frame(rater1=c(3,3,3,4,5,5,2,3,5,2,2,6,1,5,2,2,1,2,4,3),
rater2=c(3,6,4,6,2,4,2,4,3,3,2,3,3,3,2,2,1,3,3,4),
rater3=c(2,1,4,4,3,2,1,6,1,1,1,2,3,3,1,1,3,3,2,2))
KendallW(anxiety, TRUE)
# with test results
KendallW(anxiety, TRUE, test=TRUE)
# example from Siegel and Castellan (1988)
d.att <- data.frame(
id = c(4,21,11),
airfare = c(5,1,4),
climate = c(6,7,5),
season = c(7,6,1),
people = c(1,2,3),
program = c(2,3,2),
publicity = c(4,5,7),
present = c(3,4,6),
interest = c(8,8,8)
)
KendallW(t(d.att[, -1]), test = TRUE)
# which is perfectly the same as
friedman.test(y=as.matrix(d.att[,-1]), groups = d.att$id)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.