Kendall's \(\tau_{b}\)

Calculate Kendall's tau-b. The estimator could also be calculated with cor(..., method="kendall"). The calculation of confidence intervals however would not be found there.

KendallTauB(x, y = NULL, conf.level = NA, ...)

Arguments

x

a numeric vector, matrix or data.frame.

y

NULL (default) or a vector with compatible dimensions to x. If y is provided, table(x, y, ...) is calculated.

conf.level

confidence level of the interval. If set to NA (which is the default) no confidence interval will be calculated.

...

further arguments are passed to the function table, allowing i.e. to set useNA. This refers only to the vector interface.

Value

a single numeric value if no confidence intervals are requested,
and otherwise a numeric vector with 3 elements for the estimate, the lower and the upper confidence interval

References

Agresti, A. (2002) Categorical Data Analysis. John Wiley & Sons, pp. 57-59.

Kendall, M. (1955) Rank Correlation Methods, Second Edition, London: Charles Griffin and Co.

Brown, M.B.andBenedetti, J.K.(1977) Sampling Behavior of Tests for Correlation in Two-Way Contingency Tables, Journal of the American Statistical Association, 72, 309-315.

Author

Andri Signorell <andri@signorell.net>

See also

ConDisPairs yields concordant and discordant pairs

Other association measures:
GoodmanKruskalGamma, KendallTauA (tau-a), cor (method="kendall") for tau-b, StuartTauC (tau-c), SomersDelta
Lambda, GoodmanKruskalTau, UncertCoef, MutInf

Examples

# example in:
# http://support.sas.com/documentation/cdl/en/statugfreq/63124/PDF/default/statugfreq.pdf
# pp. S. 1821

tab <- as.table(rbind(c(26,26,23,18,9),c(6,7,9,14,23)))

KendallTauB(tab, conf.level=0.95)
#>     tau_b    lwr.ci    upr.ci 
#> 0.3372567 0.2114009 0.4631126