Kendall’s taub is a nonparametric measure of association based on the number of concordances and discordances in paired observations. Concordance occurs when paired observations vary together, and discordance occurs when paired observations vary differently. The formula for Kendall’s taub is

where , , and . The is the number of tied values in the th group of tied values, is the number of tied values in the th group of tied values, is the number of observations, and is defined as

PROC CORR computes Kendall’s taub by ranking the data and using a method similar to Knight (1966). The data are double sorted by ranking observations according to values of the first variable and reranking the observations according to values of the second variable. PROC CORR computes Kendall’s taub from the number of interchanges of the first variable and corrects for tied pairs (pairs of observations with equal values of X or equal values of Y).
Probability values for Kendall’s taub are computed by treating

as coming from a standard normal distribution where

and , the variance of , is computed as

where
The sums are over tied groups of values where is the number of tied values and is the number of tied values (Noether, 1967). The sampling distribution of Kendall’s partial taub is unknown; therefore, the probability values are not available.