

Kendall’s tau-b 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 tau-b 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 
         
![\[  \mr {sgn}(z) = \left\{  \begin{array}{ll} 1 &  \mr {if} \, \,  z > 0 \\ 0 &  \mr {if} \, \,  z = 0 \\ -1 &  \mr {if} \, \,  z < 0 \end{array} \right.  \]](images/procstat_corr0063.png)
PROC CORR computes Kendall’s tau-b 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 tau-b 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 tau-b 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 tau-b is unknown; therefore, the probability values are not available.