[1] Kenneth McGraw and S. P. Wong returned to the concept in 1992[2] preferring the term common language effect size.
The term probability of superiority was proposed by R. J. Grissom[3] a couple of years later.
Kerby (2014) notes that a pair, defined as a score in one group paired with a score in another group, is a core concept of the common language effect size.
[4] As another example, consider a scientific study (maybe of a treatment for some chronic disease, such as arthritis) with ten people in the treatment group and ten people in a control group.
The result, as the percent of pairs that support the hypothesis, is the common language effect size.
The Kerby simple difference formula computes the rank-biserial correlation from the common language effect size.
In other words, the correlation is the difference between the common language effect size and its complement.
For example, if the common language effect size is 60%, then the rank-biserial r equals 60% minus 40%, or r = 0.20.
The Kerby formula is directional, with positive values indicating that the results support the hypothesis.