PREp (when equating form X to Y) is calculated as
$$\mbox{PREp}=100\frac{\mu_p(e_Y(X))-\mu_p(Y)}{\mu_p(Y)}$$
where \(\mu_p(Y)=\sum_k(y_k)^ps_k\) and
\(\mu_p(e_Y(X))=\sum_j(e_Y(x_j))^pr_j\). Similar formulas can be found
when equating from Y to X.
References
Gonzalez, J. (2014). SNSequate: Standard and Nonstandard Statistical Models and Methods for Test
Equating. Journal of Statistical Software, 59(7), 1-30.
Von Davier, A., Holland, P., and Thayer, D. (2004). The Kernel Method of Test Equating.
New York, NY: Springer-Verlag.
#Example: Table 7.5 in Von Davier et al. (2004)
data(Math20EG)
mod.gauss<-ker.eq(scores=Math20EG,kert="gauss", hx = NULL, hy = NULL,degree=c(2, 3),design="EG")
PREp(mod.gauss,10)