SEED {SNSequate} | R Documentation |
Standard error of equating difference
Description
This function calculates the standard error of equating diference (SEED) as described in Von Davier et al. (2004).
Usage
SEED(eq1, eq2)
Arguments
eq1 |
An object of class |
eq2 |
An object of class |
Details
The SEED can be used as a measure to choose whether to support or not a certain equating function on another
another one. For instance, when h_X
and h_Y
tends to infinity, then the (gaussian kernel)
\hat{e}_Y(x)
equating function tends to the linear equating function
(see Theorem 4.5 in Von Davier et al, 2004 for more details). Thus, one can calculate the measure
SEED_Y(x)=\sqrt{Var(\hat{e}_Y(x)-\widehat{Lin}_Y(x))}
to decide between \hat{e}_Y(x)
and \widehat{Lin}_Y(x)
.
Value
A two column matrix with the values of SEEYx
for each x
in the first column and the values of
SEEXy
for each y
in the second column
Author(s)
Jorge Gonzalez jorge.gonzalez@mat.uc.cl
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.
See Also
Examples
#Example: Figure7.7 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")
mod.linear<-ker.eq(scores=Math20EG,kert="gauss", hx = 20, hy = 20,degree=c(2, 3),design="EG")
Rx<-mod.gauss$eqYx-mod.linear$eqYx
seed<-SEED(mod.gauss,mod.linear)$SEEDYx
plot(0:20,Rx,ylim=c(-0.8,0.8),pch=15)
abline(h=0)
points(0:20,2*seed,pch=0)
points(0:20,-2*seed,pch=0)
#Example Figure 10.4 in Von Davier (2011)
mod.unif<-ker.eq(scores=Math20EG,kert="unif", hx = NULL, hy = NULL,degree=c(2, 3),design="EG")
mod.logis<-ker.eq(scores=Math20EG,kert="logis", hx = NULL, hy = NULL,degree=c(2, 3),design="EG")
Rx1<-mod.logis$eqYx-mod.gauss$eqYx
Rx2<-mod.unif$eqYx-mod.gauss$eqYx
seed1<-SEED(mod.logis,mod.gauss)$SEEDYx
seed2<-SEED(mod.unif,mod.gauss)$SEEDYx
plot(0:20,Rx1,ylim=c(-0.2,0.2),pch=15,main="LK vs GK",ylab="",xlab="Scores")
abline(h=0)
points(0:20,2*seed1,pch=0)
points(0:20,-2*seed1,pch=0)
plot(0:20,Rx2,ylim=c(-0.2,0.2),pch=15,main="UK vs GK",ylab="",xlab="Scores")
abline(h=0)
points(0:20,2*seed2,pch=0)
points(0:20,-2*seed2,pch=0)