sirt (version 0.31-20)

equating.rasch: Equating in the Generalized Logistic Rasch Model

Description

This function does the linking in the generalized logistic item response model. Only item difficulties (different $b$ item parameters) are allowed. Mean-mean linking and the methods of Haebara and Stocking-Lord are implemented (Kolen & Brennan, 2004).

Usage

equating.rasch(x, y, theta = seq(-4, 4, len = 100), 
   alpha1 = 0, alpha2 = 0)

Arguments

x

Matrix with two columns: First column items, second column item difficulties

y

Matrix with two columns: First columns item, second column item difficulties

theta

Vector of theta values at which the linking functions shall be evaluated

alpha1

Fixed $\alpha_1$ parameter in the generalized item response model

alpha2

Fixed $\alpha_2$ parameter in the generalized item response model

Value

• B.est
  Estimated linking constants according to the methods Mean.Mean (Mean-mean linking), Haebara (Haebara method) and Stocking.Lord (Stocking-Lord method).
• descriptives
  Descriptives of the linking. The linking error (linkerror) is calculated under the assumption of simple random sampling of items
• anchor
  Original and transformed item parameters of anchor items
• transf.par
  Original and transformed item parameters of all items

References

Kolen, M. J. & Brennan, R. L. (2004). Test equating, Scaling, and Linking: Methods and Practices. New York: Springer.

See Also

For linking under more general item response models see the plink package.

Examples

##########################
# EXAMPLE 1: Linking item parameters of the PISA study

data(data.pisaPars)
pars <- data.pisaPars

# linking the tow studies with the Rasch model
mod <- equating.rasch(x=pars[,c("item","study1")] , 
			y=pars[,c("item","study2")])
##   Mean.Mean    Haebara Stocking.Lord
## 1   0.08828 0.08896269    0.09292838