equate {lordif}R Documentation

performs Stocking-Lord Equating

Description

Computes linear transformation constants to equate a set of GRM/2PL item parameters to a target scale using a common-item test characteristic curve equating procedure (Stocking & Lord, 1983)

Usage

equate(ipar.to, ipar.from, theta)

Arguments

ipar.to a data frame containing target item parameters in the following order: a, cb1, cb2,..., cb(ncat-1)
ipar.from a data frame containing to-be-equated item parameters in the following order: a, cb1, cb2,..., cb(ncat-1)
theta a theta grid (quadrature points)

Details

Computes linear transformation constants that equate a set of item parameters (ipar.from) to the scale defined by a target item parameters (ipar.to) by minimizing the squared difference between the test characteristic curves as described in Stocking and Lord (1983). The minimization is performed by the nlminb function (in stats).

Value

returns a vector of two elements c(A, X) where A is a multiplicative constant and K is an additive constant

Note

The item parameters are assumed to be on the theta metric (0,1). The number of category threshold parameters can differ across items.

Author(s)

Seung W. Choi <s-choi@northwestern.edu>

References

Stocking, M. L. & Lord, F. M. (1983). Developing a Common Metric in Item Response Theory. Applied Psychological Measurement, 7(2), 201-210.

See Also

tcc

Examples

##ipar.to is a data frame containing "target" item parameters
##ipar.from is a data frame containing "to-be-equated" item parameters
## Not run: AK <- equate(ipar.to,ipar.from)
#AK[1] contains the multiplicative constant
#AK[2] contains the additive constant

[Package lordif version 0.1-4 Index]