Computes linear transformation constants to equate a set of GRM/GPCM item parameters to a target scale using a test characteristic curve equating procedure (Stocking & Lord, 1983)
ipar.to: a data frame containing target item parameters in the following order: a, cb1, cb2,..., cb(maxCat-1)
ipar.from: a data frame containing to-be-equated item parameters in the following order: a, cb1, cb2,..., cb(maxCat-1)
theta: a theta grid
model: IRT model, either "GRM" or "GPCM"
start.AK: a vector of starting values, c(A, K) where A is a multiplicative constant and K is an additive constant
lower.AK: a vector of lower limits, c(A, K) where A is a multiplicative constant and K is an additive constant
upper.AK: a vector of upper limits, c(A, K) where A is a multiplicative constant and K is an additive constant
Details
Computes linear transformation constants (A and K) 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 (Stocking & Lord, 1983). The minimization is performed by the nlminb function (in stats).
Returns
returns a vector of two elements, c(A, K) where A is a multiplicative constant and K is an additive constant
References
Stocking, M. L. & Lord, F. M. (1983). Developing a Common Metric in Item Response Theory. Applied Psychological Measurement, 7(2), 201-210.
The item parameters are assumed to be on the theta metric (0,1). The number of category threshold parameters may differ across items but not greater than (maxCat-1).
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