equate {lordif} | R Documentation |
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)
equate(ipar.to, ipar.from, theta)
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) |
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).
returns a vector of two elements c(A, X) where A is a multiplicative constant and K is an additive constant
The item parameters are assumed to be on the theta metric (0,1). The number of category threshold parameters can differ across items.
Seung W. Choi <s-choi@northwestern.edu>
Stocking, M. L. & Lord, F. M. (1983). Developing a Common Metric in Item Response Theory. Applied Psychological Measurement, 7(2), 201-210.
##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