Model-Based Methods for Test Equating Under Item Response Theory

There are some popular criteria for computing equating coefficients based on Item Response Theory (IRT), such as Stocking_Lord method (SLcrit), Haebara method (Hcrit). In this paper some new equating criteria are driven, such as Logistic regression method (LRcrit) and symmetric relative entropy method (SREcrit). Some of these criteria may be specifically suitable for a corresponding IRT model. LRcrit could be used for the divided-by-total and difference polytomous models and may have simpler form than that of Hcrit and SLcrit. Especially, the series of LRcrit could not include the iteration algorithm in the computing procedure without losing the accuracy. And SREcrit could almost be applied to all of the models under IRT. The results of Monte Carlo study demonstrate that the new criteria have some advantages in test equating procedure, such as providing more accurate value of equating coefficients A,B or the initial value in the situations of using iteration algorithm. Moreover, they may be simpler in the form and in the computing procedure.