Comparing concurrent versus fixed parameter equating with common items: using the dichotomous and partial credit models in a mixed-item format test.

Abstract

There has been some discussion among researchers as to the benefits of using one calibration process over the other during equating. Although literature is rife with the pros and cons of the different methods, hardly any research has been done on anchoring (i.e., fixing item parameters to their pre-determined values on an established scale) as a method that is commonly used by psychometricians in large-scale assessments. This simulation research compares the fixed form of calibration with the concurrent method (where calibration of the different forms on the same scale is accomplished by a single run of the calibration process, treating all non-included items on the forms as missing or not reached), using the dichotomous Rasch (Rasch, 1960) and the Rasch partial credit (Masters, 1982) models, and the WINSTEPS (Linacre, 2003) computer program. Contrary to the belief and some researchers' contention that the concurrent run with larger n-counts for the common items would provide greater accuracy in the estimation of item parameters, the results of this paper indicate that the greater accuracy of one method over the other is confounded by the sample-size, the number of common items, etc., and there is no real benefit in using one method over the other in the calibration and equating of parallel tests forms.