Nonequivalent Groups with Covariates Design Using Propensity Scores for Kernel Equating

Abstract

In test score equating, the nonequivalent groups with covariates (NEC) design use covariates with high correlation to the test scores as a substitute for an anchor test when the latter is lacking. However, as the number of covariates increases, the number of observations for each covariate combination decreases. We suggest to use propensity scores instead, which we include in the kernel equating framework using both post-stratification and chained equating. The two approaches are illustrated with data from a large-scale assessment, and the results show an increased precision in comparison with the equivalent groups design and great similarities in comparison with the results when using an anchor test.