Evaluating a Procedure for Investigating the Multidimensional Parallelism of Standardized Tests

Abstract

Because of the numerous composites of abilities that could account for the variability in item responses attributing to the item clustering, post hoc analyses were conducted using a subset of items hypothesized to have approximate simple structure. The MIRT clustering procedure used in evaluating the complete test form information was compared with the item cluster groupings identified using a conditional covariance clustering procedure (DETECT, Kim, 1994; Zhang & Stout, 1996). The results indicated that the conditional covariance clustering procedure, in combination with the genetic algorithm used for identifying the optimal number of statistically distinct dimensions, was more effective in replicating the hypothesized dimensional structure of the subset of items.