Comparing Two Algorithms for Calibrating the Restricted Non-Compensatory Multidimensional IRT Model.

ABSTRACT: The non-compensatory class of multidimensional item response theory (MIRT) models frequently represents the cognitive processes underlying a series of test items better than the compensatory class of MIRT models. Nevertheless, few researchers have used non-compensatory MIRT in modeling psychological data. One reason for this lack of use is because non-compensatory MIRT item parameters are notoriously difficult to accurately estimate. In this article, we propose methods to improve the estimability of a specific non-compensatory model. To initiate the discussion, we address the non-identifiability of the explored non-compensatory MIRT model by suggesting that practitioners use an item-dimension constraint matrix (namely, a Q-matrix) that results in model identifiability. We then compare two

SUBMITTER: Wang C 

PROVIDER: S-EPMC5978509 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature