Effect of Item Response Theory (IRT) Model Selection on Testlet-Based Test Equating

Abstract

The local item independence assumption underlying traditional item response theory (IRT) models is often not met for tests composed of testlets. There are 3 major approaches to addressing this issue: (a) ignore the violation and use a dichotomous IRT model (e.g., the 2-parameter logistic [2PL] model), (b) combine the interdependent items to form a polytomous item and apply a polytomous IRT model (e.g., the graded response model [GRM]), and (c) apply a model that explicitly takes into account the dependence at the item level (e.g., the testlet response theory [TRT] model). In this study, a simulation was conducted to compare the performance of these 3 approaches on number-correct score equating when degrees of testlet effect were manipulated. The traditional equipercentile method was used as an evaluation baseline. The results show that the 2PL and the TRT approaches produce comparable results that more closely agree with the results of the equipercentile method than the GRM does. And the number-correct equating using the 2PL is robust to the violation of local item independence.