MULTISIB is proposed as a statistical test for assessing differential item functioning (DIF) of intentionally two-dimensional test data, such as a mathematics test designed to measure algebra and geometry. MULTISIB is based on the multidimensional model of DIF as presented in Shealy & Stout (1993), and is a direct extension of SIBTEST, its unidimensional counterpart. For an intentionally two-dimensional test, DIF is appropriately modeled to result from secondary dimensional influence from other than the two intended dimensions. Simulation studies were used to assess the performance of MULTISIB to detect DIF in intentionally two-dimensional tests. These results indicate that MULTISIB exhibited reasonably good adherence to the nominal level of significance and good power. Moreover, for each DIF model the average amount of DIF estimated over the 100 simulations of the model by MULTISIB was close to the true value, confirming its relative lack of statistical estimation bias in assessing true DIF. In addition, the simulation studies supported the importance of using the regression correction to adjust the scores on the studied item due to impact and the importance of matching examinees on two subtest scores instead of the total test score.
All Science Journal Classification (ASJC) codes
- Social Sciences (miscellaneous)
- Psychology (miscellaneous)