Oshima, Raju, and Flowers demonstrated the use of an item response theory-based technique for analyzing differential item function (DIF) and differential test function for dichotomously scored data that are intended to be multidimensional. Their study assumed that the number of intended-to-be measured dimensions was correctly identified. In practice, however, the number of dimensions may be misidentified. Therefore, the purpose of this study was to demonstrate the effects of both underestimation and overestimation of the number of intended-to-be measured dimensions on the multidimensional DIF analysis using simulated two-dimensional data with known DIF items. Results show that overestimation of the number of y traits had a consequence of decreased power. Underestimation resulted in missing a certain type of nonuniform DIF, as well as confounding the impact with DIF. Recommendations are made on how to conduct a DIF investigation with a multidimensional within-item test. (Contains 2 figures and 5 tables.)