The purpose of this study was to investigate the effect of using multidimensional items in a computer adaptive test (CAT) setting which assumes a unidimensional item response theory (IRT) framework. Previous research has suggested that the composite of multidimensional abilities being estimated by a unidimensional IRT model is not constant throughout the entire unidimensional ability scale. Results of this study suggest that univariate calibration of multidimensional data tends to "filter" out the multidimensionality. The closer an item's multidimensional composite aligns itself with the calibrated univariate ability scale's orientation, the larger the estimated discrimination parameter. If CAT item selection is based upon the amount of information an item provides, items requiring similar (theta sub 1, theta sub 2) will most often be selected. These results further imply that in a CAT different abilities throughout the theta sub 1, theta sub 2 plane could receive sets of items that discriminate between theta sub 1 and theta sub 2 to different degrees. Also, different abilities along the mapped univariate scale could receive tests having different proportions of item content. A description of the ACT Mathematics Usage Test is appended. (Author/JAZ)