Item pools or item banks used in most testing situations are inherently multidimensional. This is especially a problem in computerized adaptive testing (CAT), which is driven by item response theory; item response theory requires that the item pool be unidimensional. This series of computer simulations demonstrates how alternative item-presentation controls (content-balancing and “mini-CATs”) may be employed in CAT to estimate ability accurately in spite of the violation of unidimensionality. Averaged, shorter mini-CATs provide the most accurate estimation of ability and ameliorate problems intrinsic to violating the unidimensionality assumption of item response theory.