Aberrant behavior refers to any type of unusual behavior that would not be expected under normal circumstances. In educational and psychological testing, such behaviors have the potential to severely bias the aberrant examinee's test score while also jeopardizing the test scores of countless others. It is therefore crucial that aberrant examinees are detected so that their responses can be handled appropriately, and the validity of test score interpretations remains intact. However, one limitation of many aberrance detection methods is that they only use information from the item scores. In doing so, they overlook information from the item distractors, which, quite notably are available in all multiple-choice data. The purpose of this research is to use item scores and distractors to improve the detection of several types of aberrant behavior. Examples are provided in three different contexts: (a) person-fit assessment, (b) speededness detection, and (c) preknowledge detection. In each of these contexts, detailed simulations are conducted to show how attending to distractor selection significantly improves the detection of aberrant behavior. Real data examples are also provided to show how using item scores and distractors deepens our understanding of the various types of aberrant behavior that are observed in practice. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com.bibliotheek.ehb.be/en-US/products/dissertations/individuals.shtml.]