School psychologists use intelligence and academic achievement test scores to understand individual differences in abilities that may be directed towards learning and the learning that has already occurred. To make ethical and effective decisions regarding individualized educational programs and interventions, test users must understand the meaning of relations among intelligence and academic achievement test scores. To recommend scoring structures that will accurately reflect individual abilities and performance, test developers, too, must understand the meaning of test score relations. The purpose of this study was to use multidimensional scaling (MDS) as an alternate multivariate procedure for investigating academic achievement test score correlations and intelligence and academic achievement test score correlations in combination. MDS configurations include all tests in continuous geometric space. Close proximity of tests indicates similarity (higher correlations) and shared features, such as similar cognitive processes or content. MDS was used to analyze correlations among some of the most widely used individually administered tests of intelligence and academic achievement, including the Wechsler Intelligence Scale for Children, Fifth Edition (WISC-5), Wechsler Individual Achievement Test, Third Edition (WIAT-III), Kaufman Assessment Battery for Children, Second Edition (KABC-II), and Kaufman Test of Educational Achievement, Second Edition-Comprehensive Form (KTEA-2). Specifically, correlations from the WIAT-III (N = 181), the WISC-V with WIAT-III (N = 181), and the KABC-II with KTEA co-norming samples (Grades 1-3 [n = 592], 4-6 [n = 558], 7-9 [n = 566], and 10-12 [n = 401]) were analyzed. MDS maps were interpreted in relation to test complexity (level of inference, higher-order thinking, more adaptive demands), Cattell-Horn-Carroll (CHC) ability factors and academic domains, test content (verbal, numeric, figural), and examinee response modes (verbal, manual, paper-pencil). The results showed that three-dimensional MDS configurations were the best fit for interpreting six MDS maps. Three-dimensional interactive MDS maps are provided in a supplemental HTML file. Test complexity was less clear as a test feature that could explain test locations in the MDS maps. Intelligence tests with high g-loadings, those considered more complex, were more likely to be near the center of the configurations than intelligence tests with low g-loadings; however, academic achievement tests were more likely to be near the center than intelligence tests. Though the interpretation of complexity was unclear, organization of subtests by CHC ability (Gc, Gv, Gf, Gwm or Gsm, Gs, if applicable, and Glr/Gr/Gl, if applicable) and academic domain (reading, writing, math, oral language) was clear in all of the MDS maps. Tests were also organized more broadly into auditory-linguistic, figural-visual, reading-writing, and quantitative-numeric regions for all model results. A speed-fluency region was visible in WISC-V and WIAT-III results and a retrieval fluency region was visible in the Kaufman results. In MDS with intelligence and academic achievement tests together across different grade levels, there were mostly similar results, and additional analysis with WISC-V and WIAT-III tests showed that content and response process facets were also useful in explaining test locations. Two implications from this study are that caution may be needed when interpreting fluency scores across academic areas, and MDS provides more empirically-based validity evidence regarding content and response mode processes. [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.]