Exceptional LD Profile Types for the WISC-III and WIAT

References

• Bender, W. N., & Golden, L. B. (1990). Subtypes of students with learning disabilities as derived from cognitive, academic, behavioral, and self-concept measures. Learning Disability Quarterly, 13, 183–194.
   Web of Science ®Google Scholar
• Blakely, T. A., Crinella, F. M., Fisher, T. D., Champaigne, L., & Beck, F. W. (1994). Neuropsychological correlates of learning disabilities: Subtype identification by the Tryon clustering method. Journal of Developmental and Physical Disabilities, 6(1), 1–22.
   Google Scholar
• Boder, E. (1973). Developmental dyslexia: A diagnostic approach based on three atypical reading-spelling patterns. Developmental Medicine and Child Neurology, 15, 663–687.
   PubMed Web of Science ®Google Scholar
• Cahen, S., & Cohen, N. (1988). Significance testing of subtest score differences: The case for nonsignificant results. Journal of Psychoeducational Assessment, 6, 107–117.
   Google Scholar
• Cattell, R. B. (1949). rp and other coefficients of pattern similarity. Psychometrica, 14, 279–298.
   PubMed Web of Science ®Google Scholar
• Doehring, D. G., & Hoshko, I. M. (1977). Classification of reading problems by the 2-technique of factor analysis. Cortex, 13, 281–294.
   PubMed Web of Science ®Google Scholar
• Dunn, L. M., & Markwardt, F. C. (1970). Peabody Individual Achievement Test manual Circle Pines, MN: American Guidance Service.
   Google Scholar
• Finlan, T. G. (1992). Do state methods of quantifying a severe discrepancy result in fewer students with learning disabilities. Learning Disability Quarterly, 15, 129–134.
   Web of Science ®Google Scholar
• Glutting, J. J., & McDermott, P. A. (1990a). Patterns and prevalence of core profile types in the WPPSI standardization sample. School Psychology Review, 19, 471–491.
   Web of Science ®Google Scholar
• Glutting, J. J., & McDermott, P. A. (1990b). Score structures and applications of core profile types in the McCarthy scales standardization sample. Journal of Special Education, 24, 212–233.
   Web of Science ®Google Scholar
• Glutting, J. J., McDermott, P. A., & Knold, T. R. (1997). Ontology, structure, and diagnostic benefits of a normative subtest taxonomy from the WISC-III standardization sample. In D. P. Flanagan, J. L. Genshaft, & P. L. Harrison (Eds.), Contemporary intellectual assessment: Theories, tests, and issues (pp. 349–372). New York: Guilford.
   Google Scholar
• Glutting, J. J., McDermott, P. A., Prifitera, A., & McGrath, E. A. (1994). Core profile types for the WISC-III and WIAT: Their development and application in identifying multivariate IQ-Achievement discrepancies. School Psychology Review, 23(4), 619–639.
   Web of Science ®Google Scholar
• Glutting, J. J., McGrath, E. A., Kamphaus, R. W., & McDermott, P. A. (1992). Taxonomy and validity of subtest profiles on the Kaufman Assessment Battery for Children. Journal of Special Education, 26, 85–115.
   Web of Science ®Google Scholar
• Holcomb, W. R., Hardesty, R. A., Adams, N. A., & Ponder, H. M. (1987). WISC-R subtypes of learning disabilities: A profile analysis with cross-validation. Journal of Learning Disabilities, 20(6), 369–373.
   PubMed Web of Science ®Google Scholar
• Kavale, K. A., Fuchs, D., & Scruggs, T. E. (1994). Setting the record straight on learning disability and low achievement: Implications for policymaking. Learning Disabilities Research and Practice, 9(2), 70–77.
   Google Scholar
• Keith, T. Z., & Witta, E. L. (1997). Hierarchical and cross-age confirmatory factor analysis of the WISC-III: What does it measure? School Psychology Quarterly, 12(2), 89–107.
   Web of Science ®Google Scholar
• Luria, A. R. (1976). The neuropsychology of memory. Washington, DC: Winston.
   Google Scholar
• Mattis, S., French, J. H., & Rapin, I. (1975). Dyslexia in children and adults: Three independent neurological syndromes. Developmental Medicine and Child Neurology, 17, 150–163.
   PubMed Web of Science ®Google Scholar
• McDermott, P. A., Fantuzzo, J. W., & Glutting, J. J. (1990). Just say no to subtest analysis: A critique of Wechsler theory and practice. Journal of Psychoeducational Assessment, 8, 290–302.
   Web of Science ®Google Scholar
• McDermott, P. A., Glutting, J. J., Jones, J. N., Watkins, M. W., & Kush, J. (1989). Identification and membership of core profile types in the WISC-R standardization sample. Psychological Assessment: A Journal of Consulting and Clinical Psychology, 1, 292–299.
   Google Scholar
• McDermott, P. A., & Watkins, M. W. (1985). McDermott multidimensional assessment of children. San Antonio, TX: The Psychological Corporation.
   Google Scholar
• McGraw-Hill. (1973). Comprehensive tests of basic skills examiner's manual Monterey, CA: Author.
   Google Scholar
• Norusis, M. J. (1995). SPSS Professional Statistics 7.1. Chicago, IL: SPSS, Inc.
   Google Scholar
• Petrauskas, R., & Rourke, B. (1979). Identification of subgroups of retarded readers: A neuropsychological multivariate approach. Journal of Clinical Neuropsychology, 1, 17–37.
   Google Scholar
• Piers, E. V. (1983). Piers-Harris Children's Self Concept Scale. Los Angeles: Western Psychological Services.
   Google Scholar
• Reitan, R. (1973). Manual for the administration of neuropsychological test batteries for adults and children. Seattle, WA: University of Washington Neuropsychology Laboratory.
   Google Scholar
• Reschly, D. J., & Grimes, J. P. (1990). Best practices in intellectual assessment. In A. Thomas & J. Grimes (Eds.), Best practices in school psychology-II. Silver Spring, MD: National Association of School Psychologists.
   Google Scholar
• Reynolds, C. R. (1990). Conceptual and technical problems in learning disability diagnosis. In C. R. Reynolds & R. W. Kamphaus (Eds.), Handbook of psychological assessment of children: Intelligence and achievement. New York: Guilford.
   Google Scholar
• Reynolds, C. R., & Kaufman, A. S. (1990). Assessment of children's intelligence with the Wecshler Intelligence Scale for Children-Revised. In C. R. Reynolds & R. W. Kamphaus (Eds.), Handbook of psychological assessment of children: Intelligence and achievement. New York: Guilford.
   Google Scholar
• Schuerholz, L. J., Harris, E. L., Baumgardner, T. L., Reiss, A. L., Freund, L. S., Church, R. P., Mohr, J., & Denckla, M. B. (1995). An analysis of two discrepancy-based models and a processing-deficit approach in identifying learning disabilities. Journal of Learning Disabilities, 28(1), 18–29.
   PubMed Web of Science ®Google Scholar
• Snow, J. H., Cohen, M., & Holliman, W. B. (1985). Learning disability subgroups using cluster analysis of the WISC-R. Journal of Psychoeducational Assessment, 4, 391–397.
   Google Scholar
• Tatsuoka, M. M., & Lohnes, P. R. (1988). Multivariate analysis (2nd ed.). New York: Macmillan.
   Google Scholar
• The Psychological Corporation. (1992). Wechsler Individual Achievement Test manual San Antonio, TX: Author.
   Google Scholar
• Tryon, R. C., & Bailey, D. E. (1970). Cluster analysis. New York: McGraw Hill.
   Google Scholar
• Virginia Department of Education. (1994). Regulations governing special education programs for children with disabilities in Virginia. Richmond, VA: Author.
   Google Scholar
• Walker, H. M. (1983). Walker Problem Behavior Identification Checklist-Revised. Los Angeles: Western Psychological Services.
   Google Scholar
• Ward, J. H., Jr. (1963). Hierarchical grouping to optimize an objective function. American Statistical Association Journal, 58, 236–244.
   Web of Science ®Google Scholar
• Watkins, M. W., & Kush, J. C. (1994). Wechsler subtest analysis: The right way, the wrong way, or no way? School Psychology Review, 23(4), 640–651.
   Web of Science ®Google Scholar
• Wechsler, D. (1974). Wechsler Intelligence Scale for Children-Revised. New York: The Psychological Corporation.
   Google Scholar
• Wechsler, D. (1991). Manual for the Wechsler Intelligence Scale for Children (3rd ed.). San Antonio, TX: The Psychological Corporation.
   Google Scholar