Skip to main content

Measurement and Statistical Problems in Neuropsychological Assessment of Children

  • Chapter

The field of neuropsychology as practiced clinically has been driven in large part by the development and application of standardized diagnostic procedures that are more sensitive than medical examinations to changes in behavior, in particular higher cognitive processes, as related to brain function.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  • Adams, R. L. (1985). Review of the Luria-Nebraska neuropsychological battery. In J. V. Mitchell (Ed.), The ninth mental measurements yearbook. Lincoln: University of Nebraska Press.

    Google Scholar 

  • Angoff, W. H. (1971). Scales, norms, and equivalent scores. In R. L. Thorndike (Ed.), Educational measurement (2nd ed.). Washington, DC: American Council on Education.

    Google Scholar 

  • Arnold, B. R., Montgomery, G. T., Castaneda, I., & Langoria, R. (1994). Acculturation and performance of Hispanics on selected Halstead—Reitan neuropsychological tests. Assessment, 1, 239-248.

    Google Scholar 

  • Beglinger, L. J., Gaydos, B., Tangphao-Daniels, O., Duff, K., Karaken, D. A., Crawford, J., et al. (2005). Practice effects and the use of alternate forms in serial neuropsychological testing. Archives of Clinical Neuropsychology, 20, 517-529.

    Article  PubMed  Google Scholar 

  • Bernard, L. C., Houston, W., & Natoli, L. (1993). Malingering on neuropsychological memory tests: Potential objective indicators. Journal of Clinical Psychology, 49, 45-53.

    Article  PubMed  Google Scholar 

  • Boder, E., & Jarrico, S. (1982). Boder Test of Reading- Spelling Patterns. New York: Grune & Stratton.

    Google Scholar 

  • Boone, K., Ghaffarian, S., Lesser, I., & Hill-Gutierrez, E. (1993). Wisconsin card sorting test performance in healthy, older adults: Relationship to age, sex, education, and IQ. Journal of Clinical Psychology, 49, 54-60.

    Article  PubMed  Google Scholar 

  • Borsuk, E. R., Watkins, M. W., & Carnivez, G. L. (2006). Long-term stability of membership in a Wechsler Intelligence Scale for Children-third edition (WISC-III) subtest core profile taxonomy. Journal of Psychoeducational Assessment, 24, 52-68.

    Article  Google Scholar 

  • Broshek, D. K., & Barth, J. T. (2000). The Halstead-Reitan Neuropsychological Test Battery. In G. Groth-Marnat (Ed.), Neuropsychological assessment in clinical practice: A guide to test interpretation and integration (pp. 223-262). New York: Wiley.

    Google Scholar 

  • Brown, R. T., Reynolds, C. R., & Whitaker, J. S. (1999). Bias in mental testing since bias in mental testing. School Psychology Quarterly, 14, 208-238.

    Article  Google Scholar 

  • Burns, E. (1982). The use and interpretation of standard grade equivalents. Journal of Learning Disabilities, 15, 17-18.

    Article  Google Scholar 

  • Byrd, D. A., Miller, S. W., Reilly, J., Weber, S., Wall, T. L., & Heaton, R. K. (2006). Early environmental factors, ethnicity, and adult cognitive test performance. The Clinical Neuropsychologist, 20, 243-260.

    Article  PubMed  Google Scholar 

  • Cattell, R. B. (1966). Handbook of multivariate experimental psychology . Chicago: Rand McNally

    Google Scholar 

  • Cattin, P. (1980). Note on the estimation of the squared cross-validated multiple correlation of a regression model. Psychological Bulletin, 87, 63-65.

    Article  Google Scholar 

  • Charter, R. A. (1999). Sample size requirements for precise estimates of reliability, generalizability, and validity coefficients. Journal of Clinical and Experimental Neuropsychology, 21, 559-566.

    Article  PubMed  Google Scholar 

  • Cicchetti, D. V. (1994). Multiple comparison methods: Establishing guidelines for their valid application in neuropsychological research. Journal of Clinical and Experimental Neuropsychology, 16, 155-161.

    Article  PubMed  Google Scholar 

  • Cicchetti, D. V. (2001). The precision of reliability and validity estimates re-visited: Distinguishing between clinical and statistical significance of sample size requirements. Journal of Clinical and Experimental Neuropsychology, 23, 695-700.

    Google Scholar 

  • Coles, G. S. (1978). The learning disabilities test battery: Empirical and social issues. Howard Educational Review, 4, 313-340.

    Google Scholar 

  • Cooley, W. W., & Lohnes, P. R. (1971). Multivariate data analysis. New York: Wiley.

    Google Scholar 

  • Cronbach, L. J. (1990). Essentials of psychological testing (5th ed.). New York: Harper & Row.

    Google Scholar 

  • Cronbach, L. J., & Gleser, G. C. (1953). Assessing similarity between profiles. Psychological Bulletin, 50, 456-473.

    Article  PubMed  Google Scholar 

  • Davis, F. B. (1959). Interpretation of differences among average and individual test scores. Journal of Educational Psychology, 50, 162-170.

    Article  Google Scholar 

  • Dean, R. S. (1978). Distinguishing learning-disabled and emotionally disturbed children on the WISC-R. Journal of Consulting and Clinical Psychology, 46, 4381-4382.

    Article  Google Scholar 

  • Dean, R. S. (1985). Review of the Halstead-Reitan neuropsychological test battery. In J. V. Mitchell (Ed.), The ninth mental measurements yearbook. Lincoln: University of Nebraska Press.

    Google Scholar 

  • Demakis, G.J. (2006). Meta-analysis in neuropsychology: Basic approaches, findings, and directions. The Clinical Neuropsychologist, 20, 10-26.

    Google Scholar 

  • Dodrill, C. B. (1997). Myths of neuropsychology. The Clinical Neuropsychologist, 11, 1-17.

    Article  Google Scholar 

  • Dodrill, C. B. (1999). Myths of neuropsychology: Further considerations. The Clinical Neuropsychologist, 13, 562-572.

    PubMed  Google Scholar 

  • Dombrowski, S. C., Kamphaus, R. W., & Reynolds, C. R. (2004). After the demise of the discrepancy: Proposed learning disabilities diagnostic criteria. Professional Psychology: Research and Practice, 35, 364-372.

    Article  Google Scholar 

  • Dunleavy, R. A., Hansen, J. L., & Baade, L. E. (1981). Discriminating powers of Halstead Battery tests in assessment of 9 to 14 year old severely asthmatic children. Clinical Neuropsychology, 3, 99-12.

    Google Scholar 

  • Feldt, L. S., & Brennan, R. L. (1989). Reliability. In R. Linn (Ed.), Educational measurement (3rd ed.). New York: Macmillan Co.

    Google Scholar 

  • Fuller, G. B., & Goh, D. S. (1981). Intelligence, achievement, and visual-motor performance among learning disabled and emotionally impaired children. Psychology in the Schools, 18, 262-268.

    Article  Google Scholar 

  • Glass, G. V. (1978). Integrating findings: The meta-analysis of research. In L. Shulman (Ed.), Review of Research in Education, 5, 351-379.

    Google Scholar 

  • Glozman, J. M. (2007). A. R. Luria and the history of Russian neuropsychology. Journal of the History of the Neurosciences, 16, 168-180.

    Article  PubMed  Google Scholar 

  • Glutting, J. J., McDermott, P. A., Watkins, M. M., Kush, J. C., & Konold, T. R. (1997). The base rate problem and its consequences for interpreting children’s ability profiles. School Psychology Review, 26(2), 176-188.

    Google Scholar 

  • Glutting, J. J., Watkins, M. W., Konold, T. R., & McDermott, P. A. (2006). Distinctions without a difference: The utility of observed versus latent factors from the WISC-IV in estimating reading and math achievement on the WIAT-II. Journal of Special Education, 40, 103-114.

    Google Scholar 

  • Golden, C. J. (1981). Diagnosis and rehabilitation in clinical neuropsychology (2 nd ed.). Springfield, IL: Thomas.

    Google Scholar 

  • Golden, C. J., Moses, J. A., Jr., Graber, B., & Berg, T. (1981). Objective clinical rules for interpreting the Luria- Nebraska Neuropsychological Battery: Derivation, effectiveness, and validation. Journal of Consulting and Clinical Psychology, 49, 616-668.

    Article  PubMed  Google Scholar 

  • Gordon, R. A. (1984). Digits backward and the Mercer- Kamin law: An empirical response to Mercer’s treatment of internal validity of IQ tests. In C. R. Reynolds & R. T. Brown (Eds.), Perspectives on bias in mental testing. New York: Plenum Press.

    Google Scholar 

  • Green, P. (2003). Welcoming a paradigm shift in neuropsychology. Archives of Clinical Neuropsychology, 18, 625-627.

    Article  Google Scholar 

  • Guilford, J. P. (1954). Psychometric methods (2 nd ed.). New York: McGraw-Hill.

    Google Scholar 

  • Guilmette, T. J., & Rasile, D. (1995). Sensitivity, specificity, and diagnostic accuracy of three verbal memory measures in the assessment of mild brain injury. Neuropsychology, 9, 338-344.

    Article  Google Scholar 

  • Gutkin, T. B., & Reynolds, C. R. (1980, September). Normative data for interpreting Reitan’s index of Wechsler subtest scatter. Paper presented to the annual meeting of the American Psychological Association, Montreal.

    Google Scholar 

  • Haak, R. (1989). Establishing neuropsychology in a school setting: Organization, problems, and benefits, In C. R. Reynolds & E. Fletcher- Janzen (Eds.), Handbook of clinical child neuropsychology (pp. 489-502). New York: Plenum Press.

    Google Scholar 

  • Helms, J. E. (1992). Why is there no study of cultural equivalence in standardized cognitive ability testing? American Psychology, 47, 1083-1101.

    Article  Google Scholar 

  • Herskovits, M., & Gyarmathy, E. (1995). Types of high ability: Highly able children with an unbalanced intelligence structure. European Journal for High Ability, 6, 38-48.

    Article  Google Scholar 

  • Hishinuma, E. S., & Tadaki, S. (1997). The problem with grade and age equivalents: WIAT as a case in point. Journal of Psychoeducational Assessment, 15, 214-225.

    Article  Google Scholar 

  • Hogarty, K. Y., Kromrey, J. D., Ferron, J. M., & Hines, C. V. (2004). Selection of variables in exploratory factor analysis: An empirical comparison of a stepwise and traditional approach. Psykometrika, 69, 593-611.

    Article  Google Scholar 

  • Hynd, G. (Ed.). (1981). Neuropsychology in schools. School Psychology Review, 10 (3).

    Google Scholar 

  • Ivnik, R. J., Smith, G. E., Malec, J. F., Kokmen, E., & Tangelos, E. G. (1994). Mayo cognitive factor scales: Distinguishing normal and clinical samples by profile variability. Neuropsychology, 8, 203-209.

    Article  Google Scholar 

  • Iverson, G. L., Mendrek, A., & Adams, R. L. (2004). The persistent belief that VIQ-PIQ splits suggest lateralized brain damage. Applied Neuropsychology, 11, 85-90.

    Article  PubMed  Google Scholar 

  • Jastak, J. F., & Jastak, S. (1978). Wide Range Achievement Test. Wilmington, DE: Jastak.

    Google Scholar 

  • Jung, R. E., Yeo, R. A., Chiulli, S. J., Sibbitt Jr., W. L., & Brooks, W. M. (2000). Myths of Neuropsychology: Intelligence, neurometabolism, and cognitive ability. The Clinical Neuropsychologist, 14, 535-545.

    PubMed  Google Scholar 

  • Kamphaus, R. W. (2004). “Back to the future” of the Stanford-Binet Intelligence Scales. In M. Hersen (Ed.), Comprehensive handbook of psychological assessment (pp. 77-86). Hoboken, NJ: Wiley.

    Google Scholar 

  • Kaufman, A. S. (1976a). A new approach to the interpretation of test scatter on the WISC-R. Journal of Learning Disabilities, 9, 160-167.

    Google Scholar 

  • Kaufman, A. S. (1976b). Verbal-performance IQ discrepancies on the WISC-R. Journal of Learning Disabilities, 9, 739-744.

    Google Scholar 

  • Kaufman, A. S. (1979). Intelligence testing with the WISC-R. New York: Wiley-Interscience.

    Google Scholar 

  • Kaufman, A. S. (1990). Assessing adolescent and adult intelligence. Boston: Allyn & Bacon.

    Google Scholar 

  • Kaufman, A. S., & Kaufman, N. L.(2005). Kaufman assessment battery for children, second edition. Circle Pines, MN: American Guidance Service.

    Google Scholar 

  • Kaufman, A. S., McLean, J. E., & Reynolds, C. R. (1988). Sex, race, residence, region, and education differences on the 11 WAIS-R subtests. Journal of Clinical Psychology, 44, 231-248.

    Article  PubMed  Google Scholar 

  • Kennedy, M. L., Willis, W. G., & Faust, D. (1997). The base-rate fallacy in school psychology. Journal of Psychoeducational Assessment, 15, 292-307.

    Article  Google Scholar 

  • Kennepohl, S., Shore, D., Nabors, N., & Hanks, R. (2004). African American acculturation and neuropsychological test performance following traumatic brain injury. Journal of the International Neuropsychological Society, 10, 566-577.

    Article  PubMed  Google Scholar 

  • Labarge, A. S., McCaffrey, R. J., & Brown, T. A. (2003). Neuropsychologists' abilities to determine the predicitve value of diagnostic tests. Archives of Clinical Neuropsychology, 18, 165-175.

    PubMed  Google Scholar 

  • Livingston, R. B., Jennings, E., Reynolds, C. R., & Gray, R. M. (2003). Mulitvariate analyses of the profile stability of intelligence tests: High for IQs, low to very low for subtest analyses. Archives of Clinical Neuropsychology, 18, 487-507.

    PubMed  Google Scholar 

  • Lord, F. M., & Novick, M. R. (1968). Statistical theories of mental tests. Reading, MA: Addison-Wesley.

    Google Scholar 

  • Lowe, P. A., Mayfield, J. W., & Reynolds, C. R. (2003). Gender differences in memory test performance among children and adolescents. Archives of Clinical Neuropsychology, 18, 865-878.

    PubMed  Google Scholar 

  • Malloy, P. F., & Webster, J. S. (1981). Detecting mild brain impairment using the Luria-Nebraska Neuropsychological Battery. Journal of Consulting and Clinical Psychology, 49, 768-770.

    Article  PubMed  Google Scholar 

  • Matarazzo, J. D. (1972). Wechsler’s measurement and appraisal of adult intelligence. Baltimore: Williams & Wilkins.

    Google Scholar 

  • Mattison, R. E., Hooper, S. R.,& Carlson, G. A. (2006). Neuropsychological characteristics of Special Education students with serious emotional/behavioral disorders. Behavioral Disorders, 31, 176-188.

    Google Scholar 

  • Miles, J., & Stelmack, R. (1994). Learning disability subtypes and the effects of auditory and visual priming on visual event-related potentials to words. Journal of Clinical and Experimental Neuropsychology, 16, 43-64.

    Article  PubMed  Google Scholar 

  • Naglieri, J. A., & Paolitto, A. W. (2005). Ipsative comparisons of WISC-IV index scores. Applied Neuropsychology, 12, 208-211.

    Article  PubMed  Google Scholar 

  • Nesselroade, J., & Cattell, R. B. (1988). Handbook of multivariate experimental psychology (2 nd ed.). New York: Plenum Press.

    Google Scholar 

  • Nunnally, J. C. (1978). Psychometric theory (2 nd ed.). New York: McGraw-Hill.

    Google Scholar 

  • O' Bryant, S. E., O' Jile, J. R., & McCaffrey, R. J. (2004). Reporting of demographic variables in neuropsychological research: Trends in the current literature. The Clinical Neuropsychologist, 18, 229-233.

    Article  Google Scholar 

  • Osgood, C. E., & Suci, G. J. (1952). A measurement of relation determined by both mean differences and profile interpretation. Psychological Bulletin, 49, 251-262.

    Article  PubMed  Google Scholar 

  • Ostrosky-Solis, F., Ramirez, M., & Ardila, A. (2004). Effects of culture and education on neuropsychological testing: A preliminary study with indigenous and nonindigenous population. Applied Neuropsychology, 11, 186-193.

    Article  Google Scholar 

  • Parsons, O.A. & Prigatano, G.P. (1978). Methodological considerations in clinical neuropsychological research. Journal of Consulting and Clinical Psychology, 46, 608-619.

    Google Scholar 

  • Prigatano, G. P. (2003). Challenging dogma in neuropsychology and related disciplines. Archives of Clinical Neuropsychology, 18, 811-825.

    PubMed  Google Scholar 

  • Pedhazur, E. J., & Schmelkin, L. P. (1991). Measurement, design, and analysis. Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Petersen, N. S., Kolen, M. J., & Hoover, H. D. (1989). Scaling, norming, and equating. In R. Linn (Ed.), Educational measurement, 3rd ed. (pp. 221-262). New York: MacMillan.

    Google Scholar 

  • Piotrowski, R. J. (1978). Abnormality of subtest score differences on the WISC-R. Journal of Consulting and Clinical Psychology, 46, 569-570.

    Article  Google Scholar 

  • Plake, B. S., Reynolds, C. R., & Gutkin, T. B. (1981). A technique for the comparison of profile variability between independent groups. Journal of Clinical Psychology, 37, 142-146.

    Article  Google Scholar 

  • Purisch, A. D., Golden, C. J., & Hammeke, T. A. (1979). Discrimination of schizophrenic and brain injured patients by standardized version of Luria’s neuropsychological tests. Clinical Neuropsychology, 1, 53-59.

    Google Scholar 

  • Reschly, D., & Gresham, F. M. (1989). Current neuropsychological diagnosis of learning problems: A leap of faith. In C. R. Reynolds, & E. Fletcher-Janzen (Eds.), Handbook of clinical child neuropsychology (pp. 503-520). New York: Plenum Press.

    Google Scholar 

  • Reynolds, C. R. (1979a). Interpreting the index of abnormality when the distribution of score differences is known: Comment on Piotrowski. Journal of Consulting and Clinical Psychology, 47, 401-402.

    Google Scholar 

  • Reynolds, C. R. (1979b). Objectivity of scoring for the McCarthy drawing tests. Psychology in the Schools, 16, 367-368.

    Google Scholar 

  • Reynolds, C. R. (1981a). The problem of bias in psychological assessment. In C. R. Reynolds & T. B. Gutkin (Eds.), The handbook of school psychology. New York: Wiley.

    Google Scholar 

  • Reynolds, C. R. (1981b). Screening tests: Problems and promises. In N. Lamberts (Ed.), Special education assessment matrix. Monterey, CA: CTB McGraw Hill.

    Google Scholar 

  • Reynolds, C. R. (1982a). The importance of norms and other traditional psychometric concepts to assessment in clinical neuropsychology. In R. N. Malathesha & L. C. Hartlage (Eds.), Neuropsychology and cognition (Vol. II, pp. 55-76). The Hague: Nijhoff.

    Google Scholar 

  • Reynolds, C. R. (1982b). The problem of bias in psychological assessment. In C. R. Reynolds & T. B. Gutkin (Eds.), The handbook of school psychology (pp. 178-208). New York: Wiley.

    Google Scholar 

  • Reynolds, C. R. (1983). Some new and some unusual educational and psychological tests. School Psychology Review, 12, 481-488.

    Google Scholar 

  • Reynolds, C. R. (1984). Critical measurement issues in learning disabilities. Journal of Special Education, 18, 451-476.

    Article  Google Scholar 

  • Reynolds, C. R. (1986). Clinical acumen but psychometric naivete in neuropsychological assessment of educational disorders. Archives of Clinical Neuropsychology, 1, 121-138.

    PubMed  Google Scholar 

  • Reynolds, C. R. (1995). Test bias and the assessment of personality and intelligence. In D. Saklofske & M. Zeidner (Eds.), International handbook of personality and intelligence, (pp. 545-573). New York: Plenum Press.

    Google Scholar 

  • Reynolds, C. R., & Bigler, E. D. (1994). Manual for the test of memory and learning. Austin, TX: PRO-ED.

    Google Scholar 

  • Reynolds, C. R., Chastain, R., Kaufman, A. S., & McLean, J. (1987). Demographic influences on adult intelligence at ages 16 to 74 years. Journal of School Psychology, 25, 323-342.

    Article  Google Scholar 

  • Reynolds, C. R., & Clark, J. H. (1985). Profile analysis of standardized intelligence test performance of very low functioning individuals. Journal of School Psychology, 23, 227-283.

    Google Scholar 

  • Reynolds, C. R., & Clark, J. H. (1986). Profile analysis of standardized intelligence test performance of very low functioning individuals. Psychology in the Schools, 23, 5-12.

    Article  Google Scholar 

  • Reynolds, C. R., & Gutkin, T. B. (1979). Predicting the premorbid intellectual status of children using demographic data. Clinical Neuropsychology, 1, 36-38.

    Google Scholar 

  • Reynolds, C. R., & Gutkin, T. B. (1980). Statistics related to profile interpretation of the Peabody Individual Achievement Test. Psychology in the Schools, 17, 316-319.

    Article  Google Scholar 

  • Reynolds, C. R., Hartlage, L. C., & Haak, R. (1980, September). Lateral preference as determined by neuropsychological performance and aptitude/achievement discrepancies. Paper presented to the annual meeting of the American Psychological Association, Montreal.

    Google Scholar 

  • Reynolds, C. R., & Kaiser, S. M. (1990). Test bias in psychological assessment. In T. B. Gutkin & C. R. Reynolds (Eds.), The handbook of school psychology (2 nd ed., pp. 487-525). New York: Wiley.

    Google Scholar 

  • Reynolds, C. R. & Kamphaus, R. W. (2003). Reynolds intellectual assessment scales: Professional manual. Lutz, FL: PAR, Inc.

    Google Scholar 

  • Reynolds, C. R., & Kaufman, A. S. (1986). Clinical assessment of children’s intelligence with the Wechsler Scales. In B. Wolman (Ed.), Handbook of intelligence (pp. 601-662), New York: Wiley.

    Google Scholar 

  • Reynolds, C. R., Livingston, R. L., & Willson, V. L. (2006). Measurement and assessment in the classroom. Boston: Allyn & Bacon.

    Google Scholar 

  • Reynolds, C. R., & Ramsay, M. C. (2003). Bias in psychological assessment: An empirical review and recommendations. In J. R. Graham, J. A. Naglieri & I. B. Weiner (Eds.), Handbook of psychology: Vol. 10. Assessment psychology (pp. 67-93). New York: Wiley.

    Google Scholar 

  • Reynolds, C. R. & Voress, J. K. (2007). Test of memory and learning, second edition. Austin, TX: Pro-Ed Inc.

    Google Scholar 

  • Reynolds, C. R., & Willson, V. L. (1983, January). Standardized grade equivalents: Really! No. Well, sort of, but they lead to the valley of the shadow of misinterpretation and confusion. Paper presented to the annual meeting of the Southwestern Educational Research Association, Houston.

    Google Scholar 

  • Ris, M. D., & Noll, R. B. (1994). Long-term neurobehavioral outcome in pediatric brain tumor patients: Review and methodological critique. Journal of Clinical and Experimental Neuropsychology, 16, 21.

    Article  PubMed  Google Scholar 

  • Roffe, M. W., & Bryant, C. K. (1979). How reliable are MSCA profile interpretations? Psychology in the Schools, 16, 14-18.

    Article  Google Scholar 

  • Rourke, B. P. (1975). Brain-behavior relationships in children with learning disabilities: A research program. American Psychologist, 30, 911-920.

    Article  PubMed  Google Scholar 

  • Ruff, R. M. (2003). A friendly critique of neuropsychology: Facing the challenges of our future. Archives of Clinical Neuropsychology, 18, 847-864.

    Article  PubMed  Google Scholar 

  • Russell, E. W. (2005). Norming subjects for the Halstead Reitan battery. Archives of Clinical Neuropsychology, 20, 479-484.

    Article  PubMed  Google Scholar 

  • Russell, E. W. , Russell, S. L. K., & Hill, B. D. (2005). The fundamental psychometric status of neuropsychological batteries. Archives of Clinical Neuropsychology, 20, 785-794.

    Article  PubMed  Google Scholar 

  • Sandoval, J. (1981, August). Can neuropsychology contribute to rehabilitation in educational settings? No. Paper presented to the annual meeting of the American Psychological Association, Los Angeles.

    Google Scholar 

  • Sattler, J. M. (1974). Assessment of children’s intelligence. Philadelphia: Saunders.

    Google Scholar 

  • Satz, P., Taylor, H. G., Friel, J., & Fletcher, J. (1978). Some developmental and predictive precursors of reading disabilities: A six year follow-up. In A. L. Benton & D. Pearl (Eds.), Dyslexia: An appraisal of current knowledge. London: Oxford University Press.

    Google Scholar 

  • Schatz, P., Jay, K. A., McComb, J., & McLaughlin, J. R. (2005). Misuse of statistical tests in Archives of Clinical Neuropsychology publications. Archives of Clinical Neuropsychology, 20, 1053-1059.

    Article  PubMed  Google Scholar 

  • Selz, M., & Reitan, R. M. (1979). Rules for neuropsychological diagnosis: Classification of brain function in older children. Journal of Consulting and Clinical Psychology, 47, 258-264.

    Article  PubMed  Google Scholar 

  • Stanczak, E. M.., Stanczak, D. E..,& Templer, D. I. (2000). Subject-selection procedures in neuropsychological research: A meta-analysis and prospective study. Archives of Clinical Neuropsychology, 15, 587-601.

    PubMed  Google Scholar 

  • Tabachnick, B. G. (1979). Test scatter on the WISC-R. Journal of Learning Disabilities, 12, 60-62.

    Article  Google Scholar 

  • Taylor, R. L., & Imivey, J. K. (1980). Diagnostic use of the WISC-R and McCarthy Scales: A regression analysis approach to learning disabilities. Psychology in the Schools, 17, 327-330.

    Article  Google Scholar 

  • Thienemann, M., & Koran, L. M. (1995). Do soft signs predict treatment outcome in obsessive-compulsive disorder? Journal of Neuropsychiatry and Clinical Neurosciences, 7, 218-222.

    PubMed  Google Scholar 

  • Thompson, B. (2003). Score reliability: Contemporary thinking on reliability issues. Thousand Oaks, CA: Sage.

    Google Scholar 

  • Thompson, R. J. (1980). The diagnostic utility of WISC-R measures with children referred to a developmental evaluation center. Journal of Consulting and Clinical Psychology, 48, 440-447.

    Article  PubMed  Google Scholar 

  • Thorndike, R. L., & Hagen E. P. (1977). Measurement and evaluation in psychology and education (4th ed.). New York: Wiley.

    Google Scholar 

  • U.S. Office of Education. (1976). Education of handicapped children: Assistance to state: Proposed rulemaking. Federal Register, 41, 52404-52407.

    Google Scholar 

  • Wallbrown, F. H., Vance, H., & Pritchard, K. K. (1979). Discriminating between attitudes expressed by normal and disabled readers. Psychology in the Schools, 4, 472-477.

    Article  Google Scholar 

  • Wechsler, D. (1974). Wechsler Intelligence Scale for Children-Revised. New York: Psychological Corporation.

    Google Scholar 

  • Wherry, R. J., Sr. (1932). A new formula for predicting the shrinkage of the coefficient for multiple correlation. Annals of Mathematical Statistics, 2, 404-457.

    Google Scholar 

  • Willson, V. L., & Reynolds, C. R. (1982). Methodological and statistical problems in determining membership in clinical populations. Clinical Neuropsychology, 4, 134-138.

    Google Scholar 

  • Wong, T. M. (2006). Ethical controversies in neuropsychological test selection, administration, and interpretation. Applied Neuropsychology, 13, 68-76.

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer Science+Business Media, LLC

About this chapter

Cite this chapter

Reynolds, C.R., Mason, B.A. (2009). Measurement and Statistical Problems in Neuropsychological Assessment of Children. In: Reynolds, C.R., Fletcher-Janzen, E. (eds) Handbook of Clinical Child Neuropsychology. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-78867-8_9

Download citation

Publish with us

Policies and ethics