Skip to main content
SpringerLink
Log in

Leiter-3: Nonverbal Cognitive and Neuropsychological Assessment

  • Chapter
  • First Online:
Handbook of Nonverbal Assessment

Abstract

Authors of this chapter describe the basic characteristics, strengths, and weaknesses of the new version of the Leiter International Performance Scale (Leiter-3: Roid, Miller, Pomplun, & Koch 2013, Stoelting Company, Wood Dale, IL 60191 USA). The main strength of the Leiter-3 would be the true nonverbal character of the test, requiring no spoken directions by the examiner and no spoken responses by the examinee. In addition, the subtests have a great deal of color, are game-like, and are more engaging than some of the other nonverbal instruments that use primarily black-and-white illustrations without manipulatives such as the blocks used in the Leiter-3 cognitive subtests. Also, the Leiter-3 provides a nonverbal IQ with just four subtests, and, for differential analysis of cognitive process deficits, a companion set of memory and attention nonverbal subtests that are optional. The technical qualities are strong in terms of reliability, validity, decision-consistency accuracy, and fairness. The review in Buros Mental Measurements Yearbook (online by Martin Wiese, 2014) included several positive comments about the test, stating “The Leiter-3 authors have succeeded in their goal of constructing a reliable and valid nonverbal measure of intellectual ability and Attention/Memory.” Weaknesses are few based on the reviews to date (e.g., the global Nonverbal IQ score is not supplemented by factor index scores for fluid reasoning and visual-spatial abilities separately, relatively small number of subjects in criterion-group studies, and lower test–retest coefficients compared to internal consistency estimates).

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
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

Institutional subscriptions

References

  • Ackerman, P. T., Anhault, J. M., Dykman, R. A., & Holcomb, P. J. (1986). Effortful processing deficits in children with reading or attention disorders. Brain and Cognition, 5, 22–40.

    Article  PubMed  Google Scholar 

  • Albert, M. L. (1973). A simple test of visual neglect. Neurology, 23, 658–664.

    Article  PubMed  Google Scholar 

  • American Educational Research Association (AERA), American Psychological Association (APA), & National Council on Measurement in Education (NCME). (1999). Standards for educational and psychological testing. Washington, DC: APA.

    Google Scholar 

  • American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (DSM-V-TR) (5th ed.). Washington, DC: Author.

    Google Scholar 

  • Banken, J. A. (1985). Clinical utility of considering digits forward and digits backward as separate components of the Wechsler Adult Intelligence Scale-Revised. Journal of Clinical Psychology, 41, 686–691.

    Google Scholar 

  • Berk, R. A. (1984). A guide to criterion-test construction. Baltimore, MD: Johns Hopkins University Press.

    Google Scholar 

  • Bishop, S. L., Richler, J., & Lord, C. (2006). Association between restricted and repetitive behaviors and nonverbal IQ in children with ASD. Child Neuropsychology, 12, 247–267.

    Article  PubMed  Google Scholar 

  • Bond, T. G., & Fox, C. M. (2007). Applying the Rasch model: Fundamental measurement in the human sciences (2nd ed.). Mahwah, NJ: Routledge/Erlbaum.

    Google Scholar 

  • Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 136–162). Newbury Park, CA: Sage.

    Google Scholar 

  • Buros Center for Testing. (2014). Weise review of Leiter-3. Lincoln, NE: Buros Institute, University of Nebraska-Lincoln. www.buros.org

  • Carroll, J. B. (1993). Human cognitive abilities: A survey of factor-analytic studies. New York: Cambridge University Press.

    Book  Google Scholar 

  • CDC (Centers for Disease Control). (2007). Press release: CDC releases new data on autism spectrum disorders (ASDs) from multiple communities in the United States. Retrieved September 6, 2007, from the Centers for Disease Control Web site: http://www.cdc.gov/od/oc/media/pressrel/2007/r070208.htm

  • Cha, C. B., Najmi, S., Park, J. M., Finn, C. T., & Nock, M. K. (2010). Attentional bias toward suicide-related stimuli predicts suicidal behavior. Journal of Abnormal Psychology, 119, 616–622.

    Google Scholar 

  • Christensen, A. L. (1979). Luria’s neuropsychological investigation (2nd ed.). Copenhagen: Munksgaard.

    Google Scholar 

  • Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297−334.

    Google Scholar 

  • Dalrymple-Alford, E. C., & Budayr, B. (1966). Examination of some aspects of the Stroop color-word test. Perceptual and Motor Skills, 23, 1211–1214.

    Article  PubMed  Google Scholar 

  • Dee, H. L. (1970). Visuoconstructive and visuoperceptive deficit in patients with unilateral cerebral lesions. Neuropsychologia, 8, 305–314.

    Article  PubMed  Google Scholar 

  • Dunbar, K. N., & MacLeod, C. M. (1984). A horse race of a different color: Stroop interference patterns with transformed words. Journal of Experimental Psychology: Human Perception and Performance, 10, 622–639.

    PubMed  Google Scholar 

  • Dyer, E. N. (1973). The Stroop phenomenon and its use in the study of perceptual, cognitive, and response processes. Memory and Cognition, 1, 106–120.

    Article  PubMed  Google Scholar 

  • Dyer, F. N., & Severance, L. J. (1973). Stroop interference with successive presentations of separate incongruent words and colors. Journal of Experimental Psychology, 98, 438–439.

    Article  PubMed  Google Scholar 

  • Elliott, C. D. (2008). Differential Ability Scales—Second Edition (DAS-II). San Antonio, TX: Pearson/Psychological Corp.

    Google Scholar 

  • Flanagan, D. P., Ortiz, S. O., & Alfonso, V. (2013). Essentials of cross-battery assessment (3rd ed.). New York: Wiley.

    Google Scholar 

  • Flynn, J. R. (1987). Massive IQ gains in 14 nations: What IQ tests really measure. Psychological Bulletin, 101, 171–191.

    Article  Google Scholar 

  • Flynn, J. R. (2012). Are we getting smarter? Rising IQ in the 21st century. Cambridge, UK: Cambridge University Press.

    Book  Google Scholar 

  • Golden, C. J. (1976). The diagnosis of brain damage by the Stroop test. Journal of Clinical Psychology, 32, 654–658.

    Article  PubMed  Google Scholar 

  • Golden, C. J., Freshwater, S. M., & Golden, Z. (2003). Stroop color and word test, children’s version for ages 5–14. Wood Dale, IL: Stoelting Co.

    Google Scholar 

  • Goldstein, G., Johnson, C. R., & Minshew, N. J. (2001). Attentional processes in autism. Journal of Autism and Developmental Disorders, 31, 433–440.

    Article  PubMed  Google Scholar 

  • Gorsuch, R. L. (1983). Factor analysis (2nd ed.). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Gottschaldt, K. (1928). Hidden figures test. In G. Talland (Ed.), Deranged memory (p. 1965). New York: Academic Press.

    Google Scholar 

  • Gregory, R. J. (1996). Psychological testing (2nd ed.). Boston, MA: Allyn & Bacon.  

    Google Scholar 

  • Guilford, J. P., & Fruchter, B. (1978). Fundamental statistics in psychology and education. New York, NY: McGraw-Hill.

    Google Scholar 

  • Gustafsson, J. E. (1984). A unifying model for the structure of intellectual abilities. Intelligence, 8, 179–203.

    Article  Google Scholar 

  • Hale, J. B., Yim, M., Schneideer, A. N., Wilcox, G., Henzel, J. N., & Dixon, S. G. (2012). Cognitive and neuropsychological assessment of ADHD. In D. Flanagan & P. Harrison, Contemporary intellectual assessment (pp. 687–707). New York, NY: Guilford Press.

    Google Scholar 

  • Hambleton, R. K., Swaminathan, H., & Rogers, H. J. (1991). Fundamentals of Item response theory. Newbury Park, CA: Sage.

    Google Scholar 

  • Hardy-Braz, S. (2013). General guidelines for using the Leiter-3 with deaf/hard-of-hearing (Appendix K). In G. Roid, L. Miller, M. Pomplun, & C. Koch (Eds.), Leiter-3 manual (pp. 277–278). Wood Dale, IL: Stoelting Co.

    Google Scholar 

  • Holland, P., & Wainer, H. (Eds.). (1993). Differential item functioning. Mahwah, NJ: Routledge/Erlbaum.

    Google Scholar 

  • Hooper, H. E. (1983). Hooper visual organization test. Los Angeles, CA: Western Psychological Services.

    Google Scholar 

  • Horn, J. L., & Cattell, R. B. (1966). Refinement and test of the theory of fluid and crystallized intelligence. Journal of Educational Psychology, 57, 253–270.

    Google Scholar 

  • Jensen, A. R. (1980). Bias in mental testing. New York: The Free Press.

    Google Scholar 

  • Joreskog, K. G., & Sorbom, D. (1999). LISREL 8: User’s reference guide. Chicago: Scientific Software.

    Google Scholar 

  • Kahneman, D., & Chajczyk, D. (1983). Tests of the automaticity of reading: Dilution of Stroop effects by color-irrelevant stimuli. Journal of Experimental Psychology: Human Perception and Performance, 9, 497–509.

    PubMed  Google Scholar 

  • Kahneman, D., & Henik, A. (1981). Perceptual organization and attention. In M. Kubovy & J. R. Pomerantz (Eds.), Perceptual organization (pp. 181–211). Hillsdale, NJ: Erlbaum.

    Google Scholar 

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

    Google Scholar 

  • Kelly, M. S., Best, C. T., & Kirk, U. (1989). Cognitive processing deficits in reading disabilities: A prefrontal cortical hypothesis. Brain and Cognition, 11, 275–293.

    Article  PubMed  Google Scholar 

  • Klinger, L. G., O’Kelly, S. E., Mussey, J. L., Goldstein, S., & DeVries, M. (2012). Assessment of intellectual functioning in autism spectrum disorder. In D. Flanagan & P. Harrison, Contemporary intellectual assessment, 3rd Ed. (pp. 670–686). New York, NY: Guildford Press.

    Google Scholar 

  • Koch, C., & Barr, B. (2010). Can Task Demands Override Connectedness? Abstracts of the Psychonomic Society, 15, 56.

    Google Scholar 

  • Koch, C., & Kubovy, M. (1996, June). Interference in a color-color Stroop task. Poster presented at the Eighth Annual Convention of the American Psychological Society, San Francisco, CA.

    Google Scholar 

  • Koch, C., Lowen, J, & McWilliams, M. (2011, November). Developmental differences using a nonverbal Stroop task. Poster presented at the Object Perception, Attention, & Memory 19th Annual Conference, Seattle, WA.

    Google Scholar 

  • Koch, C., & Roid, G. (2012). Manual for the nonverbal Stroop card sorting task. Wood Dale, IL: Stoelting Company.

    Google Scholar 

  • Kuschner, E. S., Bennetto, L., & Yost, K. (2007). Patterns of nonverbal cognitive functioning in young children with autism spectrum disorders. Journal of Autism and Developmental Disorders, 37(5), 795–807.

    Google Scholar 

  • Leiter, R. G. (1938). A comparative study of the general intelligence of Caucasian and Asian children as measured by the Leiter international performance scale. Unpublished doctoral dissertation, University of Southern California, Los Angeles, CA.

    Google Scholar 

  • Leiter, R. G. (1979). Instruction manual for the Leiter international performance scale. Wood Dale, IL: Stoelting Co.

    Google Scholar 

  • Levine, M. N. (1982). Leiter international performance scale: A handbook. Los Angeles, CA: WPS.

    Google Scholar 

  • Lezak, M. D. (1995). Neuropsychological assessment (3rd ed.). New York: Oxford University Press.

    Google Scholar 

  • Lincacre, J. M., & Wright, B. D. (2000). WINSTEPS v. 3.00: Rasch item analysis computer program manual. Chicago: MESA Press.

    Google Scholar 

  • Lord, F. M. (1980). Applications of item response theory to practical testing problems. Mahwah, NJ: Erlbaum.

    Google Scholar 

  • Mather, N., & Woodcock, R. W. (2001). Woodcock-Johnson tests of cognitive ability third edition: Technical manual. Chicago: Riverside.

    Google Scholar 

  • Mayes, S. D., & Calhoun, S. L. (2003). Ability profiles in children with autism. The National Autistic Society, 6, 65–80.

    Google Scholar 

  • Mayes, S. D., & Calhoun, S. L. (2004). Influence of IQ and age in childhood autism: Lack of support for DSM-IV Asperger’s disorder. Journal of Developmental and Physical Disabilities, 3, 257–272.

    Article  Google Scholar 

  • Minshew, N. J., & Goldstein, G. (1998). Autism and a disorder of complex information processing. Mental Retardation and Developmental Disabilities, 4, 129–136.

    Article  Google Scholar 

  • Minshew, N. J., & Williams, D. L. (2007). The new neurobiology of autism: Cortex, connectivity, and neuronal organization. Neurological Review, 64, 945–950.

    Google Scholar 

  • Mundy, P., & Crowson, M. (1997). Joint attention and early social communication: Implications for research on intervention with autism. Journal of Autism and Developmental Disorders, 27, 653–675.

    Article  PubMed  Google Scholar 

  • Nelson, H. E. (1976). A modified card sorting test sensitive to frontal lobe defects. Cortex, 12, 313–324.

    Article  PubMed  Google Scholar 

  • Nordlund, C. B. (1998). An examination of behavior ratings and rater differences of ADHD subjects on the Leiter-R rating scales. Unpublished doctoral dissertation, George Fox University, Newberg, Oregon.

    Google Scholar 

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

    Google Scholar 

  • Posner, M. I., & Snyder, C. R. R. (1975). Attention and cognitive control. In R. L. Solso (Ed.), Information processing and cognition: The Loyola symposium (pp. 55–85). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Rasch, G. (1966). An item analysis which takes individual differences into account. British Journal of Mathematical and Statistical Psychology, 19, 49–57.

    Article  PubMed  Google Scholar 

  • Rasch, G. (1980). Probabilistic models for some intelligence and attainment tests. Chicago, IL: University of Chicago Press (Translated from the Danish original of 1960).

    Google Scholar 

  • Raven, J., Raven, J. C., & Court, J. H. (1998). Manual for Raven’s progressive matrices and vocabulary scales. Oxford, UK: Oxford Psychologists Press.

    Google Scholar 

  • Reynolds, C. R. (1997). Forward and backward memory span should not be combined for clinical analysis. Archives of Clinical Neuropsychology, 12, 29–40.

    Google Scholar 

  • Roid, G. H. (2003). Stanford-Binet intelligence scales—Fifth edition, examiner & technical manuals. Austin, TX: Pro-Ed.

    Google Scholar 

  • Roid, G. H., & Haladyna, T. M. (1982). A technology for test-item writing. New York: Academic Press.

    Google Scholar 

  • Roid, G. H., & Miller, L. J. (1997). Leiter international performance scale—Revised. Wood Dale, IL: Stoelting.

    Google Scholar 

  • Roid, G. H., Miller, L. J., Pomplun, M., & Koch, C. (2013). Leiter international performance scale-third edition. Wood Dale, IL: Stoelting Company.

    Google Scholar 

  • Roid, G. H., Pomplun, M., & Martin, J. (2009). Nonverbal cognitive assessment with the Leiter-R. In J. Naglieri & S. Goldstein (Eds.), A practitioner’s guide to assessment of intelligence and achievement. NY: Wiley.

    Google Scholar 

  • Roid, G. H., & Woodcock, R. W. (2000). Uses of Rasch scaling in the measurement of cognitive development and growth. Journal of Outcome Measurement, 4(2), 579–594.

    PubMed  Google Scholar 

  • Rosinski, R. R., Golinkoff, R. M., & Kukish, K. S. (1975). Automatic semantic processing in a picture-word interference task. Child Development, 46, 247–253.

    Article  Google Scholar 

  • Rourke, B. P. (1988). The syndrome of non-verbal learning disabilities. Clinical Neuropsychologist, 2, 293–330.

    Article  Google Scholar 

  • Salvia, J., & Ysseldyke, J. E. (1991). Assessment. Boston, MA: Houghton Mifflin.

    Google Scholar 

  • Sattler, J. M. (2001). Assessment of children: Cognitive applications (4th ed.). La Mesa, CA: Author.

    Google Scholar 

  • Schneider, W. J., & McGrew, K. S. (2012). The Cattell-Horn-Carroll model of intelligence. In D. Flanagan & P. Harrison, Contemporary intellectual assessment, 3rd Ed. (pp. 99–144). New York, NY: Guilford Press.

    Google Scholar 

  • Stroop, J. R. (1935). Studies of interference in serial verbal reactions. Journal of Experimental Psychology, 18, 643–662.

    Article  Google Scholar 

  • Sullivan, E. V., Sagar, H. J., & Gabrieli, J. D. (1989). Different cognitive profiles on standard behavioral tests in Parkinson’s disease and Alzheimer’s disease. Journal of Clinical and Experimental Neuropsychology, 11, 799–820.

    Google Scholar 

  • Talland, G. A. (Ed.). (1965). Deranged memory. New York: Academic Press.

    Google Scholar 

  • Tecce, J. J., & Happ, S. J. (1964). Effects of shock-arousal on a card-sorting test of color-word interference. Perceptual and Motor Skills, 19, 905–906.

    Article  PubMed  Google Scholar 

  • Thurstone, L. L., & Thurstone, T. G. (1962). Primary Mental Abilities (Rev.), Chicago, IL: Science Research Associates.

    Google Scholar 

  • U.S. Bureau of Census. (2009). Population statistics: 2008 update. Washington, DC: Author.

    Google Scholar 

  • U.S. Bureau of Census. (2011). Census 2010 summary file 1 of the United States. Washington, DC: Author.

    Google Scholar 

  • U.S. Department of Education. (2016). National Center for Education Statistics, EDFacts file 141, Data Group 678, extracted May 13, 2016, from the EDFacts Data Warehouse (internal U.S. Department of Education source); Common Core of Data (CCD), “State Nonfiscal Survey of Public Elementary and Secondary Education,” 2008–09 through 2013–14. http://nces.ed.gov/programs/digest/d15/tables/dt15_204.27.asp

  • U.S. Department of Education. (2007). Data analysis system OMB #1820-0043: “Children with disabilities receiving special education under part B of the individuals with disabilities education act”. Data updated as of July 15, 2008. Washington DC: Author, Office of Special Education Programs. Retrieved from: https://www.ideadata.org/arc_toc9.asp#partbCC

  • Volkmar, F. R., Lord, C., Bailey, A., Schultz, R. T., & Klin, A. (2004). Autism and pervasive developmental disorders. Journal of Child Psychology and Psychiatry, 45, 135–170.

    Article  PubMed  Google Scholar 

  • Wang, P. L. (1984). Modified Vygotsky concept formation test manual. Chicago, IL: Stoelting Co.

    Google Scholar 

  • Wechsler, D. (1991). Wechsler intelligence scale for children—Third Edition (WISC-III). San Antonio, TX: The Psychological Corporation.

    Google Scholar 

  • Wechsler, D. (2003). Wechsler intelligence scale for children—Fourth edition. (WISC-IV) San Antonio, TX: Pearson/PsychCorp.

    Google Scholar 

  • Wechsler, D. (2008). Wechsler adult intelligence scale—Fourth edition (WAIS-IV). San Antonio, TX: Pearson/PsychCorp.

    Google Scholar 

  • Williams, D. L., Goldstein, G., & Minshew, N. J. (2006). Neurophsychologic functioning in children with autism: Further evidence for disordered complex information-processing. Child Neuropsychology, 12, 279–298.

    Article  PubMed  PubMed Central  Google Scholar 

  • Woodcock, R. W. (1999). What can Rasch-based scores convey about a person’s test performance? In S. E. Embretson & S. L. Hershberger (Eds.), The new rules of measurement: What every psychologist and educator should know (pp. 105–128). Mahwah, NJ: Erlbaum.

    Google Scholar 

  • Woodcock, R. W., & Dahl, M. N. (1971). A common scale for the measurement of person ability and test item difficulty. (AGS Paper No. 10). Circle Pines, MN: American Guidance Service.

    Google Scholar 

  • Woodcock, R. W., McGrew, K., & Mather, N. (2000). Woodcock-Johnson tests of cognitive ability-third edition: Examiner’s manual. Chicago: Riverside.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Testing Research, 1838 Mistwood Drive NE, Keizer, OR, 97303, USA

    Gale H. Roid

  2. George Fox University, 414 N, Meridian Street, Newberg, OR, 97132, USA

    Christopher Koch

Authors
  1. Gale H. Roid
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Christopher Koch
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Gale H. Roid .

Editor information

Editors and Affiliations

  1. University of Tennessee, Knoxville, Tennessee, USA

    R. Steve McCallum

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this chapter

Cite this chapter

Roid, G.H., Koch, C. (2017). Leiter-3: Nonverbal Cognitive and Neuropsychological Assessment. In: McCallum, R. (eds) Handbook of Nonverbal Assessment. Springer, Cham. https://doi.org/10.1007/978-3-319-50604-3_8

Download citation

Publish with us

Policies and ethics

Search

Navigation