Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-02T20:15:42.147Z Has data issue: false hasContentIssue false

IQ estimate smackdown: Comparing IQ proxy measures to the WAIS-III

Published online by Cambridge University Press:  01 July 2009

RUTH SPINKS*
Affiliation:
Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, Iowa
LOWELL W. MCKIRGAN
Affiliation:
Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, Iowa
STEPHAN ARNDT
Affiliation:
Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, Iowa Iowa Consortium for Substance Abuse Research and Evaluation, University of Iowa, Iowa City, Iowa Department of Biostatistics, College of Public Health, University of Iowa, Iowa City, Iowa
KRISTIN CASPERS
Affiliation:
Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, Iowa
REBECCA YUCUIS
Affiliation:
Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, Iowa
CHRISTOPHER J. PFALZGRAF
Affiliation:
Department of Psychiatry, Carver College of Medicine, University of Iowa, Iowa City, Iowa
*
*Correspondence and reprint requests to: Ruth Spinks, Psychiatry Research, Medical Examination Building, University of Iowa, Iowa City, Iowa 52242. E-mail: [email protected]

Abstract

Brief assessments of general cognitive ability are frequently needed by neuropsychologists, and many methods of estimating intelligence quotient (IQ) have been published. While these measures typically present overall correlations with the Wechsler Adult Intelligence Scale (WAIS) Full Scale IQ, it is tacitly acknowledged that these estimates are most accurate within 1 standard deviation of the mean and that accuracy diminishes moving toward the tails of the IQ distribution. However, little work has been done to systematically characterize proxy measures at the tails of the IQ distribution. Additionally, while these measures are all correlated with the WAIS, multiple proxy measures are rarely presented in one manuscript. The current article has two goals: (1) Examine various IQ proxies against Wechsler Adult Intelligence Scale (Third Version) scores, showing the overall accuracy of each measure against the gold standard IQ measure. This comparison will assist in selecting the best proxy measure for particular clinical constraints. (2) The sample is then divided into three groups (below, average, and above-average ability), and each group is analyzed separately to characterize proxy performance at the tails of the IQ distribution. Repeated measures multivariate analysis of variance compares the different proxy measures across ability levels. All IQ estimates are represented in tables so that they can be examined side by side. (JINS, 2009, 15, 590–596.)

Type
Research Articles
Copyright
Copyright © The International Neuropsychological Society 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Axelrod, B.N., Dingell, J.D., Ryan, J.J., & Ward, L.C. (2000). Estimation of the Wechsler Adult Intelligence Scale-III with the 7-subtest short form in a clinical sample. Assessment, 7, 157161.CrossRefGoogle Scholar
Barona, A., Reynolds, C.R., & Chastain, R. (1984). A demographically based index of premorbid intelligence test for the WAIS-R. Journal of Consulting and Clinical Psychology, 52, 885887.CrossRefGoogle Scholar
Blair, J.R. & Spreen, O. (1989). Predicinting premorbid IQ: A revision of the National Adult Reading Test. The Clinical Neuropsychologist, 3, 129136.CrossRefGoogle Scholar
Crawford, J.R. & Allan, K.M. (1997). Estimating premorbid WAIS-R IQ with demographic variables: Regression equation derived from a UK sample. The Clinical Neuropsychologist, 11, 192197.CrossRefGoogle Scholar
Engelhart, C.I., Eisenstein, J., Johnson, V., & Losonczy, M. (1999). Comparison of linear equating and prorated short forms for estimating WAIS-R FSIQ in a neuropsychological population. The Clinical Neuropsychologist, 13, 9599.CrossRefGoogle Scholar
Hoover, H.D., Dunbar, S.B., & Frisbie, D.A. (2003). Iowa Tests of Basic Skills Complete/Core Battery Norms: Score conversions, student norms and school average norms, (Form A). Itasca, IL: Riverside Publishing.Google Scholar
Jeyakumar, S.L.E., Warriner, E.M., Raval, V.V., & Ahmad, S.A. (2004). Balancing the need for reliability and time efficiency: Short forms of the Wechsler Adult Intelligence Scale-III. Educational and Psychological Measurement, 64, 7187.CrossRefGoogle Scholar
Mendella, P.D., McFadden, L., Regan, J., & Medlock, L. (2000). Short-form prediction of WAIS-R scores in a sample of individuals diagnosed with multiple sclerosis. Applied Neuropsychology, 7, 102107.CrossRefGoogle Scholar
Pilgrim, B.M., Meyers, J.E., Bayless, J., & Whetstone, . (1999). Validity of the Ward seven-subtest WAIS-III short form in a neuropsychological population. Applied Neuropsychology, 6, 243246.CrossRefGoogle Scholar
Sattler, J.M. (Ed.). (2001). Assessment of children: Cognitive applications (4th ed.). San Diego, CA: Jerome M. Sattler Publishing, Inc.Google Scholar
Schoenberg, M.R., Duff, K., Scott, J.G., & Adams, R.L. (2002). An evaluation of the clinical utility of the OPIE-3 as an estimate of premorbid WAIS-III FSIQ. Clinical Neuropsychologist, 17, 308321.CrossRefGoogle Scholar
Schoenberg, M.R., Duff, K., Dorfman, K., & Adams, R.L. (2004a). Differential estimation of verbal intelligence and performance intelligence scores from combined performance and demographic variables: The OPIE-3 verbal and performance algorithms. Clinical Neuropsychology, 16, 266276.CrossRefGoogle Scholar
Schoenberg, M.R., Scott, J.G., Ruwe, W., Patton, D., & Adams, R.L. (2004b). Assumptions that underlie predicting premorbid IQ: A comment on the “Evaluation of the accuracy of two regression-based methods for estimating premorbid IQ.” Archives of Clinical Neuropsychology, 19, 11031106.CrossRefGoogle ScholarPubMed
Spinks, R., Arndt, S., Caspers, K., Yucuis, R., McKirgan, L.W., Pfalzgraf, C.J., & Waterman, E.E. (2007). School achievement strongly predicts midlife IQ. Intelligence, 35, 563567.CrossRefGoogle Scholar
Strauss, E., Sherman, E.M.S., & Spreen, O. (2006). A Compendium of Neuropsychological Tests: Administration, norms, and commentary (3rd ed.). New York, NY: Oxford University Press.Google Scholar
Wechsler, D. (1997). Wechsler Adult Intelligence Scale (3rd ed.). San Antonio, TX: The Psychological Corporation (A Division of Harcourt Assessment Company).Google Scholar
Zachary, R.A. (1986). Shipley Institute of Living Scales, revised manual. Los Angeles, CA: Western Psychological Services.Google Scholar