Assessing the Psychometric Utility of IQ Scores: A Tutorial Using the Wechsler Intelligence Scale for Children–Fifth Edition

Abstract

IQ tests provide numerous scores, but valid interpretation of those scores is dependent on how precisely each score reflects its intended construct and whether it provides unique information independent of other constructs. Thus, IQ scores must be evaluated for their reliability and dimensionality to determine their psychometric utility. As a tutorial, the Wechsler Intelligence Scale for Children–Fifth Edition (WISC-V) scores were evaluated and it was demonstrated that the WISC-V is multidimensional, but only the Full-Scale IQ (FSIQ) was found to be sufficiently reliable for clinical use. WISC-V group factors were not well defined and WISC-V index (i.e., factor) scores were contaminated with variance from other constructs and insufficiently reliable for clinical decisions. Clinicians were encouraged to go beyond structural goodness of fit and evaluate IQ test scores in terms of their reliability and ability to provide information that is not available from the general ability score as well their predictive and treatment validity. Software was provided to assist in that evaluation.

Impact Statement

IQ tests provide numerous scores, but valid interpretation of those scores is dependent on how precisely each score reflects its intended construct and whether it provides unique information independent of other constructs. Thus, IQ scores must be evaluated for their reliability and dimensionality to determine their psychometric utility. This article describes an evidence-based approach that clinicians can employ to assess the psychometric utility of IQ scores, supplies software tools to assist in that analysis, and provides a tutorial example using Wechsler Intelligence Scale for Children–Fifth Edition (WISC-V) scores.

Keywords:

• intelligence
• WISC-V
• children
• assessment
• evidence-based

ASSOCIATE EDITOR:

• Shane Jimerson

DISCLOSURE

The authors declare that they have no conflict of interest.

Correction Statement

This article has been corrected with minor changes. These changes do not impact the academic content of the article.

Notes

1 Factor transformation via the S-L procedure can be directly implemented with the free psych package in the R software system (R Development Core Team, 2020), the free FACTOR program (Lorenzo-Seva & Ferrando, 2006), and the SPSS system with syntax provided by Wolff and Preising (2005). Alternatively, the S-L procedure can be indirectly computed from the validity information extracted from the test’s technical manual with the MacOrtho program (Watkins, 2020). Variance decomposition and indices of score quality can be completed with a versatile spreadsheet contributed by Dueber (2017) that is available at https://uknowledge.uky.edu/edp_tools/1/. Similar metrics can be extracted from two R packages: BifactorIndicesCalculator at https://cran.r-project.org/web/packages/BifactorIndicesCalculator/index.html and psych at https://cran.r-project.org/web/packages/psych/index.html. The free Omega (Watkins, 2013) program can also accomplish these tasks.

2 The labels applied to omega coefficients have been inconsistent. Some authors use specific labels for omega coefficients applied to general and group factors. For example, ω for the amalgam of general and group factor variance in the general factor score (i.e., FSIQ), ω_s for the amalgam of general and group factor variance in the group factor scores (i.e., VCI, VSI, etc.), ω_h for the general factor variance in the general factor score, and ω_hs for the group factor variance in the group factor scores.

Additional information

Notes on contributors

Marley W. Watkins

Marley W. Watkins, PhD, received his PhD in school psychology from the University of Nebraska–Lincoln and has held positions with the Deer Valley Unified School District, Pennsylvania State University, Arizona State University, and Baylor University. He is currently a research professor in the Department of Educational Psychology at Baylor University. His research interests include professional issues, the psychometrics of assessment and diagnosis, individual differences, and computer applications. Dr. Watkins has published more than 170 peer-reviewed journal articles and made more than 125 presentations at professional conferences.

Gary L. Canivez

Gary L. Canivez, PhD, is professor of psychology at Eastern Illinois University and principally involved in the Specialist in School Psychology program. Before entering academia Dr. Canivez was a school psychologist for 8 years, was on the adjunct faculty of Arizona State University and Northern Arizona University, and was president of the Arizona Association of School Psychologists. Dr. Canivez currently serves as associate editor of Archives of Scientific Psychology and served as associate editor for Psychological Assessment. He is a consulting editor and frequent reviewer for numerous other school psychology, assessment, and clinically oriented journals. Dr. Canivez is a member of the Society for the Study of School Psychology, a Fellow of the Division (5) of Quantitative and Qualitative Methods and Division (16) of School Psychology of the American Psychological Association, and a Charter Fellow of the Midwestern Psychological Association. The author of over 100 research and professional publications and over 200 professional presentations and continuing professional development workshops, Dr. Canivez has research interests in psychological assessment and measurement pertaining to intelligence, achievement, personality, and psychopathology. His research has been supported by the National Institutes of Health/National Institute of Mental Health.