Predicting WAIS-IV and WMS-IV Index Scores from Age and Race Groups: A Utilization of Non-symmetrical Correspondence Analysis

Jessica Elizabeth Lutz, Fordham University

Abstract

Non-symmetrical correspondence analysis (NSCA) is a technique that uses categorical data from contingency tables to make regression-like predictions. The current study used a 1189-particpant sample from a public dataset containing Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) and Wechsler Memory Scale-Fourth Edition (WMS-IV) index score data. The sample was broken up into nine groups by combining three age groups (16-29, 30-59, and 60-90) with three race groups (Black, White, and Hispanic). There were eleven indices measured from the WAIS-IV and WMS-IV with categories of low scores, medium scores, and high scores. NSCA was run on each of the eleven indices to see if race/age group predicted the level of WAIS-IV and WMS-IV index scores. The study found that Hispanic and Black groups, regardless of age, tended to score in the low range most of the time, whereas White groups often scored in the medium or high range.^

Subject Area

Quantitative psychology|Cognitive psychology

Recommended Citation

Lutz, Jessica Elizabeth, "Predicting WAIS-IV and WMS-IV Index Scores from Age and Race Groups: A Utilization of Non-symmetrical Correspondence Analysis" (2018). ETD Collection for Fordham University. AAI10932307.
https://fordham.bepress.com/dissertations/AAI10932307

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