Estimating premorbid WAIS-R IQ with demographic variables: Regression equations derived from a UK sample

John Robertson Crawford, Kathryn M Allan

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Abstract

A sample of 200 healthy individuals, representative of the adult UK population in terms of age, gender, and occupational classification, completed a full-length WAIS-R. Demographic variables for the participants were recorded (age, gender, years of education, and occupational classification) and used to develop regression equations for the estimation of premorbid WAIS-R IQ. Stepwise multiple regression revealed that occupation was the best predictor of IQ for all three WAIS-R scales (FSIQ, VIQ, and PIQ). Age and years of education significantly increased the variance predicted. Together these three variables accounted for 53%, 53%, and 32% of the variance in FSIQ, VIQ, and PIQ, respectively. The results indicated that the demographic approach to the estimation of premorbid WAIS-R IQ has utility beyond the USA. However, in common with findings for American participants (Barona, Reynolds, & Chastain, 1984) the ability to predict PIQ was markedly inferior to that achieved for FSIQ and VIQ. A frequency table of the discrepancies between estimated premorbid IQ and obtained IQ for the present sample is provided for clinical use.

Original languageEnglish
Pages (from-to)192-197
Number of pages6
JournalClinical Neuropsychologist
Volume11
Issue number2
Publication statusPublished - May 1997

Keywords

  • CROSS-VALIDATION
  • INTELLIGENCE
  • INDEX
  • NART

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