BRIEF REPORT Estimating Premorbid WAIS-RIQ with Demographic Variables: Regression Equations Derived from a UK Sample*

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 re-gression equations for the estimation of premorbid WAIS-R IQ. Step wise 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 discrepan-cies between estimated premorbid IQ and obtained IQ for the present sample is provided for clinical use. The detection and quantification of acquired neuropsychological deficits rests upon the com-parison of an individual's current cognitiv