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the relationships of education to IQ, but splitting the sample of patients with brain damage had a striking effect. For control subjects in both halves of the sample, and for the high-education patient sample, IQ correlated substantially with V-IQ and FS-IQ (.64 .71) and moderately with P-IQ (.39 .57). However, correlations were nonsignificant and trivial ( .11 .26) for the loweducation patient sample. The diminished role in the ability of educational attainment to predict IQ for relatively poorly educated patient samples suggests that, for such samples, the brain damage itself has a more potent effect on a patient s IQ than does his or her educational attainment. Reitan and Wolfson (1996a) also looked at individual WAIS scaled scores to examine the effect of education on cognitive performance for patients with brain damage and for control subjects. Like the global results described above, level of education had a strong effect on subtest scores in the control group and a much lesser effect on scores in the patient group (see Table 8.24). In the group with brain damage, only three subtests produced significant differences (p < .05) between the high and low education subgroups (Information, Comprehension, and Vocabulary); however, in the control group, all subtests but two (Picture Completion and Object Assembly) had significant differences between the high and low education subgroups (p < .05). Likewise, correlations between education and subtest scores were larger

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TABLE 8.23 Coefficients of correlation for education vs. V-IQ, P-IQ,

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and FS-IQ for patients with brain damage and control group, each subdivided at the median for education Group Controls (N = 50) Education: Upper 50% Education: Lower 50% Brain-Damaged (N = 50) Education: Upper 50% Education: Lower 50% .66* .26* .57* .11* .64* .07* .71* .64* .39* .55* .66* .67* V-IQ P-IQ FS-IQ

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*p < .01 NOTE: Data are from Reitan and Wolfson (1996b).

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TABLE 8.24 Means on WAIS subtests for patients with brain damage and control group,

each subdivided at the median for education Brain Damage (N = 50) Subtest Information Comprehension Arithmetic Similarities Digit Span Vocabulary Digit Symbol Picture Completion Block Design Picture Arrangement Object Assembly Higher Education 10.8* 11.7* 8.6* 10.8* 7.9* 11.4* 7.0* 9.1* 8.2* 7.6* 7.7* Lower Education 8.6 9.4 6.9 8.5 6.6 8.1 6.7 7.9 7.7 7.2 8.2 Control (N = 50) Higher Education 12.5* 13.1* 12.5* 13.8* 11.2* 13.6* 12.8* 11.8* 13.0* 10.8* 11.7* Lower Education 9.9 11.0 9.1 11.0 7.8 10.3 9.2 10.4 10.6 7.8 10.5

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*p < .05 (mean for higher education is significantly larger than mean for lower education) NOTE: Data are from Reitan and Wolfson (1996a).

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for the controls than the patient sample (mean rs for Verbal subtests were .65 and .46, respectively; mean rs for Performance subtests were .46 and .17, respectively). In fact, there were no significant correlations between education and Performance scaled scores for the patients with brain damage, but there were significant correlations for four of the five Performance subtests for the control group. As noted previously, often age- and education-adjusted data based on normal samples are used to predict premorbid functioning of braindamaged patients (e.g., Barona, Reynolds, and Chastain, 1984). Thus, Reitan and Wolfson (1996b) also used their education (and age) data from control patients to develop regression equations to determine its effectiveness in predicting the IQs of their sample with brain damage. Reitan and Wolfson s results showed that, when predictions of IQs for patients with brain damage were based on relationships of IQ with age and education for the controls, the predicted

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IQ means for the patient sample differed significantly from the actual IQ means in each case. The authors conclude that the use of relationships between the attribute variables of age and education versus IQ values, when based on control subjects, are subject to error when applied to brain-damaged subjects (p. 302). They caution against adjusting IQs for patients with brain damage on the basis of normative data derived from nonbrain-damaged subjects (Reitan & Wolfson, 1996, 1997).

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