TY - JOUR
T1 - Prediction of IQ in the Mayo Older Adult Normative sample using multiple methods
AU - McCarthy, Frances M.
AU - Sellers, Alfred H.
AU - Burns, William J.
AU - Smith, Glenn
AU - Ivnik, R. J.
AU - Malec, J. F.
PY - 2003/4/1
Y1 - 2003/4/1
N2 - Using the Mayo Older Adult Normative sample (Ivnik et al., 1992) as our database, we developed regression models for estimating premorbid Full Scale (FSIQs), Verbal (VIQs), and Performance (PIQs) IQs for elderly adults. Age, years of education, and sex were the only demographic variables that showed sufficient variability; therefore, they were used as predictor variables in three stepwise procedures. The Mayo Normative FSIQs. VIQs, and PIQs served as the dependent variables. Both education and sex added significantly to the accounting of variance of both FSIQ and VIQ (p < .001, whereas education (p < .001 and age (p < .05) were significant predictors of PIQ. These models produced statistically significant multiple Rs of .54, .58, and .35 (p < .0001), with standard errors of estimate of 9.02, 8.28, and 10.77 for FSIQ, VIQ, and PIQ, respectively. Estimated FSIQs generated with the present model and the model developed by Barona and colleagues (Barona, Reynolds, & Chastain, 1984) were compared. The correlation between estimated IQs was large, the mean difference between IQs was very small, the standard deviations were nearly equal, and the categorical distributions of the two were similar. Because the Barona model is likely to be familiar to most clinicians, these findings argue in favor of the continued use of the Barona model, even when assessing people older than the WAIS-R normative sample. Extensions of these models to the WAIS-III also are discussed.
AB - Using the Mayo Older Adult Normative sample (Ivnik et al., 1992) as our database, we developed regression models for estimating premorbid Full Scale (FSIQs), Verbal (VIQs), and Performance (PIQs) IQs for elderly adults. Age, years of education, and sex were the only demographic variables that showed sufficient variability; therefore, they were used as predictor variables in three stepwise procedures. The Mayo Normative FSIQs. VIQs, and PIQs served as the dependent variables. Both education and sex added significantly to the accounting of variance of both FSIQ and VIQ (p < .001, whereas education (p < .001 and age (p < .05) were significant predictors of PIQ. These models produced statistically significant multiple Rs of .54, .58, and .35 (p < .0001), with standard errors of estimate of 9.02, 8.28, and 10.77 for FSIQ, VIQ, and PIQ, respectively. Estimated FSIQs generated with the present model and the model developed by Barona and colleagues (Barona, Reynolds, & Chastain, 1984) were compared. The correlation between estimated IQs was large, the mean difference between IQs was very small, the standard deviations were nearly equal, and the categorical distributions of the two were similar. Because the Barona model is likely to be familiar to most clinicians, these findings argue in favor of the continued use of the Barona model, even when assessing people older than the WAIS-R normative sample. Extensions of these models to the WAIS-III also are discussed.
KW - Assessment cognitive functioning
KW - Elderly geropsychology
KW - Memory
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U2 - 10.1002/jclp.10071
DO - 10.1002/jclp.10071
M3 - Article
C2 - 12652637
AN - SCOPUS:0347296272
SN - 0021-9762
VL - 59
SP - 457
EP - 463
JO - Journal of Clinical Psychology
JF - Journal of Clinical Psychology
IS - 4
ER -