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ization sample, ages 16 89 (N = 2,450); however, whenever pertinent, systematic differences due to chronological age are noted. FACTOR LOADINGS. The primary factor loading is listed for each subtest based on the oblimin-rotated 4-factor solution of the 14 WAIS-III subtests for ages 16 89, along with the secondary loading (defined for these analyses as .20) for some subtests. Data are from Table 7.6 for the three VCI subtests plus Comprehension. For the seven Performance subtests and the three Working Memory subtests, data are presented separately for ages 16 74 and 75 89 because of notable age-related differences in their factor loadings. For the elderly sample: (1) most Performance subtests had their primary factor loading on the Processing Speed factor, rather than the Perceptual Organization factor; and (2) the two Processing Speed subtests had secondary loadings on the Working Memory factor, creating a five-subtest dimension that resembles Barkley s (1997) construct of executive functioning. For all of the Performance subtests (except Object Assembly) and for the Working Memory subtests, mean factor loadings for ages 16 74 are based on data for four age groups (Psychological Corporation, 1997, pp. 108 109) and the values for ages 75 89 are from Table 7.9. Mean values for Object Assembly at ages 16 74 and 75 89 are based on oblimin-rotated factor loadings provided by Sattler and Ryan (1999, pp. 1216 1217) TABLE 10.9

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for the 13 separate standardization age groups (Psychological Corporation, 1997, excluded Object Assembly from their analyses). SUBTEST SPECIFICITY. Each subtest has a proportion of variance that is unique only to it. This uniqueness is somewhat like the inverse of g, as it is a representation of the variance that is not shared with other subtests. Subtest specificity is important to know to determine now feasible it is to interpret the unique abilities or traits attributed to a subtest. It is justifiable to interpret a subtest s unique contributions to the overall test if its unique variance exceeds the error variance and is sufficient in magnitude. About 25% or more of the total variance is generally considered a sufficient amount to warrant specific interpretation, so long as the specific variance exceeds the error variance. The specificity for each subtest was statistically calculated via an uncomplicated technique. The shared variance for each subtest was obtained (we used the squared multiple correlation), and then this common variance was subtracted from the subtest s reliability coefficient. The result of this calculation is the reliable unique variance (subtest specificity). To determine whether a task s uniqueness should be interpreted, the error variance for the subtest (one minus the reliability) was then compared to the specificity. The levels of specificity are classified as ample, adequate, or inadequate in Table 10.9.

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WAIS-III subtests categorized by their specificitya Adequate Specificity Picture Arrangement (.31/.26) Block Design (.27/.14) Information (.23/.09) Comprehension (.20/.16) Similarities (.20/.14) Vocabulary (.19/.07) Inadequate Specificity Symbol Search (.21/.23) Object Assembly (.24/.30)

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Ample Specificity Digit Span (.50/.10) Matrix Reasoning (.39/.10) Digit Symbol-Coding (.38/.16) Picture Completion (.35/.17) Letter-Number Sequencing (.34/.18) Arithmetic (.30/.12)

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Two values are listed for each subtest, first is the subtest specificity and second is the subtest s error variance. The subtests having the most ample amount of specificity include Digit Span, Matrix Reasoning, Digit Symbol-Coding, and Letter-Number Sequencing. This information on specificity indicates that all subtests have reliable and interpretable unique characteristics. However, interpretations of unique abilities should not always be made (see the steps of interpretation in 11).

Intellectual curiosity and striving Interests Outside reading Reading ability (because a word list is presented to the examinee) Richness of early environment School learning UNIQUE ABILITIES OR TRAITS MEASURED BY VOCABULARY Language development Word knowledge Empirical Analysis of Vocabulary g loadings: r = .83 (best measure) Reliability: split-half = .93, test-retest = .91 Practice effect: Trivial for ages 16 89 (gain of 0.2 scaled-score point) Subtest specificity/Error variance: 19% vs. 7% (adequate specificity) Primary Oblimin Factor Loading: Verbal Comprehension factor = .89 Most related to: Information (r = .77) Least related to: Object Assembly and Digit Symbol-Coding (r = .44) Aging Analysis of Vocabulary Mean scaled score across the adult age range (controlling for education at ages 20 89):

Age Group 16 17 18 19 20 24 25 29 30 34 35 44 45 54 55 64 Vocabulary Mean 8.6 9.2 9.5 10.0 10.5 10.7 11.4 10.8

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