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Our Response: We recommend that you take from our system what is helpful, and modify it with what you find most clinically beneficial. To new examiners, the interpretive process can be confusing at times (as your students have expressed to you). In our Steps, we attempted to simplify the process as much as possible, but there are some aspects that must remain complex. Following the cookbook approach is a good start to interpretation, but students/clinicians must also integrate their conceptual and theoretical understanding of the instrument to create an in-depth understanding of the peaks and valleys in a profile. When we are instructing students who are newly learning the WAIS-III and how to interpret it, we suggest that they go through each of the interpretive Steps one-by-one, rather than skipping any. Completing these Steps in a linear fashion initially will help to develop a more in-depth understanding of how the instrument functions, and how to best describe the results to clients. As students become more familiar with the interpretation of the instrument, then they may find it more useful to skip steps as suggested in our Decision Boxes.

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Figure S11-4 is a scatter diagram with the transformed variable x 1 x. This plot appears linear, indicating that the reciprocal transformation is appropriate. The tted regression model is

the first six Steps, it is useful to conceptualize the structure of the WAIS-III as a hierarchy in which the bottom tiers impact the tiers above (see Figure 11.5 for a pictorial description of the tiers of the WAIS-III). For example, moving through the first six steps, you may find that variability in the lowest level of the WAIS-III tiered structure (the subtests) has rippling effects all the way to the interpretability of the Full Scale IQ (top tier). Figure 11.6 depicts how variability at the lowest TABLE 11.11

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level can impact the interpretability or meaningfulness of the levels above. Figure 11.6 shows an abnormal amount of variability among the Perceptual Organization subtests, which means that the POI is not a meaningful construct to interpret. Therefore neither the POI versus PSI comparison nor POI VCI comparison can be meaningfully interpreted. This POI subtest scatter also impacts the interpretation of the P-IQ and, ultimately, the Full Scale IQ.

2 The summary statistics for this model are R2 0.9800, MSE 0.0089, and F0 1128.43 (the P value is 0.0001). A plot of the residuals from the transformed model versus y is shown in Figure S11-5. This plot does not reveal any serious problem with inequality of variance. The normal probability plot, shown in Figure S11-6, gives a mild indication that the errors come from a distribution with heavier tails than the normal (notice the slight upward and downward curve at the extremes). This normal probability plot has the z-score value plotted on the horizontal axis. Since there is no strong signal of model inadequacy, we conclude that the transformed model is satisfactory.

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Logistic Regression Linear regression often works very well when the response variable is quantitative. We now consider the situation where the response variable takes on only two possible values, 0 and 1. These could be arbitrary assignments resulting from observing a qualitative response. For

Range of subtest scaled scores considered abnormal in WMI and PSI Calculation of Range High scaled score minus low scaled score of 3 Working Memory Index Subtests High Scaled Score minus low scaled score of 2 Processing Speed Index subtests Abnormal Scatter 6 or more 4 or more Not Abnormal 0 5 0 3

L. Giuri: Role-Based Access Control on the Web using Java, in Proceedings of RBAC 99, pp. 11 18, ACM 1999 E. Gamma, R. Helm, R. Johnson, J. Vlissides: Design Patterns Elements of Reusable Object-Oriented Software, Addison-Wesley Professional, 1995 D. Gollmann: Computer Security, John Wiley & Sons, 1999 Google Security Directory

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(OA can substitute for a Performance subtest for ages 16 74)

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Figure S11-5 Plot of residuals versus tted values yi for the transformed model for the windmill data.

Although examination of Steps 1 through 6 is crucial in determining what scores to interpret, this process is different from actually interpreting them. Step 7 leads examiners to explore a variety of interpretive hypotheses derived from diverse theoretical, clinical, and research-based interpretations. The next few pages outline some of the possible interpretations of these global dimensions (also see s 8 and 9 for information on global profiles in unique populations). We organize Step 7 into the following areas: (1) general interpretation of WAIS-III Indexes, and (2) Horn and Bannatyne formulations to interpret global verbal, global nonverbal, working memory, and processing speed dimensions.

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Figure S11-6 Normal probability plot of the residuals for the transformed model for the windmill data.

The VCI, comprised of Vocabulary, Similarities, and Information, measures verbal reasoning and verbal acquired knowledge. Through answering questions, defining words, and determining how

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