By Alan S. Kaufman
The vintage textual content now up to date with a brand new interpretive method of the WAIS ;-III Assessing Adolescent and grownup Intelligence, the vintage textual content from Alan Kaufman and Elizabeth Lichtenberger, has continually supplied the main finished resource of knowledge on cognitive review of adults and teens. The newly up to date 3rd version offers very important improvements and additions that spotlight the most recent learn and interpretive equipment for the WAIS ;-III. Augmenting the normal "sequential" and "simultaneous" WAIS ;-III interpretive tools, the authors current a brand new process derived from Cattell-Horn-Carroll (CHC) thought. This strategy combines normative overview (performance relative to age friends) with ipsative review (performance relative to the person's personal suggest level). Following Flanagan and Kaufman's paintings to advance an identical CHC technique for the WISC ;-IV, Kaufman and Lichtenberger have utilized the program to the WAIS ;-III profile of ratings in addition to integrating contemporary WAIS ;-III literature. 4 appendices current the recent strategy extensive. as well as an in depth description, the authors supply a clean interpretive worksheet to aid examiners make the calculations and judgements wanted for making use of the extra steps of the recent approach, and norms tables for the hot WAIS ;-III subtest mixtures extra during this procedure. Assessing Adolescent and grownup Intelligence is still the ultimate source for the sphere, protecting not just the WAIS ;-III but additionally the WJ III ;, the KAIT, and a number of other short measures of intelligence, in addition to laying out a correct, updated dialogue of the self-discipline. the recent, theory-based interpretive procedure for the WAIS ;-III makes this an important source for practising psychologists, in addition to a complete textual content for graduate scholars.
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Extra resources for Assessing Adolescent And Adult Intelligence
65 (GMA + integrity test). Based on their review, Schmidt and Hunter concluded: (1) “of all procedures that can be used for all jobs, whether entry level or advanced, [GMA] has the highest validity and lowest application cost” (p. 264); (2) “the research evidence for the validity of GMA measures for predicting job performance is stronger than that for any other measure” (p. 264); and (3) “GMA has been shown to be the best available predictor of job-related learning” (p. 264). Jensen’s (1980) analysis of some of the same data summarized by Hunter (1986) presents a more sobering view of the ability of intelligence tests to predict job performance and training success.
When several tests are administered to a person (intelligence, language, achievement, personality, visual–motor), the results must be integrated from one test battery to the other. Intelligent testing does not apply only to the interpretation of intelligence tests. The examiner’s main role is to generate hypotheses that pertain mostly to assets and deficits within the informa- tion-processing model, and then confirm or deny these hypotheses by exploring multiple sources of evidence. This integrative, flexible, clinical–empirical methodology and philosophy, as outlined in the preceding tenets, represents the approach taken in this book for the interpretation of the WAIS-III, KAIT, WJ III, and other tests for adolescents and adults.
In general, validity evidence is provided for both verbal and nonverbal measures of intelligence. The intelligent testing philosophy, which considers the clinician’s expertise and training to be more important an aspect of the assessment process than the specific instruments administered or the scores obtained, embodies the following principles: (1) IQ tasks measure what the individual has learned; (2) IQ tasks are samples of behavior and are not exhaustive; (3) IQ tests like the WAIS-III, KAIT, and WJ III assess mental functioning under fixed experimental conditions; (4) IQ tests are optimally useful when they are interpreted from an information-processing model; and (5) hypotheses generated from IQ test profiles should be supported with data from multiple sources.