en:tests:wechsler_intelligenztest_fuer_erwachsene

Wechsler Adult Intelligence Scale - Third Edition

German language version: Wechsler Intelligenztest für Erwachsene, WIE

Just as the WIE replaced the HAWIE-R in 2006 in the German-speaking countries, the WAIS-IV has since 2012 replaced the WIE in turn. The “Wechsler Intelligenztest für Erwachsene (WIE)” described here is therefore now outdated as well. The documentation text remains only for historical reasons and for purposes of scientific comparison. We do not know whether the norms of the WIE and the German WAIS-IV differ (that is, whether examinees systematically obtain different subtest scaled scores and IQs on one procedure than on the other). There are no equivalence tables such as those available for the change from the HAWIE-R to the WIE.

The Wechsler-Intelligenztest für Erwachsene (WIE), is the German adaptation of the Wechsler Adult Intelligence Scale III (WAIS-III). The American WAIS-III was published in the USA in 1997,1) the WIE in 2006.2) David Wechsler, an American psychologist, constructed the first intelligence battery of this series in the late 1930s with the Wechsler-Bellevue Scale,3) which was intended mainly for clinical purposes. The WAIS-III and its German adaptation WIE belong to the fourth generation of the Wechsler intelligence test series.

The current test manual for the German adaptation contains only the material necessary for administration and scoring. Historical background information on the Wechsler tests can be found in the classic manual by Matarazzo4). Recent application-oriented literature on the clinical interpretation of the WAIS-III (and thus of its German counterpart) is currently available only in English.5) 6)

With their collection of 11 subtests, the predecessors HAWIE and HAWIE-R had already offered a good overview of the structure of cognitive performance, especially in cognitively impaired patients. With the WIE (WAIS-III), the composition of the subtests was changed more substantially for the first time in order to better meet the needs of neuropsychological examinations. In addition to the usual division of test performance into a verbal and a performance part, the 14 subtests of the WIE allow a division according to neuropsychological considerations, which connects the test to more modern, neuropsychologically oriented research on the structure of cognitive performance. Table 1 gives an overview of the subtests with their English names, their assignment to cognitive domains, the abbreviation customary in the English manual, the rank order of administration and the possible raw score range.

Table 1: Subtests of the WIE

Domain Subtest Abbreviation Order Raw score range
Verbal comprehension: Vocabulary VC 2 0-66
Similarities SI 4 0-33
Information IN 9 0-28
Working memory: Arithmetic AR 6 0-22
Digit Span DS 8 0-30
Letter-Number Sequencing LN 13 0-21
Perceptual organization: Picture Completion PC 1 0-25
Block Design BD 5 0-68
Matrix Reasoning MR 7 0-26
Processing speed: Digit Symbol Coding DSC 3 0-133
Symbol Search SS 12 0-60
no domain assignment: Comprehension CO 11 0-35
Object Assembly OA 14 0-52
Picture Arrangement PA 10 0-22


Only the subtests LN, MR and SS are new, but all the others have also been changed compared with the HAWIE-R, in some cases considerably.

Two of the domain names are problematic. “Verbal comprehension” is too narrow as the domain also includes the Similarities subtest, which requires the active production of a superordinate concept, something that “comprehension” covers inadequately. In TDB2Online and in the clinical report of the TDB2Online app, the term “Verbal abilities” is used, which is on the one hand more neutral and on the other more comprehensive. The second unsuitable name is “Perceptual organization” for a cognitive domain that has mainly to do with active, hands-on problem solving. In TDB2Online we make this more concrete with the term “Visual problem solving”. For the sake of completeness, it should be said that the choice of terms does not go back to the editors of the German version, but to the editors of the original English version.

For the administration of the WIE one needs the complete test kit, which in addition to the manual and an initial supply of record forms and task booklets also contains the test material for the practical subtests. These include, for example, the templates for the new Matrix Reasoning subtest or the blocks for Block Design. This test material lasts for many testing sessions, but not forever. Templates that are handled frequently have to be replaced from time to time. Only the record forms and the special task booklets for certain subtests are continuously needed as consumables.

The test material for the Wechsler tests is usually available only until a new generation of the tests appears. This is now the case. Since 2012 the successor of the WIE, the Wechsler Adult Intelligence Scale - Fourth Edition (WAIS-IV)7), has been available in German. The test material for the WIE is out of print.

Unfortunately, the manual contains many printing errors, in part also slips in the tables or numbers. To our knowledge they have never been corrected by the authors or the publisher.

The WIE is protected by copyright; the rights holder is Pearson Assessment, represented in Germany by Pearson Assessment & Information GmbH in Frankfurt/Main. Use is additionally controlled, and the material is supplied only to certain professional groups.

The copyright history of the Wechsler tests is not uninteresting. Wechsler's tests were long published by the Psychological Corporation, an organization founded in 1921 by James McKeen Cattell as a publication platform for applied psychological projects. In 1942 McKeen Cattell bequeathed most of his personal shares in the Psychological Corporation to a foundation that to this day supports applied psychological research.

The Psychological Corporation was bought by Harcourt Brace Jovanovich in 1970 and later merged with Harcourt's own test publisher. After several internal name changes, Harcourt Assessment was taken over by Reed Elsevier in 2001 and by Pearson Education in 2007, where today it belongs to Pearson's Assessment & Information Group.8)

The rights for the German versions of the Wechsler tests were held before 2011 by the publisher Huber in Bern.

All Wechsler intelligence test batteries are individually administered tests. The test material is varied and, through its diversity, helps to sustain the usually rather moderate motivation of examinees in clinical examination settings. Individual administration with only one patient also contributes to this.

The administration is described well and in detail in the test manual. With the WIE it is more difficult than with many other ability tests and has to be learned and practiced. The verbal tests, for example, are answered freely. This is good for the examinee, but it means for the examiners that the answer has to be compared with example answers in the manual and scored. One also has to know in which cases a query is required. It is not sufficient to read later that one should have queried a particular answer in order to arrive at a clear scoring. Many subtests have discontinue rules with which one must be familiar.

The administration of the complete WIE, that is, of all 13 subtests required for determining the partial IQs and the index scores (without Object Assembly), usually takes about 2 hours in psychiatric patients. To this must be added the scoring time, which depends heavily on the examiner's experience.

The 14 subtests of the WIE yield raw scores of very different origin:

  • Number of correct solutions: MR, IN, LN,
  • Number of correct solutions within a certain time: PC, DSC
  • Sum of points for the quality of a solution (0, 1 or 2 points per item): VC, SI, DS, CO
  • Sum of points for the quality of a solution (0, 1 or 2 points per item) within a certain time per item: PA
  • Complex scoring according to correctness and speed of the solution: BD, AR, OA
  • Number of correct minus number of incorrect solutions within a certain time: SS

The complex scorings according to quality and time in particular are hardly found in other tests. In theory they have the disadvantage that the raw score distributions of the subtests scored in this way are not occupied at all at some points – especially in the lower range – and jump sharply at others. In the construction of the procedures an attempt was made to compensate for this fundamental disadvantage by choosing relatively high point totals. In addition, we will see that the calculation procedures for the raw scores were chosen wisely with regard to the shape of their distribution (see below).

The raw score range varies quite strongly from subtest to subtest. In the Letter-Number Sequencing subtest it can lie between 0 and 21, in Digit Symbol Coding between 0 and 133.

Because of the different raw score ranges and because of the deviations of the raw score distributions from a normal distribution, the raw scores have been converted into so-called scaled scores by means of tables since the first generation of the Wechsler intelligence tests. In the Wechsler tests, scaled scores are standard scores with a mean of 10 and a standard deviation of 3. Nevertheless, the exact definition of the scaled scores differs between the various versions of the Wechsler tests:

  • In the Wechsler Bellevue Scale9) the scaled scores were linearly scaled as standard scores so that the overall distribution of the standardization sample had a mean of 10 and a standard deviation of 3. This definition is problematic in terms of content because the subtests exhibit very different age-related trends. A mean score of 10 defined in this way characterizes a broad age range for some subtests, particularly the verbal ones. For subtests with a sharp decline in performance with age, however, it can only truly characterize a fairly narrow age range. Another drawback is that a change in the age range of the standardization sample leads to a change in the definition of the score points. This, too, has a particularly significant effect on subtests that show a sharp decline in performance with age.
  • In the German HAWIE10), which is still based on the Wechsler-Bellevue Scale in terms of content, the score points were also scaled linearly, but in such a way that a mean of 10 and a standard deviation of 3 were achieved in the age group of young adults between 20 and 34 years of age. In doing so, the German HAWIE anticipated a methodological change in the American WAIS11), which was published almost simultaneously. The score points could now be more precisely characterized in terms of content as a performance typical of young, healthy subjects at the peak of their cognitive abilities over the course of their lives. The age range of the standardization sample no longer has any influence on this. Age-related deficits are evident on both ends of the spectrum. For example, adolescents around 16 years of age score an average of only 8 points on the vocabulary test. In contrast, 70-year-old adults score only four to six points on some subtests of the performance section. Incidentally, the limited range of scores here limits the ability to scale poor performance among older individuals.
  • Starting with the WAIS12) and continuing with the WAIS-R13) and its German version, the HAWIE-R14), raw scores were no longer scaled linearly but rather through area transformations, which ensured that the raw score scales were linearized. The age group of young adults between 20 and 34 years of age was retained as the basis.
  • In the WAIS-III15), the WIE16), the WAIS-IV17) and its German version18), this definition was unfortunately not continued. Here the scaled scores were instead defined by age group, so that a mean of 10 and a standard deviation of 3 results separately for each age group. (This variant was also already available for the WAIS-R as an alternative scoring.) In the WIE, therefore, each age group is transformed differently, and the scaled scores lose their ability to measure actual performance, including that of persons of different ages.

In TDB2Online, test results are presented in the form of age-independent performance scores. For the calculation of the performance scores for the subtests of the WAIS-III, the scaled score transformations of the age groups 20-24 and 25-29 were used. The details are explained in the next section.

For the WAIS-III there are to this day no practically usable normative data apart from those reported in the manual.

For the subtests of the WAIS-III, the conversion of raw scores into scaled scores involves a linearization by percentile-to-normal transformation and a transformation to the scaled score scale (10;3), separately for each age group. The tables in the manual give these conversion data only as whole numbers; many raw scores occupy the same scaled score. The hard steps of this conversion were first smoothed by a moving average. The order of the moving average depended on the fineness of the raw score scale. At the ends of the distribution the data were extrapolated so that the moving average could be retained. Subsequently the data were also adjusted between the age groups. According to the manual this had indeed already been done when the norms were created. In the data, however, discontinuities in the age trajectory were occasionally observed that certainly do not reflect empirical reality but are the result of the limited sample size. They were eliminated by smoothing across the age groups. Third-order smoothing was always sufficient here. Subsequently the data for the two age groups 20-24 and 25-29 were averaged. The mean was the basis for the calculation of the performance scores.

In the Comprehension subtest, the conversion tables from raw scores to scaled scores contain a maximum of 33 raw points. In fact, however, 35 raw points can be achieved in this subtest, not only 33. An error in the design of the table is probably responsible here. Since a forty-year-old with 33 raw points reaches only 15 scaled scores, one must assume that persons with higher performance also appeared in the standardization sample. In any case there is still plenty of room at the top of the scaled score scale.

For TDB2Online the table was extended upward to 35 raw points by extrapolation. This extrapolation may not correspond exactly to the empirical data, but it is certainly more correct than the situation in the manual, where performance above 33 raw points is simply ignored. In TDB2Online, therefore, all raw scores that occur can also be entered for the Comprehension subtest.

With the help of the norm tables processed in this way, the raw score distributions for individual age groups could be reconstructed. In general, the distributional properties of the raw scores are very good for most subtests, sometimes so good that a percentile-to-normal transformation would hardly have been necessary. As examples, Figures 1 to 5 below show the raw score distributions for the subtests DS, BD, CO, AR, and SI.

Figure 1: Reconstructed raw score distribution of the subtest DS for selected age groups

The raw score distribution of the subtest DS, shown in Figure 1, comes quite close to the ideal case of a raw score distribution. There are neither ceiling nor floor effects at the edges of the distribution. The young adults perform best, the adolescents between 16 and 17 years are about as high-performing as the 50-year-olds, and the older groups become successively weaker. The age effects are not very strong, however: the difference between the best and the weakest group is about 5 raw score points, with a spread of 31 (0 to 30).

Figure 2: Reconstructed raw score distribution of the subtest BD for selected age groups

The raw score distribution of the subtest BD, shown in Figure 2, also still presents a fairly symmetric picture with only slight ceiling effects. One can see that the age groups differ much more clearly in this subtest. While the 16-17-year-old adolescents are already almost as good as the young adults, the 50-year-olds are already much weaker, a tendency that continues with increasing age. The difference between the best and the weakest here is about 32 raw score points, almost half of the entire measurement range.

Figure 3: Reconstructed raw score distribution of the subtest CO for selected age groups

In the subtest CO, whose reconstructed raw score distribution can be seen in Figure 3, a clear ceiling effect appears in adults up to their 50s, which would be even more pronounced if we had not extrapolated the raw scores 34 and 35. Here the percentile-to-normal transformation can certainly bring about a normalization. In the 80-year-olds the distribution is much broader than in the young age groups. Whether this actually reflects a broader distribution of the ability among the older persons or is perhaps due only to a lack of age fairness of the items (especially the easy ones) could be clarified only by an IRT bias analysis based on the raw data.

Figure 4: Reconstructed raw score distribution of the subtest AR for selected age groups

In the subtests AR and SI (AR in Figure 4, SI in Figure 5), fairly clear ceiling effects are likewise evident, which are due to the fact that there are relatively many easy but only a few difficult items in both subtests. In principle this is not so bad for a test that is meant to differentiate more in the lower than in the upper ability range. This raw score distribution entails that precision in the upper range is not optimal, at any rate lower than in the lower range of the distribution. Given the strong age effects, it at the same time ensures that both subtests can still differentiate reasonably even at advanced age.

Figure 5: Reconstructed raw score distribution of the subtest SI for selected age groups

A linearization of the raw scores is carried out implicitly via the scaled score transformation, namely via those for the age groups 20-24 and 25-29, which are used in combination for the calculation of the performance scores.

If several subtests are summed or averaged and the result is then newly normed as a new measured value, this gives rise to a new metric that is no longer compatible with that of the subtests. This matter is explained in the general documentation in the section Multiple standardization at different levels and was made transparent using the intelligence quotients of the HAWIE-R as an example. We saw there that an examinee who reaches four scaled scores in every subtest does not obtain in the intelligence quotients the IQ of 70 that one would expect with a comparable metric (two standard deviations below the mean of his or her age group), but clearly lower values that depend on the correlation between the subtests and on the number of aggregated subtests.

In the WIE this concerns not only the three intelligence quotients but also the four indices. All seven measures were normed separately once more and therefore build up a metric of their own. We show the effect in Figure 6 using the example of a 29-year-old examinee who achieved 4 scaled scores in every subtest of the WIE.

Figure 6: WIE test profile of an examinee with 4 scaled scores in each subtest (see text)

In the TDB2Online profile, this examinee reaches a performance score (“Leistungswert”) of 70, or very close to 70, in every subtest; the small deviations from the line at 70 are due to the whole-number nature of the raw scores. Since the examinee is 29 years old, the performance scores are identical to the age-normed scores (“ASW” in the right number column). The mean performance scores in the seven domains (IQs and indices) are also all at or very close to 70, which corresponds to the aim of a uniform metric in TDB2Online.

The red circles drawn in by hand show the position of the IQ and index scores as calculated from the tables of the WIE manual. Without exception they lie below the subtest scores, with the correlation between the aggregated subtests and the number of aggregated subtests determining the extent of the metric spread. For the Processing speed index, in which only two subtests (DSC and SS) are combined, which in addition correlate only .68 (age group 24-29), the result is an index of 68, hardly lower than the two subtest scores of 70. For the Full Scale IQ, on the other hand, into which 11 subtests enter that correlate with one another on average at .54, the spread is much stronger and, with mean subtest scores of 70, yields a Full Scale IQ of only 60.

The change in the metric is not as strong in the WIE as in the HAWIE-R, because the mean intercorrelation of the subtests in the standardization sample is higher in the WIE than in the HAWIE-R.

In TDB2Online the separately standardized global measures are not taken into account any further. Instead we simply report the mean subtest performance scores or their age-normed scores, with exactly the same metric as for the subtests.

The sample for the norming of the WIE has a considerable size and a wide age range. For every age group separately there is a breakdown by educational level. These are, however, not easy to evaluate because of the different educational systems included in the norming (Switzerland, Austria, Germany, the latter with different systems in the 16 federal states), above all also when one considers the enormous span of time over which the persons in the normative sample attended school.

With regard to other details of the collection of the normative data, the manual is reticent. One learns nothing about the way the sample was drawn, nothing about the locations and nothing about agreed or fulfilled quotas (if there were any).

Adaptation and norming of the procedure were initially begun in Hannover under the responsibility of Uwe Tewes, the German editor of the predecessor version HAWIE-R19). Numerous dissertations at the Medizinische Hochschule Hannover, whose authors are mentioned in the WIE manual as collaborators in data collection20), bear witness to this. Otherwise the WIE manual contains no indication at all of Tewes's role as editor. One of these dissertations 21) shows that 99 of the 1,820 examinees tested in Germany under Tewes's responsibility came from the East German states, without any claim to representativeness. Another dissertation 22) notes that for the final publication of the WIE there were follow-up collections of individual examinees for the normative sample, by then under the responsibility of the new editors of the procedure. Presumably publishing contracts and/or agreements between the editors commissioned originally by Huber and later by Harcourt are responsible for the fact that the information on this in the manual is terse. On the other hand, it is unfortunately also a bad tradition in German test procedures that no great words are spent on sample selection.

The figures in this section summarize the performance norms and age norms of the WIE subtests as they appear in TDB2Online. Peculiarities are commented on in each case.

Figure 7 shows, in a composite graphic, the relationship between raw scores and performance scores as well as the influence of age on the (average) performance for the Vocabulary test of the WIE. In this and all following figures, the vertical lines mark the performance scores from 40 to 145. On the black horizontal line, the raw scores are plotted in their correct positions. The alternately red and blue lines contain the norm limits for all age groups at a glance. The five markers on each line stand for the percentile ranks 2.5, 16, 50, 84, and 97.5. One such line, namely the one that corresponds to the examinee's age group, is drawn (in a different form) in the TDB2Online profile sheet to help with the individual interpretation of the test results. Because the performance scores are calculated from the results of the 20-29-year-old young adults, the 5 markers of the age groups 20-24 and 25-29 always enclose the performance scores 70, 85, 100, 115, and 130.

Figure 7: Performance scores in the Vocabulary test with raw scores and age norm limits (see text)

We see in Figure 7 that the Vocabulary test of the WIE - like many of the verbal subtests, incidentally - contains relatively many easy items. Between the performance scores 55 and 70 there are 18 raw scores. At the upper end the VC measures much more coarsely: between PS 115 and 130 there are only 6 raw scores. This is partly correct and sensible. In subtests with a strong age-associated decline in performance, there must still be enough adequately differentiating items at the lower end that can measure the performance. However, the decline in performance in the verbal tests is not very strong. The mean in the 80-year-olds is only about one standard deviation below the performance of the young adults. It is noteworthy that in this subtest the 40-year-olds show the best performance, about 1/3 standard deviation better than the young adults. (This is where the comparison with the HAWIE-R belongs, discussion of whether age fairness of the items could play a role.) It is further striking that the linearization was successful in the young adults (which is tautological, because the percentile-to-normal transformation for linearization was carried out on precisely this group) and thus ensures equal spacing of the five markers, but not in the much younger or the very old. Both groups show a compression of the performance scores, above all in the lower range of the distribution, which is most likely attributable to a floor effect.

Figure 8: Performance scores in the subtest Information with raw scores and age norm limits (explanation of the figure in the text for Figure 7)

In the subtest Information (Figure 8), the situation is similar to the Vocabulary test in many respects. Here, too, the 40-year-olds are best and the 80-year-olds lie just under one standard deviation below the young adults. A certain compression of the scale at the lower end (floor effect) can likewise be noted, although distinctly smaller and only in the very old. On the other hand, there also seems to be a certain ceiling effect: the maximum raw score of 28 leads to a performance score of 134. In other subtests the maximum lies distinctly above this. The ceiling effect, however, is noticeable only in very good examinees in middle age.

Figure 9: Performance scores in the subtest Similarities with raw scores and age norm limits (explanation of the figure in the text for Figure 7)

In the subtest Similarities (Figure 9), what is seen above all is the clear ceiling effect, which was already addressed when the back-calculated distribution in Figure 5 was presented. The maximum raw score of 33 corresponds to a performance score of only 130. It is particularly noticeable in the 30-40-year-olds. At the lower end, by contrast, the graduation of item difficulty is good. The age-associated decline in performance is somewhat stronger than in the subtest Information.

Figure 10: Performance scores in the subtest Comprehension with raw scores and age norm limits (explanation of the figure in the text for Figure 7)

In the subtest Comprehension (Figure 10), too, the performance maximum is reached only in the age group 35-44, and even the 50-year-olds are still better than the young adults. It is quite possible that the test tasks here lack age fairness. (Can that also be the case for AR??)

Otherwise the skewed raw score distribution is conspicuous, which could also be seen in Figure 3. In the upper ability range the measurement is coarse, in the lower very fine. However, this could be linearized very well by the percentile-to-normal transformation, as the relatively equal spacing of the five age norm limits shows.

Figure 11: Performance scores in the subtest Arithmetic with raw scores and age norm limits (explanation of the figure in the text for Figure 7)

In the subtest Arithmetic (Figure 11), clear ceiling effects can be recognized, which mainly affect adults between 20 and 50. In the very old, a floor effect can also be noted.

In Arithmetic, the age-related decline in performance in the 85-89-year-olds already amounts to about 1 1/2 standard deviations.

Figure 12: Performance scores in the subtest Digit Span with raw scores and age norm limits (explanation of the figure in the text for Figure 7)

The subtest Digit Span (Figure 12) is among the most variance-stable subtests of the WIE. This had already been noticed in the presentation of the raw score distributions, in which there were hardly any differences between different age groups.

Figure 13: Performance scores in the subtest Letter-Number Sequencing with raw scores and age norm limits (explanation of the figure in the text for Figure 7)

The subtest Letter-Number Sequencing (Figure 13) shows a strong age-associated decline in performance, which amounts to just under two standard deviations from young adulthood to senescence. The variance increases with age.

Figure 14: Performance scores in the subtest Picture Completion with raw scores and age norm limits (explanation of the figure in the text for Figure 7)

Picture Completion, too, has many easy and few difficult items. The differentiation capacity in the lower test range is very good, also across all age levels. In the upper ability range, by contrast, the measurement is far too coarse. Only four raw score points decide whether the performance is average (raw score 21, PS 100) or in a very high ability range (raw score 25, PS 124). This performance score of 124 is moreover already the end of the measurement range.

The age-associated decline in performance is immense, over two standard deviations. Whether a lack of age fairness of the test tasks contributes to this would have to be investigated using the data material of the normative sample. After all, David Wechsler formerly counted the subtest Picture Completion among the “hold” tests, that is, the subtests that show no large decline in performance with age. (What was it like in the HAWIE-R?)

Figure 15: Performance scores in the subtest Block Design with raw scores and age norm limits (explanation of the figure in the text for Figure 7)

In Block Design, the performance optimum lies in the 25-29-year-olds. It is hard to believe that the decline in performance from 30 to about 60 should be steeper than from 60 to 90, which would be the case according to the data. Scaling effects in the scoring of the tasks or simply floor effects could play a role here.

Figure 16: Performance scores in the subtest Matrix Reasoning with raw scores and age norm limits (explanation of the figure in the text for Figure 7)

For Matrix Reasoning, what was already said about Block Design applies, although the matter is clearer here: if the mean of all persons over 70 lies at 6 raw score points or fewer, the test can no longer differentiate at the lower end and is too difficult for this age group. The differentiation capacity is also limited at the upper end: the maximum raw score of 26 corresponds to a performance score of only 126. In terms of measurement this is not so bad at all. Raven's Standard Matrices cover a somewhat wider measurement range (from PS 57 to 131 with the meta-analytic norms in TDB2Online), but need 60 instead of 26 items for this. In return, however, they also measure somewhat more precisely and finely.

Figure 17: Performance scores in the subtest Picture Arrangement with raw scores and age norm limits (explanation of the figure in the text for Figure 7)

The measurement range of the subtest Picture Arrangement is very wide. At the lower end there are no signs of a floor effect, although this subtest shows an age-associated loss of performance of about 2 standard deviations.

Figure 18: Performance scores in the subtest Digit Symbol Coding with raw scores and age norm limits (explanation of the figure in the text for Figure 7)

Digit Symbol Coding has always been the subtest with the strongest age-associated decline in performance (about 2 1/2 standard deviations into the 80s in the usual cross-sectional data). This remains so in the WIE. Owing to the extension of the test time to 120 seconds, the measurement range of the DSC is now very large, from PS 40 to 145, more than in any other subtest of the WIE.

Figure 19: Performance scores in the subtest Symbol Search with raw scores and age norm limits (explanation of the figure in the text for Figure 7)

The subtest Symbol Search also has a wide measurement range. Peculiar is the conspicuous deterioration in the age range 30 to 60, similar to Picture Arrangement, with smaller differences in the upper age range.

Figure 20: Performance scores in the subtest Object Assembly with raw scores and age norm limits (explanation of the figure in the text for Figure 7)

The subtest Object Assembly never counted among the better subtests. In the WIE, the (theoretical) measurement precision was at least somewhat improved compared with the HAWIE-R by adding two new tasks and omitting the task “Hand”. The age decline is similar to that in PA or SS.

The figures in this section summarize the performance norms and age norms of the mean global measures of the WIE, which are produced in TDB2Online in place of the indices and IQs. Here, too, only peculiarities are commented on.

Figure 21: Mean performance scores in the subtests combined into the index Verbal Comprehension, with raw scores and age norm limits (explanation of the figure in the text for Figure 7)

In verbal abilities, the highest performance in the WIE is achieved by the age groups between about 30 and 50. The two age groups that define the performance scores (20-24 and 25-29) lie about a quarter of a standard deviation below. This was not the case in the HAWIE-R. It probably has to do with the nature of the normative samples. Since both are poorly documented, this statement does not help much further. (Take up again when the HAWIE-R documentation is finished.)

Figure 22: Mean performance scores in the subtests combined into the index Working Memory, with raw scores and age norm limits (explanation of the figure in the text for Figure 7)

Working memory turns out best in the age groups around 30. That is plausible.

Figure 23: Mean performance scores in the subtests combined into the Verbal IQ, with raw scores and age norm limits (explanation of the figure in the text for Figure 7)

In the WIE, the verbal part is determined to four parts by verbal subtests (Comprehension can safely be counted among them) and to two parts by working memory tests. Whenever the two components deviate noticeably from each other, determining the global score makes no sense.

Figure 24: Mean performance scores in the subtests combined into the index Perceptual Organization, with raw scores and age norm limits (explanation of the figure in the text for Figure 7)

The measurement ranges of the three subtests belonging to visual problem solving are all somewhat limited at the top, which means that the maximum mean performance score in this domain is 128. One should keep this in mind for very gifted persons.

The three subtests intercorrelate differently: Block Design and Matrix Reasoning, at .56, correlate more highly than either of them with Picture Completion (.48 and .47). Occasionally it can certainly be sensible to consider only the two “true” abstract problem-solving tests together. Picture Completion rather measures other, everyday practical abilities.

Figure 25: Mean performance scores in the subtests combined into the index Processing Speed, with raw scores and age norm limits (explanation of the figure in the text for Figure 7)

Here the measurement range is very wide, the definition clear. There is nothing further to comment on.

Figure 26: Mean performance scores in the subtests combined into the Performance IQ, with raw scores and age norm limits (explanation of the figure in the text for Figure 7)

What was already said about the verbal part applies here: if the individual components yield different values, considering the sum makes no sense.

Figure 27: Mean performance scores in the subtests combined into the Full Scale IQ, with raw scores and age norm limits (explanation of the figure in the text for Figure 7)

In clinical questions it will rarely make sense to interpret a global score over 11 subtests. It is actually interpretable only for relatively homogeneous profiles, because it then simply reflects the central tendency of the cognitive abilities.


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5)
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