Interpretation of Wechsler Arithmetic subtest-"Intelligent" intelligence testing

This article is a good reminder that "intelligent" intelligence testing requires "knowing thy subtests."

The authors conclude "In summary, while Arithmetic may be considered a measure of concentration or working memory, it should be kept in mind that many other factors influence it and that its specificity as a concentration measure is limited."







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WAIS-IV Canadian/US norm controversy--all articles for readers to review

I previously provided an FYI post on a hot topic in Canada...claims that the new WAIS-IV Canadian norms were flawed.  There are now three articles outlining the different arguments.  The three articles, published in JPA, can be found here, here, and here.

I continue to not comment on this controversy given my obvious conflict of interest as a coauthor of the competing WJ-IV.

Kevin McGrew

Canadian-US IQ "difference/IQ test methdology flaw" reports -- wait a minute.

Recently and article was published in the Journal of Psychoeducational Assessment that raised concerns about the accuracy of the Canadian norms for the Wechsler Adult Intelligence Scale--Fourth Edition (WAIS-IV).  Social media picked up on the story with various attention-getting headlines such as "Common IQ methodology may be flawed" and "Flawed IQ scoring system: Important difference in American, Canadian scoring systems".  The article citation and abstract are below:

• Harrison, A. G., Holmes, A., Silvestri, R., & Armstrong, I. T. (2015). Implications for Educational Classification and Psychological Diagnoses Using the Wechsler Adult Intelligence Scale–Fourth Edition With Canadian Versus American Norms. Journal of Psychoeducational Assessment, 0734282915573723.

Abstract:  Building on a recent work of Harrison, Armstrong, Harrison, Iverson and Lange which suggested that Wechsler Adult Intelligence Scale–Fourth Edition (WAIS-IV) scores might systematically overestimate the severity of intellectual impairments if Canadian norms are used, the present study examined differences between Canadian and American derived WAIS-IV scores from 861 postsecondary students attending school across the province of Ontario, Canada. This broader data set confirmed a trend whereby individuals’ raw scores systematically produced lower standardized scores through the use of Canadian as opposed to American norms. The differences do not appear to be due to cultural, educational, or population differences, as participants acted as their own controls. The ramifications of utilizing the different norms were examined with regard to psychoeducational assessments and educational placement decisions particularly with respect to the diagnoses of Learning Disability and Intellectual Disability.

I have not studied the Harrison et al. study in depth, but would like to share, with his permission, portions of an email  shared with me by Dr. Larry Weiss, Vice President, Global Research & Development, Pearson Clinical and Talent Assessment (the publisher of the WAIS-IV).  Dr. Weiss and I briefly talked about this controversial paper at the recent NASP conference.

 Dr. Larry Weiss comments ( email 3-18-15 - shared with permission)

"To follow up on our discussion about the Harrison el al. paper, they found that a large percent of Canadian college students obtained scores below the average range on the WAIS-IV FSIQ when using the Canadian norms.  They considered this finding to be highly unexpected for a sample of college students, and questioned the validity of the WAIS-IV Canadian norms.  However, the authors of that study did not adequately take into account that 75% of their sample had clinical diagnoses.   

To demonstrate the impact of clinical status on IQ test scores, my research team drew a sample of American subjects matched to the Harrison sample on clinical status and educational level.  We then scored the American sample on U.S. norms, and found that the percentage obtaining below average FSIQ scores was almost identical to that reported by Harrison et. al. using Canadian norms.  This demonstrates that the Harrison et al. findings are not unique to the Canadian norms, but are due to the mixed clinical status of their sample.  Details of our matched sample analysis will appear in an upcoming issue of the Journal of Psychoeducational Assessment in an article by Miller, Weiss, Beal, Saklofske, Zhu, & Holdnack."

Although I will not comment on the specific WAIS-IV study and methodology in question, I can point out that in a special ASB (ASB #12 Use of the Woodcock-Johnson III NU Tests of Cognitive Abilities and Tests of Achievement with Canadian Populations) where I and others reported the performance of a sample of Canadians on the WJ III NU battery, when the Canadian subjects (who were a randomly selected representative sample--not a largely clinically preselected sample), where matched on critical demographic variables to a sample of US subjects, we found that "while some minor score differences are reported across the two samples, the study findings generally support the use of the U.S.-based WJ III NU norms with Canadian school-age populations."  In other words, when comparable (demographically matched) Canadian and US subjects were compared on the WJ III NU cognitive battery, no significant Canadian-US IQ scores, beyond some minor exceptions, were found.

Readers should wait until the Miller et al. (in press) response paper is released before jumping to any quick conclusions.

[Conflict of interest disclosure:  I am a coauthor of the WJ III and WJ IV, a direct competitor to the Wechsler batteries]

Sharing An Examination of the Wechsler Adult Intelligence Scales, Fourth Edition (WAIS-IV) in Individuals with Complicated Mild, Moderate and Severe Traumatic Brain Injury (TBI) via BrowZine

An Examination of the Wechsler Adult Intelligence Scales, Fourth Edition (WAIS-IV) in Individuals with Complicated Mild, Moderate and Severe Traumatic Brain Injury (TBI)
Carlozzi, Noelle E.; Kirsch, Ned L.; Kisala, Pamela A.; Tulsky, David S.
The Clinical Neuropsychologist, Vol. 29 Issue 1 – 2015: 21 - 37

10.1080/13854046.2015.1005677

University of Minnesota Users:
http://login.ezproxy.lib.umn.edu/login?url=http://www.tandfonline.com/doi/abs/10.1080/13854046.2015.1005677

Non-University of Minnesota Users: (Full text may not be available)
http://www.tandfonline.com/doi/abs/10.1080/13854046.2015.1005677

Accessed with BrowZine, supported by University of Minnesota.


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WJ IV update: WJ IV g-scores (GIA,BIA,Gf-Gc composite) correlations with WISC-IV/WAIS-IV FS and GAI IQ scores

In the WJ IV technical manual (McGrew, LaForte, Schrank, 2014) concurrent validity results are presented for the WJ IV COG with the WISC-IV and WAIS-IV (click here for WJ IV COG overview and select correlation information from tech. manual).

A number of psychologists have asked about correlations between the primary WJ IV COG g-scores and the Wechsler General Ability Index (GAI).  They are not presented in the technical manual.  I have now computed those correlations, as well as a few others with the Wechsler GAI, and they are now part of the SlideShare at the link above and are also reported below.  Click on image to enlarge.

Is the WAIS-IV factor structure the same in samples of people with ID/MR? This article says "yes"

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Errror in Dr. James Flynn's (2009) WAIS-IV norming data: Quest blog post by Dr. Dale Watson

This is a guest blog post by Dr. Dale Watson.  The opinions expressed do not necessarily reflect the official position of the ICDP blog or the blogmaster.  However, it is of interest to note that the error Dr. James Flynn (2009) made in reporting the WAIS-IV norming date (here reported by Dr. Dale Watson) is true, and was also in a published review that I received a few days after I received Dr. Watson's guest post.  This second verification source (Kaufman, Dillon, & Kirsch, 2013) will be the subject of my next post.

Dr. Dale Watson's guest post 

In an article entitled, The WAIS-III and WAIS-IV: Daubert motions favor the certainly false over the approximately true, Dr. James Flynn analyzed data from a number of IQ tests, including the WAIS-R, WAIS-III, and WAIS-IV to estimate the rate of the “Flynn Effect” on the Wechsler scales in the U.S. over time.[i] He concluded, as have others, that in order to account for the obsolescence of aging IQ test norms, a “Flynn Effect” adjustment of 0.30 points per year from the date of a tests norming should be applied to the obtained IQ test scores (Flynn, 2009; Fletcher et al., 2010). For example, if the WAIS-III (normed in 1995) was administered to an individual in 2005, the obtained IQ should be downwardly adjusted by 0.30 x 10 or 3.0 points. Thus, an obtained IQ score of 72 would result in a Flynn-adjusted score of 69. Such adjustments have been recommended for use in Atkins evaluations (Flynn, 2009; Gresham & Reschly, 2011; cf Hagen et al., 2010).[ii]

Flynn compared the IQ scores obtained on the WAIS-III and the WAIS-IV in a sample of 240 examinees reported in the Technical and Interpretive Manual for the WAIS-IV (2008).[iii] The Technical Manual reported that the mean IQs differed by 2.9 points with the sample mean for the WAIS-IV being 100 and for the WAIS-III 102.9 (Wechsler, 2008, p. 75). However, because these IQ scores were calculated using different combinations of subtests, Flynn re-calculated the IQ scores utilizing the same combination of 11 subtest scores used on the WAIS-III to calculate the IQs. Flynn (2009) noted, “The list of subtests used to compute Full Scale IQ had not only changed, but had dropped from 11 to 10. But, once again, they gave the comparison group all 11 of the old WAIS-III subtests, and once again that was fortunate because it meant that the true obsolescence of the WAIS-III could be measured. I calculated the total standard score the group got on the same 11 WAIS-III and WAIS-IV subtests. Using the totals and the WAIS-III conversion table, I calculated Full Scale IQs for the two tests” (p. 102). 

In examining Flynn’s Table 2, it appears that these calculations included scores for the Picture Arrangement subtest for both the WAIS-III and WAIS-IV. However, the Picture Arrangement subtest is not included in the WAIS-IV so it is quite unclear how this calculation was performed. Moreover, there is a footnote to this table indicating that the “WAIS-IV estimate is eccentric in carrying over WISC-III subtests (and scoring vs. the WAIS-III tables)…” but the meaning of this statement is also uncertain. In addition, substitution of the Symbol Search subtest for Picture Arrangement appears to yield very similar results.

In any case, the point of this note is not to recalculate Flynn’s estimates but rather to point out what appears to be a discrepancy between WAIS-IV norming date provided by Flynn and that found in the Technical and Interpretive Manual for the WAIS-IV. Flynn indicated that the WAIS-IV was normed in 2006 (Table 1) whereas the Manual reported, “The WAIS-IV normative data was established using a sample collected from March 2007 to April 2008.” [iv] If we use 2007 as the mid-point norming date, the time between the norming of the WAIS-III and WAIS-IV is 12 years and not 11 as provided by Flynn. Using the Flynn 2006 date resulted in a calculated Flynn Effect between the WAIS-III and WAIS-IV of 0.306 points per year (+3.37 / 11 years). Using the norming date provided in the manual resulted in a calculated score of 0.281 points per year (+3.37 / 12 years). It is understood that this discrepancy of just 0.025 points is of little practical significance but it should be noted nonetheless. Moreover, the metaphorical splitting of hairs is not uncommon when discussing the Flynn Effect. Hagan et al. (2010) asserted, “Decades of FE research and testimony… depict the amount of this shift as a moving target. For example, Flynn (1998) once identified the annual shift as 0.25 rather than 0.30, but later testified in Ex Parte Eric Dewayne Cathey (2010) that 0.29 would be appropriate. Schalock et al. (2010) have called for an annual adjustment of 0.33” pp. 1-2.[v] Flynn has acknowledged that the results reported in his report are estimates for the Wechsler scales, writing, “It is quite possible that the rate of gain on Wechsler tests is 0.275 or 0.325 points per year” (Flynn, 2009, p. 104). The recalculation noted here is consistent with this judgment. Further, the weight of the available evidence, including that of a recent meta-analysis, continues to support the Flynn Effect adjustment of 0.3 points per year.[vi]

---

[i] Flynn, J. R. (2009). The WAIS-III and WAIS-IV: Daubert motions favor the certainly false over the approximately true. Applied Neuropsychology, 16(2), 98-104. doi: 10.1080/09084280902864360

[ii] Gresham, F. M., & Reschly, D. J. (2011). Standard of practice and Flynn Effect testimony in death penalty cases. Intellectual and Developmental Disabilities, 49(3), 131-140. doi: 10.1352/1934-9556-49.3.131

[iii] Wechsler, D. (2008). Wechsler Adult Intelligence Scale: Technical and interpretive manual (4^th ed.). San Antonio, TX: Pearson.

[iv] Id., p. 22.

[v] Hagan, L. D., Drogin, E. Y., & Guilmette, T. J. (2010). IQ scores should not be adjusted for the Flynn Effect in capital punishment cases. Journal of Psychoeducational Assessment, 28(5), 474-476. doi: 10.1177/0734282910373343

[vi] Fletcher, J. M., Stuebing, K. K., & Hughes, L. C. (2010). IQ scores should be corrected for the Flynn Effect in high-stakes decisions. Journal of Psychoeducational Assessment, 28(5), 469-473. doi: 10.1177/0734282910373341

Video tutorial: Estimating latent WISC-IV and WAIS-IV scores for individuals--Dr. Joel Schneider

Dr. Joel Schneider has done it again.  A brilliant video tutorial demonstrating how latent factor scores can be used, via Excel templates he provides, to interpret scores on the WISC-IV and WAIS-IV.  This is complex material but his beautiful visual video tutorial makes it easier to understand the complex constructs.  Dr. Schneider continues to push the envelope on psychometric based IQ test score interpretation.

Research Byte: Structural and incremental validity of WAIS-IV

 

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Research Byte: Which is better measure of intelligence? WAIS-III or WAIS-IV

A new article comparing the changes from the WAIS-III to the WAIS-IV with implications for Atkins cases by Taub and Benson. Below is the abstract. Dr. Taub can be contacted via this link.

A previous IAP AP101 report dealing with WAIS-III/WAIS-IV structural changes is worth reading when reviewing this current article.

 

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Research byte: WAIS-IV Visual Puzzles study

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Research bytes: WAIS-IV practice effect study

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Research bytes: Two new Wechsler embedded malingering index studies

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IAP101 Brief #12: Use of IQ component part scores as indicators of general intelligence in SLD and MR/ID diagnosis

   
            Historically the concept of general intelligence (g), as operationalized by intelligence test battery global “full scale” IQ scores, has been central to the definition and classification of individuals with a specific learning disability (SLD) as well as individuals with an intellectual disability (ID).  More recently, contemporary definitions and operational criteria have elevated intelligence test battery composite or part scores to a more prominent role in diagnosis and classification of SLD and more recently in ID.

            In the case of SLD, third-method “consistency” definitions prominently feature component or part scores in (a) the identification of consistency between low achievement and relevant cognitive abilities or processing disorders and (b) the requirement that an individual demonstrate relative cognitive and achievement strengths (see Flanagan, Fiorello & Ortiz, 2010).  The global IQ score is de-emphasized in the third-method SLD methods.

            In contrast, the 11^th edition of the AAIDD Intellectual Disability: Definition, Classification, and Systems of Supports manual (AAIDD, 2010) placed general intelligence, and thus global composite IQ scores, as central to the definition of intellectual functioning.  This has not been without challenge.  For example, the AAIDD ID definition has been criticized for an over-reliance on the construct of general intelligence and for ignoring contemporary psychometric theoretical and empirical research that has converged on a multidimensional hierarchical model of intelligence (viz., Cattell-Horn-Carroll or CHC theory).

The potential constraints of the “ID-as-a-general-intelligence-disability” definition was anticipated by the Committee on Disability Determination for Mental Retardation, in its National Research Council report “Mental Retardation:  Determining Eligibility for Social Security Benefits” (Reschly, Meyers & Hartel, 2001).  This national committee of experts concluded that “during the next decade, even greater alignment of intelligence tests and the IQ scores derived from them and the Horn-Cattell and Carroll models is likely.  As a result, the future will almost certainly see greater reliance on part scores, such as IQ scores for Gc and Gf, in addition to the traditional composite IQ.  That is, the traditional composite IQ may not be dropped, but greater emphasis will be placed on part scores than has been the case in the past” (Reschly et al., 2002, p. 94).  The committee stated that “whenever the validity of one or more part scores (subtests, scales) is questioned, examiners must also question whether the test’s total score is appropriate for guiding diagnostic decision making.  The total test score is usually considered the best estimate of a client’s overall intellectual functioning.  However, there are instances in which, and individuals for whom, the total test score may not be the best representation of overall cognitive functioning.” (p. 106-107).

            The increased emphasis on intelligence test battery composite part scores in SLD and ID diagnosis and classification raises a number of measurement and conceptual issues (Reschly et al., 2002).  For example, what are statistically significant differences?  What is a meaningful difference?  What appropriate cognitive abilities should serve as proxies of general intelligence when the global IQ is questioned?  What should be the magnitude of the total test score? 

Appropriate cognitive abilities will only be the only issue discussed here.  This issue addresses  which component or part scores are more correlated with general intelligence (g)—that is, what component part scores are high g-loaders?  The traditional consensus has been that measures of Gc (crystallized intelligence; comprehension-knowledge) and Gf (fluid intelligence or reasoning) are the highest g-loading measures and constructs and are the most likely candidates for elevated status when diagnosing ID (Reschly et al., 2002).  Although not always stated explicitly, the third method consistency SLD definitions specify that an individual must demonstrate “at least an average level of general cognitive ability or intelligence” (Flanagan et al., 2010, p.745), a statement that implicitly suggests cognitive abilities and component scores with high g-ness.

Table 1 is intended to provide guidance when using component part scores in the diagnosis and classification of SLD and ID (click on images to enlarge and use the browser zoom feature  to view; it is recommended you click here to access a PDF copy of the table..and also zoom in on it).  Table 1 presents a summary of the comprehensive, nationally normed, individually administered intelligence batteries that possess satisfactory psychometric characteristics (i.e., national norm samples, adequate reliability and validity for the composite g-score) for use in the diagnosis of ID and SLD.

The “Composite g-score” column lists the global general intelligence score provided by each intelligence battery.  This score is the best estimate of a person’s general intellectual ability, which currently is most relevant to the diagnosis of ID as per AAIDD.  All composite g-scores listed in Table 1 meet Jensen’s (1998) psychometric sampling error criteria as valid estimates of general intelligence.  As per Jensen’s number of tests criterion, all intelligence batteries g-composites are based on a minimum of nine tests that sample at least three primary cognitive ability domains.  As per Jensen’s variety of tests criterion (i.e., information content, skills and demands for a variety of mental operations), the batteries, when viewed from the perspective of CHC theory, vary in ability domain coverage—four (CAS, SB5), five (KABC-II, WISC-IV, WAIS-IV), six (DAS-II) and seven (WJ III) (Flanagan, Ortiz & Alfonso, 2007; Keith & Reynolds, 2010).   As recommended by Jensen (1998), “the particular collection of tests used to estimate g should come as close as possible, with some limited number of tests, to being a representative sample of all types of mental tests, and the various kinds of test should be represented as equally as possible” (p. 85).  Users should consult sources such as Flanagan et al. (2007) and Keith and Reynolds, 2010) to determine how each intelligence battery approximates Jensen’s optimal design criterion, the specific CHC domains measured, and the proportional representation of the CHC domains in each batteries composite g-score.

Also included in Table 1 are the component part scales provided by each battery (e.g., WAIS-IV Verbal Comprehension Index, Perceptual Reasoning Index, Working Memory Index, and Processing Speed Index), followed by their respective within-battery g-loadings.[1]  Examination of the g-ness of composite scores from existing batteries (see last three columns in Table 1) suggests the traditional assumption that measures of Gf and Gc are the best proxies of general intelligence may not hold across all intelligence batteries.[2] 

In the case of the SB5, all five composite part scores are very similar in g-loadings (h² = .72 to .79).  No single SB5 composite part score appears better than the other SB5 scores for suggesting average general intelligence (when the global IQ score is not used for this purpose).  At the other extreme is the WJ III where the Fluid Reasoning, Comprehension-Knowledge, Long-term Storage and Retrieval cluster scores are the best g-proxies for part-score based interpretation within the WJ III.  The WJ III Visual Processing and Processing Speed clusters are not composite part scores that should be emphasized as indicators of general intelligence.  Across all batteries that include a processing speed component part score (DAS-II, WAIS-IV, WISC-IV, WJ III) the respective processing speed scale is always the weakest proxy for general intelligence and thus, would not be viewed as a good estimate of general intelligence. 

            It is also clear that one cannot assume that composites with similar sounding names of measured abilities should have similar relative g-ness status within different batteries.  For example, the Gv (visual-spatial or visual processing) clusters in the DAS-II (Spatial Ability), SB5 (Visual-Spatial Processing) are relatively strong g-measures within their respective battery, but the same cannot be said for the WJ III Visual Processing cluster.  Even more interesting are the differences in the WAIS-IV and WISC-IV relative g-loadings for similarly sounding index scores. 

For example, the Working Memory Index is the highest g-loading component part score (tied with Perceptual Reasoning Index) in the WAIS-IV but is only third (out of four) in the WISC-IV.   The Working Memory Index is comprised of the Digit Span and Arithmetic subtests in the WAIS-IV and the Digit Span and the Letter-Number Sequencing subtests in the WISC-IV.  The Arithmetic subtest has been reported to be a factorially complex test which may tap fluid intelligence (Gf-RQ—quantitative reasoning), quantitative knowledge (Gq), working memory (Gsm), and possible processing speed (Gs; Keith & Reynolds, 2010; Phelps, McGrew, Knopik & Ford, 2005).   The factorially complex characteristics of the Arithmetic subtest (which, in essence, makes it function like a mini-g proxy) would explain why the WAIS-IV Working Memory Index is a good proxy for g in the WAIS-IV but not in the WISC-IV. The WAIS-IV and WISC-IV Working Memory Index scales, although named the same, are not measuring identical constructs.

A critical caveat is that the g-loadings cannot be compared across different batteries.  g-loadings may change when the mixture of measures included in the analyses change.  Different "flavors" of g can result (Carroll, 1993; Jensen, 1998). The only way to compare the g-ness across batteries is with appropriately designed cross- or joint-battery analysis (e.g., WAIS-IV, SB5 and WJ III analyzed in a common sample).

The above within and across intelligence battery examples illustrates that those who use component part scores as an estimate of a person’s general intelligence must be aware of the composition and psychometric g-ness of the component scores within each intelligence battery.  Not all component part scores in different intelligence batteries are created equal (with regard to g-ness).  Also, not all similarly named factor-based composite scores may measure the same identical construct and may vary in degree of within battery g-ness.  This is not a new problem in the context of naming factors in factor analysis, and by extension, factor-based intelligence test composite scores, Cliff (1983) described this nominalistic fallacy in simple language—“if we name something, this does not mean we understand it” (p. 120). 

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[1] As noted in the footnotes in Table 1, all composite score g-loadings were computed by Kevin McGrew by entering the smallest number (and largest age ranges covered) of the published correlation matrices within each intelligence batteries technical manual (note the exception for the WJ III) in order to obtain an average g-loading estimate.  It would have been possible to calculate and report these values for each age-differentiated correlation matrix for each intelligence battery.  However, the purpose of this table is to provide the best possible average value across the entire age-range of each intelligence battery.  Floyd and colleagues have published age-differentiated g-loadings for the DAS-II and WJ III.  Those values were not used as they are based on the use of the principal common factor analysis method, a method that  analyzes the reliable shared variance among tests.  Although principal factor and principal component loadings typically will order measures in the same relative position, the principal factor loadings typically will be lower.  Given that the imperfect manifest composite scale scores are those that are utilized in practice, and to also allow uniformity in the calculation of the g-loadings reported in Table 1, principal component analysis was used in this work. The same rationale was used for not using the latent factor loadings on a higher-order g-factor in SEM/CFA analysis of each test battery.  Loadings from CFA analyses represent the relations between the underlying theoretical ability constructs and g purged of measurement error.  Also, frequently the final CFA solutions reported in a batteries technical manual (or independent journal articles) allow tests to be factorially complex (load on more than one latent factor), a measurement model that does not resemble the real world reality of the manifest/observed composite scores used in practice.  Latent factor loadings on a higher-order g-factor will often differ significantly from principal component loadings based on the manifest measures, both in absolute magnitude and relative size (e.g., see high Ga loading on g in WJ III technical manual which is at variance with the manifest variable based Ga loading reported in Table 1) 

[2] The h² values are the values that should be used to compare the relative amount of g-variance present in the component part scores within each intelligence battery.

Canadian WAIS-IV: New cognitive proficiency index scores now available

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New Cognitive Processing Index score now available for Canadian WAIS-IV

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More support for CHC interpretation of the WAIS-IV

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Yet another CFA study of the WAIS-IV standardization data that suggests the CHC framework is likely the most vablid interpretative framework for the WAIS-IV. Other posts in support of this conclusion can be found here and here.



Of particular note is the continued finding, consistent with my interpretation of the literature that the Arithmetic subtest is a factorially complex and mixed measure of 2-3 different CHC domains and thus, should NOT be interpreted as a strong indicator of any particular CHC domain. This does not mean it is a bad test. On the contrary, factorially complex tests are sometimes some of the best predictors of other outcomes because they measure multiple abilities (which makes them function as mini g-proxies). The point, reinforced by this latest study, is that Arithmetic is not a good strong indicator of a single CHC domain and has considerable construct irrelevant variance when interpreted within a CHC framework

Conflict of interest note - I am a coauthor of the WJ III which is a competitor to the WAIS-IV

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Special issue of Assessment journal on the WAIS-IV and WMS-IV research

The journal Assessment just published a special issue on the WASI-IV/WMS-IV. I love the journal cover (see above)


Frazier, T. W. (2011). Introduction to the Special Section on Advancing WAIS-IV and WMS-IV Clinical Interpretation. Assessment, 18(2), 131-132.

Bowden, S. C., Saklofske, D. H., & Weiss, L. G. (2011). Augmenting the Core Battery With Supplementary Subtests: Wechsler Adult Intelligence Scale-IV Measurement Invariance Across the United States and Canada. Assessment, 18(2), 133-140.

Brooks, B. L., Holdnack, J. A., & Iverson, G. L. (2011). Advanced Clinical Interpretation of the WAIS-IV and WMS-IV: Prevalence of Low Scores Varies by Level of Intelligence and Years of Education. Assessment, 18(2), 156-167.

Drozdick, L. W., & Cullum, C. M. (2011). Expanding the Ecological Validity of WAIS-IV and WMS-IV With the Texas Functional Living Scale. Assessment, 18(2), 141-155.


Gregoire, J., Coalson, D. L., & Zhu, J. J. (2011). Analysis of WAIS-IV Index Score Scatter Using Significant Deviation from the Mean Index Score. Assessment, 18(2), 168-177.

Holdnack, J., Goldstein, G., & Drozdick, L. (2011). Social Perception and WAIS-IV Performance in Adolescents and Adults Diagnosed With Asperger's Syndrome and Autism. Assessment, 18(2), 192-200.

Holdnack, J. A., Zhou, X. B., Larrabee, G. J., Millis, S. R., & Salthouse, T. A. (2011). Confirmatory Factor Analysis of the WAIS-IV/WMS-IV. Assessment, 18(2), 178-191


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intelligence IQ tests IQ testing IQ scores CHC intelligence theory CHC theory Cattell-Horn-Carroll human cognitive abilities psychology school psychology individual differences cognitive psychology neuropsychology neuroscience psychology special education educational psychology psychometrics psychological assessment psychological measurement IQs Corner general intelligence WAIS-IV WMS-IV Wechsler Adult Intelligence Scale Wechsler Batteries

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AP101 Brief #8 (guest brief): Independent CFA of the French WAIS-IV by Golay et al. (2011)

This IAP AP101 Brief Report was sent to me for posting by Philippe Golay.  It is reproduced "as is" with only minor editing.  This is a guest blog/brief report.  Figures included should be possible to enlarge by double clicking on them.

If other folks have completed research related to this blog, and would like to make brief post reports, please contact the blogmaster @ iap@earthlink.net

Philippe Golay, Isabelle Reverte, Thierry Lecerf,
University of Geneva, Switzerland

The fourth edition of the French Wechsler Intelligence Scale for Adult (WAIS-IV) was recently released (Editions du Centre de Psychologie Appliquée – ECPA, 2011). The French WAIS-IV was standardized on a representative sample of 876 people in France ranging in age from 16 to 79. However, for some subtests (Letter Number, Figure Weights and Cancellation), normative data were restricted to 730 participants (and from 16 to 69 years only). In the French WAIS-IV manual, confirmatory Factor analyses were reported, and models with 1, 2, 3 and 4 factors were presented. CFAs supported a factorial structure with 4 factors. Surprisingly, no models based on the Cattell-Horn-Carroll (CHC) theory were reported in the technical manual of the French WAIS-IV. Thus, the main goal of this VERY brief report is to provide a preliminary independent examination of the factor structure of the French WAIS-IV according to the CHC theory. Analyses were conducted on the basis of the subtest inter-correlation matrix and the standard deviations reported in the French manual (p. 50). We used the Akaike Information Criterion (AIC) to compare models.

In the first step, models based on the four-factors solution were tested: four-correlated factors (VCI, PRI, WMI, PSI) and a hierarchical model with four factors and one general factor. We also tested modified versions of the basic 4 factor models because they were suggested and reported in the technical manual. This variant included correlated error terms for Digit Span and Letter Number Sequencing, a cross-loading for Figure Weight on the WMI factor and a cross-loading for Arithmetic on the VCI factor. The model fit of both four factor models (with or without g) was greatly increased as a result. We also tested a bifactor model, in which all subtests scores directly load onto a general factor and also onto one first-order group factor. Results indicated that the bifactor “WAIS-IV” model fits better the data than the other WAIS-IV models.

In a second step, we tested a couple of CHC-based models. We retained a model (fig.1) in which Arithmetic loads both on Gsm and Gf but does not include a cross-loading for Figure Weight on the Gsm factor. This model was better than the basic four-factors WAIS model but slightly less adequate than both modified four-factors solutions. Finally, we tested a bifactor CHC-based model (fig.2). This model with 5 uncorrelated group factors and a first order g factor showed the best fit to the data. The results are summarized in figure 3.

These preliminary results indicated that CHC-based interpretation of the French WAIS-IV is also a valid alternative. Furthermore, bifactor models showed better fit to the data than their higher-order counterparts. This challenges a rather implicit but nevertheless strong assumption that the relationship between the general factor and each subtest is only mediated by the broad abilities.

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Research brief: WAIS-IV US-Canadian factor and score comparability

The transportability of the meaning of an intelligence test batteries composite scores across countries/cultures is important when a test is originally developed and normed in one country and is then adapted and used in a second country.

Bowden et al (2010) recently investigated the factorial invariance of the WAIS-IV across US and Canadian samples. The results are summarized in the abstract below (click to enlarge). The WAIS-IV was found to measure the same theoretical constructs across the two countries. However, the reported difference in latent mean factor intercepts indicated that the WAIS-IV provides higher scores with Canadian subjects. The need for Canadian norms are suggested.






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