Bootstrap Exploratory Graph Analysis of the WISC-V with a Clinical Sample.

One important aspect of construct validity is structural validity. Structural validity refers to the degree to which scores of a psychological test are a reflection of the dimensionality of the construct being measured. A factor analysis, which assumes that unobserved latent variables are responsible for the covariation among observed test scores, has traditionally been employed to provide structural validity evidence. Factor analytic studies have variously suggested either four or five dimensions for the WISC-V and it is unlikely that any new factor analytic study will resolve this dimensional dilemma. Unlike a factor analysis, an exploratory graph analysis (EGA) does not assume a common latent cause of covariances between test scores. Rather, an EGA identifies dimensions by locating strongly connected sets of scores that form coherent sub-networks within the overall network. Accordingly, the present study employed a bootstrap EGA technique to investigate the structure of the 10 WISC-V primary subtests using a large clinical sample (N = 7149) with a mean age of 10.7 years and a standard deviation of 2.8 years. The resulting structure was composed of four sub-networks that paralleled the first-order factor structure reported in many studies where the fluid reasoning and visual-spatial dimensions merged into a single dimension. These results suggest that discrepant construct and scoring structures exist for the WISC-V that potentially raise serious concerns about the test interpretations of psychologists who employ the test structure preferred by the publisher.

Exploratory Factor Analyses of the French WISC-V (WISC-VFR) for Five Age Groups: Analyses Based on the Standardization Sample.

This study investigated the factor structure of the French Wechsler Intelligence Scale for Children-Fifth Edition with five standardization sample age groups (6-7, 8-9, 10-11, 12-13, 14-16 years) using hierarchical exploratory factor analysis followed by Schmid-Leiman procedure. The primary research questions included (a) how many French Wechsler Intelligence Scale for Children-Fifth Edition factors should be extracted and retained in each age subgroup, (b) how are subtests associated with the latent factors, (c) was there evidence for the publisher's claim of five first-order factors and separate Visual Spatial and Fluid Reasoning factors, (d) what proportion of variance was due to general intelligence versus the first-order group ability factors following a Schmid-Leiman procedure, and (e) do results support the age differentiation hypothesis? Results suggested that four factors might be sufficient for all five age groups and results did not support the distinction between Visual Spatial and Fluid Reasoning factors. While the general factor accounted for the largest portions of variance, the four first-order factors accounted for small unique portions of variance. Results did not support the age differentiation hypothesis because the number of factors remained the same across age groups, and there was no change in the percentage of variance accounted for by the general factor across age groups.

Long-term stability of Wechsler Intelligence Scale for Children-fifth edition scores in a clinical sample.

This study investigated the stability of Wechsler Intelligence Scale for Children-Fifth Edition (WISC-V) scores for 225 children and adolescents from an outpatient neuropsychological clinic across, on average, a 2.6 year test-retest interval. WISC-V mean scores were relatively constant but subtest stability score coefficients were all below 0.80 (M = 0.66) and only the Verbal Comprehension Index (VCI), Visual Spatial Index (VSI), and omnibus Full Scale IQ (FSIQ) stability coefficients exceeded 0.80. Neither intraindividual subtest difference scores nor intraindividual composite difference scores were stable across time (M = 0.26 and 0.36, respectively). Rare and unusual subtest and composite score differences as well as subtest and index scatter at initial testing were unlikely to be repeated at retest (kappa = 0.03 to 0.49). It was concluded that VCI, VSI, and FSIQ scores might be sufficiently stable to support normative comparisons but that none of the intraindividual (i.e. idiographic, ipsative, or person-relative) measures were stable enough for confident clinical decision making.

Construct validity of the BASC-3 teacher rating scales: Independent hierarchical exploratory factor analyses with the normative sample.

The Behavior Assessment System for Children-Third Edition (BASC-3) is the most recent edition and the Teacher Rating Scales (TRS) was reported to be the most frequently used test in school psychology practice. Despite its popularity, there is a lack of independent empirical research regarding psychometric properties. The BASC-3 Manual, while quite detailed in many respects, lacks important details in reporting TRS item- and scale-level factor analyses limiting confidence in construct validity based on internal structure. The present study examined the latent factor structure of the BASC-3 TRS Preschool, Child, and Adolescent Clinical and Adaptive scales using best practices in exploratory factor analysis (EFA). EFA was conducted with the Clinical and Adaptive scales jointly, and with the Clinical scales separately, to aid interpretive clarity. Results indicated theoretically consistent alignment of the BASC-3 TRS Clinical scales to their specified factors (Externalizing, Internalizing, and School Problems) and an additional factor (Social Disengagement) was identified, suggesting a possible new latent construct for a composite scale score containing the Withdrawal and Atypicality scales. Variance partitioning applied to second-order EFA and model-based validity statistics, however, indicated that the composite scales (Externalizing, Internalizing, School Problems, and Social Disengagement) appear to lack sufficient unique variance for confident clinical interpretation in isolation. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Construct Validity of the German Wechsler Intelligence Scale for Children-Fifth Edition: Exploratory and Confirmatory Factor Analyses of the 15 Primary and Secondary Subtests.

The latent factor structure of the German Wechsler Intelligence Scale for Children-Fifth edition (German WISC-V) was examined using complementary hierarchical exploratory factor analyses (EFAs) with Schmid and Leiman transformation and confirmatory factor analyses (CFAs) for all reported models from the German WISC-V Technical Manual and rival bifactor models using the standardization sample (N = 1,087) correlation matrix of the 15 primary and secondary subtests. EFA results did not support a fifth factor (Fluid Reasoning). A four-factor model with the dominant general intelligence (g) factor resembling the WISC-IV was supported by EFA. CFA results indicated the best representation was a bifactor model with four group factors, complementing EFA results. Present EFA and CFA results replicated other independent assessments of standardization and clinical samples of the United States and international versions of the WISC-V and indicated primary, if not exclusive, interpretation of the Full Scale IQ as an estimate of g.

Construct Validity of the WISC-V in Clinical Cases: Exploratory and Confirmatory Factor Analyses of the 10 Primary Subtests.

Independent exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) research with the Wechsler Intelligence Scale for Children-Fifth Edition (WISC-V) standardization sample has failed to provide support for the five group factors proposed by the publisher, but there have been no independent examinations of the WISC-V structure among clinical samples. The present study examined the latent structure of the 10 WISC-V primary subtests with a large (N = 2,512), bifurcated clinical sample (EFA, n = 1,256; CFA, n = 1,256). EFA did not support five factors as there were no salient subtest factor pattern coefficients on the fifth extracted factor. EFA indicated a four-factor model resembling the WISC-IV with a dominant general factor. A bifactor model with four group factors was supported by CFA as suggested by EFA. Variance estimates from both EFA and CFA found that the general intelligence factor dominated subtest variance and omega-hierarchical coefficients supported interpretation of the general intelligence factor. In both EFA and CFA, group factors explained small portions of common variance and produced low omega-hierarchical subscale coefficients, indicating that the group factors were of poor interpretive value.

Construct validity of the Wechsler Intelligence Scale For Children - Fifth UK Edition: Exploratory and confirmatory factor analyses of the 16 primary and secondary subtests.

BACKGROUND: There is inadequate information regarding the factor structure of the Wechsler Intelligence Scale for Children - Fifth UK Edition (WISC-VUK ; Wechsler, 2016a, Wechsler Intelligence Scale for Children-Fifth UK Edition, Harcourt Assessment, London, UK) to guide interpretation. AIMS AND METHODS: The WISC-VUK was examined using complementary exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) for all models proposed by Wechsler (2016b, Wechsler Intelligence Scale for Children-Fifth UK Edition: Administration and scoring manual, Harcourt Assessment, London, UK) as well as rival bifactor models. SAMPLE: The WISC-VUK standardization sample (N = 415) correlation matrix was used in analyses due to denial of standardization sample raw data. RESULTS: EFA did not support a theoretically posited fifth factor because only one subtest (Matrix Reasoning) had a salient pattern coefficient on the fifth factor. A model with four group factors and a general intelligence factor resembling the Wechsler Intelligence Scale for Children - Fourth Edition (WISC-IV; Wechsler, 2003, Wechsler Intelligence Scale for Children-Fourth Edition, Psychological Corporation, San Antonio, TX, USA) was supported by both EFA and CFA. General intelligence (g) was the dominant source of subtest variance and large omega-hierarchical coefficients supported interpretation of the Full Scale IQ (FSIQ) score. In contrast, the four group factors accounted for small portions of subtest variance and low omega-hierarchical subscale coefficients indicated that the four-factor index scores were of questionable interpretive value independent of g. Present results replicated independent assessments of the Canadian, Spanish, French, and US versions of the WISC-V (Canivez, Watkins, & Dombrowski, 2016, Psychological Assessment, 28, 975; 2017, Psychological Assessment, 29, 458; Fennollar-Cortés & Watkins, 2018, International Journal of School & Educational Psychology; Lecerf & Canivez, 2018, Psychological Assessment; Watkins, Dombrowski, & Canivez, 2018, International Journal of School and Educational Psychology). CONCLUSION: Primary interpretation of the WISC-VUK should be of the FSIQ as an estimate of general intelligence.

Cognitive profile analysis in school psychology: History, issues, and continued concerns.

Intelligence testing remains a fixture in school psychology training and practice. Despite their popularity, the use of IQ tests is not without controversy and researchers have long debated how these measures should be interpreted with children and adolescents. A controversial aspect of this debate relates to the utility of cognitive profile analysis, a class of interpretive methods that encourage practitioners to make diagnostic decisions and/or treatment recommendations based on the strengths and weaknesses observed in ability score profiles. Whereas numerous empirical studies and reviews have challenged long-standing assumptions about the utility of these methods, much of this literature is nearly two decades old and new profile analysis methods (e.g., XBA, PSW) have been proffered. To help update the field's understanding of these issues, the present review traces the historical development of cognitive profile analysis and (re)introduces readers to a body of research evidence suggesting new and continued concerns with the use of these methods in school psychology practice. It is believed that this review will serve as a useful resource to practitioners and trainers for understanding and promoting a countering view on these matters.

"Complementary exploratory and confirmatory factor analyses of the French WISC-V: Analyses based on the standardization sample": Correction to Lecerf and Canivez (2018).

Reports an error in "Complementary exploratory and confirmatory factor analyses of the French WISC-V: Analyses based on the standardization sample" by Thierry Lecerf and Gary L. Canivez (Psychological Assessment, 2018[Jun], Vol 30[6], 793-808). In the original article a production error resulted in the deletion of subtests in the "French WISC-V subtest" column and the misalignment of factor names in the "Eigenvalue" column of Table 1. The corrected table is included in this erratum. The online version of this article has been corrected. (The following abstract of the original article appeared in record 2017-57791-001.) Interpretation of the French Wechsler Intelligence Scale for Children-Fifth Edition (French WISC-V; Wechsler, 2016a) is based on a 5-factor model including Verbal Comprehension (VC), Visual Spatial (VS), Fluid Reasoning (FR), Working Memory (WM), and Processing Speed (PS). Evidence for the French WISC-V factorial structure was established exclusively through confirmatory factor analyses (CFAs). However, as recommended by Carroll (1995); Reise (2012), and Brown (2015), factorial structure should derive from both exploratory factor analysis (EFA) and CFA. The first goal of this study was to examine the factorial structure of the French WISC-V using EFA. The 15 French WISC-V primary and secondary subtest scaled scores intercorrelation matrix was used and factor extraction criteria suggested from 1 to 4 factors. To disentangle the contribution of first- and second-order factors, the Schmid and Leiman (1957) orthogonalization transformation (SLT) was applied. Overall, no EFA evidence for 5 factors was found. Results indicated that the g factor accounted for about 67% of the common variance and that the contributions of the first-order factors were weak (3.6 to 11.9%). CFA was used to test numerous alternative models. Results indicated that bifactor models produced better fit to these data than higher-order models. Consistent with previous studies, findings suggested dominance of the general intelligence factor and that users should thus emphasize the Full Scale IQ (FSIQ) when interpreting the French WISC-V. (PsycINFO Database Record

Hierarchical exploratory factor analyses of the Woodcock-Johnson IV Full Test Battery: Implications for CHC application in school psychology.

The Woodcock-Johnson (fourth edition; WJ IV; Schrank, McGrew, & Mather, 2014a) was recently redeveloped and retains its linkage to Cattell-Horn-Carroll theory (CHC). Independent reviews (e.g., Canivez, 2017) and investigations (Dombrowski, McGill, & Canivez, 2017) of the structure of the WJ IV full test battery and WJ IV Cognitive have suggested the need for additional factor analytic exploration. Accordingly, the present study used principal axis factoring (PAF) followed by the Schmid and Leiman (SL; Schmid & Leiman, 1957) procedure with the 2 school-aged correlation matrices from the normative sample to determine the degree to which the WJ IV total battery structure could be replicated. Although 7 factors emerged across the 9 to 19 age range, the pattern of subtests loadings did not fully cohere with the structure presented in the Technical Manual, most notably for the academic fluency subtests. Also, the Fluid Reasoning (Gf) and Quantitative Reasoning (Gq) subtests coalesced to form a combined factor rather than 2 separate factors and the Long Term Retrieval (Gltr) subtests aligned with a variety of different factors. The results of this study indicated that the general intelligence factor variance far exceeded the variance attributed to the lower-order CHC factors. The combination of subtest migration and nominal total/common variance of the CHC lower-order factors suggests caution when interpreting the myriad CHC-related indices when making high stakes decisions. Implications for clinical practice are discussed. (PsycINFO Database Record

Complementary exploratory and confirmatory factor analyses of the French WISC-V: Analyses based on the standardization sample.

Interpretation of the French Wechsler Intelligence Scale for Children-Fifth Edition (French WISC-V; Wechsler, 2016a) is based on a 5-factor model including Verbal Comprehension (VC), Visual Spatial (VS), Fluid Reasoning (FR), Working Memory (WM), and Processing Speed (PS). Evidence for the French WISC-V factorial structure was established exclusively through confirmatory factor analyses (CFAs). However, as recommended by Carroll (1995); Reise (2012), and Brown (2015), factorial structure should derive from both exploratory factor analysis (EFA) and CFA. The first goal of this study was to examine the factorial structure of the French WISC-V using EFA. The 15 French WISC-V primary and secondary subtest scaled scores intercorrelation matrix was used and factor extraction criteria suggested from 1 to 4 factors. To disentangle the contribution of first- and second-order factors, the Schmid and Leiman (1957) orthogonalization transformation (SLT) was applied. Overall, no EFA evidence for 5 factors was found. Results indicated that the g factor accounted for about 67% of the common variance and that the contributions of the first-order factors were weak (3.6 to 11.9%). CFA was used to test numerous alternative models. Results indicated that bifactor models produced better fit to these data than higher-order models. Consistent with previous studies, findings suggested dominance of the general intelligence factor and that users should thus emphasize the Full Scale IQ (FSIQ) when interpreting the French WISC-V. (PsycINFO Database Record

Construct validity of the Wechsler Intelligence Scale for Children - Fourth UK Edition with a referred Irish sample: Wechsler and Cattell-Horn-Carroll model comparisons with 15 subtests.

BACKGROUND: Irish educational psychologists frequently use the Wechsler Intelligence Scale for Children - Fourth UK Edition (WISC-IVUK ; Wechsler, 2004, Wechsler Intelligence Scale for Children-Fourth UK Edition, London, UK, Harcourt Assessment) in clinical assessments of children with learning difficulties. Unfortunately, reliability and validity studies of the WISC-IVUK standardization sample have not yet been reported. Watkins et al. (2013, International Journal of School and Educational Psychology, 1, 102) found support for a bifactor structure with a large sample (N = 794) of Irish children who were administered the 10 WISC-IVUK core subtests in clinical assessments of learning difficulties and dominance of general intelligence. Because only 10 subtests were available, Cattell-Horn-Carroll (CHC; McGrew, 1997, 2005, Contemporary intellectual assessment: Theories, tests, and issues, New York, NY: Guilford; Schneider & McGrew, 2012, Contemporary intellectual assessment: Theories, tests, and issues, New York, NY, Guilford Press) models could not be tested and compared. AIM, SAMPLE AND METHOD: The present study utilized confirmatory factor analyses to test the latent factor structure of the WISC-IVUK with a sample of 245 Irish children administered all 15 WISC-IVUK subtests in evaluations assessing learning difficulties in order to examine CHC- and Wechsler-based models. One through five, oblique first-order factor models and higher order versus bifactor models were examined and compared using CFA. RESULTS: Meaningful differences in fit statistics were not observed between the Wechsler and CHC representations of higher-order or bifactor models. In all four structures, general intelligence accounted for the largest portions of explained common variance, whereas group factors accounted for small to miniscule portions of explained common variance. Omega-hierarchical subscale coefficients indicated that unit-weighted composites that would be generated by WISC-IVUK group factors (Wechsler or CHC) would contain little unique variance and thus be of little value. CONCLUSION: These results were similar to those from other investigations, further demonstrating the replication of the WISC-IV factor structure across cultures and the importance of focusing primary interpretation on the FSIQ.

Exploratory and hierarchical factor analysis of the WJ-IV Cognitive at school age.

Exploratory and confirmatory factor analytic studies were not reported in the Technical Manual for the Woodcock-Johnson, 4th ed. Cognitive (WJ IV Cognitive; Schrank, McGrew, & Mather, 2014b) Instead, the internal structure of the WJ IV Cognitive was extrapolated from analyses based on the full WJ IV test battery (Schrank, McGrew, & Mather, 2014b). Even if the veracity of extrapolating from the WJ IV full battery were accepted, there were shortcomings in the choices of analyses used and only limited information regarding those analyses was presented in the WJ IV Technical Manual (McGrew, Laforte, & Shrank, 2014). The present study examined the structure of the WJ IV Cognitive using exploratory factor analysis procedures (principal axis factoring with oblique [promax] rotation followed by application of the Schmid-Leiman, 1957, procedure) applied to standardization sample correlation matrices for 2 school age groups (ages 9-13; 14-19). Four factors emerged for both the 9-13 and 14-19 age groups in contrast to the publisher's proposed 7 factors. Results of these analyses indicated a robust manifestation of general intelligence (g) that exceeded the variance attributed to the lower-order factors. Model-based reliability estimates supported interpretation of the higher-order factor (i.e., g). Additional analyses were conducted by forcing extraction of the 7 theoretically posited factors; however, the resulting solution was only partially aligned (i.e., Gs, Gwm) with the theoretical structure promoted in the Technical Manual and suggested the preeminence of the higher-order factor. Results challenge the hypothesized structure of the WJ IV Cognitive and raise concerns about its alignment with Cattell-Horn-Carroll theory. (PsycINFO Database Record

Structural validity of the Wechsler Intelligence Scale for Children-Fifth Edition: Confirmatory factor analyses with the 16 primary and secondary subtests.

The factor structure of the Wechsler Intelligence Scale for Children-Fifth Edition (WISC-V; Wechsler, 2014a) standardization sample (N = 2,200) was examined using confirmatory factor analyses (CFA) with maximum likelihood estimation for all reported models from the WISC-V Technical and Interpretation Manual (Wechsler, 2014b). Additionally, alternative bifactor models were examined and variance estimates and model-based reliability estimates (ω coefficients) were provided. Results from analyses of the 16 primary and secondary WISC-V subtests found that all higher-order CFA models with 5 group factors (VC, VS, FR, WM, and PS) produced model specification errors where the Fluid Reasoning factor produced negative variance and were thus judged inadequate. Of the 16 models tested, the bifactor model containing 4 group factors (VC, PR, WM, and PS) produced the best fit. Results from analyses of the 10 primary WISC-V subtests also found the bifactor model with 4 group factors (VC, PR, WM, and PS) produced the best fit. Variance estimates from both 16 and 10 subtest based bifactor models found dominance of general intelligence (g) in accounting for subtest variance (except for PS subtests) and large ω-hierarchical coefficients supporting general intelligence interpretation. The small portions of variance uniquely captured by the 4 group factors and low ω-hierarchical subscale coefficients likely render the group factors of questionable interpretive value independent of g (except perhaps for PS). Present CFA results confirm the EFA results reported by Canivez, Watkins, and Dombrowski (2015); Dombrowski, Canivez, Watkins, and Beaujean (2015); and Canivez, Dombrowski, and Watkins (2015). (PsycINFO Database Record

Factor structure of the Differential Ability Scales-Second Edition: Exploratory and hierarchical factor analyses with the core subtests.

The present study examined the factor structure of the Differential Ability Scales-Second Edition (DAS-II; Elliott, 2007a) standardization sample using exploratory factor analyses, multiple factor extraction criteria, and hierarchical exploratory factor analyses (Schmid & Leiman, 1957) not included in the DAS-II Introductory and Technical Handbook (Elliott, 2007b). Exploratory factor analyses with multiple factor extraction criteria and hierarchical analyses with the Schmid and Leiman (1957) procedure were conducted with the 3 DAS-II standardization samples (Lower Early Years [Ages 2:6-3:5], Upper Early Years [Ages 3:6-6:11], School-Age [Ages 7:0-17:11]). All factor extraction criteria suggested 1 factor despite the author and publisher recommended and promoted 2 (Ages 2:6-3:5) or 3 (Ages 3:6-6:11, Ages 7:0-17:11) factors. Results indicated that most DAS-II subtests were properly associated with the theoretically proposed first-order factors. Hierarchical exploratory analyses with the Schmid and Leiman procedure, however, found that the hierarchical g factor accounted for large portions of total and common variance, while the 2 or 3 first-order factors accounted for small portions of total and common variance. It was concluded that the DAS-II provides strong measurement of general intelligence but clinical interpretation should be primarily at that level. (PsycINFO Database Record

Factor structure of the Wechsler Intelligence Scale for Children-Fifth Edition: Exploratory factor analyses with the 16 primary and secondary subtests.

The factor structure of the 16 Primary and Secondary subtests of the Wechsler Intelligence Scale for Children-Fifth Edition (WISC-V; Wechsler, 2014a) standardization sample was examined with exploratory factor analytic methods (EFA) not included in the WISC-V Technical and Interpretive Manual (Wechsler, 2014b). Factor extraction criteria suggested 1 to 4 factors and results favored 4 first-order factors. When this structure was transformed with the Schmid and Leiman (1957) orthogonalization procedure, the hierarchical g-factor accounted for large portions of total and common variance while the 4 first-order factors accounted for small portions of total and common variance; rendering interpretation at the factor index level less appropriate. Although the publisher favored a 5-factor model where the Perceptual Reasoning factor was split into separate Visual Spatial and Fluid Reasoning dimensions, no evidence for 5 factors was found. It was concluded that the WISC-V provides strong measurement of general intelligence and clinical interpretation should be primarily, if not exclusively, at that level. (PsycINFO Database Record

Construct Validity and Diagnostic Utility of the Cognitive Assessment System for ADHD.

OBJECTIVE: The Das-Naglieri Cognitive Assessment System (CAS) is a test of cognitive abilities based on the Planning, Attention, Simultaneous, and Successive Theory (PASS). Studies of CAS performance by children with ADHD typically show lowest performance on Planning and deficits on Attention, but normal Simultaneous and Successive processing. Such distinct group differences studies support construct validity and are necessary, but not sufficient, for establishing diagnostic utility. METHOD: Students meeting Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev.; DSM-IV-TR) criteria for ADHD (n = 20) and matched controls (n = 20) were assessed with the CAS to examine distinct group differences and diagnostic utility of CAS in correctly classifying the individuals from both groups. RESULTS: CAS PASS scores were significantly related to ADHD characteristics demonstrating both distinct group differences (with medium to large effect sizes) and diagnostic utility (with medium effect sizes). CONCLUSION: Support was observed for CAS PASS score characteristics previously observed among students with ADHD, and this is the first study to report on the diagnostic utility of CAS PASS scores. Given the small sample, additional large-scale studies and cross-validation is needed. (J. of Att. Dis. 2016; 20(6) 519-529).

Incremental validity of WISC-IV(UK) factor index scores with a referred Irish sample: predicting performance on the WIAT-II(UK.).

BACKGROUND: Subtest and factor scores have typically provided little incremental predictive validity beyond the omnibus IQ score. AIMS: This study examined the incremental validity of Wechsler Intelligence Scale for Children - Fourth UK Edition (WISC-IV(UK) ; Wechsler, 2004a, Wechsler Intelligence Scale for Children - Fourth UK Edition, Harcourt Assessment, London, UK) and factor index scores in predicting academic achievement on the Wechsler Individual Achievement Test - Second UK Edition (WIAT-II(UK) ; Wechsler, 2005a, Wechsler Individual Achievement Test-Second UK Edition, Pearson, London, UK), beyond that predicted by the WISC-IV(UK) FSIQ. SAMPLE: The sample included 1,014 Irish children (ages 6-0 to 16-9) who were referred for evaluation of learning difficulties. METHOD: Hierarchical multiple regression analyses were used with the WISC-IV(UK) FSIQ (Block 1) and factor index scores (Block 2) as predictors and WIAT-II(UK) subtest and composite scores as dependent variables. RESULTS: The WISC-IV(UK) FSIQ accounted for statistically significant and generally large portions of WIAT-II(UK) subtest and composite score variance. WISC-IV(UK) factor index scores combined to provide statistically significant increments in prediction of most WIAT-II(UK) subtest and composite scores over and above the FSIQ; however, the effect sizes were mostly small as previously observed (i.e., Canivez, 2013a, Psychol. Assess., 25, 484; Glutting et al., 2006, J. Spec. Educ., 40, 103; Nelson et al., 2013, Psychol. Assess., 25, 618). Individually, the WISC-IV(UK) factor index scores provided small unique contributions to predicting WIAT-II(UK) scores. CONCLUSION: This, in combination with studies of apportioned variance from bifactor confirmatory factor analysis (Watkins et al., 2013, Int. J. Sch. Educ. Psychol., 1, 102), indicated that the WISC-IV(UK) FSIQ should retain the greatest weight in WISC-IV(UK) interpretation.

Construct validity of the WISC-IV with a referred sample: direct versus indirect hierarchical structures.

The Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is one of the most frequently used intelligence tests in clinical assessments of children with learning difficulties. Construct validity studies of the WISC-IV have generally supported the higher order structure with four correlated first-order factors and one higher-order general intelligence factor, but recent studies have supported an alternate model in which general intelligence is conceptualized as a breadth factor rather than a superordinate factor (M. W. Watkins, 2010, Structure of the Wechsler Intelligence Scale for Children-Fourth Edition among a national sample of referred students, Psychological Assessment, Vol. 22, pp. 782-787; M. W. Watkins, G. L. Canivez, T. James, K. & R. Good, in press, Construct validity of the WISC-IVUK with a large referred Irish sample, International Journal of School and Educational Psychology). WISC-IV core subtest data obtained from evaluations to assess learning difficulties in 345 children (224 boys, 121 girls) were examined. One through four, first order factor models and indirect versus direct hierarchical models were compared using confirmatory factor analyses. The correlated four-factor Wechsler model provided good fit to these data, but the direct hierarchical model showed statistically significant improvement over the indirect hierarchical model and correlated four-factor model. The direct hierarchical model was judged the best explanation of the WISC-IV factor structure, with the general factor accounting for 71.6% of the common variance while the first order factors accounted for 2.4-10.3% of the common variance. Thus, the results with the present sample of referred children were similar to those from other investigations (G. E. Gignac, 2005, Revisiting the factor structure of the WAIS-R: Insights through nested factor modeling, Assessment, Vol. 12, pp. 320-329; G. E. Gignac, 2006, The WAIS-III as a nested factors model: A useful alternative to the more conventional oblique and higher-order models, Journal of Individual Differences, Vol. 27, pp. 73-86; P. Golay, I. Reverte, J. Rossier, N. Favez, & T. Lecerf, 2012, Further insights on the French WISC-IV factor structure through Bayesian structural equation modeling. Psychological Assessment, advance online publication; M. W. Watkins, 2010, Structure of the Wechsler Intelligence Scale for Children-Fourth Edition among a national sample of referred students, Psychological Assessment, Vol. 22, pp. 782-787; M. W. Watkins, G. L. Canivez, T. James, K. & R. Good, in press, Construct validity of the WISC-IV(UK) with a large referred Irish sample, International Journal of School and Educational Psychology) supporting primary interpretation of the Full Scale IQ rather than the factor index scores.

Incremental criterion validity of WAIS-IV factor index scores: relationships with WIAT-II and WIAT-III subtest and composite scores.

The present study examined the incremental validity of Wechsler Adult Intelligence Scale-4th Edition (WAIS-IV; Wechsler, 2008a) factor index scores in predicting academic achievement on the Wechsler Individual Achievement Test-2nd Edition (WIAT-II; Psychological Corporation, 2002a) and on the Wechsler Individual Achievement Test-3rd Edition (WIAT-III; Wechsler, 2009a) beyond that predicted by the WAIS-IV Full Scale IQ (FSIQ). As with previous intelligence test incremental validity studies, the WAIS-IV FSIQ accounted for statistically significant and generally large portions of WIAT-II and WIAT-III subtest and composite score variance. WAIS-IV factor index scores combined to provide statistically significant increments in variance accounted for in most WIAT-II and WIAT-III subtest and composite scores over and above the FSIQ score; however, the effect sizes ranged from trivial to medium as observed in investigations with other intelligence tests (i.e., Glutting, Watkins, Konold, & McDermott, 2006; Youngstrom, Kogos, & Glutting, 1999). Individually, the WAIS-IV factor index scores provided trivial to small unique contributions to predicting WIAT-II and WIAT-III scores. This finding indicated that the FSIQ should retain primacy and greatest interpretive weight in WAIS-IV interpretation, as previously indicated by WAIS-IV subtest variance partitions form hierarchical exploratory factor analyses (Canivez & Watkins, 2010a, 2012b).