Exploratory Factor Analyses of the Intelligence and Development Scales-2: Implications for Theory and Practice

The factor structure of the intelligence and scholastic skills domains of the Intelligence and Development Scales-2 was examined using exploratory factor analyses with the standardization and validation sample (N = 2,030, aged 5 to 20 years). Results partly supported the seven proposed intelligence group factors. However, the theoretical factors Visual Processing and Abstract Reasoning as well as Verbal Reasoning and Long-Term Memory collapsed, resulting in a five-factor structure for intelligence. Adding the three scholastic skills subtests resulted in an additional factor Reading/Writing and in Logical-Mathematical Reasoning showing a loading on abstract Visual Reasoning and the highest general factor loading. A data-driven separation of intelligence and scholastic skills is not evident. Omega reliability estimates based on Schmid-Leiman transformations revealed a strong general factor that accounted for most of the true score variance both overall and at the group factor level. The possible usefulness of factor scores is discussed.

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.

Evidence for the interpretation of Social, Academic, and Emotional Behavior Risk Screener (SAEBRS) scores: An argument-based approach to screener validation

In accordance with an argument-based approach to validation, the purpose of the current study was to yield evidence relating to Social, Academic, and Emotional Behavior Risk Screener (SAEBRS) score interpretation. Bifactor item response theory analyses were performed to examine SAEBRS item functioning. Structural equation modeling (SEM) was used to simultaneously evaluate intra- and inter-scale relationships, expressed through (a) a measurement model specifying a bifactor structure to SAEBRS items, and (b) a structural model specifying convergent and discriminant relations with an outcome measure (i.e., Behavioral and Emotional Screening System [BESS]). Finally, hierarchical omega coefficients were calculated in evaluating the model-based internal reliability of each SAEBRS scale. IRT analyses supported the adequate fit of the bifactor model, indicating items adequately discriminated moderate and high-risk students. SEM results further supported the fit of the latent bifactor measurement model, yielding superior fit relative to alternative models (i.e., unidimensional and correlated factors). SEM analyses also indicated the latent SAEBRS-Total Behavior factor was a statistically significant predictor of all BESS subscales, the SAEBRS-Academic Behavior predicted BESS Adaptive Skills subscales, and the SAEBRS-Emotional Behavior predicted the BESS Internalizing Problems subscale. Hierarchical omega coefficients indicated the SAEBRS-Total Behavior factor was associated with adequate reliability. In contrast, after accounting for the total scale, each of the SAEBRS subscales was associated with somewhat limited reliability, suggesting variability in these scores is largely driven by the Total Behavior scale. Implications for practice and future research are discussed.

Investigating the Theoretical Structure of the Differential Ability Scales—Second Edition Through Hierarchical Exploratory Factor Analysis

When the Differential Ability Scales–Second Edition (DAS-II) was developed, the instrument’s content, structure, and theoretical orientation were amended. Despite these changes, the Technical Handbook did not report results from exploratory factor analytic investigations, and confirmatory factor analyses were implemented using selected subtests across the normative age groups from the total battery. To address these omissions, the present study investigated the theoretical structure of the DAS-II using principal axis factoring followed by the Schmid–Leiman procedure with participants from the 5- to 8-year-old age range to determine the degree to which the DAS-II theoretical structure proposed in the Technical Handbook could be replicated. Unlike other age ranges investigated where at most 14 subtests were administered, the entire DAS-II battery was normed on participants aged 5 to 8 years, making it well suited to test the full instrument’s alignment with theory. Results suggested a six-factor solution that was essentially consistent with the Cattell–Horn–Carroll (CHC)-based theoretical structure suggested by the test publisher and simple structure was attained. The only exception involved two subtests (Picture Similarities and Early Number Concepts) that did not saliently load on a group factor. Implications for clinical practice are discussed.

Exploratory Bifactor Analysis: The Schmid-Leiman Orthogonalization and Jennrich-Bentler Analytic Rotations

Analytic bifactor rotations have been recently developed and made generally available, but they are not well understood. The Jennrich-Bentler analytic bifactor rotations (bi-quartimin and bi-geomin) are an alternative to, and arguably an improvement upon, the less technically sophisticated Schmid-Leiman orthogonalization. We review the technical details that underlie the Schmid-Leiman and Jennrich-Bentler bifactor rotations, using simulated data structures to illustrate important features and limitations. For the Schmid-Leiman, we review the problem of inaccurate parameter estimates caused by the linear dependencies, sometimes called "proportionality constraints," that are required to expand a p correlated factors solution into a (p + 1) (bi)factor space. We also review the complexities involved when the data depart from perfect cluster structure (e.g., item cross-loading on group factors). For the Jennrich-Bentler rotations, we describe problems in parameter estimation caused by departures from perfect cluster structure. In addition, we illustrate the related problems of (a) solutions that are not invariant under different starting values (i.e., local minima problems) and (b) group factors collapsing onto the general factor. Recommendations are made for substantive researchers including examining all local minima and applying multiple exploratory techniques in an effort to identify an accurate model.

Incremental Criterion Validity of the WJ-III COG Clinical Clusters

The current study examined the incremental validity of the clinical clusters from the Woodcock–Johnson III Tests of Cognitive Abilities (WJ-III COG) for predicting scores on the Woodcock–Johnson III Tests of Achievement (WJ-III ACH). All participants were children and adolescents ( N = 4,722) drawn from the nationally representative WJ-III standardization sample. Hierarchical multiple regression analyses were used to assess for cluster-level effects after controlling for the variance accounted for by the General Intellectual Ability (GIA) composite score. Consistent with previous studies, the GIA accounted for clinically significant portions of WJ-III ACH score variance in all of the regression models with R2 values ranging from .33 to .63. The clinical cluster scores collectively accounted for small to moderate incremental effects with no meaningful effects observed for individual indicators. Potential implications of these results for empirically supported interpretation of the WJ-III COG are discussed.

Exploratory Bifactor Analysis of the WJ-III Achievement at School Age via the Schmid–Leiman Orthogonalization Procedure

The structure of academic achievement measures has been rarely investigated in the literature apart from that which appears in the instruments’ technical manuals. This is concerning, given the widespread use of academic achievement instruments when making educational decisions about children. The Woodcock–Johnson III (WJ-III) Achievement for school-aged children (age 9-19) was investigated using exploratory bifactor analysis via the Schmid–Leiman (SL) orthogonalization procedure. This is the first time the SL has been applied to an academic achievement measure. The results revealed a unidimensional model of academic achievement across the standard 11 subtest battery, a two- or three-factor model at age 9 to 13 in the extended battery, and a two-factor model at age 14 to 19 across the extended battery. Forcing the four-factor fit in the standard battery required extracting eigenvalues as low as 0.67 and yielded areas of both convergence with and divergence from the structure posited in the Technical Manual. Forcing the six-factor fit across the extended battery yielded Heywood Cases, a lack of convergence of the factor solution, and the need to truncate iterations at 2 to force the fit. The results of this study indicate that the WJ-III Achievement is a solid model of general achievement across the 9 to 19 age range. Examination of omega coefficients, the divergent factor structure, and the small amount of variance accounted for by the lower order factors suggest caution when interpreting beyond this level (i.e., the academic clusters). Implications for interpretation of the WJ-III Achievement at age 9 to 19 are discussed.

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.