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Assessment of measurement invariance across populations is essential for meaningful comparison of test scores, and is especially relevant where repeated measurements are required for educational assessment or clinical diagnosis. Establishing measurement invariance legitimizes the assumption that test scores reflect the same psychological trait in different populations or across different occasions. Examination of Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) U.S. standardization samples revealed that a first-order 5-factor measurement model was best fitting across 9 age groups from 16 years to 69 years. Strong metric invariance was found for 3 of 5 factors and partial intercept invariance for the remaining 2. Pairwise comparisons of adjacent age groups supported the inference that cognitive-trait group differences are manifested by group differences in the test scores. In educational and clinical settings these findings provide theoretical and empirical support to interpret changes in the index or subtest scores as reflecting changes in the corresponding cognitive abilities. Further, where clinically relevant, the subtest score composites can be used to compare changes in respective cognitive abilities. The model was supported in the Canadian standardization data with pooled age groups but the sample sizes were not adequate for detailed examination of separate age groups in the Canadian sample. (PsycINFO Database Record

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Objective: To replicate a seven-factor model previously reported for the Delis–Kaplan Executive Function System (D-KEFS). Method: This study used the D-KEFS standardization sample including 1,750 non-clinical participants. Several seven-factor models previously reported for the D-KEFS were re-evaluated using confirmatory factor analysis (CFA). Previously published bi-factor models were also tested. These models were compared with a three-factor a priori model based on Cattell–Horn–Carroll (CHC) theory. Measurement invariance was examined across three age cohorts. Results: All previously reported models failed to converge when tested with CFA. None of the bi-factor models converged after large numbers of iterations, suggesting that bi-factor models are ill-suited to represent the D-KEFS scores as reported in the test manual. Although poor fit was initially observed for the three-factor CHC model, inspection of modification indices showed potential for improvement by including method effects via correlated residuals for scores derived from similar tests. The final CHC model showed good to excellent fit and strong metric measurement invariance across the three age cohorts with minor exceptions for a subset of Fluency parameters. Conclusions: CHC theory extends to the D-KEFS, supporting findings from previous studies that executive functions can be integrated into CHC theory.

Objective The 10 core subtests of the Wechsler Adult Intelligence Scale-IV (WAIS-IV) suffice to produce the 4 index scores for clinical assessments. Factor analytic studies with the full complement of 15 subtests reveal a 5-factor structure that aligns with Cattell–Horn–Carroll taxonomy of cognitive abilities. The current study investigates the validity of 5-factor structure in a clinical setting with reduced number of 10 subtests. Method Confirmatory factor analytic models were fitted to a clinical neurosciences archival data set (n_Male = 166, n_Female = 155) and to 9 age-group samples of the WAIS-IV standardization data (n = 200 for each group). The clinical and the standardization samples differed as (a) the former comprised scores from patients, aged 16 to 91, with disparate neurological diagnosis whereas the latter was demographically stratified, (b) only the 10 core subtests in the former but all 15 subtests in the latter were administered, and (c) the former had missing data, but the latter was complete. Result Despite empirical constraints to eliciting 5 factors with only 10 indicators, the well-fitting, 5-factor (acquired knowledge, fluid intelligence, short-term memory, visual processing, and processing speed) measurement model evinced metric invariance between the clinical and standardization samples. Conclusion The same cognitive constructs are measured on the same metrics in every sample examined and provide no reason to reject the assumption that the 5 underlying latent abilities of the 15 subtest version in the standardization samples can also be inferred from the 10 subtest version in clinical populations.