Objectives: This study aimed to identify a well-fitting and theoretically justified item-level latent factor structure for the Wechsler Memory Scales (WMS)-IV verbal paired associates (VerbalPA) subtest to facilitate the ease and accuracy of score interpretations for patients with lateralized temporal lobe epilepsy (TLE). Methods: Archival data were used from 250 heterogeneous neurosciences patients who were administered the WMS-IV as part of a standard neuropsychological assessment. Three theoretically motivated models for the latent structure of VerbalPA were tested using confirmatory factor analysis. The first model, based on cognitive principles of semantic processing from hub-and-spoke theory, tested whether performance is related to specific semantic features of target words. The second, motivated by the Cattell–Horn–Carroll (CHC) model of cognitive abilities, investigated whether the associative properties of items influence performance. A third, Hybrid model tested whether performance is related to both semantic and associative properties of items. The best-fitting model was tested for diagnostic group effects contrasting the heterogeneous neuroscience patients with subsets of left and right TLE (n = 51, n = 26, respectively) patients. Results: The Hybrid model was found to have the best fit. Patients with left TLE scored significantly less well than the heterogeneous neurosciences sample on selected semantic factor scores, although the effect size was small. Conclusions: Future editions of the WMS may consider implementing a semantic scoring structure for the VerbalPA to facilitate test score interpretation. Additionally, these results suggest that principles of hub-and-spoke theory may be integrated into CHC cognitive ability taxonomy.
Objective To investigate the factor structure of the verbal paired-associates (VPA) subtest in the WMS-III using a theoretically driven model of semantic processing previously found to be well-fitting for the WMS-IV version of the test. Method Archival data were used from 267 heterogeneous neurosciences patients and 223 seizure disorder patients who completed the WMS-III as part of a standard neuropsychological evaluation. Confirmatory factor analysis was used to test theoretically driven models for VPA based on principles of semantic processing. Four nested models of different complexities were examined and compared for goodness-of-fit using chi-squared difference testing. Measurement invariance testing was conducted across heterogeneous neuroscience and seizure disorder samples to test generality of the factor model. Results After removing items with limited variability (very easy or very hard; 12 of 40 items), a four-factor model was found to be best-fitting in the present patient samples. The four factors were “recreational”, “functional”, “material”, and “symbolic”, each representing semantic knowledge associated with the function of the target word referent. This model subsequently met the criteria for the strict measurement invariance, showing good overall fit when factor loadings, thresholds, and residuals were held to equality across samples. Conclusions The results of this study provide further evidence that “arbitrary” associations between word pairs in VPA items have an underlying semantic structure, challenging the idea that unrelated hard-pairs are semantic-free. These results suggest that a semantic-structure model may be implemented as an alternative scoring in future editions of the WMS to facilitate interpretation.
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.
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