The interpretation of the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) is based on a 4-factor model, which is only partially compatible with the mainstream Cattell-Horn-Carroll (CHC) model of intelligence measurement. The structure of cognitive batteries is frequently analyzed via exploratory factor analysis and/or confirmatory factor analysis. With classical confirmatory factor analysis, almost all crossloadings between latent variables and measures are fixed to zero in order to allow the model to be identified. However, inappropriate zero cross-loadings can contribute to poor model fit, distorted factors, and biased factor correlations; most important, they do not necessarily faithfully reflect theory. To deal with these methodological and theoretical limitations, we used a new statistical approach, Bayesian structural equation modeling (BSEM), among a sample of 249 French-speaking Swiss children (8 -12 years). With BSEM, zero-fixed cross-loadings between latent variables and measures are replaced by approximate zeros, based on informative, small-variance priors. Results indicated that a direct hierarchical CHC-based model with 5 factors plus a general intelligence factor better represented the structure of the WISC-IV than did the 4-factor structure and the higher order models. Because a direct hierarchical CHC model was more adequate, it was concluded that the general factor should be considered as a breadth rather than a superordinate factor. Because it was possible for us to estimate the influence of each of the latent variables on the 15 subtest scores, BSEM allowed improvement of the understanding of the structure of intelligence tests and the clinical interpretation of the subtest scores.

Exploratory and confirmatory factor analyses reported in the French technical manual of the WISC-IV provides evidence supporting a structure with four indices: Verbal Comprehension (VCI), Perceptual Reasoning (PRI), Working Memory (WMI), and Processing Speed (PSI). Although the WISC-IV is more attuned to contemporary theory, it is still not in total accordance with the dominant theory: the Cattell-Horn-Carroll (CHC) theory of cognitive ability. This study was designed to determine whether the French WISC-IV is better described with the four-factor solution or whether an alternative model based on the CHC theory is more appropriate. The intercorrelations matrix reported in the French technical manual was submitted to confirmatory factor analysis. A comparison of competing models suggests that a model based on the CHC theory fits the data better than the current WISC-IV structure. It appears that the French WISC-IV in fact measures six factors: crystallized intelligence (Gc), fluid intelligence (Gf), short-term memory (Gsm), processing speed (Gs), quantitative knowledge (Gq), and visual processing (Gv). We recommend that clinicians interpret the subtests of the French WISC-IV in relation to this CHC model in addition to the four indices.

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IAG : Normes Francophones 1 Résumé Le WISC-IV permet le calcul du QI Total et de quatre indices factoriels : Compréhension Verbale, Raisonnement perceptif, Vitesse de traitement et Mémoire de Travail. En 1998, Prifitera et collègues ont préconisé le calcul de l'Indice d'Aptitude Général (IAG) comme alternative au QIT, et cela à partir des scores de Compréhension verbale et de Raisonnement Perceptif. La première étude présentée dans cet article a pour objectif d'établir les normes francophones pour le score IAG du WISC-IV, en utilisant une procédure d'approximation statistique. La deuxième étude vise à examiner la validité de ces normes, en les confrontant à des données recueillies sur un échantillon de soixante enfants. La corrélation entre QIT et IAG est de .91, et la différence relative moyenne de 0,18 point. Ces normes permettent d'utiliser le score IAG comme alternative au QIT dans certaines situations diagnostiques.