Structural equation analysis of the California verbal learning test - Children's version in the standardization sample

Maximum-likelihood confirmatory factor analysis was applied to 13 qualitative and quantitative variables that were selected on the basis of specific theoretical and practical criteria from the California Verbal Learning Test-Children's Version (CVLT-C) standardization sample. Analyses were designed to determine which of 6 hypothetical, oblique factor solutions could best explain learning and memory as measured by the CVLT-C. Competing latent-variable models were identified on the basis of previous studies, as well as distinctions suggested by the CVLT-C format. The findings suggested that a 5-factor model (composed of Attention Span, Learning Efficiency, Free Delayed Recall, Cued Delayed Recall, and Inaccurate Recall) fit the data relatively best in terms of superior fit and acceptable parsimony. I conclude that this 5-factor model is a useful and valid predictor of CVLT-C performance variability.