Structural equation analysis of the California verbal learning test‐children's version in the standardization sample

Abstract

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.