Abstract
Several recent investigations have utilized cluster analytic procedures to elucidate profiles of verbal learning on the California Verbal Learning Test following traumatic brain injury (TBI). Although the results of these studies have contributed to our understanding of verbal learning following TBI, limitations in sample composition and methodology render the results difficult to evaluate. The current study provides an analysis of verbal learning clusters in the most comprehensive sample (n = 160) of TBI patients reported thus far. Results obtained from multiple hierarchical agglomerative clustering procedures suggested the presence of two distinct clusters, the first consisting of performance patterns falling within normal limits and the second consisting of moderate-to-severe impairment. Two iterative partitioning analyses further suggested a reliable solution with better-than-chance agreement (kappa coefficients >.85, p < .001). Thus, it is concluded that a two-cluster classification solution provides a parsimonious understanding of verbal learning profiles after TBI.
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More From: Journal of Clinical and Experimental Neuropsychology
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