The Penn Computerized Neurocognitive Battery (CNB)* was designed to measure performance accuracy and speed on specific neurobehavioral domains using tests that were previously validated with functional neuroimaging. The goal of the present study was to evaluate the neuropsychological theory used to construct the CNB by confirming the factor structure of the tests composing it. Method: In a large community sample (N 9,138; age range 821), we performed a correlated-traits confirmatory factor analysis (CFA) and multiple exploratory factor analyses (EFAs) on the 12 CNB measures of Efficiency (which combine Accuracy and Speed). We then performed EFAs of the Accuracy and Speed measures separately. Finally, we performed a confirmatory bifactor analysis of the Efficiency scores. All analyses were performed with Mplus using maximum likelihood estimation. Results: Results strongly support the a priori theory used to construct the CNB, showing that tests designed to measure executive, episodic memory, complex cognition, and social cognition aggregate their loadings within these domains. When Accuracy and Speed were analyzed separately, Accuracy produced 3 reliable factors: executive and complex cognition, episodic memory, and social cognition, while speed produced 2 factors: tests that require fast responses and those where each item requires deliberation. The statistical Fit of almost all models described above was acceptable (usually excellent).
Conclusions: Based on the analysis from these large-scale data, the CNB offers an effective means for measuring the integrity of intended neurocognitive domains in about 1 hour of testing and is thus suitable for large-scale clinical and genomic studies.
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