Psychometric Properties of the Penn Computerized Neurocognitive Battery

By Tyler M. Moore, S. Reise, Raquel E. Gur, Hakon Hakonarson, Ruben C. Gur. Neuropsychology, 2014

332 citations recorded by the source corpus.

Objective 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. A crucial step in determining whether the CNB has attained its objective is to assess its factor structure. 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 = 9138; age range 8-21), we performed a correlated-traits confirmatory factor analysis (CFA) and multiple exploratory factor analyses (EFA’s) on the twelve CNB measures of Efficiency (which combine Accuracy and Speed). To further explore the measures contributing to Efficiency, we then performed EFA’s 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 three reliable factors: executive and complex cognition, episodic memory and social cognition, while speed produced two factors: tests that require fast responses and those where each item requires deliberation. The interpretability and statistical “Fit” of almost all models described above was acceptable (usually excellent). Conclusions Based on the well powered analysis from these large scale data, the CNB offers an effective means for measuring the integrity of intended neurocognitive domains in about one hour of testing and is thus suitable for large-scale clinical and genomic studies.

Subfields: Applied Psychology, Cognitive Neuroscience, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/ca079506a2141b127817fd140f6e6f1d6b037c61