Psychometric properties and factor structure of an expanded CERAD neuropsychological battery in an elderly VA sample

• Published in: Archives of clinical neuropsychology Vol. 21; no. 4; pp. 359 - 365
• Main Authors: Jones, Scott N., Ayers, Catherine R.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Ltd 01.05.2006; Elsevier
• Subjects: Aged; Aged, 80 and over; Alzheimer Disease - diagnosis; Alzheimer Disease - physiopathology; Biological and medical sciences; Degenerative and inherited degenerative diseases of the nervous system. Leukodystrophies. Prion diseases; Dementia; Dementia - diagnosis; Dementia - physiopathology; Factor analysis; Female; Geriatric Assessment; Humans; Logistic Models; Male; Medical sciences; Middle Aged; Neurology; Neuropsychological Tests - statistics & numerical data; Psychology. Psychoanalysis. Psychiatry; Psychometrics; Psychometrics. Diagnostic aid systems; Psychopathology. Psychiatry; Screening evaluation; Techniques and methods; Veterans; Screening evaluation; Factor analysis; Dementia; Human; Evaluation; Nervous system diseases; Cognitive disorder; Neuropsychological test; Psychometrics; Medical screening; Cerebral disorder; Senile dementia; Test validation; Central nervous system disease; Degenerative disease; Veteran; Elderly
• ISSN: 0887-6177; 1873-5843
• DOI: 10.1016/j.acn.2006.03.004

Recent research by Strauss and Fritsch [Strauss, M.E., & Fritsch, T. (2004). Factor structure of the CERAD neurophysiological battery. Journal of the International Neuropsychological Society, 10, 559–565] suggested additions to the original Consortium to Establish a Registry for Alzheimer's Disease (CERAD) neuropsychological battery. In the present study, the data from a clinical series of military veteran patients referred for neuropsychological evaluation of suspected dementia using an Expanded CERAD battery was explored. Logistic regression analysis and exploratory factor analysis with quantitative methods for determining the number of factors strongly supported the addition of the Indiana University Token Test. A one-factor model best accounted for the demented subjects data and a two-factor model emerged when the total sample (demented and non-demented subjects) data were factor analyzed. The benefit of using computational methods for determining the number of underlying factors was discussed.