FULL-INFORMATION MODELS FOR MULTIPLE PSYCHOMETRIC TESTS - ANNUALIZED RATES OF CHANGE IN NORMAL AGING AND DEMENTIA

The rates of change for five widely used psychometric tests were analy zed to compare how much more variance reduction can be achieved using full-information methods relative to the single-equation methods previ ously used in dementia research. Nondemented controls and subjects wit h Alzheimer disease (AD), probable/possible vascular dementia (VD), or mixed dementia (MD) were evaluated. A cohort design was followed, wit h follow-up of three demented groups and one normal control group; dat a were analyzed in a multiple-equation regression model estimated with full-information methods. The study was conducted at Alzheimer's Dise ase Research Center sites at the University of California, Irvine, and at the University of Southern California. In all, 226 patients and co ntrols who had completed initial assessment and at least one annual re assessment were included in the study. Dependent variables were annual ized rates of change in the Mini-Mental State Examination (MMSE), the Short-Blessed Dementia Rating Scale (DRS), the Consortium to Establish a Registry for Alzheimer's Disease drawings test (CD), the WAIS-R Blo ck Design test (WRB), and the Boston Naming Test (BNT). Independent va riables were dementia severity, diagnosis (AD, VD, MD, or control), se x, age, marital status, education, and age at onset. Full-information methods reduced the variance in the change scores by greater than or e qual to 25% compared with previous studies, The model's prediction of a test's rate of change was almost entirely due to dementia stage and diagnosis. The effects of other explanatory variables (sex, marital st atus, age, and education) were weak and statistically insignificant. W hen the effects of other independent variables were controlled AD and MD patients were found to decline at significantly faster rates than V D patients. Full-information methods, relative to single-equation meth ods, substantially reduce the variance of rates of change for multiple psychometric tests. They do so by simultaneously considering the corr elated error terms in the regressions for each dependent psychometric change score variable. The robustness of these results to minor variat ions in follow-up time suggests that annualization is a reasonably val id procedure for making change scores comparable. This study's results suggest that change scores in psychometric tests provide information that can be used to aid differential diagnosis. However, the large var iances of change scores preclude many other uses. Finally, since stand ardization of psychometric change scores translates all tests to the s ame scale (0-100%), standardized change scores are easier to interpret . The analysis of standardized change scores deserves further investig ation.