Neuropsychological test norms — UDS version 3
Sandra Weintraub and colleagues plan to publish norms for version 3 of the UDS neuropsychological tests in 2016–2017. Until then, please reference:
- the paper below on UDS versions 1 and 2; and
- results from the crosswalk study, which used equipercentile equating to determine equivalent scores between the old (version 1 and 2) and new (version 3) UDS neuropsychological tests.
Neuropsychological test means — UDS versions 1 and 2
Sandra Weintraub's article containing this information is available here (PDF). Dr. Weintraub warns that the posted summaries of test scores for non-demented subjects should not be treated as formal "norms:"
"This is a preliminary report on non-demented subjects and does not by any means represent 'normative values' in the way that portray psychometric rigor and adjustments for age, education, and other variables that turned out to affect scores (gender). Furthermore, we did not have a sufficient number of subjects at lower educational levels so that we did not want to attempt normative tables prior to getting a larger sample.
(All data were developed for the more detailed paper by Weintraub et al. in Alzheimer's Disease and Associated Disorders).
In addition, test means are now available for the Spanish version of the UDS [Benson et al., Alzheimer's & Dementia] .
Normative calculator for neuropsychological tests, UDS versions 1 and 2
Weintraub and colleagues [Weintraub 2009] (PDF) provided descriptive information from initial neuropsychological data of more than 3,000 clinically cognitively normal older adults and developed linear regression models to estimate the impact of age, sex, and education on test performance. The report by Weintraub et al. provided in-depth descriptive information about cognitively normal older adults in the UDS, but it was not intended as a normative study.
However, by combining the initial results of Weintraub and colleagues with additional statistical information obtained from the study's authors (for example, root mean square errors for model variables), we have sought to create a useful regression-based norms calculator that provides estimated z-scores while taking into consideration the individual's sex, education level, and/or age and to make this straightforward tool available on the web for clinical research use at the National Institute on Aging Alzheimer's Disease Program UDS sites. In addition, we aimed to provide an easy and accessible method for calculating norms that other researchers and clinicians can apply to their own unique, site-specific data sets.