Establishing regression-based reliable change scores for the UDS3

 
   Lead Investigator:    Victoria Williams
   Institution      :    University of Wisconsin - Madison
   E-Mail           :    vwilliams@medicine.wisc.edu
   Proposal ID      :    1414



   Proposal Description:
   1. This projects aims to utilize all available NACC UDS3 data from non-impaired participants to derive longitudinal regression-based formulas for predicting reliable change. Regression-based reliable change formulas have been previously published for the UDS2 (Gavett et al., 2015), however, these regression formulas seem to be currently lacking for the UDS3. I plan to replicate the methods from this approach in the UDS2 taken by Gavett et al., to provide updated reliable change indices for the UDS3. Publishing the results of this study will provide those working with the NACC UDS3 data to be able to assess clinically meaningful change in cognitive performance following repeat assessment.  2. As a secondary aim, I also plan to explore the creation of by-domain composite scores using factor analysis. These analyses will generate factor weightings for each variable in order to provide a succinct summary measure of overall performance within a cognitive domain. Resultant factor scores could     subsequently be used to characterize a participant's overall cognitive profile, and to create a summary graph to visually depict cognitive strengths/weaknesses as an aid to formulating clinical presentation.    References:                                                                       Gavett, B. E., Ashendorf, L.,  Gurnani, A. S. (2015). Reliable change on         neuropsychological tests in the Uniform Data Set. Journal of the International   Neuropsychological Society, 21(7), 558-567.