NIH R01 · 2025
Statistical Methods for Accurate Estimation and Prediction in Alzheimer's Disease
Project Summary Longitudinal cohort studies are a rich resource for estimation and modeling of Alzheimer's disease (AD) progression. Datasets extracted from these studies often feature complex truncation (selection) and censoring. Estimates based on these datasets are used for (1) clinical trial design; (2) improved understanding of AD progression, risk and prevention; and (3) individual prediction, but do not fully account for the complex truncation. This proposal develops methods that make proper adjustments and thereby enhance each of these essential needs in AD. Use of time-to-event endpoints in clinical trials for AD is supported by regulatory authorities when the time origin and the…
From the public funding record at NIH RePORTER. Describes the funded project, not the reviews below.