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A Functional Decline Model for Prevalent Cohort Data

Liu, Xinhua; Tsai, Wei-Yann; Stern, Yaakov

Longitudinal designs are often used for studying the natural history of diseases. Data sets typically consist of short series of repeated measures on prevalent cases. We propose a growth model approach to the analysis of follow-up data to describe functional decline and associated risk factors in disease progression. We illustrate the model with an application to longitudinal data that describe the time-evolution of cognitive decline in a cohort of patients with Alzheimer's disease.

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More About This Work

Academic Units
Neurology
Published Here
February 22, 2018
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