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Activity Number: 313
Type: Contributed
Date/Time: Tuesday, August 2, 2016 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistics in Epidemiology
Abstract #319228 View Presentation
Title: Statistical Modeling of Subject and Proxy Observations Using Weighted GEE
Author(s): Mina Hosseini* and Nagaraj K. Neerchal and Ann L. Gruber-Baldini
Companies: and University of Maryland Baltimore County and UMB
Keywords: Proxy ; GEE ; Weighted GEE ; WGEE
Abstract:

In epidemiological studies when the patients become unable to provide responses by themselves due to advancing severity of their conditions, proxy responses by a relative or a caregiver "proxy" are used. The resulting dataset contains a monotonically decreasing missing pattern for subject observations and a monotonically increasing missing pattern for proxy observations. Some statistical models are being investigated that can analyze subject and proxy observations together so that relevant parameters and their standard errors can be estimated in a single framework. The method of weighted Generalized Estimating Equations (GEE), which is commonly used for handling missing data, is applied to the combined proxy and subject dataset.


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