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Activity Number: 658
Type: Contributed
Date/Time: Thursday, August 2, 2012 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #306521
Title: Longitudinal Data Analysis with Measurement Errors and Nonignorable Missing Data
Author(s): Chi-hong Tseng*+ and Robert Elashoff and Gang Li
Companies: University of California at Los Angeles and University of California at Los Angeles and University of California at Los Angeles
Address: 10940 Wilshire, LA, CA, 90024, United States
Keywords: selection model ; missing not at random ; repeated measurement

Measurement errors problem occurs frequently in biological and clinical studies. The presence of measurement errors causes biased and inconsistent parameter estimates and leads to erroneous conclusions to various degrees in data analysis. In this research, we consider longitudinal outcome with measurement errors and non-ignorable missing data. We use the selection model to handle the non-ignorable missing data in the presence of measurement errors, and a pseudo likelihood approach for parameter estimation. Simulation study is carried out and a real data example from the Scleroderma lung study is used to demonstrate the effectiveness of this method.

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