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Activity Number: 187
Type: Contributed
Date/Time: Monday, August 10, 2015 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract #315131 View Presentation
Title: A Mixed-Effects Model for Nonignorable Missing Longitudinal Data
Author(s): Xuan Bi* and Annie Qu
Companies: University of Illinois at Urbana-Champaign and University of Illinois at Urbana-Champaign
Keywords: Missing not at random ; Non-monotone missing pattern ; Quadratic inference function ; Refreshment sampling ; Shared-parameter model

Nonignorable missing data occur frequently in longitudinal studies. Estimation bias may arise if a missing mechanism is misspecified. To address this issue, we introduce a mixed-effects estimating equation approach, which enables one to recover missing information from the measurement process and the missing process simultaneously. The proposed method proves consistency and asymptotic normality of the fixed-effect estimation under shared-parameter models and an extended shared-parameter model. In simulation studies, we show the effectiveness of the proposed method under different missing mechanisms in conjunction with robustness against model assumption violation. In addition, it is applied to the election poll survey data from 2007-2008 Associated Press-Yahoo! News which involves multiple refreshment samples.

Authors who are presenting talks have a * after their name.

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