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Activity Number:
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24
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Type:
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Contributed
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Date/Time:
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Sunday, July 29, 2007 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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| Abstract - #310001 |
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Title:
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A Local Sensitivity Analysis Approach to Longitudinal Binary Data with Nonignorable Dropout
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Author(s):
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Hui Xie*+
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Companies:
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University of Illinois at Chicago
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Address:
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1924 Wilmette Avenue, Wilmette, IL, 60091,
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Keywords:
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Missing data ; Missing not at Random ; Nonignorability
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Abstract:
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Longitudinal binary data subject to potentially nonignorable dropout is a challenging problem. Frequently an analysis has to rely on some strong but unverifiable assumptions, among which ignorability is a key one. Sensitivity analysis has been advocated to assess the likely effect of alternative assumptions about dropout mechanism on such an analysis. Previously Ma et al. (2005) applied a general index of local sensitivity to nonignorability (ISNI} (Troxel et al. 2004) to measure the sensitivity of MAR estimates to small departures from ignorability for continuous longitudinal outcomes. We extend the ISNI methodology to handle longitudinal binary data subject to nonignorable dropout. Through a simulation study, we evaluate the performance of the proposed methodology. We then illustrate the method in two real examples.
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