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Abstract Details
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Activity Number:
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461
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Type:
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Contributed
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Date/Time:
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Wednesday, August 3, 2011 : 8:30 AM to 10:20 AM
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Sponsor:
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ENAR
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| Abstract - #300624 |
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Title:
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A Broad Framework for Joint Modeling
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Author(s):
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Geert Molenberghs*+
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Companies:
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Universiteit Hasselt/Katholieke Universiteit Leuven
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Address:
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Center for Statistics, Diepenbeek, B3590, Belgium
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Keywords:
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incomplete data ;
longitudinal data ;
joint modeling
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Abstract:
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Joint modeling is often interpreted in the narrow sense of modeling together a longitudinal and time-to-event outcome. However, the specific features of two (or more) outcomes recorded simultaneously, together with te phenomenon of unobservables, is very common, though disparate: informative cluster sizes; models for incomplete data; sequential trials; and time-to-event with censoring, to name a few. Starting from an extendes shared-parameter-model framework, we provide a comprehensive encompassing framework, within which we highlight communalities and differences. Connections with both likelihood inference and inverse probability weighting are brought to the forefront.
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Authors who are presenting talks have a * after their name.
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