Abstract Details
Activity Number:
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194
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Type:
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Contributed
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Date/Time:
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Monday, August 5, 2013 : 10:30 AM to 12:20 PM
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Sponsor:
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Biometrics Section
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Abstract - #309624 |
Title:
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Modeling Longitudinal Changepoint Data: Gradual or Abrupt Transition, or Simply a Linear Trend?
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Author(s):
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Shahedul Khan*+
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Companies:
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University of Saskatchewan
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Keywords:
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Longitudinal data ;
Changepoint data ;
Mixed-effects model
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Abstract:
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Data showing a trend that characterizes a change due to a system shock are commonly observed over time in biological, medical and health applications. As a result of the shock, a particular trajectory can exhibit an either gradual or abrupt transition. Moreover, a few profiles may also exhibit a seemingly linear trend. An example is an experiment on 38 rats conducted with an objective to collect information about the state of hypothermia and resuscitation strategy immediately after a 60% hemorrhage. In practice, hypothermia results in an initial increase in core body temperature before a decrease takes place. We found that a few rats appeared unusual, exhibiting linearly decreasing trends throughout. Although it would require further subject-matter research to investigate the physiological reason of such behavior, we develop a Bayesian modelling framework for bent-cable regression of longitudinal data to simultaneously account for gradual and abrupt transitions, as well as the linear trends over time. The proposed methodology has many attractive properties and has allowed us to model data from a scientific problem of great practical interest.
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Authors who are presenting talks have a * after their name.
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