Abstract Details
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Activity Number:
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562
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Type:
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Contributed
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Date/Time:
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Wednesday, August 6, 2014 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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Abstract #312963
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Title:
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Joint Models of Longitudinal Outcomes and Informative Time
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Author(s):
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Jangdong Seo*+ and Khalil Shafie
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Companies:
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University of Northern Colorado and University of Northern Colorado
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Keywords:
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longitudinal data analysis ;
joint model
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Abstract:
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In a longitudinal data analysis, it is commonly assumed that time intervals for collecting outcomes are predetermined; same across all subjects and have no information regarding the measured variables. However, in practice occasionally researchers might have irregular time intervals and informative time schedule, which violate the above assumptions. Hence, if traditional statistical methods are used for this situation, the results would be biased. In this study, we present a joint model of longitudinal outcome and informative schedule. This model is designed to handle outcomes from a member of the exponential family of distributions with informative time following an exponential distribution. For the proposed model, maximum likelihood estimation of the parameters and their asymptotic properties will be discussed.
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Authors who are presenting talks have a * after their name.
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