Abstract Details
Activity Number:
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249
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Type:
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Contributed
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Date/Time:
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Monday, August 4, 2014 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistical Consulting
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Abstract #312989
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Title:
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Rate Data Modeling: Using the Organ Procurement and Transplantation Network/United Network for Organ Sharing Database
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Author(s):
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Meng-Ru Cheng*+ and Amylou Dueck and Evan P. Kransdorf and Octavio E. Pajaro and Yu-Hui Chang
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Companies:
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Mayo Clinic and Mayo Clinic and Mayo Clinic and Mayo Clinic and Mayo Clinic
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Keywords:
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rate data ;
Poisson regression ;
negative binomial regression ;
zero-inflation
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Abstract:
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Poisson regression is widely used for analyzing count and rate data in clinical research. However, the assumption for equal variance and mean is difficult to satisfy in many practical settings. The purpose of this presentation is to demonstrate the range of analyses available for rate data. Approaches are illustrated with heart transplant data from the OPTN/UNOS database. We will examine the effect of match for ethnicity between organ donor and recipient on the rate of coronary allograft vasculopathy (CAV) events after heart transplant. The model diagnostics including scale and dispersion parameters will be evaluated for Poisson regression, negative binomial regression, zero-inflated Poisson Regression, and zero-inflated negative binomial regression. The model fit statistics and results will be compared and contrasted across different models. For each of the four fitted models, the graphics will be presented. The models ultimately show that match for ethnicity increases the risk of CAV for Caucasians but decreases the risk for Latinos, to varying degrees depending on the model selected.
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Authors who are presenting talks have a * after their name.
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