Activity Number:
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242
- Contributed Poster Presentations: Biometrics
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Type:
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Contributed
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Date/Time:
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Monday, July 31, 2017 : 2:00 PM to 3:50 PM
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Sponsor:
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Biometrics Section
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Abstract #324266
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Title:
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The Evaluation of Integrals of the Form [f(s,t)*Bivariate Normal(s,t)]. Application to Correlated Bivariate Logistic-Gaussian Models
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Author(s):
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Edmund Ameyaw* and Paul Bezandry and Victor Apprey and John Kwagyan
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Companies:
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Howard University and Howard University and Howard University and Howard University College of Medicine, General Clinical Research Center
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Keywords:
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Correlated Data ;
Logistic -Gaussian Distribution ;
Maximum Marginal Likelihood ;
Bivariate Response ;
Gauss-Hermite quadrature
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Abstract:
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The Logistic-Gaussian distribution is used in statistical applications to account for clustering among binary outcomes. However, its extension and applicability to bivariate outcomes is limited. We developed a model for correlated bivariate binary data that incorporated the Logistic-Gaussian distribution. A bivariate normally distributed variate is decomposed into a product of two univariate normally distributed variate and applied to the development of a correlated bivariate logistic Gaussian model. Bivariate response probabilities in terms of random effects models are formulated, and maximum marginal likelihood estimation procedures based on Gauss-Hermite quadrature are used. Application to the analysis of vision loss in diabetic retinopathy is discussed.
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Authors who are presenting talks have a * after their name.