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Edmund Essah Ameyaw

Department of Mathematics, Howard University



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Paul Bezandry

Department of Mathematics, Howard University



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Victor Apprey

College of Medicine, Howard University



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John Kwagyan

College of Medicine, Howard University



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242 – Contributed Poster Presentations: Biometrics

The Evaluation of Integrals of the Form Equation: Application to Correlated Bivariate Logistic-Gaussian Models

Sponsor: Biometrics Section
Keywords: Correlated Data, Logistic -Gaussian Distribution, Maximum Marginal Likelihood, Bivariate Response, Gauss-Hermite quadrature

Edmund Essah Ameyaw

Department of Mathematics, Howard University

Paul Bezandry

Department of Mathematics, Howard University

Victor Apprey

College of Medicine, Howard University

John Kwagyan

College of Medicine, Howard University

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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