3128 Copula-Based Regression Models for Correlated Bivariate Binary Outcomes: Application to Ophthalmologic Data Structures

OBJECTIVES/SPECIFIC AIMS: To account for association between the pair of binary outcomes, we adopt the Clayton and Frank copulas to indirectly specify their joint distributions. METHODS/STUDY POPULATION: We propose a regression model for the joint modelling of correlated bivariate outcomes using cop...

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Detalles Bibliográficos
Autores principales: Alqahtani, Haifa, Kwagyan, John
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2019
Materias:
Basic/Translational Science/Team Science
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6799175/
http://dx.doi.org/10.1017/cts.2019.19
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author Alqahtani, Haifa
Kwagyan, John
author_facet Alqahtani, Haifa
Kwagyan, John
author_sort Alqahtani, Haifa
collection PubMed
description OBJECTIVES/SPECIFIC AIMS: To account for association between the pair of binary outcomes, we adopt the Clayton and Frank copulas to indirectly specify their joint distributions. METHODS/STUDY POPULATION: We propose a regression model for the joint modelling of correlated bivariate outcomes using copulas. RESULTS/ANTICIPATED RESULTS: develop full maximum likelihood inference.
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spelling pubmed-67991752019-10-28 3128 Copula-Based Regression Models for Correlated Bivariate Binary Outcomes: Application to Ophthalmologic Data Structures Alqahtani, Haifa Kwagyan, John J Clin Transl Sci Basic/Translational Science/Team Science OBJECTIVES/SPECIFIC AIMS: To account for association between the pair of binary outcomes, we adopt the Clayton and Frank copulas to indirectly specify their joint distributions. METHODS/STUDY POPULATION: We propose a regression model for the joint modelling of correlated bivariate outcomes using copulas. RESULTS/ANTICIPATED RESULTS: develop full maximum likelihood inference. Cambridge University Press 2019-03-27 /pmc/articles/PMC6799175/ http://dx.doi.org/10.1017/cts.2019.19 Text en © The Association for Clinical and Translational Science 2019 http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-ncnd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
spellingShingle Basic/Translational Science/Team Science
Alqahtani, Haifa
Kwagyan, John
3128 Copula-Based Regression Models for Correlated Bivariate Binary Outcomes: Application to Ophthalmologic Data Structures
title 3128 Copula-Based Regression Models for Correlated Bivariate Binary Outcomes: Application to Ophthalmologic Data Structures
title_full 3128 Copula-Based Regression Models for Correlated Bivariate Binary Outcomes: Application to Ophthalmologic Data Structures
title_fullStr 3128 Copula-Based Regression Models for Correlated Bivariate Binary Outcomes: Application to Ophthalmologic Data Structures
title_full_unstemmed 3128 Copula-Based Regression Models for Correlated Bivariate Binary Outcomes: Application to Ophthalmologic Data Structures
title_short 3128 Copula-Based Regression Models for Correlated Bivariate Binary Outcomes: Application to Ophthalmologic Data Structures
title_sort 3128 copula-based regression models for correlated bivariate binary outcomes: application to ophthalmologic data structures
topic Basic/Translational Science/Team Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6799175/
http://dx.doi.org/10.1017/cts.2019.19
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