Exact Posterior distribution of risk ratio in the Kumaraswamy–Binomial model

In categorical data analysis, the $2\times 2$ contingency tables are commonly used to assess the association between groups and responses, this is achieved by using some measures of association, such as the contingency coefficient, odds ratio, risk relative, etc. In a Bayesian approach, the risk rat...

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Main Authors: Andrade, Jose A. A., Rathie, Pushpa
Format: Article
Language:English
Published: Académie des sciences 2023-09-01
Series:Comptes Rendus. Mathématique
Online Access:https://comptes-rendus.academie-sciences.fr/mathematique/articles/10.5802/crmath.469/
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author Andrade, Jose A. A.
Rathie, Pushpa
author_facet Andrade, Jose A. A.
Rathie, Pushpa
author_sort Andrade, Jose A. A.
collection DOAJ
description In categorical data analysis, the $2\times 2$ contingency tables are commonly used to assess the association between groups and responses, this is achieved by using some measures of association, such as the contingency coefficient, odds ratio, risk relative, etc. In a Bayesian approach, the risk ratio is modeled according to a Beta-Binomial model, which has exact posterior distribution, due to the conjugacy property of the model. In this work, we provide the exact posterior distribution of the relative risk for the non-conjugate Kumaraswamy–Binomial model. The results are based on special functions and we give exact expressions for the posterior density, moments, and cumulative distribution. An example illustrates the theory.
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spelling doaj-art-e8820b8450ac4704b210b75287a590d92025-02-07T11:09:17ZengAcadémie des sciencesComptes Rendus. Mathématique1778-35692023-09-01361G61063106910.5802/crmath.46910.5802/crmath.469Exact Posterior distribution of risk ratio in the Kumaraswamy–Binomial modelAndrade, Jose A. A.0Rathie, Pushpa1Department of Statistics and Applied Mathematics, Federal University of Ceara, 60455-670, Fortaleza-Ce, BrazilDepartment of Statistics, University of Brasilia, 70910-900, Brasilia-DF, BrazilIn categorical data analysis, the $2\times 2$ contingency tables are commonly used to assess the association between groups and responses, this is achieved by using some measures of association, such as the contingency coefficient, odds ratio, risk relative, etc. In a Bayesian approach, the risk ratio is modeled according to a Beta-Binomial model, which has exact posterior distribution, due to the conjugacy property of the model. In this work, we provide the exact posterior distribution of the relative risk for the non-conjugate Kumaraswamy–Binomial model. The results are based on special functions and we give exact expressions for the posterior density, moments, and cumulative distribution. An example illustrates the theory.https://comptes-rendus.academie-sciences.fr/mathematique/articles/10.5802/crmath.469/
spellingShingle Andrade, Jose A. A.
Rathie, Pushpa
Exact Posterior distribution of risk ratio in the Kumaraswamy–Binomial model
Comptes Rendus. Mathématique
title Exact Posterior distribution of risk ratio in the Kumaraswamy–Binomial model
title_full Exact Posterior distribution of risk ratio in the Kumaraswamy–Binomial model
title_fullStr Exact Posterior distribution of risk ratio in the Kumaraswamy–Binomial model
title_full_unstemmed Exact Posterior distribution of risk ratio in the Kumaraswamy–Binomial model
title_short Exact Posterior distribution of risk ratio in the Kumaraswamy–Binomial model
title_sort exact posterior distribution of risk ratio in the kumaraswamy binomial model
url https://comptes-rendus.academie-sciences.fr/mathematique/articles/10.5802/crmath.469/
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