In categorical data analysis, the 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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Jose A. A. Andrade 1 ; Pushpa Rathie 2
@article{CRMATH_2023__361_G6_1063_0, author = {Jose A. A. Andrade and Pushpa Rathie}, title = {Exact {Posterior} distribution of risk ratio in the {Kumaraswamy{\textendash}Binomial} model}, journal = {Comptes Rendus. Math\'ematique}, pages = {1063--1069}, publisher = {Acad\'emie des sciences, Paris}, volume = {361}, year = {2023}, doi = {10.5802/crmath.469}, language = {en}, }
TY - JOUR AU - Jose A. A. Andrade AU - Pushpa Rathie TI - Exact Posterior distribution of risk ratio in the Kumaraswamy–Binomial model JO - Comptes Rendus. Mathématique PY - 2023 SP - 1063 EP - 1069 VL - 361 PB - Académie des sciences, Paris DO - 10.5802/crmath.469 LA - en ID - CRMATH_2023__361_G6_1063_0 ER -
Jose A. A. Andrade; Pushpa Rathie. Exact Posterior distribution of risk ratio in the Kumaraswamy–Binomial model. Comptes Rendus. Mathématique, Volume 361 (2023), pp. 1063-1069. doi : 10.5802/crmath.469. https://comptes-rendus.academie-sciences.fr/mathematique/articles/10.5802/crmath.469/
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