title: Bayesian inference of risk ratio of two proportions using a double sampling scheme.
abstract: We consider Bayesian point and interval estimation for a risk ratio of two proportion parameters using two independent samples of binary data subject to misclassification. In order to obtain model identifiability, we apply a double sampling scheme. For the identifiable model, we propose a Bayesian method for statistical inference for a two proportion risk ratio. Specifically, we derive an easy-to-implement closed-form sampling algorithm to draw from the posterior distribution of interest. We demonstrate the efficiency of our algorithm for Bayesian inference via Monte Carlo simulation studies and using a real data example.
authors: Department of Clinical Sciences and Simmons Cancer Center, UT Southwestern Medical Center, Dallas, Texas 75390-8822, USA. rahardja@gmail.com
authors: Dewi
authors: D
authors: Rahardja
authors: Dean M
authors: DM
authors: Young
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D003198:Computer Simulation; D006801:Humans; D015233:Models, Statistical; D009010:Monte Carlo Method; D016017:Odds Ratio; D012107:Research Design; D013269:Stochastic Processes