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Markov Chain Monte Carlo-Based Bayesian Analysis of Binary Response Regression, with Illustration in Dose-Response Assessment
2009
Modern Applied Science
This paper deals with the Bayesian analysis of binary response regression using Markov chain Monte Carlo (MCMC) methods, more specifically the Metropolis sampler, for posterior simulation. The methodology is illustrated with real-world data from a bioassay experiment. Inference about quantities of typical interest in the dose-response setting such as the lethal dose is discussed as well. MCMC are routinely implemented through popular Bayesian software such as Win-/Open-BUGS. However, these
doi:10.5539/mas.v3n4p19
fatcat:dxcxqhivgnhlxd4uw6y3d6kjsu