A General Gibbs Sampling Algorithm for Analyzing Linear Models Using the Sas System
نویسندگان
چکیده
A general Gibbs sampling algorithm for analyzing a broad class of linear models under a Bayesian framework is presented using Markov Chain Monte Carlo (MCMC) methodology in the SAS system. The analysis of a North Central Cancer Treatment Group (NCCTG) oncology clinical trial involving a two-period two-treatment crossover design is presented as an example. Results for the Bayesian model are compared to standard linear models analysis of variance procedures.
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