StATS: Steps in a typical Bayesian model (January 24, 2005)
I editorialized a year ago about this on the evidence-based Health List. "Should proponents of EBM be concerned about understanding the Bayesian philosophy? In my opinion, no. I think we'll gradually see Bayesian philosophy creep in to the design and analysis of clinical trials. For example, there are good Bayesian solutions, I understand, to the tricky issue of early stopping of clinical trials. But I doubt that we will see a wholesale rejection of both p-values AND confidence intervals in my lifetime. Too many people like me fail to fully understand the Bayesian paradigm for this to happen. So from a practical viewpoint, most of the medical research for the foreseeable future will be analyzed using the Frequentist paradigm."
John Platt recently mentioned two paper on the same list. Goodman Toward Evidence-Based Medical Statistics. 1: The P Value Fallacy Annals of Internal Medicine, 15 June 1999. 130:995-1004. Steven N. Goodman, MD, PhD Toward Evidence-Based Medical Statistics. 2: The Bayes Factor Annals of Internal Medicine, 15 June 1999. 130:1005-1013.
I also got an email encouraging me to write about Bayesian Statistics from
Bill Jefferys. He suggested Tom Loredo's "Bayesian Inference for the Physical
Sciences" (BIPS) page as a good resource.
Another good source of information is an article in the Journal of Statistics Education, which is available on the web.
Teaching Inference About Proportions Using Bayes and Discrete Models
Albert, J. (1995) Journal of Statistics Education [Online], 3(3)
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