Category: Bayesian statistics (created 2007-05-30). In Bayesian statistics, the researcher specifies a probability distribution prior to the start of the experiment that represents his/her degree of belief about the possible values of a process being studied. After data is collected, the Bayesian analysis produces a posterior distribution that combines  information from data with information from the prior distribution.

Articles are arranged by date with the most recent entries at the top. You can find outside resources at the bottom of this page. Other entries about Bayesian statistics can be found in the Bayesian statistics page at the StATS website.

2008

  1. P.Mean: What does the FDA think about Bayesian statistics (created 2008-07-08). The FDA is, in general, a cautious agency (as it should be), but they are allowing newer approaches for establishing efficacy and safety of new drugs. Many of these new approaches involve Bayesian methods. A draft guidance "Guidance for the Use of Bayesian Statistics in Medical Device Clinical Trials - Draft Guidance for Industry and FDA Staff" is available in HTML format or PDF format.
  2. P.Mean: Distrust of a Bayesian meta-analysis (created 2008-07-01). A regular correspondent on the evidence based health email discussion group (BA) raised some questions about the use of a Bayesian hierarchical model in a meta-analysis. He was worried about whether this approach would be appropriate for this type of data.

Outside resources:

  1. Bayesian Models for Gene Expression With DNA Microarray. Joseph G. Ibrahim, Ming-Hui Chen, Robert J. Gray. J American Statistical Association 2002: 97(457); 88-99. [PDF]. Description: This article presents a Bayesian selection criteria for identifying a small set of genes that can distinguish between different types of tissue.
  2. Decision theoretic designs for Phase II clinical trials with multiple outcomes. Nigel Stallard. Biometrics 1999: 55; 971-77. [Medline]. Description: This article provides a Bayesian approach to handling multiple comparisons in a trial where with multiple safety and efficacy endpoints.
  3. Empirical-Bayes adjustments for multiple comparisons are sometimes useful. S. Greenland, J. M. Robins. Epidemiology 1991: 2(4); 244-51. Description: This article proposes situations where adjustments for multiple comparisons are appropriate. The authors offer Empirical-Bayes and fully Bayesian approaches and describe their advantages over the traditional Bonferroni approach.
  4. Overview of Computer Intensive Statistical Inference Procedures (P. Adam Kelly). Description: This page provides a nice overview of the permutation test, randomization test, Monte Carlo estimation, bootstrapping, the jackknife, and Markov Chain Monte Carlo methods. This website was last verified on 2007-08-31. www.hsrd.houston.med.va.gov/AdamKelly/resampling.html

Creative Commons License All of the material above this paragraph is licensed under a Creative Commons Attribution 3.0 United States License. This page was written by Steve Simon and was last modified on 2008-11-25. The material below this paragraph links to my old website, StATS. Although I wrote all of the material listed below, my ex-employer, Children's Mercy Hospital, has claimed copyright ownership of this material. The brief excerpts shown here are included under the fair use provisions of U.S. Copyright laws.

2008

[[Links to old material were accidentally deleted. I'll fix this soon.]]

What now?

Browse other categories at this site

Browse through the most recent entries

Get help