Review of EPA's Integrated Risk Information System (IRIS) Process (2014) / Chapter Skim
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Appendix C: Primer on Bayesian Method
Appendix C: Primer on Bayesian Method
Pages 150-154
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From page 150... ...
= 0.01. Now suppose that John Smith is routinely screened for HIV with the new blood test and that the test comes back positive.
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From page 151... ...
In that case, the Bayesian approach allows one to incorporate base rates easily and test reliability into a calculation of what one actually cares about: the probability of having HIV after getting a test result. In more general settings, the Bayesian approach can be used to transfer prior knowledge in one part of a model effectively into posterior knowledge in another part of the model of interest.
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From page 152... ...
The X-axis shows the size of (which in a simple linear model is the size of the IQ drop that one would expect in a 6-year-old after an exposure to enough lead to increase blood lead by 1 g/dL) , and the Y-axis is the posterior probability of , given our prior knowledge and the data that have been measured in 6year-olds.
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From page 153... ...
The major danger with Bayesian models for meta-analysis comes with specifying prior distributions for the between-study variance because information for this parameter is limited by the number of studies available and not by the size of each study. Typical noninformative priors do not work well, and some care must be taken to choose one that is sufficiently informative.
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