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Topics in Bayesian inference : induced priors, proof loading for combination drugs, and distribution of archaeological skeletal assemblages.

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dc.contributor.advisor Seaman, John Weldon, 1956-
dc.contributor.advisor Stamey, James D.
dc.contributor.author Seaman, John W., 1984-
dc.contributor.other Baylor University. Dept. of Statistical Sciences. en
dc.date.copyright 2010-05
dc.identifier.uri http://hdl.handle.net/2104/7961
dc.description.abstract Many illnesses are often treated with a combination of drugs. These combinations can be more effective than using any of the component drugs individually, but may lead to increased safety concerns. Prior to human trials with the combination, what can be said about efficacy and/or safety of the combination? An experimental design known as proof loading allows us to obtain preliminary estimates about the joint probability of an adverse event, without exposing patients to the combination drug. We propose a Bayesian distribution-free approach to proof loading as a possible solution to this problem. Our proof-loading model requires the specification of prior distributions. As we shall see, the priors are conditional and induce a prior on the joint probability of an adverse event. We consider this problem of induced priors more generally, examining several examples in the literature as well as our own prior structure. We offer a straight-forward protocol for handling induced priors. As an applied chapter, we propose a Bayesian model for studying distributions of bone types in archaeological bone assemblages. Anthropologists are interested in the evenness of an assemblage of bones across bone types. Based on the evenness of the distribution, hypotheses can be formed about the species of the hunter and what kind of transport strategy was required. We compare our method to a current method in examples and in a small-scale simulation study. Here again the issue of induced priors becomes important. en
dc.rights Baylor University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. Contact librarywebmaster@baylor.edu for inquiries about permission. en
dc.subject Bayesian inference. en
dc.subject Transformed priors. en
dc.subject Evenness criterion. en
dc.subject Proof loading. en
dc.subject Drug combination. en
dc.title Topics in Bayesian inference : induced priors, proof loading for combination drugs, and distribution of archaeological skeletal assemblages. en
dc.type Thesis en
dc.description.degree Ph.D. en
dc.rights.accessrights Worldwide access. en
dc.rights.accessrights Access changed 3/18/13.
dc.contributor.department Statistical Sciences. en


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