Defense Date

3-30-2006

Graduation Date

Spring 1-1-2006

Availability

Worldwide Access

Submission Type

thesis

Degree Name

MS

Department

Computational Mathematics

School

McAnulty College and Graduate School of Liberal Arts

Committee Chair

John C. Kern

Committee Member

Frank D'Amico

Committee Member

Kathleen Taylor

Keywords

Bayesian Analysis, Bayesian Hierarchical Modeling, Markov Chain, MCMC, Monte Carlo

Abstract

This thesis explores a Bayesian hierarchical model to compare treatment effectiveness for menopausal symptom relief. Specifically, this model recognizes the discrete nature of the data, as well as its time dependency. Bayesian analysis is used to make inference on each individual profile, as well as on a group profile for each treatment group.

Format

PDF

Language

English

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