Bayesian Analysis of Discrete Longitudinal Data

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.

Name thesis:degree_name

MS

Level thesis:degree_level

Worldwide Access

Discipline thesis:degree_discipline

Computational Mathematics

Year dc:date.available

2006

Author dc:creator

• Bernini, Nicholas

Contributors dc:contributor

• John C. Kern
• Frank D'Amico
• Kathleen Taylor

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

Language dc:language

English

Repository record dc:identifier

https://dsc.duq.edu/etd/19

OAI identifier oai:identifier

oai:dsc.duq.edu:etd-1018