Date of Award

12-2021

Degree Type

Thesis

Degree Name

Master of Science - Mathematical Sciences

Department

College of Science and Mathematics

First Advisor

Jacob Turner

Second Advisor

Jeremy Becnel

Third Advisor

Kent Riggs

Fourth Advisor

Robert Henderson

Abstract

In this work, we take a close look at a general extension to the traditional AB/BA
crossover design that is commonly used in clinical trials to determine the effectiveness
of new candidate drugs. While the traditional crossover design requires each patient
in the study to be measured on both treatment A and treatment B, we consider the
possibility of additional measurements being available on each patient. This produces
designs such as the AABB/BBAA design which has been used in previous studies.
A general test statistic will be derived to test for treatment effects as well as its
corresponding power function to aid in sample size determination to aid statistical
planning. Lastly, we explore the theoretical power of our testing procedure and
compare it to simulated power studies to verify how well sample size determinations
will work in practice.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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