Advisor

Shafie, Khalil

Committee Member

Yu, Han

Committee Member

Bahaedin, Khaledi

Committee Member

Apawu, Aaron

Department

College of Education and Behavioral Sciences; Department of Applied Statistics and Research Methods

Institution

University of Northern Colorado

Type of Resources

Text

Place of Publication

Greeley, (Colo.)

Publisher

University of Northern Colorado

Date Created

5-2022

Extent

246 pages

Digital Origin

Born digital

Abstract

The benefits of longitudinal data in clinical research are immense, owing to the potential to detect phenomenon changes and trends over time. An avalanche of traditional methods exist for the analysis of this data kind, most of which are predicated on the assumption of fixed time design for study individuals. This assumption however, is not always tenable. Consider occurrences that can alter the time or visit profile of subjects in a clinical trial, such as adverse events. These may result in not just irregular visit times, but also unbalanced data on subject outcomes. Hence, one can consider visit times to be informative, because subsequent subject visits can be altered based on current visits. In this dissertation, we developed Bayesian joint models for analyzing such scenarios. More broadly, the models jointly analyzed longitudinal outcomes resulting from the exponential class of distributions (specifically, Poisson, Bernoulli and Gamma longitudinal outcomes) and informative visit times drawn from the exponential distribution. A simulation approach was employed to investigate and validate the influence of controlled variations in visit patterns, prior and sample size schemes on model performance. As an application example, the Bayesian Bernoulli-Exponential joint model was applied to a bladder cancer data to study the effect of previous tumor occurrences on the likelihood of subsequent recurrence in subjects, while also studying the effect of other prognostic factors.

Degree type

PhD

Degree Name

Doctoral

Local Identifiers

Oduro_unco_0161D_11014.pdf

Rights Statement

Copyright is held by the author.

Available for download on Tuesday, November 01, 2022

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