Year of Publication

2017

Degree Name

Doctor of Philosophy (PhD)

Document Type

Doctoral Dissertation

College

Public Health

Department

Epidemiology and Biostatistics

First Advisor

Dr. Richard J. Charnigo

Second Advisor

Dr. David Fardo

Abstract

This dissertation involves an application of mixture of regression models to 114 individuals who are cognitively intact (from the Alzheimer's Disease and Neuroimaging Initiative-ADNI, data). The correct number of components in the model were estimated with the Singular BIC (SBIC), marking the first time it has been applied to such a problem. The smallest true model in conjunction with the approximation of SBIC was fixed at 1. The resulting posterior probabilities from the model were used to estimate the probability of a person transitioning and risk plots were obtained that could in principle be used by clinicians to identify patients at risk. This work also proposed a model selection criterion for mixture of regression models with application to the ADNI data. Finally simulation studies were conducted to compare the performance of the novel model selection and existing criteria.

Digital Object Identifier (DOI)

https://doi.org/10.13023/ETD.2017.100

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