A Bayesian Evaluation of Subtyping Methods in Parkinson’s Disease
Parkinson’s disease (PD) has significant heterogeneity in its presentation. To explain this heterogeneity, several motor subtypes have been proposed. These subtypes make assumptions about how symptoms change over time, the ability to measure symptoms, and the relationships between different symptoms...
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| Format: | Thesis |
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Curtin University
2019
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| Online Access: | http://hdl.handle.net/20.500.11937/79166 |
| Summary: | Parkinson’s disease (PD) has significant heterogeneity in its presentation. To explain this heterogeneity, several motor subtypes have been proposed. These subtypes make assumptions about how symptoms change over time, the ability to measure symptoms, and the relationships between different symptoms within a given disease subtype. However, current statistical approaches cannot test these assumptions. This thesis used Bayesian statistics to evaluate the assumptions underlying current subtyping methods and developed a new model of PD motor subtypes. |
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