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...

Full description

Bibliographic Details
Main Author: Johnson, Andrew Robert
Format: Thesis
Published: Curtin University 2019
Online Access:http://hdl.handle.net/20.500.11937/79166
_version_ 1848764014122762240
author Johnson, Andrew Robert
author_facet Johnson, Andrew Robert
author_sort Johnson, Andrew Robert
building Curtin Institutional Repository
collection Online Access
description 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.
first_indexed 2025-11-14T11:12:37Z
format Thesis
id curtin-20.500.11937-79166
institution Curtin University Malaysia
institution_category Local University
last_indexed 2025-11-14T11:12:37Z
publishDate 2019
publisher Curtin University
recordtype eprints
repository_type Digital Repository
spelling curtin-20.500.11937-791662020-05-14T09:25:35Z A Bayesian Evaluation of Subtyping Methods in Parkinson’s Disease Johnson, Andrew Robert 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. 2019 Thesis http://hdl.handle.net/20.500.11937/79166 Curtin University fulltext
spellingShingle Johnson, Andrew Robert
A Bayesian Evaluation of Subtyping Methods in Parkinson’s Disease
title A Bayesian Evaluation of Subtyping Methods in Parkinson’s Disease
title_full A Bayesian Evaluation of Subtyping Methods in Parkinson’s Disease
title_fullStr A Bayesian Evaluation of Subtyping Methods in Parkinson’s Disease
title_full_unstemmed A Bayesian Evaluation of Subtyping Methods in Parkinson’s Disease
title_short A Bayesian Evaluation of Subtyping Methods in Parkinson’s Disease
title_sort bayesian evaluation of subtyping methods in parkinson’s disease
url http://hdl.handle.net/20.500.11937/79166