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http://hdl.handle.net/11375/29133
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DC Field | Value | Language |
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dc.contributor.advisor | Balakrishnan, Narayanaswamy | - |
dc.contributor.advisor | Davies, Katherine | - |
dc.contributor.author | Pitt, Matilda | - |
dc.date.accessioned | 2023-10-25T20:51:55Z | - |
dc.date.available | 2023-10-25T20:51:55Z | - |
dc.date.issued | 2023 | - |
dc.identifier.uri | http://hdl.handle.net/11375/29133 | - |
dc.description.abstract | This thesis introduces a new bivariate cure rate model and develops an ExpectationMaximization (EM) algorithm in R to fit the model. Within survival analysis, cure rate models describe scenarios wherein part of the population is cured and therefore would never experience the event of interest. Under this set-up, bivariate cure rate models are needed when there is a pair of events of interest. Here, a Moran-Downton bivariate Weibull distribution is used to model the paired event times of the susceptible individuals. An EM algorithm is developed here and implemented in R for this parametric bivariate cure rate model. Simulation studies are then performed to evaluate the performance of the developed model-fitting methods and finally the algorithm is applied to a real life dataset on diabetic retinopathy. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | Statistics | en_US |
dc.title | Bivariate Mixture Cure Rate Model with Moran-Downton Weibull Distribution and Associated EM Algorithm Implementation | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Mathematics and Statistics | en_US |
dc.description.degreetype | Thesis | en_US |
dc.description.degree | Master of Science (MSc) | en_US |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
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Pitt_Matilda_J_finalsubmission2023September_Masters.pdf | 512.27 kB | Adobe PDF | View/Open |
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