Please use this identifier to cite or link to this item:
http://hdl.handle.net/11375/29133
Title: | Bivariate Mixture Cure Rate Model with Moran-Downton Weibull Distribution and Associated EM Algorithm Implementation |
Authors: | Pitt, Matilda |
Advisor: | Balakrishnan, Narayanaswamy Davies, Katherine |
Department: | Mathematics and Statistics |
Keywords: | Statistics |
Publication Date: | 2023 |
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. |
URI: | http://hdl.handle.net/11375/29133 |
Appears in Collections: | Open Access Dissertations and Theses |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Pitt_Matilda_J_finalsubmission2023September_Masters.pdf | 512.27 kB | Adobe PDF | View/Open |
Items in MacSphere are protected by copyright, with all rights reserved, unless otherwise indicated.