Modelling techniques for time-to-event data analysis

Abstract

This thesis focusses on the cumulative hazard function as a tool for modelling time-to-event data, as opposed to the more common hazard or survival functions. By focussing on and providing a detailed discussion of the properties of these functions a new framework is explored for building complex models from, the relatively simple, cumulative hazards.Parametric families are thoroughly explored in this thesis by detailing types of parameters for time-to-event models. The discussion leads to the proposal of combination parametric families, which aim to provide flexible behaviour of the cumulative hazard function.A common issue in the analysis of time-to-event data is the presence of informative censoring. This thesis explores new models which are useful for dealing with this issue.

Date of Award	22 Nov 2018
Original language	English
Awarding Institution	University of Bath
Supervisor	Karim Anaya-Izquierdo (Supervisor)