Main content

The Cumulative Effects of Time-Varying Covariates in Survival Analysis

Show full item record

Title: The Cumulative Effects of Time-Varying Covariates in Survival Analysis
Author: Lowe, Matthew
Department: Department of Mathematics and Statistics
Program: Mathematics and Statistics
Advisor: Horrocks, JulieDarlington, Gerarda
Abstract: Joint models for survival are modern statistical techniques for modelling the effect of time-varying covariates measured with error on the hazard of survival. Previous research has demonstrated that joint models have less bias compared to traditional Cox models with time-varying covariates. This thesis compares three association structures for joint models: the current value specification, the cumulative specification, and the weighted cumulative specification. The three methods were compared on two real data sets. A simulation study compared the three specifications when fit to data generated according to the current value specification. Results from the simulation show that the current value and weighted cumulative specifications provide similar estimates, with small bias and accurate standard deviation.
Date: 2020-11
Rights: Attribution 4.0 International

Files in this item

Files Size Format View
Lowe_Matthew_202012_MSc.pdf 630.7Kb PDF View/Open

This item appears in the following Collection(s)

Show full item record

Attribution 4.0 International Except where otherwise noted, this item's license is described as Attribution 4.0 International
The library is committed to ensuring that members of our user community with disabilities have equal access to our services and resources and that their dignity and independence is always respected. If you encounter a barrier and/or need an alternate format, please fill out our Library Print and Multimedia Alternate-Format Request Form. Contact us if you’d like to provide feedback:  (email address)