The aim of this thesis is to develop methodology for combining multiple endpoints within a single statistical analysis that compares the responses of patients treated with a novel treatment with those of control patients treated conventionally. The focus is on interval-censored bivariate survival data, and five real data sets from previous studies concerning multiple responses are used to illustrate the techniques developed. The background to survival analysis is introduced by a general description of survival data, and an overview of existing methods and underlying models is included. A review is given of two of the most popular survival analysis methods, namely the logrank test and Cox's proportional hazards model. The global score test m...
Objectives. 1. Identify the most appropriate test to be used when the equality of survival curves is...
In clinical practice the event of interest does not always occur equally across the study time perio...
Studies with time-to-event endpoints and small sample sizes are commonly seen; however, most statist...
In clinical trials, the main purpose is often to compare efficacy between experimental and control t...
The question of how to compare survival between two or more groups is considered mainly with a view ...
Multiple biomarkers (surrogate endpoints) are often used to predict the failure event, as well as to...
In clinical studies of survival, additional endpoints on patients may be collected over the course o...
Survival data arises when there is interest in the length of time until a particular event occurs e....
Although semi- and non-parametric approaches are frequently used to analyse survival data, there are...
Survival analysis is a collection of statistical procedures for data analysis where the outcome vari...
The aim of the thesis is to critically review, apply and where appropriate develop statistical metho...
Aims and objectives. This paper describes when and why survival analysis is used and describes the u...
Most analyses of survival data use primarily Kaplan-Meier plots, logrank tests and Cox models. We ha...
In the analysis of censored survival data, it is frequently of interest to determine the efficacy of...
Objective: To develop statistical tools that utilize combined initial survival data and post-resusci...
Objectives. 1. Identify the most appropriate test to be used when the equality of survival curves is...
In clinical practice the event of interest does not always occur equally across the study time perio...
Studies with time-to-event endpoints and small sample sizes are commonly seen; however, most statist...
In clinical trials, the main purpose is often to compare efficacy between experimental and control t...
The question of how to compare survival between two or more groups is considered mainly with a view ...
Multiple biomarkers (surrogate endpoints) are often used to predict the failure event, as well as to...
In clinical studies of survival, additional endpoints on patients may be collected over the course o...
Survival data arises when there is interest in the length of time until a particular event occurs e....
Although semi- and non-parametric approaches are frequently used to analyse survival data, there are...
Survival analysis is a collection of statistical procedures for data analysis where the outcome vari...
The aim of the thesis is to critically review, apply and where appropriate develop statistical metho...
Aims and objectives. This paper describes when and why survival analysis is used and describes the u...
Most analyses of survival data use primarily Kaplan-Meier plots, logrank tests and Cox models. We ha...
In the analysis of censored survival data, it is frequently of interest to determine the efficacy of...
Objective: To develop statistical tools that utilize combined initial survival data and post-resusci...
Objectives. 1. Identify the most appropriate test to be used when the equality of survival curves is...
In clinical practice the event of interest does not always occur equally across the study time perio...
Studies with time-to-event endpoints and small sample sizes are commonly seen; however, most statist...