Aims

To present a statistical methodology for the analysis of survival time data stemming from medical experiments where patients are subjected to a treatment.

Learning Objectives

At the end of this module you should be able to:

• Provide descriptive statistics and graphical summaries of information contained in data from survival experiments in medical studies
• Use estimation and hypothesis testing for inference
• Use proportional hazards regression techniques to make inferences about the possible relationship between survival time and potential risk factors.

Syllabus

• Basic quantifiers of survival: survival and hazard function.
• Parametric models for survival dat
• Censoring and truncation.
• Estimation of basic quantities for censored data.
• Univariate estimation, hypothesis testing.
• Proportional hazards regression.

Recommended Texts

J P Klein & M L Moeschberger,  Survival Analysis: Techniques for Censored and Truncated Data.

Teaching

Spring Term, 2 lectures and 1 practical class per week.

Assessment

2 hour examination (90%) and coursework (10%).

Prerequisites

Core algebra, Calculus, Statistics I, Statistics II.