Survival Analysis (SVA)

To enable students to analyse data from studies in which individuals are followed up until a particular event occurs, e.g. death, cure, relapse, making use of follow-up data also for those who do not experience the event, with proper attention to underlying assumptions and a major emphasis on the practical interpretation and communication of results.


Dr Ken Beath, Dept of Mathematics and Statistics, Macquarie University

A/Prof Jun Ma Macquarie University, Department of Statistics Semester 1
General outline


Epidemiology, Mathematical Background for Biostatistics, Probability and Distribution Theory, Principles of Statistical Inference, Linear Models

Time commitment

8-12 hours total study time per week

Semester availability

Semester 1


3 assignments: Assignment 1 (30%) Censoring and Truncation, Survival Summaries, KaplanMeier, Simple Cox models Assignment 2 (40%) Cox Models including interactions and stratification, Model building, diagnostics, predicted survival and cumulative hazard, Assignment 3 (30%) Time-dependent covariates, parametric models, multivariate survival, graphical presentation

Prescribed Texts

Hosmer D W, Lemeshow S, May S. Applied Survival Analysis: Regression modeling of time to event data, 2nd Edition. Wiley Interscience, 2008 For details, including ISBN, see the BCA Textbook and Software Guide

Recommended Texts

Recommended – not compulsory: Cleves M, Gould W, Gutierrez R, Marchenko Y. An Introduction to Survival Analysis Using Stata, 3rd edition, 2010. Stata Press – or

Special Computer Requirements

Stata (R optional) statistical software


Kaplan-Meier life tables; logrank test to compare two or more groups; Cox’s proportional hazards regression model; checking the proportional hazards assumption; time-dependent covariates; multiple or recurrent events; sample size calculations for survival studies.

Special Computer Requirements

Course notes, assignment material and interaction facilities available online