Analysis of time to event data (Survival analysis)
Friday 4 November, 9:00am-1:00pm
Registration opens: Monday 17 October, 10am
Burwood Corporate Centre, Deakin Burwood Campus
In survival analysis, subjects are usually followed over a specified time period and the focus of the study is on the time at which an event of interest occurs. Why not use linear regression to model the survival time as a function of a set of predictor variables? Ordinary linear regression cannot effectively handle the censoring of observations. Survival methods correctly incorporate information from both censored and uncensored observations in the analysis.
The aim of this workshop is to provide the participants with basic concepts and techniques on how to analyse time-to-event (survival) data, including censoring, hazard and survival functions, Kaplan-Meier curves and logrank tests. An important focus of the workshop will be using data sets from clinical and epidemiological studies to illustrate the statistical methods and to show how to make scientific interpretations from the numerical results. The learning objective of this workshop is to give each participant an understanding and experience to interpret an analysis of time-to-event data.
This is a workshop to introduce survival analysis methods. Topics include:
- Why survival data needs special techniques
- Censoring of observations
- Estimation and comparison of survival curves with the Kaplan-Meier method
- Introduction to the Cox Proportional Hazard model
Who should attend?
PhD students and early career researchers within the Faculty of Health.
The workshop assumes some working knowledge of statistics and regression models.
Workshop participant numbers are capped to allow for discussion and interaction. We expect a high demand for these workshops therefore we strongly encourage registration ONLY if you can attend. We do understand that unforeseen circumstances occur which can prevent attendance, and in that case we ask that you cancel your registration AS A PRIORITY so that places can be filled by other interested candidates.
Mohammadreza Mohebbi, PhD, Senior Researcher Biostatistics