Introduction to Survival Analysis
Survival data arise in a literal form from trials concerning life-threatening conditions, but the methodology can also be applied to other waiting times such as the duration of pain relief. This course discusses both the analysis and the design of clinical trials in which the response variable is a survival time.
This course emphasises the practical aspects of analysing survival data and interpreting models, but the underlying theory is explained as appropriate. In practical sessions participants apply the methods covered to a simulated clinical trial.
Most of the topics on the course are covered in the book Modelling Survival Data in Medical Research, by Dr Dave Collett (Associate Director of Statistics and Clinical Audit at NHS Blood and Transplant), published by Chapman and Hall/CRC.
Who Should Attend?
Statisticians engaged in medical research in public sector industries and in the pharmaceutical and related industries, who have little or no experience of dealing with survival data. No previous experience of R, SAS or Stata is required.
How You Will Benefit
This course will give a thorough introduction to survival analysis from basic methods through to commonly-used modelling approaches.
What Do We Cover?
Practical work will be done in: SAS. Participants may instead choose to use R or Stata.
Note: For practical work, participants must bring their own laptop with a fully licensed version of their chosen software.
Related Courses: Non-Proportional Hazards: Modelling the Restricted Mean Survival Time using R; Advanced Survival Analysis using R; Survival Analysis for Medical and Health Professionals; Advanced Topics in Survival Analysis; Survival Analysis using R.