Statistical Services Centre

Applied Statistics at the University of Reading
...making sense of statistics

Advanced Topics in Survival Analysis


The most commonly used methods of dealing with survival, and other 'time to event' data, are based on the assumption of proportional hazards. This course is concerned with models for different types of data structure, or with different underlying assumptions.

During lectures and practical sessions the statistical package SAS is used to illustrate the methodologies.

Who Should Attend?

Statisticians in medical research in public sector institutions and in the pharmaceutical and related industries, who already have some familiarity with modelling survival data. In particular, some experience in using proportional hazards models will be advantageous.

How You Will Benefit

If you deal regularly with survival data and need more tools for their analysis, then this course will introduce you to a range of different survival analysis models.

What Do We Cover?

  • Overview of the Cox and Weibull proportional hazards models
  • The counting process input style
  • Accelerated failure time models
  • Time-dependent variates
  • Non-proportional hazards
  • Interval censored survival data
  • Informative censoring
  • Frailty models
  • Competing risks
  • Other parametric survival models.

Available Software

This course has practical exercises written for: SAS

Extra Information

Guest Presenters

Professor Dave Collett is the author of two highly acclaimed textbooks: Modelling Survival Data in Medical Research and Modelling Binary Data. He is currently Associate Director of Statistics and Clinical Audit at NHS Blood and Transplant, and is a Visiting Professor of Statistics at the Southampton Statistical Sciences Research Institute, University of Southampton.

Dr Alan Kimber is a Reader in the School of Mathematical Sciences, University of Southampton. He is Head of Statistics and also Deputy Director of the Southampton Statistical Sciences Research Institute. He has taught survival analysis for many years, has published a variety of journal articles in this subject area and has used survival analysis methods in applications in medicine, reliability engineering, materials science and sport.

Related Courses: Survival Analysis for Medical and Health Professionals; Survival Analysis using R; Introduction to Survival Analysis; Bayesian Survival Analysis

Discounts and consecutive courses: Additional discounts are available when you book Bayesian Survival Analysis course together with this course. Price: £1285 in total.

Course Dates

11 - 13 July 2017

Duration: 3 days

Price: £995

An Academic discount is available for this course

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Page last updated: November 20 2017 09:09:36.