Centre for Research Informatics Training

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Survival (time-to-event) analysis

Event details

Starting Tue 6 Oct 2026
eLearning (CCRIT) (map, venue information)
in-person

Sessions

  • 6 October 2026 — 09:30 to 17:00 — eLearning (CCRIT)

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About the course

An applied introduction to survival analysis for researchers who plan to use this method in their own research or studies.

The course focuses on key concepts and practical skills, with applied examples and datasets to teach implementation and model interpretation.

The course makes use of R and the survival/survminer packages. Some code in early chapters is also provided in Python using the lifelines package.

By the end of the course, participants should be able to:

  • Recognise key features of time-to-event data (e.g., censoring)
  • Visualise time-to-event data with survival curves
  • Run a log-rank test to compare survival curves
  • Build multivariate Cox regression models for more complex datasets
  • Interpret the output and assumptions of the above statistical tests
  • Know the limitations of the above statistical tests

Intended audience

This course is suitable for:

  • postgraduate students, postdoctoral researchers, and other researchers working with experimental or observational data
  • participants working on time-to-event data
  • researchers who already understand linear models and want to extend their statistical toolkit
  • participants with a working knowledge of R (and RStudio or similar IDE)

Prerequisites

Although this course is aimed at a non-specialist audience, it assumes that all attendees already have knowledge of core statistical concepts, especially linear modelling.

A working knowledge of R (and RStudio or similar IDE) is required. This is not an introductory programming course.

We strongly recommend first attending Core Statistics and/or Data Analysis in R if you do not already have equivalent statistical and basic R training.

Course fees

All fees are per full training day.

Category Fee
Industry full charge £130.00
Academic / Government / charity concessionary £65.00
Cambridge University staff members / postdocs / visitors £65.00
Cambridge University registered students Free
Cambridge University registered students non-attendance £22.00
Special events Per event

Payment options will be provided in booking confirmation emails sent after registration.

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General information

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