Short courses


Survival Analysis (Time-to-Event Data): an Introduction

  • 9:30am to 1pm
  • 2 days


This short course for non-statisticians will introduce you to the concept of modelling time-to-event data ('survival analysis').

Survival/time-to-event analysis is appropriate when the outcome of interest is an event and that event has not occurred for everyone in the dataset. The outcome can be something negative (e.g. death, recurrence of a tumour) or something positive (e.g. recovery, task completion).

The simplest analysis is the log-rank test that assesses differences according to a single factor. Cox proportional hazards regression is appropriate to investigate the rate at which the event occurs according to several potential predictors. Both will be covered in this course.

This course takes place online, over two mornings (9:30am to 1pm). 

This course is run by UCL's Centre for Applied Statistics Courses (CASC), part of the UCL Great Ormond Street Institute of Child Health (ICH).

Course content

This workshop will cover the following topics:

  • Use of Kaplan-Meier plots
  • Life tables
  • Cox regression analyses
  • Hazard ratios
  • How to set up the data for analysis
  • Including interaction terms in the models
  • Assessing model outliers
  • Interpretation of SPSS output

Software used

Please note that there will be no actual computer work during the workshop. Although SPSS is used for illustration purposes, the workshop is suitable if you're using other software packages.

The datasets can be taken away and models fitted using alternative software.

Who this course is for

The course is for non statisticians and is open to anyone who wants to learn about the basics of survival/time-to-event analysis.

Knowledge of the very basics of statistics (such as means, standard deviation, confidence intervals, etc.) is beneficial.

Learning outcomes

By the end of this course you should be able to:

  • recognise the applicability of time-to-event/survival analyses
  • understand censoring
  • understand how life-tables and Kaplan-Meier plots are constructed
  • understand the applicability and limitations of log-rank testing
  • have a basic understanding of Cox proportional hazards regression
  • compare Cox models and identify outliers
  • know how to set up a dataset for time-varying covariates

Cost and concessions

The fees are as follows:

  • External delegates (non UCL) - £150
  • UCL staff, students, alumni - £75*
  • ICH/GOSH staff and doctoral students - free    

* valid UCL email address and/or UCL alumni number required upon registration


You can request a certificate of attendance for this course once you've completed it. Please send your request to ich.statscou@ucl.ac.uk

Include the following in your email:

  • the name of the completed course for which you'd like a certificate
  • how you'd like your name presented on the certificate (if the name/format differs from the details you gave during registration)


Read the cancellation policy for this course on the ICH website. Please send all cancellation requests directly to the course administrator.

Find out about other statistics courses

CASC's stats courses are for anyone requiring an understanding of research methodology and statistical analyses. The courses will allow non-statisticians to interpret published research and/or undertake their own research studies.

Find out more about CASC's full range of statistics courses, and the continuing statistics training scheme (book six one-day courses and get a seventh free.) 

Course team

Dr Chibueze Ogbonnaya

Dr Chibueze Ogbonnaya

Since joining the teaching team at CASC in February 2019, Chibueze has contributed to the teaching and development of short courses. He currently leads and co-leads short courses on MATLAB, missing data, regression analysis and survival analysis. Chibueze has a BSc in Statistics from the University of Nigeria, where he briefly worked as a teaching assistant after graduation. He then moved to the University of Nottingham for his MSc and PhD in Statistics. His research interests include functional data analysis, applied machine learning and distribution theory.

Dr Eirini Koutoumanou

Dr Eirini Koutoumanou

Eirini has a BSc in Statistics from Athens University of Economics and Business and an MSc in Statistics from Lancaster University (funded by the Engineering and Physical Sciences Research Council). She joined UCL GOS Institute of Child Health in 2008 to develop a range of short courses for anyone interested in learning new statistical skills. Soon after, CASC was born. In 2014, she was promoted to Senior Teaching Fellow. In 2019, she successfully passed her PhD viva on the topic of Copula models and their application within paediatric data. Since early 2020 she has been co-directing CASC with its founder, Emeritus Professor Angie Wade and has been the sole Director of CASC since January 2022.

Learner reviews

"A well-taught and helpful course. Thank you!"

"Excellent course. Only stats course I have understood all the way through. Angie Wade was a great teacher - very clear. Both tutors very approachable with queries about specifics of my project. Thank you very much."

"Enjoyed the course - the course administrator was very good and explained it well. I feel that I have gained from going on this course."

"Very enjoyable, good value for money."

Course information last modified: 19 Apr 2022, 10:11