This course runs online. There will be a short pre-recorded lecture and practical to do as pre-course preparation. The main course will be taught live, consecutively over 2 full days and 1 half day. There will be online lectures, practicals (mostly in Stata) and Q&A sessions. A short pre-recorded summary of each day will be made available.

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

1. calculate and interpret measures of disease rates and exposure effects;
2. manage and manipulate survival-time data in Stata;
3. produce and interpret graphical displays appropriate for survival analysis;
4. analyse survival-time data using Poisson and Cox regression models;
5. evaluate the uses and limitations of different methods for rates and survival analysis;
6. compare and test the assumptions made by different statistical methods;
7. model covariates which vary through time in survival analyses; and
8. interpret the results of survival analyses presented in the published literature.

The course is intended for researchers and analysts who wish to analyse and understand survival-time data (time to event data). We focus on popular methods of analysing these types of data, mainly Poisson and Cox regression.

The course will cover:

1. definition of rates and the relation between risks and rates;
2. manipulating person-time data in Stata using the st commands;
3. analysis of rates using Mantel-Haenszel methods and Poisson regression;
4. splitting follow-up time to allow for exposures that change with time;
5. introduction to survival analysis;
6. log rank tests and Cox proportional hazards regression;
7. testing for proportional hazards and modelling non-proportional hazards;
8. survival-time data management; and
9. choosing between survival analysis methods.

Please note that 'repeated measures' analyses, in which multiple events or measurements are recorded in the same person over time, are not covered in this course.

Dr David Carslake is a senior research associate in the MRC Integrative Epidemiology Unit at the University of Bristol. He has made extensive use of survival analysis methods, particularly Cox regression in instrumental variable analyses.

Dr Theresa Redaniel is a senior lecturer in Health Services Research and Epidemiology in Bristol Medical School. Her interests include health care evaluation, health services delivery, adverse childhood experiences, and mental health.

Dr Suzanne Ingle is a research fellow in Medical Statistics in Bristol Medical School. She has more than ten years' experience using survival analyses, particularly competing risk models, in HIV research.

Professor Jonathan Sterne is a professor of Medical Statistics and Epidemiology in Bristol Medical School, Director of the NIHR Bristol Biomedical Research Centre and Director of Health Data Research UK South-West. His interests include methods to make causal inferences from observational electronic health record data, methodology for systematic reviews and meta-analyses, and the clinical epidemiology of HIV and AIDS.

Dr Elinor Curnow is a senior research associate in Biostatistics and Epidemiology in Bristol Medical School.

Dr Adam Trickey is a research fellow in Bristol Medical School investigating the links between climate change and HIV in sub-Saharan Africa.

To make sure the course is suitable for you and you will benefit from attending, please ensure you meet the following prerequisites before booking:

Before booking this course, please make sure you read the information provided above about the target audience and prerequisites. It is important that you have access to the relevant IT resources needed for the course and meet the knowledge prerequisites to ensure you can get the most from the course.

Bookings are taken via our online booking system, for which you must register an account. To check if you are eligible for free or discounted courses please see our fees and voucher packs page. All bookings are subject to our terms & conditions, which can be read in full here.

For help and support with booking a course refer to our booking information page, FAQs or feel free to contact us directly. For available payment options please see: How to pay your short course fees.

Participants are granted access to our virtual learning platform (Blackboard) 1 to 2 weeks in advance of the course. This allows time for any pre-course work to be completed and to familiarise with the platform.

To gain the most from the course, we recommend that you attend in full and participate in all interactive components. We endeavour to record all live lecture sessions and upload these to the online learning environment within 24 hours. This allows course participants to review these sessions at leisure and revisit them multiple times. Please note that we do not record breakout sessions.

All course participants retain access to the online learning materials and recordings for 3 months after the course. 

University of Bristol staff and postgraduate students who do not wish to attend the full course may instead register for access to the 'Materials & Recordings' version of this course: Further information and bookings. 

100% of attendees recommend this course*.
*Attendee feedback from 2024.

Here is a sample of feedback from the last run of the course:

"Teachers enthusiastic and obviously very knowledgeable which is reassuring. The structure of lecture, then practical, then a break worked very well.” - Course feedback, June 2024.

"Content was very thorough and clear. Options for practical in demo and breakout rooms provided options for working separately.” - Course feedback, June 2024.

"Course layout was good. It started with basic concepts with complexity added in a step-wise manner, adequate time for practicals. Working alongside tutor-led practicals was useful as also picked up some general additional STATA tips and short hands.” - Course feedback, June 2024.

"Overall all the course lecturers/ facilitators were excellent; they gave very clear explanations and were friendly/approachable and open to questions.” - Course feedback, June 2024.

"Course has been a great introduction to survival analysis which I am using within my PhD. The testing of the proportional hazards assumption was particularly useful.” - Course feedback, June 2024.