Introduction to Rates and Survival Analysis

Coronavirus (COVID-19) information

The Short Course Programme in Population Health Sciences has been temporarily suspended.


We anticipate opening bookings in late November 2020.

Information on this page relates to the last run of the course and is for reference only. 

Mailing List

Sign up to our mailing list to be notified when bookings reopen. 

We may need to make responsive changes to our future programme to follow the latest Public Health, Government and University guidance on coronavirus (COVID-19).

Please be aware that all information about short courses planned for 2021 is provisional and subject to change.

Course dates

25 - 26 June 2020

Course duration

2 days (approximately 7 hours of lectures and 5 hours of practicals).
Registration will start at 9am on the first day, the course will finish by 5pm on the final day.

Course tutors

Dr David Carslake, Dr Theresa Redaniel (course organisers), Prof. Jonathan Sterne, Dr. Sue Ingle, Dr. Rosy Reynolds, Dr. Tim Jones, Dr. Fanny Kilpi and Dr. Michelle Taylor

Course aims

The course aims to give students a grounding in the theory behind the methods most commonly used to analyse rates and survival-time data, as well as extensive hands-on experience of their application in Stata software.

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. This topic is covered in the 'Analysis of Repeated Measures' course.

Course objectives

By the end of the course students 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.  

Who the course is intended for

The course is intended for researchers and analysts who wish to analyse and understand data in the form of rates (events which occur over a specified period of time). We focus on popular methods of analysing these types of data, mainly Poisson and Cox regression.

Prerequisites - Participants should have a knowledge of regression analyses and their implementation in Stata of at least the level achieved in the 'Introduction to Linear and Logistic Regression Models' short course. Computer practicals are an important component of the course and will use the Stata software package. Familiarity with Stata is a prerequisite for this course.

Course outline

  • Definition of rates and the relation between risks and rates
  • Manipulating person-time data in Stata using the st commands
  • Analysis of rates using Mantel-Haenszel methods and Poisson regression
  • Splitting follow-up time to allow for exposures that change with time
  • Introduction to survival analysis
  • Log rank tests and Cox proportional hazards regression
  • Graphical displays for survival analysis
  • Cox models with continuously time-varying covariates

Please note: Practical sessions of this course will be held in a computer lab, so you will not need to bring a laptop. This course will use Stata v15.0Please bring a scientific calculator with you.

Recommended reading

The following texts may be useful, but are not required reading:

  • For those planning to attend other Departmental statistics courses we would recommend a copy of: Kirkwood BR, Sterne JAC, Essential Medical Statistics, 2nd ed. Oxford: Blackwell Science 2003 - but it is not compulsory for this course.   
  • An Introduction to Survival Analysis Using Stata, 3rd edition. Mario Cleeves, William Gould, Roberto Gutierrez, Yulia Marchenko. Stata Press 2010.   
  • Survival Analysis and Epidemiological Tables Reference Manual. Stata Press 2011.   
  • Collett D. Modelling Survival Data in Medical Research. 2nd Edition. Chapman and Hall 2003.   
  • Clayton D. and Hills M. Statistical Models in Epidemiology. Oxford University Press 1993. 

Just what it said on the box - perfect intro to survival analyses!

Course feedback, May 2018

Course fee


More information on course fees, fee waivers and reduced prices.

Course venue

Bristol Medical School
Canynge Hall
39 Whatley Road
United Kingdom

Map and directions

Course refreshments

We provide morning and afternoon refreshment breaks, including tea and coffee, biscuits and fresh fruit.

If you have specific dietary needs we ask that you let us know in advance.

Lunch is not included. There are a range of local cafes and supermarkets nearby for students to purchase lunch. 


Information about accommodation in the area.


For further information please email

Edit this page