Introduction to Rates and Survival Analysis

An online short course

This 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.

Course date 14 - 15 June 2021
Course fee £440
Course Organisers Dr David Carslake & Dr Theresa Redaniel

Prerequisites

Please ensure you meet the following prerequisites before booking:

Knowledge Participants should be familiar with the basic Stata commands used to open a dataset, get help on a command, and explore, create and edit variables.
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.
Software Participants will need a computer and internet connection capable of video conferencing whilst running Stata (datasets used in the course are all small). 
You must have Stata (version 12 or later)* installed in advance of the course.
*Internal University of Bristol participants will be provided with access to Stata version 16 on the first day of the course.

Course format

This 2-day course will be online and mainly consist of lectures and Stata-based practicals and will be in a mixture of live online and asynchronous formats. There will be plenty of opportunities for questions and troubleshooting. The live sessions will take place between 09:00 and 17:00 on the two scheduled days of the course, together with generous breaks and some asynchronous material to be completed on these days. Participants should therefore be able to dedicate these days to the course. There will also be about a half day's worth of preparatory sessions which participants will need to complete before the 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.

Course outline

  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. Graphical displays for survival analysis
  8. Cox models with continuously time-varying covariates

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.

Online Course Bookings


Bookings are open for online courses running in 2021.

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

Course feedback, May 2018

Coronavirus (COVID-19)

We may need to make responsive changes to our courses at short notice in order to follow the latest Public Health, Government and University guidance on coronavirus (COVID-19).

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