Introduction to Survival Analysis Training Course 2018

Thursday 7th June 2018 – Registration from 09:00-0930.

It is not necessary to bring a laptop – we will be using a computer lab.

This is a one-day workshop led by SLS staff (Prof Gillian Raab) on survival analysis for time to event data suitable for those with experience of statistical analyses but new to this type of analysis. This course would be of particular interest to those considering using the Scottish Longitudinal Study to analyse time to event data.

This workshop will introduce methods to display and model time to event data, including Kaplan-Meier plots and Cox proportional hazards regression. The survival analysis theory will be complimented with hands-on practical sessions using either SPSS or Stata (R if sufficient interest is indicated) on training datasets. Presentations of real projects will also be given to demonstrate research potential.

The course is intended for postgraduate students, academics and social or health researchers interested in learning how to do survival analysis in a statistical package. The course assumes some skills in statistical analysis, in particular a good knowledge of multiple regression and logistic regression would be beneficial. Additionally, a familiarity with using either SPSS, Stata or R syntax/command files is essential.

Course programme:

  • Features of survival data including censoring and truncation
  • Plotting survival data
  • Log-rank tests
  • Hazard rates
  • Cox proportional hazard models

Booking information: 

  • Price: Standard Registration – £30; Fee Exemption – Q-Step or PhD students at Edinburgh University/ADRC-S staff/LONGPOP ESR 
  • Lunch provided for all registered participants.
  • Places limited to 20 – Early registration is recommended.

Book your place via the online registration here


This course is being jointly run by the LSCS and the European H2020 project “Methodologies and Data mining techniques for the analysis of Big Data based on Longitudinal Population and Epidemiological Registers” (LONGPOP).


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