Event History Analysis (online)



Organised by:

The University of Edinburgh


Dr Kevin Ralston is a lecturer in Sociology and Quantitative Methods at The University of Edinburgh


Intermediate (some prior knowledge)


Laura Marshall
Usher communications
Working week: Monday - Thursday

video conference logo

Venue: Online


This course introduces the analysis and modelling of event history data. Event history analysis (also known as survival analysis or failure time analysis) is widely used in the social sciences where the interest is on analysing time to events. This may be outcomes such as job changes, marriage timing, birth of children or time to divorce. The course is taught through a series of short presentations with accompanying practical applied examples and exercises.


The course will be especially beneficial for those who have a knowledge of regression analysis and who want to extend their knowledge to techniques for longitudinal analyses. The course will provide attendees with the information required to undertake and interpret their own event history analysis.


The course begins by covering introductory issues in event history. This includes descriptive approaches to event history data such as life-tables, survival plots, hazard plots and the log-rank test. This provides insight into two underlying key concepts, the hazard function, the survivor function. The initial part of the course also considers what event history data looks like and how to set Stata up for event history analysis using the stset command.


We will then move on to cover event history models. These include the Cox proportional hazard model, alternative parametric approaches to Cox and discrete-time models. We will also look at how to check the proportional hazard assumption.

Having put in place the foundations we will go on to look at some more advanced issues. In the final section of the course we will outline an approach to take account of interval censored data before looking at competing risks models.

Course Timings: 10:00 - 16:00

Some familiarity with (and access to) Stata. Familiarity with alternative statistical analysis packages that transfer to Stata is also sufficient. Understanding of standard statistical analysis techniques such as OLS regression and/or other GLM models would be beneficial.


The fee per teaching day is: • £30 per day for students registered at UK/EU University. • £60 per day for staff at UK/EU academic institutions, UK/EU Research Councils researchers, UK/EU public sector staff and staff at UK/EU registered charity organisations and recognised UK/EU research institutions. • £100 per day for all other participants In the event of cancellation by the delegate a full refund of the course fee is available up to two weeks prior to the course. NO refunds are available after this date. If it is no longer possible to run a course due to circumstances beyond its control, NCRM reserves the right to cancel the course at its sole discretion at any time prior to the event. In this event every effort will be made to reschedule the course. If this is not possible or the new date is inconvenient a full refund of the course fee will be given. NCRM shall not be liable for any costs, losses or expenses that may be incurred as a result of its cancellation of a course, including but not limited to any travel or accommodation costs. The University of Southampton’s Online Store T&Cs also continue to apply.

Website and registration:




Longitudinal Data Analysis, Event History Analysis, Stata, Survival analysis, longitudinal analysis

Related publications and presentations:

Longitudinal Data Analysis
Event History Analysis

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