Longitudinal Data Analysis


13/02/2024 - 15/02/2024

Organised by:

University College London


Dr Giorgio Di Gessa


Intermediate (some prior knowledge)


Olivia Evans - olivia.evans@ucl.ac.uk
Dr Giorgio Di Gessa - g.di-gessa@ucl.ac.uk

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Venue: Online


Online sessions 13 – 15 February 2024, 9.30am – 1.00pm


This course is for anyone needing to analyse longitudinal/panel data. UCL hosts many of the leading longitudinal studies in the UK and course examples will be taken from these studies. The aim of the course is to provide an introduction to, and hands-on experience of, the analysis of longitudinal studies. Statistical techniques that are most commonly used for the analysis of longitudinal data will be presented, alongside practical examples of how they have been successfully implemented. The course will use the statistical packages Stata and R.


There will be 7 sessions, 6 taught live via Zoom. Live sessions will consist of a lecture followed by a computer practical session (Stata and R) in which datasets will be given and attendees will learn how to perform statistical analyses and interpret and evaluate the results. The additional self-paced session is on Event History Analysis, in which a pre-recorded lecture can be watched and computer practical exercises performed; solutions to the practicals will be provided.


The course is suitable for full-time and part-time PhD and MSc students in any year of study, and members of staff. It is aimed at those using quantitative data in any scientific or educational research area. Attendees must have a basic knowledge of regression modelling techniques.


Course content:

1.         Introduction to clustered data 

2.         Growth curve models for continuous outcomes and binary data

3.         Random effects models for continuous outcomes and binary data

4.         Extra self-paced session available on Event History Analysis 


By the end of this course you will be able to:

•           Understand why analysis of longitudinal data requires methods that take account of clustering of repeat measures within individuals

•           Use and compare different methods for analysing data from longitudinal studies

•           Gain experience in building models for analysing longitudinal data

•           Interpret and communicate results


£200. A limited number of discounted places (£100) are available for PhD/MSc students.

Website and registration:




Quantitative Data Handling and Data Analysis

Related publications and presentations:

Quantitative Data Handling and Data Analysis

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