Institute of Epidemiology & Health Care


Longitudinal Data Analysis

This four-day Online course is designed to give participants a good understanding of a range of techniques for longitudinal data analysis. It will use a mixture of theoretical sessions and practical sessions (using Stata) to illustrate concepts. Examples will primarily be taken from health research, such as the English Longitudinal Study of Ageing (ELSA).

The course will cover:

•         Random effects models for continuous outcome

•         Growth curve models

•         Random effects models for binary data

•         Event history analysis


Course leaders

Shaun Scholes

Dr Shaun Scholes 

Shaun is Senior Research Associate in the Department of Epidemiology and Public Health at UCL. He works on the annual reports for the Health Survey for England and his research interests include socioeconomic inequalities in physical activity and hypertension in the UK and worldwide.


Paola Zaninotto

Dr Paola Zaninotto

Paola is Associate Professor in Medical Statistics in the Department of Epidemiology and Public Health at UCL. Her research focuses on trajectories of physical health and wellbeing in older adults as well as determinants of healthy ageing.

Dr Owen Nicholas

Owen is a Senior Research Associate in UCL’s Department of Statistical Science working on the interactions between climate, food systems and health.

Jenny Head

Professor Jenny Head

Jenny is Professor of Medical and Social Statistics in the Department of Epidemiology and Public Health at UCL. Her research focuses on determinants of healthy ageing and healthy working lives.


Participants should have a good understanding and experience of applying and interpreting multiple linear regression models and logistic regression models. Participants should have prior experience of using a statistical package to analyse data such as Stata to gain the most out of the course. Please note we do not provide the statistical software.


To provide students with the skills needed to design longitudinal research and conduct appropriate analyses using longitudinal data including the use of random effects models for repeated measures data and event history analysis.

Learning outcomes

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

  • Use methods to identify between and within individual variation in outcomes
  • Use and interpret models for longitudinal outcomes
  • Use and interpret growth curve models
  • Use and interpret models for event history data
  • Propose, evaluate and select models
  • Interpret and communicate results


You will receive a certificate of attendance if you attend both days of the course. Please note the course does not receive UCL credits.

Cost and concessions

The fees are: 

  • Full rate: £250
  • Reduced rate for PhD students at UK higher education institutes: £150

Reserve a place on this course

Last Booking Date: 1st November 2020

Book your place now