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Institute of Epidemiology & Health Care

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Longitudinal Data Analysis

This two-day course aims to provide a good understanding of a range of techniques for longitudinal data analysis and hands on experience of the analysis of longitudinal studies. It includes a mixture of theoretical sessions and practical sessions (using STATA) to illustrate concepts. Practical sessions will use data from longitudinal studies of health research, such as the English Longitudinal Study of Ageing (ELSA).

The course will cover: 

  • Random effects models for continuous outcomes
  • 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.

Pre-requisites

  • Experience of using STATA or similar package
  • Experience of linear and logistic regression
  • Experience of data analysis

Learning outcomes

By the end of the course you’ll 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

Certification

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: £400
  • Reduced rate for group bookings of four people or more: £300
  • Reduced rate for PhD students at UK higher education institutes: £300

How to Apply

Last Booking Date: 26th April 2019

Book your place now

Provisional timetable

The course runs from 9.30am - 5.30pm on both days. Please note this timetable may be subject to change.

 Monday 13th May 2019Tuesday 14th May 2019
9.15Registration and welcome 
09:30-11:00Random effects models for continuous outcomesRandom effects models for binary outcomes
11:00-11:30Coffee breakCoffee break
11:30-13:00Computer practical sessionComputer practical session
13:00-14:00LunchLunch
14:00-15:30Growth curve modelsEvent history analysis
15:30-16:00Coffee breakCoffee break
16:00-17:30Computer practical sessionComputer practical session