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Longitudinal Data Analysis

Course Description

The aim of the course is to provide an introduction to and hands on experience of the analysis longitudinal studies using: 

  • Random effects models for continuous outcome
  • Growth curve models
  • GEE models for continuous outcomes
  • Random effects models for binary data
  • GEE models for binary data
  • Event history

The course will comprise a brief introduction with 4 lectures of 90 minutes length and 4 practicals of 90 minutes, with tea breaks!  

Pre-requisites are: 

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


The Graduate School commissions one repeat of this course per academic year. This course is also delivered externally by National Centre for Research Methods (NCRM). To book a place on NCRM course please contact the course organiser, Owen Nicholas.

Next NCRM course 

Application deadline: 16 June 2014
Course dates: 30/06/2014 - 01/07/2014

Researcher Development Framework Categories

A1) Knowledge base

Course Recommended for

This course is particularly relevant to the following groups:

  • Students in Social & Historical Sciences
  • Students in Medical Sciences

Course Organisers

  • Course Director - Ms Jenny Head - (Research Department of Epidemiology & Public Health)
  • Course Tutor - Dr Mai Stafford - (Research Department of Epidemiology & Public Health)
  • Organiser - Dr Owen Nicholas - (Research Department of Epidemiology & Public Health)
  • Course Tutor - Dr Paola Zaninotto - (Research Department of Epidemiology & Public Health)
  • Course Tutor - Prof Amanda Sacker - (Research Department of Epidemiology & Public Health)
  • Administrator - Ms Kasia Bronk - (Graduate School)

Course Links



NCRM course: 30 Jun - 1 Jul 2014

Once you have completed your training, please log your points here.
Preparatory Work:

5-8 Nov 2013 expand

Page last updated: 22nd July 2010